Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

Donanemab is an amyloid-targeting therapy that resulted in robust amyloid plaque reduction and slowed Alzheimer's disease (AD) progression compared with placebo in the phase II TRAILBLAZER-ALZ study (NCT03367403). The objectives of the current analyses are to characterize (i) the population pharmacokinetics of donanemab, (ii) the relationship between donanemab exposure and amyloid plaque reduction (response), and (iii) the relationship between donanemab exposure and amyloid-related imaging abnormalities with edema or effusions (ARIA-E). Model development included data from participants with mild cognitive impairment or mild to moderate dementia due to AD from the phase Ib study on donanemab (NCT02624778) and participants with early symptomatic AD from the TRAILBLAZER-ALZ study. The analysis showed donanemab has a terminal elimination half-life of 11.8 days. Body weight and antidrug antibody titer impact donanemab exposure but not the pharmacodynamic response. Maintaining a donanemab serum concentration above 4.43 μg/mL (95% confidence interval: 0.956, 10.4) is associated with amyloid plaque reduction. The time to achieve amyloid plaque clearance (amyloid plaque level < 24.1 Centiloids) varied depending on the baseline amyloid level, where higher baseline levels were associated with fewer participants achieving amyloid clearance. The majority of participants achieved amyloid clearance by 52 weeks on treatment. Apolipoprotein ε4 carriers, irrespective of donanemab serum exposure, were 4 times more likely than noncarriers to have an ARIA-E event by 24 weeks.

Targeted protein degradation (TPD) has emerged as a potentially transformational therapeutic modality with considerable promise. Molecular glue degraders remodel the surface of E3 ligases inducing interactions with neosubstrates resulting in their polyubiquitination and proteasomal degradation. Molecular glues are clinically precedented and have demonstrated the ability to degrade proteins-of-interest (POIs) previously deemed undruggable due to the absence of a traditional small molecule binding pocket. Heterobifunctional proteolysis targeting chimeras (PROTACs) possess ligands for an E3 complex and the POIs, which are chemically linked together, and similarly hijack the ubiquitin machinery to deplete the target. There has been a recent surge in the number of degraders entering clinical trials, particularly directed toward cancer. Nearly all utilize CRL4CRBN as the E3 ligase, and a relatively limited diversity of POIs are currently targeted. In this review, we provide an overview of the degraders in clinical trials and provide a perspective on the lessons learned from their development and emerging human data that will be broadly useful to those working in the TPD field.

Over 20% of US Food and Drug Administration (FDA)-approved drugs in the United States are metabolized by the hepatic enzyme cytochrome P450 2D6 (CYP2D6). The gene encoding CYP2D6 is highly polymorphic and genetic variation has been shown to impact drug response for many commonly dispensed drugs including opioids and antidepressants. Thus, it is important to understand an individual's CYP2D6 metabolizer status to optimize treatment outcomes for patients taking medications that are metabolized by this enzyme. Consequently, clinical CYP2D6 pharmacogenetic testing is being implemented by a growing number of health centers. Furthermore, clinical guidelines currently recommend adapting therapeutic regimens based on CYP2D6 genotype-informed phenotype. However, CYP2D6 genetic variation varies considerably across global populations and many allelic variants, or star alleles, are predominantly found in certain ancestral populations. Although CYP2D6 genetic variation has been extensively studied, there is still a paucity of information for many non-European populations. As has been shown for other pharmacogenes in randomized controlled trials, results from European populations cannot simply be extrapolated to other groups and, in some cases, even has the potential to cause harm. Therefore, enhanced inclusion in pharmacogenetic studies is urgently needed to increase ancestral representation, determine the extent of global CYP2D6 genetic variation (e.g., ancestry-specific variants), and determine the clinical impact of this variation on clinical treatment outcome. This review highlights knowledge gaps, challenges, and future directions in CYP2D6 pharmacogenomics through a unique pharmacoequity lens to address health inequities that hamper our ability to optimize drug therapy for improved pharmacological outcomes in diverse populations globally.

The decentralized clinical trial (DCT) approach is increasingly recognized as a means to accelerate the development of potential therapeutic interventions. DCTs have a crucial advantage over traditional clinical trials: patients are monitored in their environment using technology (e.g., wearables), that capture data as they continue in daily life. This narrative review outlines a gap analysis focused on the frameworks and guidance from expert working groups and regulatory agencies for the design and execution of DCTs. Eight DCT elements guided the analysis and summarized the frameworks and guidance: (1) suitability, (2) protocol, (3) investigational medicinal product (IMP) supply, (4) investigators and health care providers, (5) safety, (6) regulatory and ethics, (7) data and technology, and (8) engagement, communication, and advocacy. Based on the gap analysis, two key takeaways were identified: (1) a need for a comprehensive sustainability assessment of each DCT element; and (2) current frameworks and guidance provide recommendations on social sustainability and some on economic sustainability. DCTs are an essential evolution in healthcare research; however, more guidance related to a comprehensive assessment of designing and executing sustainable DCTs is needed. This is especially the case for environmental sustainability, including, for example, carbon footprint and disposal of IMPs and sensors.

Cell and gene therapy (CGT) describes a broad category of medicinal products with potential applications to prevent and treat human disease in multiple therapeutic areas. These therapies leverage the use of modified nucleic acids, altered cells or tissue, or both. The modality, mechanism, route of administration, and therapeutic indication for a CGT product will influence the challenges and opportunities for early clinical development, some of which may be highly specific to the product under consideration. Both the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) encourage early interaction between sponsor and health authority to align on key elements of the CGT development program.

Regulators are faced with many challenges surrounding health data usage, including privacy, fragmentation, validity, and generalizability, especially in the European Union, for which synthetic data may provide innovative solutions. Synthetic data, defined as data artificially generated rather than captured in the real world, are increasingly being used for healthcare research purposes as a proxy to real-world data (RWD). Currently, there are barriers particularly challenging in Europe, where sharing patient's data is strictly regulated, costly, and time-consuming, causing delays in evidence generation and regulatory approvals. Recent initiatives are encouraging the use of synthetic data in regulatory decision making and health technology assessment to overcome these challenges, but synthetic data have still to overcome realistic obstacles before their adoption by researchers and regulators in Europe. Thus, the emerging use of RWD and synthetic data by pharmaceutical and medical device industries calls regulatory bodies to provide a framework for proper evidence generation and informed regulatory decision making. As the provision of data becomes more ubiquitous in scientific research, so will innovations in artificial intelligence, machine learning, and generation of synthetic data, making the exploration and intricacies of this topic all the more important and timely. In this review, we discuss the potential merits and challenges of synthetic data in the context of decision making in the European regulatory environment. We explore the current uses of synthetic data and ongoing initiatives, the value of synthetic data for regulatory purposes, and realistic barriers to the adoption of synthetic data in healthcare.

Model-informed drug development (MIDD) is a process that integrates drug exposure-based, biological, and statistical models to enhance the benefit-risk balance in drug development. The US Food and Drug Administration (FDA) MIDD Paired Meeting Pilot Program provides a platform to apply MIDD approaches to drug development and to seek regulatory feedback in a collaborative and streamlined process prior to submission for approval. Eli Lilly and Company (Lilly) participated in the Pilot Program to seek agency alignment to enhance the initial approved dosing regimens of cetuximab (Erbitux; Eli Lilly and Company, Indianapolis, IN) and ramucirumab (Cyramza; Eli Lilly and Company) without conducting additional clinical trials. Here, we describe the overall MIDD strategy at Lilly, the process with the FDA, and the impact of implementing the approach.

Genome editing holds the potential for curative treatments of human disease, however, clinical realization has proven to be a challenging journey with incremental progress made up until recently. Over the last decade, advances in clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) systems have provided the necessary breakthrough for genome editing in the clinic. The progress of investigational CRISPR therapies from bench to bedside reflects the culmination of multiple advances occurring in parallel, several of which intersect with clinical pharmacology and translation. Directing the CRISPR therapy to the intended site of action has necessitated novel delivery platforms, and this has resulted in special considerations for the complete characterization of distribution, metabolism, and excretion, as well as immunogenicity. Once at the site of action, CRISPR therapies aim to make permanent alterations to the genome and achieve therapeutically relevant effects with a single dose. This fundamental aspect of the mechanism of action for CRISPR therapies results in new considerations for clinical translation and dose selection. Early advances in model-informed development of CRISPR therapies have incorporated key facets of the mechanism of action and have captured hallmark features of clinical pharmacokinetics and pharmacodynamics from phase I investigations. Given the recent emergence of CRISPR therapies in clinical development, the landscape continues to evolve rapidly with ample opportunity for continued innovation. Here, we provide a snapshot of selected topics in clinical pharmacology and translation that has supported the advance of systemically administered in vivo and ex vivo CRISPR-based investigational therapies in the clinic.

The promise of transforming digital technologies into treatments is what drives the development of digital therapeutics (DTx), generally known as software applications embedded within accessible technologies-such as smartphones-to treat, manage, or prevent a pathological condition. Whereas DTx solutions that successfully demonstrate effectiveness and safety could drastically improve the life of patients in multiple therapeutic areas, there is a general consensus that generating therapeutic evidence for DTx presents challenges and open questions. We believe there are three main areas where the application of clinical pharmacology principles from the drug development field could benefit DTx development: the characterization of the mechanism of action, the optimization of the intervention, and, finally, its dosing. We reviewed DTx studies to explore how the field is approaching these topics and to better characterize the challenges associated with them. This leads us to emphasize the role that the application of clinical pharmacology principles could play in the development of DTx and to advocate for a development approach that merges such principles from development of traditional therapeutics with important considerations from the highly attractive and fast-paced world of digital solutions.

Fluoropyrimidine (FP) chemotherapy is associated with severe, life-threatening toxicities, particularly among patients who carry deleterious germline variants in the DPYD gene. Pretreatment DPYD testing is standard of care throughout most of Europe; however, it has not been recommended in clinical practice guidelines in the United States. Due to increased risk of severe toxicity, a Citizen's Petition asked the US Food and Drug Administration (FDA) to update language in FP drug labels to recommend DPYD testing as part of a boxed warning and recommend FP dose reduction in patients carrying deleterious germline variants. In response, the FDA updated the capecitabine package insert to inform patients about the toxicity risk and test availability and consider DPYD testing. However, the FDA did not include a testing recommendation or requirement, or a boxed warning. Additionally, the FDA did not recommend FP dose adjustment in DPYD variant carriers. This review provides a critical assessment of the DPYD-FP pharmacogenetic association using the FDA's previously published Pharmacogenetic Pyramid, demonstrating that the evidence is compelling for recommending DPYD testing prior to FP treatment. Additionally, the FDA's stated concerns about recommending DPYD testing and DPYD-guided FP dose adjustment are addressed and discussed in the context of the FDA's other genetic testing and dose adjustment recommendations. We call on the FDA to follow our European counterparts in recommending DPYD testing and genotype-based dose adjustment to ensure patients with cancer receive safe and effective FP chemotherapy.

Regulators and Health Technology Assessment (HTA) bodies are increasingly familiar with, and publishing guidance on, external controls derived from real-world data (RWD) to generate real-world evidence (RWE). We recently conducted a systematic literature review (SLR) evaluating publicly available information on the use of RWD-derived external controls to contextualize outcomes from uncontrolled trials submitted to the European Medicines Agency (EMA), the US Food and Drug Administration (FDA), and/or select HTA bodies. The review identified several key operational and methodological aspects for which more detailed guidance and alignment within and between regulatory agencies and HTA bodies is necessary. This paper builds on the SLR findings by delineating a set of key takeaways for the responsible generation of fit-for-purpose RWE. Practical methodological and operational guidelines for designing, conducting, and reporting RWD-derived external control studies are explored and discussed. These considerations include: (i) early engagement with regulators and HTA bodies during the study planning phase; (ii) consideration of the appropriateness and comparability of external controls across multiple dimensions, including eligibility criteria, temporality, population representation, and clinical evaluation; (iii) ensuring adequate sample sizes, including hypothesis testing considerations; (iv) implementation of a clear and transparent strategy for assessing and addressing data quality, including data missingness across trials and RWD; (v) selection of comparable and meaningful endpoints that are operationalized and analyzed using appropriate analytic methods; and (vi) conduct of sensitivity analyses to assess the robustness of findings in the context of uncertainty and sources of potential bias.

Instructions for administration with regard to food are a key aspect of how patients experience oral drugs. Through potential effects on pharmacokinetics, the food condition can influence safety and efficacy, and thereby is one of many dimensions of dose optimization. Regulatory guidance from major health authorities advocates for the early investigation of food effect (FE) in clinical development. In oncology, exploratory FE (eFE) evaluation is often incorporated into the first-in-human (FIH) studies in patients to inform food condition of later clinical studies. However, the design aspects of such exploratory assessments are generally under-reported and barely described, and yet complex, due to uniqueness of FIH study design and drug development process in oncology. Herein, we review literature of eFE assessment study design in oncology in patients, and present the Novartis experience in the design, execution, and impact of eFE in FIH oncology studies from 2014 to 2021. Based on this, we propose a roadmap for eFE assessment in early clinical drug development for oncology drugs in patients, including a framework for common study design options with a focus on study- and patient-level timing for typical scenarios. We also provide a broad spectrum of decision-making factors which should be evaluated to drive the design and implementation of eFE assessment, spanning from clinical development strategy, FIH study design, to compound-specific features.

Novel drug treatments for pediatric patients with cancer are urgently needed. Success of drug development in pediatric oncology has been promising, but many drugs still fail in translation from preclinical to clinical phases. To increase the translational potential, several improvements have been implemented, including the use of clinically achievable concentrations in the drug testing phase. Although pharmacokinetic (PK) parameters of numerous investigated drugs are published, a comprehensive PK overview of the most common drugs in pediatric oncology could guide preclinical trial design and improve the translatability into clinical trials. A review of the literature was conducted for PK parameters of 74 anticancer drugs, from the drug sensitivity profiling library of the INdividualized Therapy FOr Relapsed Malignancies in Childhood (INFORM) registry. PK data in the pediatric population were reported and complemented by adult parameters when no pediatric data were available. In addition, blood-brain barrier (BBB)-penetration assessment of drugs was provided by using the BBB score. Maximum plasma concentration was available for 73 (97%), area under the plasma concentration-time curve for 69 (92%), plasma protein binding for 66 (88%), plasma half-life for 57 (76%), time to maximum concentration for 54 (72%), clearance for 52 (69%), volume of distribution for 37 (49%), lowest plasma concentration reached by the drug before the next dose administration for 21 (28%), and steady-state concentration for 4 (5%) of drugs. Pediatric PK data were available for 48 (65%) drugs. We provide a comprehensive review of PK data for 74 drugs studied in pediatric oncology. This data set can serve as a reference to design experiments more closely mimicking drug PK conditions in patients, and may thereby increase the probability of successful clinical translation.

The US Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceuticals and Medical Devices Agency (PMDA) guidances on small-molecule drug-drug interactions (DDIs), with input from the International Transporter Consortium (ITC), recommend the evaluation of nine drug transporters. Although other clinically relevant drug uptake and efflux transporters have been discussed in ITC white papers, they have been excluded from further recommendation by the ITC and are not included in current regulatory guidances. These include the ubiquitously expressed equilibrative nucleoside transporters (ENT) 1 and ENT2, which have been recognized by the ITC for their potential role in clinically relevant nucleoside analog drug interactions for patients with cancer. Although there is comparatively limited clinical evidence supporting their role in DDI risk or other adverse drug reactions (ADRs) compared with the nine highlighted transporters, several in vitro and in vivo studies have identified ENT interactions with non-nucleoside/non-nucleotide drugs, in addition to nucleoside/nucleotide analogs. Some noteworthy examples of compounds that interact with ENTs include cannabidiol and selected protein kinase inhibitors, as well as the nucleoside analogs remdesivir, EIDD-1931, gemcitabine, and fialuridine. Consequently, DDIs involving the ENTs may be responsible for therapeutic inefficacy or off-target toxicity. Evidence suggests that ENT1 and ENT2 should be considered as transporters potentially involved in clinically relevant DDIs and ADRs, thereby warranting further investigation and regulatory consideration.

During the coronavirus disease 2019 (COVID-19) pandemic, the urgency for updated evidence to inform public health and clinical care placed systematic literature reviews (SLRs) at the cornerstone of research. We aimed to summarize evidence on prognostic factors for COVID-19 outcomes through published SLRs and to critically assess quality elements in the findings' interpretation. An umbrella review was conducted via electronic databases from January 2020 to April 2022. All SLRs (and meta-analyses) in English were considered. Data screening and extraction were conducted by two independent reviewers. AMSTAR 2 tool was used to assess SLR quality. The study was registered with PROSPERO (CRD4202232576). Out of 4,564 publications, 171 SLRs were included of which 3 were umbrella reviews. Our primary analysis included 35 SLRs published in 2022, which incorporated studies since the beginning of the pandemic. Consistent findings showed that, for adults, older age, obesity, heart disease, diabetes, and cancer were more strongly predictive of risk of hospitalization, intensive care unit admission, and mortality due to COVID-19. Male sex was associated with higher risk of short-term adverse outcomes, but female sex was associated with higher risk of long COVID. For children, socioeconomic determinants that may unravel COVID-19 disparities were rarely reported. This review highlights key prognostic factors of COVID-19, which can help clinicians and health officers identify high-risk groups for optimal care. Findings can also help optimize confounding adjustment and patient phenotyping in comparative effectiveness research. A living SLR approach may facilitate dissemination of new findings. This paper is endorsed by the International Society for Pharmacoepidemiology.

Disease progression modeling (DPM) represents an important model-informed drug development framework. The scientific communities support the use of DPM to accelerate and increase efficiency in drug development. This article summarizes International Consortium for Innovation & Quality (IQ) in Pharmaceutical Development mediated survey conducted across multiple biopharmaceutical companies on challenges and opportunities for DPM. Additionally, this summary highlights the viewpoints of IQ from the 2021 workshop hosted by the US Food and Drug Administration (FDA). Sixteen pharmaceutical companies participated in the IQ survey with 36 main questions. The types of questions included single/multiple choice, dichotomous, rank questions, and open-ended or free text. The key results show that DPM has different representation, it encompasses natural disease history, placebo response, standard of care as background therapy, and can even be interpreted as pharmacokinetic/pharmacodynamic modeling. The most common reasons for not implementing DPM as frequently seem to be difficulties in internal cross-functional alignment, lack of knowledge of disease/data, and time constraints. If successfully implemented, DPM can have an impact on dose selection, reduction of sample size, trial read-out support, patient selection/stratification, and supportive evidence for regulatory interactions. The key success factors and key challenges of disease progression models were highlighted in the survey and about 24 case studies across different therapeutic areas were submitted from various survey sponsors. Although DPM is still evolving, its current impact is limited but promising. The success of such models in the future will depend on collaboration, advanced analytics, availability of and access to relevant and adequate-quality data, collaborative regulatory guidance, and published examples of impact.

Real-world data (RWD)-derived external controls can be used to contextualize efficacy findings for investigational therapies evaluated in uncontrolled trials. As the number of submissions to regulatory and health technology assessment (HTA) bodies using external controls rises, and in light of recent regulatory and HTA guidance on the appropriate use of RWD, there is a need to address the operational and methodological challenges impeding the quality of real-world evidence (RWE) generation and the consistency in evaluation of RWE across agencies. This systematic review summarizes publicly available information on the use of external controls to contextualize outcomes from uncontrolled trials for all indications from January 1, 2015, through August 20, 2021, that were submitted to the European Medicines Agency, the US Food and Drug Administration, and/or select major HTA bodies (National Institute for Health and Care Excellence (NICE), Haute Autorité de Santé (HAS), Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG), and Gemeinsamer Bundesausschuss (G-BA)). By systematically reviewing submissions to regulatory and HTA bodies in the context of recent guidance, this study provides quantitative and qualitative insights into how external control design and analytic choices may be viewed by different agencies in practice. The primary operational and methodological aspects identified for discussion include, but are not limited to, engagement of regulators and HTA bodies, approaches to handling missing data (a component of data quality), and selection of real-world endpoints. Continued collaboration and guidance to address these and other aspects will inform and assist stakeholders attempting to generate evidence using external controls.

Since the 21st Century Cures Act was signed into law in 2016, real-world data (RWD) and real-world evidence (RWE) have attracted great interest from the healthcare ecosystem globally. The potential and capability of RWD/RWE to inform regulatory decisions and clinical drug development have been extensively reviewed and discussed in the literature. However, a comprehensive review of current applications of RWD/RWE in clinical pharmacology, particularly from an industry perspective, is needed to inspire new insights and identify potential future opportunities for clinical pharmacologists to utilize RWD/RWE to address key drug development questions. In this paper, we review the RWD/RWE applications relevant to clinical pharmacology based on recent publications from member companies in the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) RWD Working Group, and discuss the future direction of RWE utilization from a clinical pharmacology perspective. A comprehensive review of RWD/RWE use cases is provided and discussed in the following categories of application: drug-drug interaction assessments, dose recommendation for patients with organ impairment, pediatric plan development and study design, model-informed drug development (e.g., disease progression modeling), prognostic and predictive biomarkers/factors identification, regulatory decisions support (e.g., label expansion), and synthetic/external control generation for rare diseases. Additionally, we describe and discuss common sources of RWD to help guide appropriate data selection to address questions pertaining to clinical pharmacology in drug development and regulatory decision making.

Warfarin is extensively metabolized by cytochrome P450 2C9 (CYP2C9). Concomitant use with the potent CYP2C9 inducer, rifampin, requires close monitoring and dosage adjustments. Although, in theory, warfarin dose increase should overcome this interaction, most reported cases over the last 50 years have not responded even to high warfarin doses, but some have responded to modest doses. To investigate the genetic polymorphisms' impact on this unexplained interpatient variability, we performed genotyping of CYP2C9, VKORC1, and CYP4F2 for warfarin and rifampin concomitant receivers from 2016 to 2022 at Hamad Medical Corporation, Doha, Qatar. We identified and included 36 patients: 22 responders and 14 nonresponders. Warfarin-responders were significantly more likely to have one or more warfarin-sensitizing CYP2C9/VKORC1 alleles than nonresponders (odds ratio = 23.2, 95% confidence interval = 3.2-195.6; P = 0.0001). The mean genetic-based pre-interaction calculated dose was significantly lower for responders than for nonresponders (P < 0.001); and was negatively correlated with warfarin sensitivity index (WSI) (r = -0.58; P = 0.0002). The median percentage time in therapeutic range and mean WSI were significantly higher in the warfarin-sensitizing CYP2C9/VKORC1 alleles carriers than noncarriers (P = 0.017 and 0.0004, respectively). Whereas the warfarin-sensitizing CYP2C9/VKORC1 genotypes were associated with modest on-rifampin warfarin dose requirements, the noncarriers would have required more than double these doses to respond. Warfarin-sensitizing CYP2C9/VKORC1 genotypes and low genetic-based warfarin calculated doses were associated with higher warfarin sensitivity and better anticoagulation quality in patients receiving rifampin concomitantly.

Comment in Clin Pharmacol Ther. 2023 Mar;113(3):473-475.

The new In Vitro Diagnostic Regulation (EU) 2017/746 (IVDR) introduces important changes in the EU legal framework for companion diagnostics (CDx), including a new risk-based classification system for in vitro diagnostic tests (IVDs), a first legal definition for CDx and enhanced involvement of notified bodies in the conformity assessment and certification process of CDx. The IVDR also establishes an important link between the assessment of a CDx and the corresponding medicinal product by requiring the notified body to seek a scientific opinion from the medicines regulator on the suitability of the CDx for use with the concerned medicinal product(s) before issuing an IVD certificate. Whereas the IVDR aims at establishing a robust regulatory framework for IVDs, it is also associated with several challenges, such as insufficient capacity of notified bodies and readiness of manufacturers. To ensure timely access for patients to essential IVDs, a progressive roll-out for this new legislation has been introduced. In addition, the new consultation process for CDx requires increased collaboration and alignment of assessments performed by the different stakeholders involved in this process. The European Medicines Agency (EMA) and notified bodies are currently building experience based on the first CDx consultation procedures that have been submitted from January 2022 onward. In the current article, we describe the new European regulatory framework for certification of CDx and highlight several challenges for medicine and CDx co-development. In addition, we briefly touch upon the interplay between the Clinical Trial Regulation (EU) No. 536/2014 (CTR) and the IVDR.

With the promise of a potentially "single dose curative" paradigm, CAR-T cell therapies have brought a paradigm shift in the treatment and management of hematological malignancies. Both CAR-T and TCR-T cell therapies have also made great progress toward the successful treatment of solid tumor indications. The field is rapidly evolving with recent advancements including the clinical development of "off-the-shelf" allogeneic CAR-T therapies that can overcome the long and difficult "vein-to-vein" wait time seen with autologous CAR-T therapies. There are unique clinical pharmacology, pharmacometric, bioanalytical, and immunogenicity considerations and challenges in the development of these CAR-T and TCR-T cell therapies. Hence, to help accelerate the development of these life-saving therapies for the patients with cancer, experts in this field came together under the umbrella of International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) to form a joint working group between the Clinical Pharmacology Leadership Group (CPLG) and the Translational and ADME Sciences Leadership Group (TALG). In this white paper, we present the IQ consortium perspective on the best practices and considerations for clinical pharmacology and pharmacometric aspects toward the optimal development of CAR-T and TCR-T cell therapies.

A different drug-drug interaction (DDI) scenario may exist in patients with chronic kidney disease (CKD) compared with healthy volunteers (HVs), depending on the interplay between drug-drug and disease (drug-drug-disease interaction (DDDI)). Physiologically-based pharmacokinetic (PBPK) modeling, in lieu of a clinical trial, is a promising tool for evaluating these complex DDDIs in patients. However, the prediction confidence of PBPK modeling in the severe CKD population is still low when nonrenal pathways are involved. More mechanistic virtual disease population and robust validation cases are needed. To this end, we aimed to: (i) understand the implications of severe CKD on statins (atorvastatin, simvastatin, and rosuvastatin) pharmacokinetics (PK) and DDI; and (ii) predict untested clinical scenarios of statin-roxadustat DDI risks in patients to guide suitable dose regimens. A novel virtual severe CKD population was developed incorporating the disease effect on both renal and nonrenal pathways. Drug and disease PBPK models underwent a four-way validation. The verified PBPK models successfully predicted the altered PKs in patients for substrates and inhibitors and recovered the observed statin-rifampicin DDIs in patients and the statin-roxadustat DDIs in HVs within 1.25- and 2-fold error. Further sensitivity analysis revealed that the severe CKD effect on statins PK is mainly mediated by hepatic BCRP for rosuvastatin and OATP1B1/3 for atorvastatin. The magnitude of statin-roxadustat DDI in patients with severe CKD was predicted to be similar to that in HVs. PBPK-guided suitable dose regimens were identified to minimize the risk of side effects or therapeutic failure of statins when co-administered with roxadustat.

The promise of viral vector-based gene therapy (GT) as a transformative paradigm for treating severely debilitating and life-threatening diseases is slowly coming to fruition with the recent approval of several drug products. However, they have a unique mechanism of action often necessitating a tortuous clinical development plan. Expertise in such complex therapeutic modality is still fairly limited in this emerging class of adeno-associated virus (AAV) vector-based gene therapies. Because of the irreversible mode of action and incomplete understanding of genotype-phenotype relationship and disease progression in rare diseases careful considerations should be given to GT product's benefit-risk profile. In particular, special attention needs to be paid to safe dose selection, reliable dose exposure response (including clinically relevant endpoints), or creative approaches in study design targeting small patient populations during clinical development. We believe that quantitative tools encompassed within model-informed drug development (MIDD) framework fits quite well in the development of such novel therapies, as they enable us to benefit from the totality of data approach in order to support dose selection as well as optimize clinical trial designs, end point selection, and patient enrichment. In this thought leadership paper, we provide our collective experiences, identify challenges, and suggest areas of improvement in applications of modeling and innovative trial design in development of AAV-based GT products and reflect on the challenges and opportunities for incorporating MIDD tools and more in rational development of these products.

The Centre of Regulatory Excellence (CoRE) launched an annual lecture series in 2021 in Singapore to honor the memory of the late Professor Sir Alasdair Breckenridge, CoRE's founding Chair, and foster dialogue on global biomedical and regulatory perspectives, challenges, and advances. The 2022 Sir Alasdair Breckenridge Lecture "Success and Opportunities in the Pandemic" was delivered by Dr Penny M Heaton, former CEO of the Bill & Melinda Gates Foundation Research Institute and current Global Therapeutics Lead for Vaccines at Johnson & Johnson. Dr Heaton highlighted key lessons on the importance of trust, collaboration, and transparency in the context of health care and vaccine production.

Aminoglycoside antibiotic exposure can result in ototoxicity and irreversible hearing loss among individuals that harbor the m.1555A>G variant in the mitochondrial 12S rRNA gene, MT-RNR1. Importantly, pre-emptive m.1555A>G screening has been shown to reduce the prevalence of pediatric aminoglycoside-induced ototoxicity; however, professional guidelines to support and guide post-test pharmacogenomic counseling in this context are not currently available. This Perspective highlights key issues with delivering MT-RNR1 results, including longitudinal familial care considerations and communicating m.1555A>G heteroplasmy.

Direct oral anticoagulants (DOACs) have increasingly replaced warfarin for treating patients with non-valvular atrial fibrillation (NVAF). DOACs have been demonstrated to be more useful than warfarin, which was highlighted at its ethnic differences in efficacy and safety; however, the regional differences of DOACs remain unclear. We conducted a systematic review, meta-analysis, and meta-regression to evaluate the efficacy and safety of DOACs in patients from Asian and non-Asian regions with NVAF. We systematically searched randomized control trials published before August 2019. We defined 11 studies comprising 7,118 Asian and 53,282 non-Asian patients, totaling 60,400 patients with NVAF. The risk ratios (RRs) of DOACs were calculated against warfarin. The efficacy of DOACs was significantly higher in Asian regions regarding stroke/systemic embolism events (RR: 0.62 and 95% confidence interval (CI): 0.49-0.78 for the Asian region; RR: 0.83 and 95% CI: 0.75-0.92 for non-Asian regions; P interaction: 0.02), when compared with warfarin. The safety of DOACs was significantly higher in Asian regions regarding major bleeding (RR: 0.62 and 95% CI: 0.51-0.75 for Asian regions; RR: 0.90 and 95% CI: 0.76-1.05 for non-Asian regions; P interaction: 0.004), compared with warfarin. In addition, we conducted meta-regression analysis to discuss the true regional differences of DOACs to warfarin. The meta-regression analysis, which adjusts the effect of individual backgrounds in each study, indicated that the regional differences were observed in the efficacy but not in drug safety. These results suggest that treatment with DOACs may be more effective than the conventional warfarin in the Asian region.

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Antibiotics are a known cause of idiosyncratic drug-induced liver injury (DILI). According to the Centers for Disease Control and Prevention, the five most commonly prescribed antibiotics in the United States are azithromycin, ciprofloxacin, cephalexin, amoxicillin, and amoxicillin-clavulanate. We quantified the frequency of acute DILI for these common antibiotics in the All of Us Research Program, one of the largest electronic health record (EHR)-linked research cohorts in the United States. Retrospective analyses were conducted applying a standardized phenotyping algorithm to de-identified clinical data available in the All of Us database for 318,598 study participants. Between February 1984 and December 2022, more than 30% of All of Us participants (n = 119,812 individuals) had been exposed to at least 1 of our 5 study drugs. Initial screening identified 591 potential case patients that met our preselected laboratory-based phenotyping criteria. Because DILI is a diagnosis of exclusion, we then used phenome scanning to narrow the case counts by (i) scanning all EHRs to identify all alternative diagnostic explanations for the laboratory abnormalities, and (ii) leveraging International Classification of Disease 9th revision (ICD)-9 and ICD 10th revision (ICD)-10 codes as exclusion criteria to eliminate misclassification. Our final case counts were 30 DILI cases with amoxicillin-clavulanate, 24 cases with azithromycin, 24 cases with ciprofloxacin, 22 cases with amoxicillin alone, and < 20 cases with cephalexin. These findings demonstrate that data from EHR-linked research cohorts can be efficiently mined to identify DILI cases related to the use of common antibiotics.

Generating evidence from real-world data requires fit-for-purpose study design and data. In addition to validity, decision makers require transparency in the reasoning that underlies study design and data source decisions. The 2019 Structured Preapproval and Postapproval Comparative Study Design Framework to Generate Valid and Transparent Real-World Evidence (SPACE) and the 2021 Structured Process to Identify Fit-For-Purpose Data (SPIFD)-intended to be used together-provide a step-by-step guide to identify decision grade, fit-for-purpose study design and data. In this update (referred to as "SPIFD2" to encompass both the design and data aspects) we provide an update to these frameworks that combines the templates into one, more explicitly calls for articulation of the hypothetical target trial and sources of bias that may arise in the real-world emulation, and provides explicit references to the Structured Template and Reporting Tool for Real-World Evidence (STaRT-RWE) tables that we suggest using immediately after invoking the SPIFD2 framework. Following the steps recommended in the SPIFD2 process requires due diligence on the part of the researcher to ensure that every aspect of study design and data selection is rationalized and supported by evidence. The resulting stepwise documentation enables reproducibility and clear communication with decision makers, and it increases the likelihood that the evidence generated is valid, fit-for-purpose, and sufficient to support healthcare and regulatory decisions.

Comment in Clin Pharmacol Ther. 2023 Jun;113(6):1183-1184.

Understanding cannabis-drug interactions is critical given regulatory changes that have increased access to and use of cannabis. Cannabidiol (CBD) and Δ-9-tetrahydrocannabinol (Δ9-THC), the most abundant phytocannabinoids, are in vitro reversible and time-dependent (CBD only) inhibitors of several cytochrome P450 (CYP) enzymes. Cannabis extracts were used to evaluate quantitatively potential pharmacokinetic cannabinoid-drug interactions in 18 healthy adults. Participant received, in a randomized cross-over manner (separated by ≥ 1 week), a brownie containing (i) no cannabis extract (ethanol/placebo), (ii) CBD-dominant cannabis extract (640 mg CBD + 20 mg Δ9-THC), or (iii) Δ9-THC-dominant cannabis extract (20 mg Δ9-THC and no CBD). After 30 minutes, participants consumed a cytochrome P450 (CYP) drug cocktail consisting of caffeine (CYP1A2), losartan (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and midazolam (CYP3A). Plasma and urine samples were collected (0-24 hours). The CBD + Δ9-THC brownie inhibited CYP2C19 > CYP2C9 > CYP3A > CYP1A2 (but not CYP2D6) activity, as evidenced by an increase in the geometric mean ratio of probe drug area under the plasma concentration-time curve (AUC) relative to placebo (AUCGMR ) of omeprazole, losartan, midazolam, and caffeine by 207%, 77%, 56%, and 39%, respectively. In contrast, the Δ9-THC brownie did not inhibit any of the CYPs. The CBD + Δ9-THC brownie increased Δ9-THC AUCGMR by 161%, consistent with CBD inhibiting CYP2C9-mediated oral Δ9-THC clearance. Except for caffeine, these interactions were well-predicted by our physiologically-based pharmacokinetic model (within 26% of observed interactions). Results can be used to help guide dose adjustment of drugs co-consumed with cannabis products and the dose of CBD in cannabis products to reduce interaction risk with Δ9-THC.

Acetaminophen (APAP) is commonly taken in overdose and can cause acute liver injury via the toxic metabolite NAPQI formed by cytochrome (CYP) P450 pathway. We aimed to evaluate the concentrations of APAP metabolites on presentation following an acute APAP poisoning and whether these predicted the subsequent onset of hepatotoxicity (peak alanine aminotransferase > 1,000 U/L). The Australian Toxicology Monitoring (ATOM) study is a prospective observational study, recruiting via two poison information centers and four toxicology units. Patients following an acute APAP ingestion presenting < 24 hours post-ingestion were recruited. Initial samples were analyzed for APAP metabolites, those measured were the nontoxic glucuronide (APAP-Glu) and sulfate (APAP-Sul) conjugates and NAPQI (toxic metabolite) conjugates APAP-cysteine (APAP-Cys) and APAP-mercapturate (APAP-Mer). The primary outcome was hepatotoxicity. In this study, 200 patients were included, with a median ingested dose of 20 g, 191 received acetylcysteine at median time of 5.8 hours post-ingestion. Twenty-six patients developed hepatotoxicity, one had hepatotoxicity on arrival (excluded from analysis). Those who developed hepatotoxicity had significantly higher total CYP metabolite concentrations: (36.8 μmol/L interquartile range (IQR): 27.8-51.7 vs. 10.8 μmol/L IQR: 6.9-19.5) and these were a greater proportion of total metabolites (5.4%, IQR: 3.8-7.7) vs. 1.7%, IQR: 1.3-2.6, P < 0.001)]. Furthermore, those who developed hepatotoxicity had lower APAP-Sul concentrations (49.1 μmol/L, IQR: 24.7-72.2 vs. 78.7 μmol/L, IQR: 53.6-116.4) and lower percentage of APAP-Sul (6.3%, IQR: 4.6-10.9 vs. 13.1%, IQR, 9.1-20.8, P < 0.001)]. This study found that those who developed hepatotoxicity had higher APAP metabolites derived from CYP pathway and lower sulfation metabolite on presentation. APAP metabolites may be utilized in the future to identify patients who could benefit from increased acetylcysteine or newer adjunct or research therapies.

Trimethoprim is predicted to inhibit several thiamine transporters, including the primary thiamine intestinal absorptive transporter, ThTR-2, and the hepatic and renal organic cation transporters, OCT1, OCT2, and MATEs. To investigate the effect of trimethoprim on thiamine absorption, studies were conducted in cells, mice, and healthy volunteers and supported by use of real-world data. In a randomized, crossover clinical study, seven healthy volunteers were given a single oral dose of thiamine or thiamine plus trimethoprim, followed by blood sampling. The thiamine area under the curve (AUC) increased with trimethoprim co-administration (P value = 0.031). Similar results were seen in mice. Trimethoprim appeared to act on thiamine absorption through inhibition of hepatic OCT1 as evidenced from its ability to modulate levels of isobutyrylcarnitine and propionylcarnitine, OCT1 biomarkers identified from metabolomic analyses. Real-world data further supported this finding, showing an association between trimethoprim use and higher levels of triglycerides, LDL cholesterol, and total cholesterol, consistent with OCT1 inhibition (P values: 2.2 × 10-16 , 5.75 × 10-7 , and 5.82 × 10-7 , respectively). These findings suggest that trimethoprim increases plasma levels of thiamine by inhibiting hepatic OCT1. Trimethoprim reduced urinary excretion and clearance of biomarkers for OCT2 and MATEs, consistent with inhibition of renal organic cation transporters. This inhibition did not appear to play a role in the observed increases in thiamine levels. This study highlights the potential for drug-nutrient interactions involving transporters, in addition to transporters' established role in drug-drug interactions.

Optimizing Ponatinib Treatment in CP-CML (OPTIC) was a randomized, phase II dose-optimization trial of ponatinib in chronic phase-chronic myeloid leukemia (CP-CML) resistant to ≥ 2 tyrosine kinase inhibitors or with T315I mutation. Patients were randomized to starting doses of 45-, 30-, or 15-mg ponatinib once daily. Patients receiving 45- or 30-mg reduced to 15-mg upon achievement of ≤ 1% BCR::ABL1IS (≥ molecular response with 2-log reduction (MR2)). The exposure-molecular response relationship was described using a four-state, discrete-time Markov model. Time-to-event models were used to characterize the relationship between exposure and arterial occlusive events (AOEs), grade ≥ 3 neutropenia, and thrombocytopenia. Increasing systemic exposures were associated with increasing probability of transitioning from no response to ≥ MR1, and from MR1 to ≥ MR1, with odds ratios of 1.63 (95% confidence interval (CI), 1.06-2.73) and 2.05 (95% CI, 1.53-2.89) for a 15-mg dose increase, respectively. Ponatinib exposure was a significant predictor of AOEs (hazard ratio (HR) 2.05, 95% CI, 1.43-2.93, for a 15-mg dose increase). In the exposure-safety models for neutropenia and thrombocytopenia, exposure was a significant predictor of grade ≥ 3 thrombocytopenia (HR 1.31, 95% CI, 1.05-1.64, for a 15-mg dose increase). Model-based simulations predicted a clinically meaningful higher rate of ≥ MR2 response at 12 months for the 45-mg starting dose (40.4%) vs. 30-mg (34%) and 15-mg (25.2%). The exposure-response analyses supported a ponatinib starting dose of 45 mg with reduction to 15 mg at response for patients with CP-CML.

Comment in Clin Pharmacol Ther. 2023 Apr;113(4):770. Clin Pharmacol Ther. 2023 Jun;113(6):1183-1184.

Due to their negative effects on hypoxic pulmonary vasoconstriction, dihydropyridine calcium channel inhibitors (DCCIs) can lead to hypoxia in patients with a pulmonary shunt. To date, only preclinical studies and case reports have focused on this potential adverse drug reaction. We aimed to assess the reporting association between DCCIs and hypoxia using the World Health Organization pharmacovigilance database (VigiBase). We performed a disproportionality analysis to evaluate the strength of the reporting association between i.v. clevidipine and nicardipine, thought to be a surrogate of patients in the intensive care unit, and hypoxia. The information component and the lower end of its 95% credibility interval were used to evaluate disproportionality. A description of the cases was made. Secondary outcomes included the association between all DCCIs and hypoxia compared with other treatments with similar indications, urapidil and labetalol, regardless of the route of administration. Association between oral nicardipine and hypoxia was also searched. A statistically significant signal of hypoxia was found for intravenous clevidipine and nicardipine. The time to onset was reported with a median of 2 days (interquartile range 1.5-4.5). Four dechallenges were performed with intravenous nicardipine, leading to the resolution of the symptoms. Regardless of the route of administration, a signal of hypoxia was also found for nimodipine but not for other drugs, including comparators. For nicardipine no signal of hypoxia was found with the oral route of administration. Our pharmacovigilance database analysis showed a significant association between the use of intravenous DCCIs and hypoxia.

Molnupiravir (MOV) is an oral antiviral for the treatment of coronavirus disease 2019 (COVID-19) in outpatient settings. This analysis investigated the relationship between β-D-N4-hydroxycytidine (NHC) pharmacokinetics and clinical outcomes in patients with mild to moderate COVID-19 in the phase III part of the randomized, double-blind, placebo-controlled MOVe-OUT trial. Logistic regression models of the dependency of outcomes on exposures and covariates were constructed using a multistep process. Influential covariates were identified first using placebo arm data, followed by assessment of exposure-dependency in drug effect using data from both the placebo and MOV arms. The exposure-response (E-R) analysis included 1,313 participants; 630 received MOV and 683 received placebo. Baseline viral load, baseline disease severity, age, weight, viral clade, active cancer, and diabetes were identified as significant determinants of response using placebo data. Absolute measures of viral load on days 5 and 10 were strong on-treatment predictors of hospitalization. An additive area under the curve (AUC)-based maximum effect (Emax ) model with a fixed Hill coefficient of 1 best represented the exposure-dependency in drug effect and the AUC50 was estimated to be 19,900 nM hour. Patients at 800 mg achieved near maximal response, which was larger than for 200 or 400 mg. The final E-R model was externally validated and predicted that the relative reduction in hospitalization with MOV treatment would vary with patient characteristics and factors in the population. In conclusion, the E-R results support the MOV dose of 800 mg twice daily to treat COVID-19. Many patient characteristics and factors impacted outcomes beyond drug exposures.

Oral azacitidine (oral-AZA) maintenance is approved for adults with acute myeloid leukemia (AML) in remission post-intensive chemotherapy, not proceeding to hematopoietic stem cell transplantation. This study aimed to develop a population pharmacokinetic (PopPK) model to characterize oral-AZA concentration-time profiles in patients with AML, myelodysplastic syndrome, or chronic myelomonocytic leukemia. PopPK-estimated exposure parameters were used to evaluate exposure-response relationships in the phase III QUAZAR AML-001 study. The PopPK dataset comprised 286 patients with 1,933 evaluable oral-AZA concentration records. The final PopPK model was a one-compartment model with first-order absorption incorporating an absorption lag time and first-order elimination. Regression analyses identified two oral-AZA exposure parameters (area under the plasma concentration-time curve at steady state (AUCss ); maximum plasma concentration (Cmax )) as statistically significant predictors for relapse-free survival (hazard ratio (HR) = 0.521, P < 0.001; HR = 0.630, P = 0.013; respectively), and AUCss as a significant predictor for overall survival (HR = 0.673, P = 0.042). The probability of grade ≥ 3 neutropenia was significantly increased with increases in AUCss (odds ratio (OR) = 5.71, 95% confidence interval (CI) = 2.73-12.62, P < 0.001), cumulative AUC through cycles 1 to 6 (OR = 2.71, 95% CI = 1.76-4.44, P < 0.001), and Cmax at steady-state (OR = 2.38, 95% CI = 1.23-4.76, P = 0.012). A decreasing trend was identified between AUCss and relapse-related schedule extensions, vs. an increasing trend between AUCss and event-related dose reductions. As the majority (56.8%) of patients required no dose modifications, and the proportions requiring schedule extension (19.4%) or dose reduction (22.9%) were almost equal, oral-AZA 300 mg once daily for 14 days is the optimal dosing schedule balancing survival benefit and safety risk.

Oral formulations prepared from the leaves of the kratom (Mitragyna speciosa) plant are increasingly used for their opioid-like effects to self-manage opioid withdrawal and pain. Calls to US poison centers involving kratom exposures increased >50-fold from 2011-2017, one-third of which reported concomitant use of kratom with drugs of abuse. Many of these drugs are eliminated primarily via cytochrome P450 (CYP) 3A and CYP2D6, raising concerns for potential adverse pharmacokinetic kratom-drug interactions. The impact of a single low dose of kratom tea (2 g) on the pharmacokinetics of the CYP3A probe midazolam (2.5 mg) and CYP2D6 probe dextromethorphan (30 mg) were assessed in 12 healthy adult participants after oral administration. Kratom showed no effect on dextromethorphan area under the plasma concentration time-curve (AUC) and maximum concentration (Cmax ; geometric mean ratio (90% confidence interval) 0.99 (0.83-1.19) and 0.96 (0.78-1.19), respectively) but a modest increase in midazolam AUC and Cmax (1.39 (1.23-1.57) and 1.50 (1.32-1.70), respectively). Lack of change in midazolam half-life (1.07 (0.98-1.17)) suggested that kratom primarily inhibited intestinal CYP3A. This inference was further supported by a physiologically based pharmacokinetic drug interaction model using the abundant alkaloid mitragynine, a relatively potent CYP3A time-dependent inhibitor in vitro (KI , ~4 μM; kinact , ~0.07 min-1 ). This work is the first to clinically evaluate the pharmacokinetic drug interaction potential of kratom. Co-consuming kratom with certain drugs extensively metabolized by CYP3A may precipitate serious interactions. These data fill critical knowledge gaps about the safe use of this increasingly popular natural product, thereby addressing ongoing public health concerns.

Recently, multiple chimeric antigen receptor T-cell (CAR-T)-based therapies have been approved for treating hematological malignancies, targeting CD19 and B-cell maturation antigen. Unlike protein or antibody therapies, CAR-T therapies are "living cell" therapies whose pharmacokinetics are characterized by expansion, distribution, contraction, and persistence. Therefore, this unique modality requires a different approach for quantitation compared with conventional ligand binding assays implemented for most biologics. Cellular (flow cytometry) or molecular assays (polymerase chain reaction (PCR)) can be deployed with each having unique advantages and disadvantages. In this article, we describe the molecular assays utilized: quantitative PCR (qPCR), which was the initial platform used to estimate transgene copy numbers and more recently droplet digital PCR (ddPCR) which quantitates the absolute copy numbers of CAR transgene. The comparability of the two methods in patient samples and of each method across different matrices (isolated CD3+ T-cells or whole blood) was also performed. The results show a good correlation between qPCR and ddPCR for the amplification of same gene in clinical samples from a CAR-T therapy trial. In addition, our studies show that the qPCR-based amplification of transgene levels was well-correlated, independent of DNA sources (either CD3+ T-cells or whole blood). Our results also highlight that ddPCR can be a better platform for monitoring samples at the early phase of CAR-T dosing prior to expansion and during long-term monitoring as they can detect samples with very low copy numbers with high sensitivity, in addition to easier implementation and sample logistics.

Primary human hepatocytes (PHHs) have been the gold standard in vitro model for the human liver and are crucial to predict hepatic drug-drug interactions. The aim of this work was to assess the utility of 3D spheroid PHHs to study induction of important cytochrome P450 (CYP) enzymes and drug transporters. The 3D spheroid PHHs from three different donors were treated for 4 days with rifampicin, dicloxacillin, flucloxacillin, phenobarbital, carbamazepine, efavirenz, omeprazole, or β-naphthoflavone. Induction of CYP1A1, CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, and CYP3A4, and transporters P-glycoprotein (P-gp)/ABCB1, multidrug resistance-associated protein 2 (MRP2)/ABCC2, ABCG2, organic cation transporter 1 (OCT1)/SLC22A1, SLC22A7, SLCO1B1, and SLCO1B3 were evaluated at mRNA and protein levels. Enzyme activity of CYP3A4, CYP2B6, CYP2C19, and CYP2D6 were also assessed. Induction of CYP3A4 protein and mRNA correlated well for all donors and compounds and had a maximal induction of five- to sixfold for rifampicin, which closely correlates to induction observed in clinical studies. Rifampicin induced the mRNA of CYP2B6 and CYP2C8 by 9- and 12-fold, whereas the protein levels of these CYPs reached 2- and 3-fold induction, respectively. Rifampicin induced CYP2C9 protein by 1.4-fold, whereas the induction of CYP2C9 mRNA was over 2-fold in all donors. Rifampicin induced ABCB1, ABCC2, and ABCG2 by 2-fold. In conclusion, 3D spheroid PHHs is a valid model to investigate mRNA and protein induction of hepatic drug-metabolizing enzymes and transporters, and this model provides a solid basis to study induction of CYPs and transporters, which translates to clinical relevance.

Grapefruit is a moderate to strong inactivator of CYP3A4, which metabolizes up to 50% of marketed drugs. The inhibitory effect is mainly attributed to furanocoumarins present in the fruit, irreversibly inhibiting preferably intestinal CYP3A4 as suicide inhibitors. Effects on CYP3A4 victim drugs can still be measured up to 24 hours after grapefruit juice (GFJ) consumption. The current study aimed to establish a physiologically-based pharmacokinetic (PBPK) grapefruit-drug interaction model by modeling the relevant CYP3A4 inhibiting ingredients of the fruit to simulate and predict the effect of GFJ consumption on plasma concentration-time profiles of various CYP3A4 victim drugs. The grapefruit model was developed in PK-Sim and coupled with previously developed PBPK models of CYP3A4 substrates that were publicly available and already evaluated for CYP3A4-mediated drug-drug interactions. Overall, 43 clinical studies were used for model development. Models of bergamottin (BGT) and 6,7-dihydroxybergamottin (DHB) as relevant active ingredients in GFJ were established. Both models include: (i) CYP3A4 inactivation informed by in vitro parameters, (ii) a CYP3A4 mediated clearance estimated during model development, as well as (iii) passive glomerular filtration. The final model successfully describes interactions of GFJ ingredients with 10 different CYP3A4 victim drugs, simulating the effect of the CYP3A4 inactivation on the victims' pharmacokinetics as well as their main metabolites. Furthermore, the model sufficiently captures the time-dependent effect of CYP3A4 inactivation as well as the effect of grapefruit ingestion on intestinal and hepatic CYP3A4 concentrations.

Realistic models predicting hepatobiliary processes in health and disease are lacking. We therefore aimed to develop a physiologically relevant human liver model consisting of normothermic machine perfusion (NMP) of explanted diseased human livers that can assess hepatic extraction, clearance, biliary excretion, and drug-drug interaction (DDI). Eleven livers were included in the study, seven with a cirrhotic and four with a noncirrhotic disease background. After explantation of the diseased liver, NMP was initiated. After 120 minutes of perfusion, a drug cocktail (rosuvastatin, digoxin, metformin, and furosemide; OATP1B1/1B3, P-gp, BCRP, and OCT1 model compounds) was administered to the portal vein and 120 minutes later, a second bolus of the drug cocktail was co-administered with perpetrator drugs to study relevant DDIs. The explanted livers showed good viability and functionality during 360 minutes of NMP. Hepatic extraction ratios close to in vivo reported values were measured. Hepatic clearance of rosuvastatin and digoxin showed to be the most affected by cirrhosis with an increase in maximum plasma concentration (Cmax ) of 11.50 and 2.89 times, respectively, compared with noncirrhotic livers. No major differences were observed for metformin and furosemide. Interaction of rosuvastatin or digoxin with perpetrator drugs were more pronounced in noncirrhotic livers compared with cirrhotic livers. Our results demonstrated that NMP of human diseased explanted livers is an excellent model to assess hepatic extraction, clearance, biliary excretion, and DDI. Gaining insight into pharmacokinetic profiles of OATP1B1/1B3, P-gp, BCRP, and OCT1 model compounds is a first step toward studying transporter functions in diseased livers.

Failure to perform adequate dose adjustment in patients with liver cirrhosis may be associated with increased toxicity. We compared the prediction of area under the curve (AUC) and clearance for the six compounds of the Basel phenotyping cocktail (caffeine, efavirenz, flurbiprofen, omeprazole, metoprolol, and midazolam) using a well-known physiology-based pharmacokinetic approach (physiologically-based pharmacokinetic [PBPK] approach, Simcyp) and a novel top-down method based on the systemic clearance in healthy volunteers adjusted for markers of liver and renal dysfunction ("top-down approach"). With few exceptions, plasma concentration-time curves were accurately predicted by the PBPK approach. In comparison to the measured AUC and clearance of these drugs in patients with liver cirrhosis and healthy controls, except for efavirenz, the estimates of both approaches were within two standard deviations of the mean for total and free drug concentrations. For both approaches, a correction factor for dose adjustment in patients with liver cirrhosis could be calculated for the drugs administered. AUCs calculated using the adjusted doses were comparable to the AUCs measured in control subjects, with slightly more accurate predictions generated by the PBPK approach. For drugs with a free fraction < 50%, predictions using free drug concentrations were more accurate than with total drug concentrations. In conclusion, both methods provided good qualitative predictions of the changes by liver cirrhosis in the pharmacokinetics of the six compounds investigated. The top-down approach is easier to implement but the PBPK approach predicted changes in drug exposure more accurately than the top-down approach and provided reliable estimates for plasma concentrations.

In June 2021, the US Food and Drug Administration (FDA) granted accelerated approval to aducanumab, a monoclonal antibody indicated for the treatment of Alzheimer's disease. The accelerated approval decision was controversial due to concerns about the use of an unvalidated surrogate measure, beta-amyloid, as the basis for approval and a lack of clinical outcome benefit. Between October 2021 and September 2022, we conducted a survey of a nationally representative group of internists, medical oncologists, and cardiologists to understand perspectives around aducanumab's approval and how this FDA decision may influence trust in other drugs approved through the accelerated approval program. Among 214 physician respondents familiar with the accelerated approval of aducanumab, 184 (86%) would not prescribe or recommend aducanumab. Further, 143 (67%) physicians reported losing trust in other drugs approved through the accelerated approval program due to the FDA's decision with aducanumab. As a growing number of similar novel Alzheimer's disease treatments are on the horizon, the first of which, lecanemab, already has received accelerated approval in January 2023, our survey findings provide insight into the impact of the FDA's regulatory decisions on the perspectives and prescribing behavior of physicians concerning these novel drug treatments.

Live biotherapeutic products (LBPs) are human microbiome therapies showing promise in the clinic for a range of diseases and conditions. Describing the kinetics and behavior of LBPs poses a unique modeling challenge because, unlike traditional therapies, LBPs can expand, contract, and colonize the host digestive tract. Here, we present a novel cellular kinetic-pharmacodynamic quantitative systems pharmacology model of an LBP. The model describes bacterial growth and competition, vancomycin effects, binding and unbinding to the epithelial surface, and production and clearance of butyrate as a therapeutic metabolite. The model is calibrated and validated to published data from healthy volunteers. Using the model, we simulate the impact of treatment dose, frequency, and duration as well as vancomycin pretreatment on butyrate production. This model enables model-informed drug development and can be used for future microbiome therapies to inform decision making around antibiotic pretreatment, dose selection, loading dose, and dosing duration.

Hybrid designs with both randomized arms and an external control cohort preserve key features of randomization and utilize external information to augment clinical trials. In this study, we propose to leverage high-quality, patient-level concurrent registries to enhance clinical trials and illustrate the impact on trial design for amyotrophic lateral sclerosis. The proposed methodology was evaluated in a randomized, placebo-controlled clinical trial. We used patient-level information from a well-defined, population-based registry, that was running parallel to the randomized clinical trial, to identify concurrently nonparticipating, eligible patients who could be matched with trial participants, and integrate them into the statistical analysis. We assessed the impact of the addition of the external controls on the treatment effect estimate, precision, and time to reach a conclusion. During the runtime of the trial, a total of 1,141 registry patients were alive; 473 (41.5%) of them fulfilled the eligibility criteria and 133 (11.7%) were enrolled in the study. A matched control population could be identified among the nonparticipating patients. Augmenting the randomized controls with matched external controls could have avoided unnecessary randomization of 17 patients (-12.8%) as well as reducing the study duration from 30.1 months to 22.6 months (-25.0%). Matching eligible external controls from a different calendar period led to bias in the treatment effect estimate. Hybrid trial designs utilizing a concurrent registry with rigorous matching can minimize bias due to a mismatch in calendar time and differences in standard of care, and may accelerate the development of new treatments.

Metformin is the first-line drug for type 2 diabetes (T2D) while acarbose is suggested as a viable alternative in Chinese patients with newly diagnosed T2D. However, few biomarkers have been established to guide the choice between these two agents. Mitochondrial DNA (mtDNA) copy number (mtDNA-CN) is a biomarker of mitochondrial function, which is associated with various metabolic outcomes. Using data from the trial of Metformin and Acarbose in Chinese as the Initial Hypoglycaemic Treatment (MARCH) (metformin n = 214; acarbose n = 198), we examined whether mtDNA-CN was associated with response to the drugs in terms of glycemic response and β-cell function protection response. The glycemic response is defined as the maximum glucose reduction of glycated hemoglobin A1c , fasting plasma glucose, or postprandial blood glucose during 48 weeks. β-cell function protection response is defined as the maximum increment of insulinogenic index (IGI) or disposition index (DI). For all three glycemic responses, mtDNA-CN was not significantly associated with either metformin or acarbose. Importantly, for β-cell function protection response, we found the increased mtDNA-CN was significantly associated with more IGI increment (beta: 0.84; 95% confidence interval (CI), 0.02 to 1.66) in the metformin group, but less IGI increment (beta: -1.38; 95% CI, -2.52 to -0.23) in the acarbose group. A significant interaction (P = 0.008) between mtDNA-CN and the treatment group was observed. Consistent results were also obtained when DI increment was used as a measure of β-cell function response. This study demonstrated the potential application of mtDNA-CN in guiding the treatment choice between metformin and acarbose based on β-cell protection.

A real-world association between direct oral anticoagulant (DOAC) concentration and clinical outcomes among Asian patients with atrial fibrillation (AF) is reported herein. Patients with AF aged ≥ 20 years who used DOAC for ≥ 3 days were enrolled. Trough and peak DOAC concentrations were measured and compared with the expected range reported in clinical trials. The Cox proportional hazard model was used to investigate the association between concentration and outcomes. From January 2016 to July 2022, a total of 859 patients were enrolled. Among them, 22.5%, 24.7%, 36.4%, and 16.4% were on dabigatran, rivaroxaban, apixaban, and edoxaban, respectively. Compared with clinical trials, the proportion of DOAC concentrations higher or lower than the expected range were 9.0% and 14.6% for trough, respectively, and 20.9% and 12.1% for peak, respectively. The average follow-up duration was 2.4 ± 1.6 years. The incidence of stroke and systemic thromboembolism (SSE) was 1.31 per 100-person years, and low trough concentration predicted SSE (hazard ratio (HR) = 2.78 (1.20, 6.46)). The incidence of major bleeding was 1.64 per 100-person years, and high trough was associated with major bleeding (HR = 2.63 (1.09, 6.39)). The association between peak concentration and SSE or major bleeding was nonsignificant. Off-label underdosing (odds ratio (OR) = 2.69 (1.70, 4.26)), once daily DOAC dosing (OR = 3.22 (2.07, 5.01)), and high creatinine clearance (OR = 1.02 (1.01, 1.03)) caused low trough concentration. Contrarily, congestive heart failure was significantly associated with high trough concentration (OR = 1.71 (1.01, 2.92)). In conclusion, trough DOAC concentration measurements should be considered among patients at risk of out-of-expected range DOAC concentrations.

2,5-dimethoxy-4-bromophenethylamine (2C-B) is a hallucinogenic phenethylamine derived from mescaline. Observational and preclinical data have suggested it to be capable of producing both subjective and emotional effects on par with other classical psychedelics and entactogens. Whereas it is the most prevalently used novel serotonergic hallucinogen to date, it's acute effects and distinctions from classical progenitors have yet to be characterized in a controlled study. We assessed for the first time the immediate acute subjective, cognitive, and cardiovascular effects of 2C-B (20 mg) in comparison to psilocybin (15 mg) and placebo in a within-subjects, double-blind, placebo-controlled study of 22 healthy psychedelic-experienced participants. 2C-B elicited alterations of waking consciousness of a psychedelic nature, with dysphoria, subjective impairment, auditory alterations, and affective elements of ego dissolution largest under psilocybin. Participants demonstrated equivalent psychomotor slowing and spatial memory impairments under either compound compared with placebo, as indexed by the Digit Symbol Substitution Test, Tower of London, and Spatial Memory Task. Neither compound produced empathogenic effects on the Multifaceted Empathy Test. 2C-B induced transient pressor effects to a similar degree as psilocybin. The duration of self-reported effects of 2C-B was shorter than that of psilocybin, largely resolving within 6 hours. Present findings support the categorization of 2C-B as a psychedelic of moderate experiential depth at doses given. Tailored dose-effect studies are needed to discern the pharmacokinetic dependency of 2C-B's experiential overlaps.

Oncolytic viruses (OVs) represent a potential therapeutic strategy in cancer treatment. However, there is currently a lack of comprehensive quantitative models characterizing clinical OV kinetics and distribution to the tumor. In this work, we present a mechanistic modeling framework for V937 OV, after intratumoral (i.t.) or intravascular (i.v.) administration in patients with cancer. A minimal physiologically-based pharmacokinetic model was built to characterize biodistribution of OVs in humans. Viral dynamics was incorporated at the i.t. cellular level and linked to tumor response, enabling the characterization of a direct OV killing triggered by the death of infected tumor cells and an indirect killing induced by the immune response. The model provided an adequate description of changes in V937 mRNA levels and tumor size obtained from phase I/II clinical trials after V937 administration. The model showed prominent role of viral clearance from systemic circulation and infectivity in addition to known tumor aggressiveness on clinical response. After i.v. administration, i.t. exposure of V937 was predicted to be several orders of magnitude lower compared with i.t. administration. These differences could be overcome if there is high virus infectivity and/or replication. Unfortunately, the latter process could not be identified at the current clinical setting. This work provides insights on selecting optimal OV considering replication rate and infectivity.

Mercaptopurine is a cornerstone of maintenance chemotherapy in childhood acute lymphoblastic leukemia (ALL). Its cytotoxic effects are mediated by 6-thioguanine nucleotides (TGNs) incorporation into lymphocyte DNA. Thiopurine methyltransferase (TPMT) inactivates mercaptopurine, and deficiency resulting from genetic variants increases TGN exposure and hematopoietic toxicity. Although mercaptopurine-dose reduction reduces toxicity risk without compromising relapse rate in patients with TPMT deficiency, dosing recommendations for those with moderately reduced activity (intermediate metabolizer (IM)) are less clear and their clinical impacts have yet to be established. This cohort study assessed the effect of TPMT IM status on mercaptopurine-associated toxicity and TGN blood exposure in pediatric patients with ALL initiated on standard dose mercaptopurine. Of 88 patients studied (mean age 4.8 years), 10 (11.4%) were TPMT IM, and all had undergone ≥ 3 cycles of maintenance therapy (80% completed). A larger proportion of TPMT IM than normal metabolizers (NM) had febrile neutropenia (FN) during the first two cycles of maintenance, reaching significance in the second cycle (57% vs. 15%, respectively; odds ratio = 7.33, P < 0.05). Compared to NM, FN events occurred more frequently and with prolonged duration in IM in cycles 1 and 2 (adjusted P < 0.05). IM had a 2.46-fold increased hazard ratio for FN, and about twofold higher TGN level than NM (P < 0.05). Myelotoxicity was more common in IM than NM (86% vs. 42%, respectively) during cycle 2 (odds ratio = 8.2, P < 0.05). TPMT IM initiated at a standard mercaptopurine dose are at greater risk for FN during early cycles of maintenance therapy, thus our findings support genotype-guided dose adjustment to reduce toxicity.

Ixazomib has been approved in several countries as single-agent maintenance therapy in newly diagnosed multiple myeloma, in both posttransplant and transplant-ineligible settings, based on two phase III studies. In these maintenance studies, patients were initially administered 3 mg ixazomib, escalating to 4 mg if the initial dose level was well tolerated through Cycles 1-4. Here, we report the results of exposure-response analyses of TOURMALINE-MM4, wherein relationships between exposure and clinical response, dose adjustments, and selected adverse events were evaluated. Similar progression-free survival benefits were observed across the range of ixazomib exposures achieved in the study. Moreover, increased ixazomib exposures corresponded to a higher probability of maintaining complete response. Exposure was not a significant predictor (P > 0.05) of hematological adverse events (anemia, neutropenia, thrombocytopenia) and peripheral neuropathy; however, higher exposures did correlate to increased probabilities of experiencing diarrhea, vomiting, nausea, rash, and fatigue. While ixazomib exposure was not predictive of dose reductions, lower apparent clearance values (corresponding to higher systemic exposures) were correlated with a reduced likelihood of escalating to the 4 mg dose. Thus, the dose titration approach balanced patient benefit and risk; it ensured that only patients for whom the 3 mg dose was safe/tolerable escalated to the higher dose, while maximizing the fraction of patients (85%) who were able to derive additional clinical benefit at 4 mg. Collectively, these results highlight the value of safety-driven personalized dosing to maximize patient benefit/risk.

The objective of this analysis was to describe patterns of prescription medication use during pregnancy, including secular trends, with consideration of indication, and distributions of use within demographic subgroups. We conducted a descriptive secondary analysis using data from 9,755 women whose infants served as controls in two large United States case-control studies from 1997-2011 and 2014-2018. After excluding vitamin, herbal, mineral, vaccine, i.v. fluid, and topical products and over-the-counter medications, the proportion of women that reported taking at least one prescription medication in the first trimester increased over the study years, from 37% to 50% of women. The corresponding proportions increased with increasing maternal age and years of education, were highest for non-Hispanic White women (47%) and lowest for Hispanic women (24%). The most common indication for first trimester use of a medication was infection (12-15%). Increases were observed across the years for medications used for indications related to nausea/vomiting, depression/anxiety, infertility, thyroid disease, diabetes, and epilepsy. The largest relative increase in use among women was observed for medications to treat nausea/vomiting, which increased from 3.8% in the earliest years of the study (1997-2001) to 14.8% in 2014-2018, driven in large part by ondansetron use. Prescription medication use in the first trimester of pregnancy is common and increasing. Many medical conditions require treatments among pregnant women, often involving pharmacotherapy, which necessitates consideration of the risk and safety profiles for both mother and fetus.

The US Food and Drug Administration's (FDA's) routine postmarketing drug safety monitoring may lead to safety-related labeling changes for identified risks. Additionally, the Best Pharmaceuticals for Children Act (BPCA) and Pediatric Research Equity Act (PREA) require the FDA to conduct postmarket pediatric-focused safety reviews of adverse events. The purpose of these pediatric reviews is to identify risks associated with drug or biological products 18 months after the FDA approves a pediatric labeling change pursuant to studies conducted under the BPCA or PREA. These reviews are presented to the FDA Pediatric Advisory Committee (PAC) or publicly posted on FDA's website. The aim of this study was to evaluate the impact of pediatric reviews prompted by BPCA/PREA from October 1, 2013, to September 30, 2019. The impact was quantified by the number of new safety signals identified and the subsequent safety-related labeling changes resulting from pediatric reviews relative to safety-related labeling changes triggered by other data sources. Among 163 products with at least one pediatric review completed, a new safety signal that resulted in a safety-related labeling change was found for 5 of these products (representing 3 active ingredients); none described risks specific to the pediatric population. Between October 2013 and September 2021, there were 585 safety-related labeling changes implemented for products with at least one completed pediatric review. Less than 1% of 585 safety-related labeling changes were the result of a mandated pediatric review. Our study suggests that mandated pediatric reviews conducted 18 months after a pediatric labeling change provided minimal value over other postmarket safety surveillance activities.

Clinical trials have demonstrated the benefit of PD-1/PD-L1 blocking antibodies for the treatment of patients with advanced non-small cell lung cancer (NSCLC) in defined patient populations that often exclude patients with moderate or severe hepatic or renal impairment. We assessed the association between overall survival (OS) and baseline organ function in patients with advanced NSCLC treated with PD-1/PD-L1 blocking antibodies in real-world data (RWD; patient-level data from electronic health records) and pooled clinical trial data submitted to the US Food and Drug Administration (FDA). The Kaplan-Meier estimator was used to estimate OS in different subgroups based on organ function. Unadjusted and adjusted Cox proportional hazards models were used to estimate the association between OS and organ function. In this hypothesis-generating study, baseline renal impairment did not appear to be associated with OS, while patients with baseline liver impairment had shorter OS. RWD provided information on a broader range of renal and hepatic function than was evaluated in clinical trials and hold promise to complement trial data in better understanding populations not represented in clinical trials.

The Research Acceleration for Cure and Equity (RACE) for Children Act requires sponsors to submit a Pediatric Study Plan (PSP) with a proposed pediatric investigation of new molecularly targeted drugs and biologics that are intended for treatment of adult cancers, and whose target is relevant to pediatric cancer or provide a justification for a plan to request a deferral or waiver of the required investigation. A landscape analysis was performed to identify trends in information gaps associated with a sponsor's first initial PSP (iPSP) submission for oncologic new molecular entities received in 2021. Comments sent to sponsors by the US Food and Drug Administration (FDA) during the review process of each evaluated iPSP were categorized using nine flags relating to different portions of the PSP. For iPSPs that included a plan for a full waiver request, the most common information gap was inadequate justification based on molecular target relevance. All other sponsor proposed plans (deferral and/or partial waiver or investigation) were found to have information gaps related to clinical study features, clinical pharmacology, and/or missing clinical or nonclinical data. This landscape analysis of iPSPs shows the trends in comments that often occur during initial review and may help to provide sponsors with more direction for preparing an adequate iPSP to fulfill statutory requirements aimed at ensuring pediatric patients are considered in the development of new molecularly targeted drugs.

Dabigatran is the first of four direct-acting oral anticoagulants approved to prevent stroke in adult patients with atrial fibrillation using a fixed two-dose scheme compared with warfarin dosing adjusted to a prothrombin time range associated with optimal risk reduction in stroke and serious bleeding. The pivotal phase III trial found dabigatran, depending on dose, is superior to warfarin in stroke reduction and similar in bleeding risk while also showing dabigatran efficacy and safety correlate with steady-state plasma concentrations. Because the relationship between dabigatran dose and plasma concentration is highly variable, a previously developed population pharmacokinetic model of over 9,000 clinical trial patients was used as a basis for simulations comparing the performance of dosing via the drug label to other proposed doses and regimens. Assessment of dosing regimen performance was based on simulations of trough plasma levels within the therapeutic concentration range of 75-150 ng/mL over a renal function range of 15-250 mL/min creatinine clearance, representing extremes for real-world patients. An improved regimen that best achieves this therapeutic range was identified, requiring five different dosing schedules, corresponding to specified renal function ranges, compared with the two approved in the label. The discussion focuses on how this information could better inform patient outcomes and future dabigatran development.

Face recognition deficits occur in diseases such as prosopagnosia, autism, Alzheimer's disease, and dementias. The objective of this study was to evaluate whether degrading the architecture of artificial intelligence (AI) face recognition algorithms can model deficits in diseases. Two established face recognition models, convolutional-classification neural network (C-CNN) and Siamese network (SN), were trained on the FEI faces data set (~ 14 images/person for 200 persons). The trained networks were perturbed by reducing weights (weakening) and node count (lesioning) to emulate brain tissue dysfunction and lesions, respectively. Accuracy assessments were used as surrogates for face recognition deficits. The findings were compared with clinical outcomes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set. Face recognition accuracy decreased gradually for weakening factors less than 0.55 for C-CNN, and 0.85 for SN. Rapid accuracy loss occurred at higher values. C-CNN accuracy was similarly affected by weakening any convolutional layer whereas SN accuracy was more sensitive to weakening of the first convolutional layer. SN accuracy declined gradually with a rapid drop when nearly all nodes were lesioned. C-CNN accuracy declined rapidly when as few as 10% of nodes were lesioned. CNN and SN were more sensitive to lesioning of the first convolutional layer. Overall, SN was more robust than C-CNN, and the findings from SN experiments were concordant with ADNI results. As predicted from modeling, brain network failure quotient was related to key clinical outcome measures for cognition and functioning. Perturbation of AI networks is a promising method for modeling disease progression effects on complex cognitive outcomes.

Although the United States and Europe have shifted to the prescription use of oral diclofenac due to several serious incidences of cardiotoxicity, it is one of the most commonly used over-the-counter (OTC) pain medicines in major parts of the world. We elucidated the quantitative and tissue-specific contribution of uridine diphosphate-glucuronosyltransferases 17 (UGT2B17) in diclofenac metabolism and pharmacokinetics (PK). UGT2B17 is one of most deleted genes in humans with the gene deletion frequency ranging from ~ 20% in White population to 90% in Japanese population. The human intestinal and liver microsomes isolated from the high-UGT2B17 expressing individuals showed 21- and 4-fold greater rate of diclofenac glucuronide (DG) formation than in the null-UGT2B17 carriers, respectively. The greater contribution of intestinal UGT2B17 was confirmed by a strong correlation (R = 0.78, P < 0.001) between UGT2B17 abundance and DG formation in individual intestinal microsomes (n = 14). However, because UGT2B17 is a minor UGT isoform in the liver, DG formation rate correlated better with the expression of UGT2B7. The proteomics-informed physiologically-based pharmacokinetic (PBPK) model explains the reported higher exposure of diclofenac in women consistent with ~ 3-fold lower expression of UGT2B17. Similarly, our in silico predictions also corroborate with the reported higher exposure and lower standard clinical dose of diclofenac in Japanese population. Therefore, variable UGT2B17 mediated metabolism of oral diclofenac is a cause of concern, especially in the developing countries where it is still used as an OTC drug. The ontogeny data of UGTs in human hepatocytes can be utilized in developing PBPK models for predicting PK in the pediatric population.

The impact of electronic health record (EHR) discontinuity (i.e., receiving care outside of a given EHR system) on EHR-based risk prediction is unknown. We aimed to assess the impact of EHR-continuity on the performance of clinical risk scores. The study cohort consisted of patients aged ≥ 65 years with ≥ 1 EHR encounter in the 2 networks in Massachusetts (MA; 2007/1/1-2017/12/31, internal training and validation dataset), and one network in North Carolina (NC; 2007/1/1-2016/12/31, external validation dataset) that were linked with Medicare claims data. Risk scores were calculated using EHR data alone vs. linked EHR-claims data (not subject to misclassification due to EHR-discontinuity): (i) combined comorbidity score (CCS), (ii) claim-based frailty score (CFI), (iii) CHAD2 DS2 -VASc, and (iv) Hypertension, Abnormal renal/liver function, Stroke, Bleeding, Labile, Elderly, and Drugs (HAS-BLED). We assessed the performance of CCS and CFI predicting death, CHAD2 DS2 -VASc predicting ischemic stroke, and HAS-BLED predicting bleeding by area under receiver operating characteristic curve (AUROC), stratified by quartiles of predicted EHR-continuity (Q1-4). There were 319,740 patients in the MA systems and 125,380 in the NC system. In the external validation dataset, AUROC for EHR-based CCS predicting 1-year risk of death was 0.583 in Q1 (lowest) EHR-continuity group, which increased to 0.739 in Q4 (highest) EHR-continuity group. The corresponding improvement in AUROC was 0.539 to 0.647 for CFI, 0.556 to 0.637 for CHAD2 DS2 -VASc, and 0.517 to 0.556 for HAS-BLED. The AUROC in Q4 EHR-continuity group based on EHR alone approximates that based on EHR-claims data. The prediction performance of four clinical risk scores was substantially worse in patients with lower vs. high EHR-continuity.

Dipeptidyl peptidase-4 inhibitors (DPP-4i) interact with sulfonylureas to increase their risk of hypoglycemia. Our population-based study assessed whether intraclass pharmacologic heterogeneity among sulfonylureas (long- vs. short-acting) and DPP-4i (peptidomimetic vs. non-peptidomimetic) modifies this interaction. We conducted a cohort study using the UK's Clinical Practice Research Datalink Aurum linked to hospitalization and vital statistics data. We assembled a cohort of patients initiating sulfonylureas (2007-2020). Using a time-varying exposure definition, we assessed the risk of severe hypoglycemia (hospitalization with or death due to hypoglycemia) associated with (i) concomitant use of long-acting sulfonylureas (glimepiride and glibenclamide) with DPP-4i compared with concomitant use of short-acting sulfonylureas (gliclazide and glipizide) with DPP-4i; and (ii) concomitant use of sulfonylureas with peptidomimetic DPP-4i (saxagliptin and vildagliptin) compared with concomitant use of sulfonylureas with non-peptidomimetic DPP-4i (sitagliptin, linagliptin, and alogliptin). Time-dependent Cox models estimated confounder-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs). Our cohort included 196,138 sulfonylurea initiators. During a median follow-up of 6 years, 8,576 events of severe hypoglycemia occurred. Compared with concomitant use of short-acting sulfonylureas with DPP-4i, concomitant use of long-acting sulfonylureas with DPP-4i was not associated with the risk of severe hypoglycemia (adjusted HR: 0.87, 95% CI: 0.65-1.16). Compared with concomitant use of sulfonylureas with non-peptidomimetic DPP-4i, concomitant use of sulfonylureas with peptidomimetic DPP-4i was also not associated with the risk of severe hypoglycemia (HR: 0.96, 95% CI: 0.76-1.22). Intra-class pharmacologic heterogeneity did not modify the association between concomitant use of sulfonylureas (short- vs. long-acting) and DPP-4i (peptidomimetic vs. non-peptidomimetic) and the risk of severe hypoglycemia.

Flucloxacillin is a widely used antibiotic. It is an agonist to the nuclear receptor PXR that regulates the expression of cytochrome P450 (CYP) enzymes. Treatment with flucloxacillin reduces warfarin efficacy and plasma concentrations of tacrolimus, voriconazole, and repaglinide. We conducted a translational study to investigate if flucloxacillin induces CYP enzymes. We also investigated if flucloxacillin induces its own metabolism as an autoinducer. We performed a randomized, unblinded, two-period, cross-over, clinical pharmacokinetic cocktail study. Twelve healthy adults completed the study. They ingested 1 g flucloxacillin 3 times daily for 31 days, and we assessed the full pharmacokinetics of the Basel cocktail drugs on days 0, 10, and 28, and plasma concentrations of flucloxacillin on days 0, 9, and 27. The 3D spheroid of primary human hepatocytes (PHHs) were exposed to flucloxacillin (concentration range: 0.15-250 μM) for 96 hours. Induction of mRNA expression, protein abundance, and enzyme activity of CYP enzymes were assessed. Flucloxacillin treatment reduced the metabolic ratio of midazolam (CYP3A4), (geometric mean ratio (GMR) 10 days (95% confidence interval (CI)): 0.75 (0.64-0.89)) and (GMR 28 days (95% CI): 0.72 (0.62-0.85)). Plasma concentrations of flucloxacillin did not change during 27 days of treatment. Flucloxacillin caused concentration-dependent induction of CYP3A4 and CYP2B6 (mRNA, protein, and activity), CYP2C9 (mRNA and protein), CYP2C19 (mRNA and activity), and CYP2D6 (activity) in 3D spheroid PHH. In conclusion, flucloxacillin is a weak inducer of CYP3A4, which may lead to clinically relevant drug-drug interactions for some narrow therapeutic range drugs that are substrates of CYP3A4.

Eltrombopag is clinically approved for use in immune thrombocytopenia (ITP), chronic hepatitis C-related thrombocytopenia, and aplastic anemia and suitable for children; however, data on its overall safety profile are scarce. This study aimed to explore the clinical features of adverse drug events (ADEs) associated with eltrombopag in different age groups using individual case safety reports (ICSRs) from the World Health Organization database VigiBase and the US Food and Drug Administration Adverse Event Reporting System database from 2008 to 2022 in combination with a meta-analysis of data from randomized clinical trials in the literature from inception to July 28, 2022. We conducted disproportionality analyses by grouping patients into the following age groups: 0-17 (0-23 months, 2-11 years, and 12-17 years), 18-64, and ≥ 65 years. The ADEs about hepatobiliary disorders, thrombosis, skin and subcutaneous tissue disorders, infections, and so on were observed more differently in each age group. Meta-analysis results showed differences in the four system organ classes between adults and children with ITP: infections and infestations, general disorders and administration site conditions, skin and subcutaneous tissue disorders, and investigations. The adverse drug reactions in the latest version of instructions were searched in the databases to analyze their postmarketing safety signal strength. We observed signals of elevated alanine aminotransferase, aspartate aminotransferase, and blood bilirubin levels in all age groups. For children, urinary tract infection and back pain showed signals. Due to the inherent limitations of pharmacovigilance studies, more experiments are needed to assess the risks of eltrombopag in different ages.

Ethosuximide was identified as the optimal option for new-onset childhood absence epilepsy (CAE) in a randomized, two-phase dose escalation comparative effectiveness trial of ethosuximide, lamotrigine, and valproic acid. However, 47% of ethosuximide initial monotherapy participants experienced short-term treatment failure. This study aimed to characterize the initial monotherapy ethosuximide exposure-response relationship and to propose model-informed precision dosing guidance. Dose titration occurred over a 16-20-week period until patients experienced seizure freedom or intolerable side effects. Subjects with initial monotherapy failure were randomized to one of the other two medications and dose escalation was repeated. A population pharmacokinetic model was created using plasma concentration data (n = 1,320), collected at 4-week intervals from 211 unique participants during both the initial and second monotherapy phases. A logistic regression analysis was performed on the initial monotherapy cohort (n = 103) with complete exposure-response data. Eighty-four participants achieved seizure freedom with a wide range of ethosuximide area under the curves (AUC) ranging from 420 to 2,420 μg·h/mL. AUC exposure estimates for achieving a 50% and 75% probability of seizure freedom were 1,027 and 1,489 μg·h/mL, respectively, whereas the corresponding cumulative frequency of intolerable adverse events was 11% and 16%. Monte Carlo Simulation indicated a daily dose of 40 and 55 mg/kg to achieve 50% and 75% probability of seizure freedom in the overall population, respectively. We identified the need for adjusted mg/kg dosing in different body weight cohorts. This ethosuximide proposed model-informed precision dosing guidance to achieve seizure freedom carries promise to optimize initial monotherapy success for patients with CAE.

Resistant hypertension is defined as uncontrolled blood pressure (BP) despite the use of three or more antihypertensive drugs of different classes. Although genetic factors may greatly contribute to hypertension with resistance to multiple drug classes, more than for general hypertension, its pathogenesis remains unknown. To reveal the genetic background of resistant hypertension, we categorized 32,239 patients whose data were obtained from the BioBank Japan Project, by prescription of 7 classes of antihypertensive drugs and performed genome-wide association studies (GWAS). Our GWAS identified four loci with significant association (P < 5 × 10-8 ): rs6445583 in CACNA1D and rs12308051 in the intergenic region on chromosome 12 for angiotensin II receptor blockers, rs35497065 in FOXA3 for calcium channel blockers, and rs11066280 in HECTD4 for αβ-blockers. Because these loci are known to be susceptibility loci for hypertension and/or BP, our results indicate that resistant hypertension is caused by a combination of excessive BP and drug resistance to each antihypertensive pharmacological class. Furthermore, to investigate the genetic difference between BP traits and the treatment effectiveness of antihypertensive drugs, we performed gene-set analysis and calculated the genetic correlation continuously. Most of the genetic factors were in common between BP traits and antihypertensive effectiveness, but it seems that the genetic architecture of the drug response to antihypertensive treatment is more complicated than BP traits. This corresponds to the well-known mosaic theory of hypertension. Our findings reveal the complex pathogenesis of hypertension with resistance to multiple classes of antihypertensive drugs.

The STRIDE (Single Tremelimumab Regular Interval Durvalumab) regimen of single-dose tremelimumab 300 mg, plus durvalumab 1,500 mg every 4 weeks demonstrated potential for long-term survival in studies of unresectable hepatocellular carcinoma (uHCC; Study 22 and HIMALAYA). The aim of this analysis was to investigate changes in proliferating CD4+ Ki67+ and CD8+ Ki67+ T cells and their relationship with tremelimumab exposure in patients with uHCC. Median cell count, change from baseline, and percent change from baseline in CD4+ and CD8+ T cells peaked around 14 days after STRIDE. A model of CD4+ and CD8+ T cell response to tremelimumab exposure was developed. Patients with lower baseline T cell counts had a greater percent change from baseline in T cell response to tremelimumab, and baseline T-cell count was included in the final model. With the full covariate model, the half-maximal effective concentration (EC50 ) of tremelimumab was 6.10 μg/mL (standard error = 1.07 μg/mL); > 98.0% of patients were predicted to have a minimum plasma concentration greater than EC50 with tremelimumab 300 or 750 mg. For EC75 (9.82 μg/mL), 69.5% and 98.2% of patients were predicted to exceed the EC75 with tremelimumab 300 and 750 mg, respectively. This analysis supports the clinical hypothesis that combination anti-cytotoxic T-lymphocyte-associated antigen 4 (anti-CTLA-4) and anti-programmed cell death ligand-1 (anti-PD-L1) therapy primes an immune response that may then be sustained by anti-PD-L1 monotherapy and supports the clinical utility of the STRIDE regimen in patients with uHCC. These insights may also help inform dose selection of anti-CTLA-4 plus anti-PD-L1 combination strategies.

The activity of the membrane transporters organic anion-transporting polypeptide 1B1 (OATP1B1) & breast cancer resistance protein (BCRP) (rosuvastatin) and P-glycoprotein (P-gp) (fexofenadine) was evaluated in patients with chronic hepatitis C virus (HCV) infection (n = 28), genotypes 1 and 3, investigated before the treatment with direct-acting antiviral agents (Phase 1) and up to 30 days after the assessment of the virologic response (Phase 2). Participants allocated in Groups 1 (n = 15; F0/F1 and F2, mild to moderate liver fibrosis) and 2 (n = 13; F3 and F4, advanced course of liver fibrosis/cirrhosis) received in both phases fexofenadine (10 mg) and rosuvastatin (2 mg). OATP1B1 & BCRP activity (rosuvastatin area under the plasma concentration-time curve of rosuvastatin from time zero to infinity (AUC0-∞ )) was reduced in Groups 1 and 2, respectively, by 25% (ratio 0.75 (0.53-0.82), P < 0.01) and 31% (ratio 0.69 (0.46-0.85), P < 0.05) in Phase 1 compared with Phase 2. OATP1B1 & BCRP activity was reduced in Phases 1 and 2, respectively, by 49% (median ratio 1.51 (1.17-2.20), P < 0.05) and 61% (ratio 1.39 (1.16-2.02), P < 0.01) in Group 2 compared with Group 1. P-gp activity (fexofenadine AUC0-∞ ) was also reduced in Phase 1 compared with Phase 2 (ratio Phase2/Phase1 0.79 (0.66-0.96) in Group 1 and 0.81 (0.69-0.96) in Group 2) as well as in Group 2 compared with Group 1 in both Phases (ratio Group2/Group1 1.47 (1.08-2.01) in Phase 1 and 1.51 (1.10-2.07) in Phase 2). Thus, clinicians administering OATP1B1 & BCRP and P-gp substrates with low therapeutic indexes should consider the evolution of the treatment and the stage of HCV infection.

Using pharmacogenetics (PGx) to inform clinical decision making can benefit patients but clinical use of PGx testing has been limited. Existing genetics data obtained in the course of research could be used to identify patients who are suspected, but have not yet been confirmed, to carry clinically actionable genotypes, in whom confirmatory genetic testing could be conducted for highly efficient PGx implementation. Herein, we demonstrate that it is regulatorily and technically feasible to implement PGx by identifying suspected carriers of actionable genotypes within an institutional genetics data repository and conduct confirmatory PGx testing immediately prior to that patient receiving the PGx-relevant drug, using a case study of DPYD testing prior to fluoropyrimidine chemotherapy. In 2 years since launching this program, ~ 3,000 suspected DPYD carriers have been passively monitored and one confirmed DPYD carrier was prevented from receiving unacceptably toxic fluoropyrimidine treatment, for minimal cost and effort. Now that we have demonstrated the feasibility of this strategy, we plan to transition to PGx panel testing and expand implementation to other genes and drugs for which the evidence of clinical benefit of PGx-informed treatment is high but PGx testing is not generally conducted. This highly efficient implementation process will maximize the clinical benefits of testing and could be explored at other institutions that have research-only genetic data repositories to expand the number of patients who benefit from PGx-informed treatment while we continue to work toward wide-scale adoption of PGx testing and implementation.

Tocilizumab and sarilumab are IL-6-receptor antagonists registered for rheumatoid arthritis (RA), with equal effectiveness and safety. Switching from tocilizumab to sarilumab could be a strategy to reduce injection burden, in case of drug shortages, and to reduce costs. This study therefore aims to investigate the effectiveness and safety of switching patients with RA with well-controlled disease under tocilizumab treatment to sarilumab. Patients with RA with low Disease Activity Score 28 (DAS28;-CRP < 2.9 or < 3.5 with clinical judgment), on stable dose tocilizumab (> 6 months) were offered to switch to sarilumab. Patients who switched and consented were followed for 6 months. Sarilumab was started at 200 mg and double the last tocilizumab interval. Co-primary outcomes at 6 months were (i) the 90% confidence interval (CI) of DAS28-CRP change from baseline compared with the non-inferiority margin of 0.6 and (ii) the 90% CI of the proportion of patients persisting with sarilumab, compared with a prespecified minimum of 70%. Of 50 invited patients, 25 agreed to switch to sarilumab, and 23 patients switched and were included. One patient was lost to follow-up immediately after inclusion, therefore 22 patients are included in the analyses. At 6 months, mean change in DAS28-CRP was 0.48 (90% CI: 0.11-0.87), compared with the non-inferiority margin of 0.6. Sarilumab persistence was 68% (90% CI: 51-82%, 15 out of 22 patients), compared with the prespecified minimum of 70%. Non-medical switching from tocilizumab to sarilumab in patients doing well on tocilizumab failed to show non-inferiority regarding disease activity and drug persistence.

Trial results may not be generalizable to target populations treated in clinical practice with different distributions of baseline characteristics that modify the treatment effect. We used outcome models developed with trial data to predict treatment effects in Medicare populations. We used data from the Randomized Evaluation of Long-Term Anticoagulation Therapy trial (RE-LY), which investigated the effect of dabigatran vs. warfarin on stroke or systemic embolism (stroke/SE) among patients with atrial fibrillation. We developed outcome models by fitting proportional hazards models in trial data. Target populations were trial-eligible Medicare beneficiaries who initiated dabigatran or warfarin in 2010-2011 ("early") and 2010-2017 ("extended"). We predicted 2-year risk ratios (RRs) and risk differences (RDs) for stroke/SE, major bleeding, and all-cause death in the Medicare populations using the observed baseline characteristics. The trial and early target populations had similar mean (SD) CHADS2 scores (2.15 (SD 1.13) vs. 2.15 (SD 0.91)) but different mean ages (71 vs. 79 years). Compared with RE-LY, the early Medicare population had similar predicted benefit of dabigatran vs. warfarin for stroke/SE (trial RR = 0.63, 95% confidence interval (CI) = 0.50 to 0.76 and RD = -1.37%, -1.96% to -0.77%, Medicare RR = 0.73, 0.65 to 0.82 and RD = -0.92%, -1.26% to -0.59%) and risks for major bleeding and all-cause death. The time-extended target population showed similar results. Outcome model-based prediction facilitates estimating the average treatment effects of a drug in different target populations when treatment and outcome data are unreliable or unavailable. The predicted effects may inform payers' coverage decisions for patients, especially shortly after a drug's launch when observational data are scarce.

Pharmacogenomics studies how genes influence a person's response to treatment. When complex phenotypes are influenced by multiple genetic variations with little effect, a single piece of genetic information is often insufficient to explain this variability. The application of machine learning (ML) in pharmacogenomics holds great potential - namely, it can be used to unravel complicated genetic relationships that could explain response to therapy. In this study, ML techniques were used to investigate the relationship between genetic variations affecting more than 60 candidate genes and carboplatin-induced, taxane-induced, and bevacizumab-induced toxicities in 171 patients with ovarian cancer enrolled in the MITO-16A/MaNGO-OV2A trial. Single-nucleotide variation (SNV, formerly SNP) profiles were examined using ML to find and prioritize those associated with drug-induced toxicities, specifically hypertension, hematological toxicity, nonhematological toxicity, and proteinuria. The Boruta algorithm was used in cross-validation to determine the significance of SNVs in predicting toxicities. Important SNVs were then used to train eXtreme gradient boosting models. During cross-validation, the models achieved reliable performance with a Matthews correlation coefficient ranging from 0.375 to 0.410. A total of 43 SNVs critical for predicting toxicity were identified. For each toxicity, key SNVs were used to create a polygenic toxicity risk score that effectively divided individuals into high-risk and low-risk categories. In particular, compared with low-risk individuals, high-risk patients were 28-fold more likely to develop hypertension. The proposed method provided insightful data to improve precision medicine for patients with ovarian cancer, which may be useful for reducing toxicities and improving toxicity management.

During systemic inflammation, pro-inflammatory cytokines alter metabolism and transport of drugs affecting the clinical outcome. We used an in vivo like human 3D liver spheroid model to study the effects and mechanisms of pro-inflammatory cytokines on the expression of 9 different genes encoding enzymes responsible for the metabolism of > 90% of clinically used drugs. Treatment of spheroids with pathophysiologically relevant concentrations of IL-1β, IL-6, or TNFα resulted in a pronounced decrease in mRNA expression of CYP3A4 and UGT2B10 within 5 hours. The reduction of CYP1A2, CYP2C9, CYP2C19, and CYP2D6 mRNA expression was less pronounced, whereas the pro-inflammatory cytokines caused increased CYP2E1, and UGT1A3 mRNA expression. The cytokines did not influence expression of key nuclear proteins, nor the activities of specific kinases involved in the regulation of genes encoding drug metabolizing enzymes. However, ruxolitinib, a JAK1/2 inhibitor, inhibited the IL-6 dependent increase in CYP2E1 and the decrease in CYP3A4 and UGT2B10 mRNA expression. We evaluated the effect of TNFα in hepatocytes in 2D plates and found a rapid decrease in drug-metabolizing enzyme mRNA both in the absence or presence of the cytokines. Taken together, these data suggest that pro-inflammatory cytokines regulate multiple gene- and cytokine-specific events seen in in vivo and in 3D but not in 2D liver models. We propose that the 3D spheroid system is suitable for the prediction of drug metabolism under conditions of inflammation and constitutes a versatile system for short- and long-term preclinical and mechanistic studies of cytokine-induced changes in drug metabolism.

Whereas islet autoantibodies (AAs) are well-established risk factors for developing type 1 diabetes (T1D), there is a lack of biomarkers endorsed by regulators to enrich clinical trial populations for those at risk of developing T1D. As such, the development of therapies that delay or prevent the onset of T1D remains challenging. To address this drug development need, the Critical Path Institute's T1D Consortium (T1DC) acquired patient-level data from multiple observational studies and used a model-based approach to evaluate the utility of islet AAs as enrichment biomarkers in clinical trials. An accelerated failure time model was developed, discussed in our previous publication, which provided the underlying evidence required to receive a qualification opinion for islet AAs as enrichment biomarkers from the European Medicines Agency (EMA) in March 2022. To further democratize the use of the model for scientists and clinicians, we developed a Clinical Trial Enrichment Graphical User Interface. The interactive tool allows users to specify trial participant characteristics, including the percentage of participants with a specific AA combination. Users can specify ranges for participant baseline age, sex, blood glucose measurement from the 120-minute timepoints of an oral glucose tolerance test, and HbA1c. The tool then applies the model to predict the mean probability of a T1D diagnosis for that trial population and renders the results to the user. To ensure adequate data privacy and to make the tool open-source, a deep learning-based generative model was used to generate a cohort of synthetic subjects that underpins the tool.

To protect people from severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, tremendous research efforts have been made toward coronavirus disease 19 (COVID-19) treatment development. Externally controlled trials (ECTs) may help reduce their development time. To evaluate whether ECT using real-world data (RWD) of patients with COVID-19 is feasible enough to be used for regulatory decision making, we built an external control arm (ECA) based on RWD as a control arm of a previously conducted randomized controlled trial (RCT), and compared it to the control arm of the RCT. The electronic health record (EHR)-based COVID-19 cohort dataset was used as RWD, and three Adaptive COVID-19 Treatment Trial (ACTT) datasets were used as RCTs. Among the RWD datasets, eligible patients were evaluated as a pool of external control subjects of the ACTT-1, ACTT-2, and ACTT-3 trials, respectively. The ECAs were built using propensity score matching, and the balance of age, sex, and baseline clinical status ordinal scale as covariates between the treatment arms of Asian patients in each ACTT and the pools of external control subjects was assessed before and after 1:1 matching. There was no statistically significant difference in time to recovery between ECAs and the control arms of each ACTT. Among the covariates, the baseline status ordinal score had the greatest influence on the building of ECA. This study demonstrates that ECA based on EHR data of COVID-19 patients could sufficiently replace the control arm of an RCT, and it is expected to help develop new treatments faster in emergency situations, such as the COVID-19 pandemic.

Sodium-glucose co-transporter 2 (SGLT2) inhibitors, including canagliflozin, reduce the risk of cardiovascular and kidney outcomes in patients with and without type 2 diabetes, albeit with a large interindividual variation. The underlying mechanisms for this variation in response might be attributed to differences in SGLT2 occupancy, resulting from individual variation in plasma and tissue drug exposure and receptor availability. We performed a feasibility study for the use of [18 F]canagliflozin positron emission tomography (PET) imaging to determine the association between clinical canagliflozin doses and SGLT2 occupancy in patients with type 2 diabetes. We obtained two 90-minute dynamic PET scans with diagnostic intravenous [18 F]canagliflozin administration and a full kinetic analysis in 7 patients with type 2 diabetes. Patients received 50, 100, or 300 mg oral canagliflozin (n = 2:4:1) 2.5 hours before the second scan. Canagliflozin pharmacokinetics and urinary glucose excretion were measured. The apparent SGLT2 occupancy was derived from the difference between the apparent volume of distribution of [18 F]canagliflozin in the baseline and post-drug PET scans. Individual canagliflozin area under the curve from oral dosing until 24-hours (AUCP0-24h ) varied largely (range 1,715-25,747 μg/L*hour, mean 10,580 μg/L*hour) and increased dose dependently with mean values of 4,543, 6,525, and 20,012 μg/L*hour for 50, 100, and 300 mg, respectively (P = 0.046). SGLT2 occupancy ranged between 65% and 87%, but did not correlate with canagliflozin dose, plasma exposure, or urinary glucose excretion. We report the feasibility of [18 F]canagliflozin PET imaging to determine canagliflozin kidney disposition and SGLT2 occupancy. This suggests the potential of [18 F]canagliflozin as a tool to visualize and quantify clinically SGLT2 tissue binding.

Clinical outcomes of tamoxifen (TAM) treatment show wide interindividual variability. Comedications and genetic polymorphisms of enzymes involved in TAM metabolism contributes to this variability. Drug-drug and drug-gene interactions have seldom been studied in African Black populations. We evaluated the effects of commonly co-administered medicines on TAM pharmacokinetics in a cohort of 229 South African Black female patients with hormone-receptor positive breast cancer. We also investigated the pharmacokinetic effects of genetic polymorphism in enzymes involved in TAM metabolism, including the variants CYP2D6*17 and *29, which have been mainly reported in people of African descent. TAM and its major metabolites, N-desmethyltamoxifen (NDM), 4-OH-tamoxifen, and endoxifen (ENDO), were quantified in plasma using the liquid chromatography-mass spectrometry. The GenoPharm open array was used to genotype CYP2D6, CYP3A5, CYP3A4, CYP2B6, CYP2C9, and CYP2C19. Results showed that CYP2D6 diplotype and CYP2D6 phenotype significantly affected endoxifen concentration (P < 0.001 and P < 0.001). CYP2D6*17 and CYP2D6*29 significantly reduced the metabolism of NDM to ENDO. Antiretroviral therapy had a significant effect on NDM levels and the TAM/NDM and NDM/ENDO metabolic ratios but did not result in significant effects on ENDO levels. In conclusion, CYP2D6 polymorphisms affected endoxifen concentration and the variants CYP2D6*17 and CYP2D6*29 significantly contributed to low exposure levels of ENDO. This study also suggests a low risk of drug-drug interaction in patients with breast cancer on TAM.

Rozibafusp alfa (AMG 570) is a first-in-class bispecific IgG2-peptide fusion designed to inhibit inducible T-cell costimulator ligand (ICOSL) and B-cell activating factor (BAFF). The pharmacokinetics (PK) and pharmacodynamics (PD) of rozibafusp alfa were investigated in two randomized, placebo-controlled clinical studies: a phase Ia single ascending-dose study (7-700 mg subcutaneously (s.c.)) in healthy subjects and a phase Ib multiple ascending-dose study (70-420 mg s.c. every 2 weeks (q2w)) in patients with rheumatoid arthritis. Rozibafusp alfa exhibited nonlinear PK and dose-related and reversible dual-target engagement. Maximal reduction of naïve B cells from baseline (> 40%), reflective of BAFF inhibition, was achieved with rozibafusp alfa exposure (area under the concentration-time curve from time 0 to time infinity (AUCinf ) and AUC within a dosing interval from day 0 to day 14 (AUCtau )) above 51 and 57 days•μg/mL for the single-dose (≥ 70 mg) and multiple-dose studies (≥ 70 mg q2w), respectively. ICOSL receptor occupancy on circulating B cells, a surrogate PD end point for ICOSL inhibition, was directly related to drug concentration. PK/PD analysis showed > 90% RO at rozibafusp alfa ≥ 22.2 μg/mL (≥ 420-mg single dose or ≥ 210 mg q2w multiple dose), with saturation occurring at higher drug concentrations. These results informed the design and dose selection of a phase IIb study assessing the safety and efficacy of rozibafusp alfa in patients with active systemic lupus erythematosus.

Taiwan's National Health Insurance (NHI) program forced discontinuation of biologic use in Crohn's disease (CD) after a limited treatment duration, regardless of disease activity. This study investigated the retreatment rate and suboptimal outcomes (i.e., CD-related surgeries, hospitalizations, emergency room visits, and oral steroid flare-ups) after forced discontinuation. This retrospective cohort study was conducted using data from the NHI Database. Patients who received ≥40 weeks of biologic treatment followed by a forced discontinuation were included. The time of biologic retreatment and the cumulative incidence of suboptimal outcomes after the forced discontinuation as well as related risk factors were analyzed. Included were 215 patients (68% male). At the beginning of biologic therapy, the mean age (±SD) was 35.7 (±13.5) years, and the disease duration was 4.46 (±3.52) years. The median (interquartile range) biologic treatment duration was 57.86 (50.3-83.3) weeks. Within the first year after forced discontinuation, 67% of patients (n = 144) were retreated with a second course of biologics, and 53% of patients (n = 114) experienced at least one suboptimal outcome. The independent risk factors associated with the occurrence of suboptimal outcomes were CD-related emergency room visits and hospitalizations during biologic therapy (hazard ratio: 2.49; 95% confidence interval: 1.59-3.89). More than two-thirds of patients with CD required biological retreatment within 1 year after a forced discontinuation. The substantial proportion of patients with poor disease outcomes highlights the need to continue the biologic.

We assess the longitudinal tumor growth inhibition (TGI) metrics and overall survival (OS) predictions applied to patients with advanced biliary tract cancer (BTC) enrolled in IMbrave151 a multicenter randomized phase II, double-blind, placebo-controlled trial evaluating the efficacy and safety of atezolizumab with or without bevacizumab in combination with cisplatin plus gemcitabine. Tumor growth rate (KG) was estimated for patients in IMbrave151. A pre-existing TGI-OS model for patients with hepatocellular carcinoma in IMbrave150 was modified to include available IMbrave151 study covariates and KG estimates and used to simulate IMbrave151 study outcomes. At the interim progression-free survival (PFS) analysis (98 patients, 27 weeks follow-up), clear separation in tumor dynamic profiles with a faster shrinkage rate and slower KG (0.0103 vs. 0.0117 week-1 ; tumor doubling time 67 vs. 59 weeks; KG geometric mean ratio of 0.84) favoring the bevacizumab containing arm was observed. At the first interim analysis for PFS, the simulated OS hazard ratio (HR) 95% prediction interval (PI) of 0.74 (95% PI: 0.58-0.94) offered an early prediction of treatment benefit later confirmed at the final analysis, observed HR of 0.76 based on 159 treated patients and 34 weeks of follow-up. This is the first prospective application of a TGI-OS modeling framework supporting gating of a phase III trial. The findings demonstrate the utility for longitudinal TGI and KG geometric mean ratio as relevant end points in oncology studies to support go/no-go decision making and facilitate interpretation of the IMbrave151 results to support future development efforts for novel therapeutics for patients with advanced BTC.

Cannabis use during pregnancy may cause fetal toxicity driven by in utero exposure to (-)-∆9 -tetrahydrocannabinol (THC) and its psychoactive metabolite, (±)-11-hydroxy-∆9 -THC (11-OH-THC). THC concentrations in the human term fetal plasma appear to be lower than the corresponding maternal concentrations. Therefore, we investigated whether THC and its metabolites are effluxed by placental transporters using the dual cotyledon, dual perfusion, term human placenta. The perfusates contained THC alone (5 μM) or in combination (100-250 nM) with its metabolites (100 nM or 250 nM 11-OH-THC, 100 nM COOH-THC), plus a marker of P-glycoprotein (P-gp) efflux (1 or 10 μM saquinavir), and a passive diffusion marker (106 μM antipyrine). All perfusions were conducted with (n = 7) or without (n = 16) a P-gp/BCRP (breast-cancer resistance protein) inhibitor, 4 μM valspodar. The maternal-fetal and fetal-maternal unbound cotyledon clearance indexes (m-f-CLu,c,i and f-m-CLu,c,i ) were normalized for transplacental antipyrine clearance. At 5 μM THC, the m-f-CLu,c,i , 5.1 ± 2.1, was significantly lower than the f-m-CLu,c,i , 13 ± 6.1 (P = 0.004). This difference remained in the presence of valspodar or when the lower THC concentrations were perfused. In contrast, neither metabolite, 11-OH-THC/COOH-THC, had significantly different m-f-CLu,c,i vs. f-m-CLu,c,i . Therefore, THC appears to be effluxed by placental transporter(s) not inhibitable by the P-gp/BCRP antagonist, valspodar, while 11-OH-THC and COOH-THC appear to passively diffuse across the placenta. These findings plus our previously quantified human fetal liver clearance, extrapolated to in vivo, yielded a THC fetal/maternal steady-state plasma concentration ratio of 0.28 ± 0.09, comparable to that observed in vivo, 0.26 ± 0.10.

Since 2006, the European conditional marketing authorization (CMA) aims to facilitate timely patient access to medicinal products for which there is an unmet medical need by accepting less comprehensive data than normally required. The granting of CMA requires a positive benefit-risk balance, unmet medical needs to be fulfilled, likely submission of comprehensive data postauthorization, and the benefit of immediate availability to outweigh the risks of data noncomprehensiveness. Since its first use, more than half of all CMAs represent (hemato-)oncology indications. Therefore, we aimed to investigate the conditions in which CMA has been applied for anticancer medicinal products and whether they have changed over time. We retrospectively assessed the European public assessment reports of the 30 anticancer medicinal products granted CMA in 2006-2020 (51% of all 59 CMAs). Comparison of 2006-2013 to 2014-2020 highlighted increased proportions of proactively requested CMAs (+40%), medicinal products that addressed unmet medical needs by providing a major therapeutic advantage over authorized treatments (+38%), and orphan designated indications (+32%). In contrast, it showed decreased proportions of medicinal products for which a scientific advisory group was consulted (-55%) and phase III randomized controlled trial data were available (-38%). This suggests that applicants and the European Medicines Agency have learned how to use the CMA as a regulatory tool, among others, through better planning and proactive interaction. However, the increasing number of granted CMAs complicates the establishment of unmet medical need and the benefit-risk balance, especially in crowded indications and when only phase II uncontrolled trials are available.

Although some tumor lysis syndrome (TLS) cases have been reported with patients with multiple myeloma (MM) taking monoclonal antibodies (mAbs), the association between TLS and mAbs remains mostly unknown. We aim to investigate the association between TLS and mAbs and describe clinical features. We conducted a disproportionality analysis to investigate the link between mAbs and TLS by excluding known confounders and compared with other anticancer drugs. The association between mAbs and TLS was evaluated using information component (IC). Drug-drug interaction signals were calculated based on the Ω shrinkage measure. Parametric distribution with the goodness-of-fit test was used for the reported time-to-onset analysis. From 2016 Q1, to 2022 Q4, a total of 274 TLS with mAbs were reported in the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. There were 27% of patients with TLS with mAbs who died and 20.1% occurred a life-threatening situation. Daratumumab, elotuzumab, and belantamab mafodotin presented a robust disproportionate signal of TLS after excluding known confounders (IC025  > 0). Daratumumab had the highest disproportionate signal of TLS among all anticancer drugs for MM. Reported time-to-onset analysis showed the median days for TLS with daratumumab, isatuximab, elotuzumab, and belantamab mafodotin were 1.5, 14.5, 5.5, and 5.5 days, respectively. The drug-drug interaction analysis showed the co-administration of drugs known to increase urate, induce hyperkalemia, or hypocalcemia elevated the reporting frequency for TLS with mAbs (Ω025  > 0). Our postmarketing pharmacovigilance analysis detected the reporting association of TLS and mAbs in patients with MM. Additional studies with robust epidemiological study designs that can validate these findings are warranted.

Evidence to define target ranges for tacrolimus (Tac) and mycophenolic acid (MPA) exposure after the first year of kidney transplantation is limited. We investigated the association of measurements at 1 year and repeated measurements of real-world Tac-trough levels (C0 ) and abbreviated area under the curve from zero to 12 hours (AUC0-12h ) of Tac and MPA with biopsy-proven acute rejection (BPAR) between years 1 and 3 post-transplant in 968 kidney transplant recipients (KTRs). Thirty-five (3.6%) out of 968 KTRs experienced BPAR. Both Tac-AUC0-12h (hazard ratio (HR): 0.39, 95% confidence interval (CI): 0.30-0.50, P < 0.001), Tac-C0 (HR: 0.46, 95% CI: 0.38-0.57, P < 0.001) and MPA-AUC0-12h at 1 year (HR: 0.80, 95% CI: 0.68-0.94, P = 0.006), as well as repeated measurements of Tac-C0 (HR: 0.70, 95% credibility interval (CrI): 0.61-0.82, P < 0.001), and of MPA-AUC0-12h (HR: 0.75, 95% CrI: 0.62-0.93, P < 0.001) were associated with BPAR. In our population, the recommended target range for Tac-AUC0-12h at 1 year would be 75-95 ng*hour/mL and a Tac-C0 5-7 ng/mL. The Tac-AUC0-12h predicted BPAR better than Tac-C0 and identified KTRs with over- or underexposure despite supposedly adequate Tac-C0 . We did not find evidence to recommend another target than the consensus range of 30-60 mg*hour/L for MPA-AUC0-12h after the first year of transplantation. To our knowledge, this is a first study on the simultaneous exposure of Tac and MPA at year 1 and subsequent BPAR up to year 3, which may help define the therapeutic target window for the longer term.

The antiretroviral drug efavirenz remains widely used in children and mothers during breastfeeding in tuberculosis-endemic areas. Evaluating the safety of efavirenz during breastfeeding requires an understanding of its pharmacokinetics (PKs) in breast milk, its exposure in the breastfed infant, and the potential influence of polymorphisms in drug disposition genes. The interplay of these factors between the mother and the nursing infant is a complex scenario that can be readily investigated using physiologically-based PK (PBPK) modeling. A verified PBPK model for efavirenz describing the CYP3A4- and CYP2B6-mediated auto-induction during multiple dosing was reported previously and was applied in this study to predict the exposure of efavirenz in vulnerable populations, including children (down to the age of 3 months), mothers, and breastfeeding infants, accounting for the various CYP2B6 genotypes. Predicted pharmacokinetic parameters for mothers, breastfeeding infants, and children aged ≥ 3 months were reasonably consistent with observed data, irrespective of CYP2B6 genotype. The clinically significant trend toward higher infant efavirenz exposure from GG/GG to TT/TT composite maternal/infant CYP2B6 genotypes was captured reasonably well by the PBPK model. Thereafter, simulations were performed to determine the adequacy of the current World Health Organization (WHO; ≥ 3 years) and the US Food and Drug Administration (FDA; ≥ 3 months) weight-based dosing regimens for efavirenz in children according to CYP2B6 genotype. The findings of this study indicate that PBPK models can be used in designing studies in vulnerable populations and providing guidance on optimal doses based on developmental physiology and pharmacogenetics.

Mavacamten is a first-in-class, oral, selective, allosteric, reversible cardiac myosin inhibitor approved by the US Food and Drug Administration for the treatment of adults with symptomatic New York Heart Association functional class II-III obstructive hypertrophic cardiomyopathy. Mavacamten is metabolized in the liver, predominantly via cytochrome P450 (CYP) enzymes CYP2C19 (74%), CYP3A4 (18%), and CYP2C9 (8%). A physiologically-based pharmacokinetic (PBPK) model was developed using Simcyp version 19 (Certara, Princeton, NJ). Following model verification, the PBPK model was used to explore the effects of strong CYP3A4 and CYP2C19 inducers, and strong, moderate, and weak CYP2C19 and CYP3A4 inhibitors on mavacamten pharmacokinetics (PK) in a healthy population, with the effect of CYP2C19 phenotype predicted for poor, intermediate, normal, and ultrarapid metabolizers. The PBPK model met the acceptance criteria for all verification simulations (> 80% of model-predicted PK parameters within 2-fold of those observed clinically). A weak induction effect was predicted when mavacamten was administered with a strong CYP3A4 inducer in poor metabolizers. Moderate reductions in mavacamten exposure were predicted with a strong CYP2C19/CYP3A4 inducer in all CYP2C19 phenotypes. Except for the effect of strong CYP2C19 inhibitors on ultrarapid metabolizers, steady-state area under plasma concentration-time curve and maximum plasma concentration values were weakly affected (< 2-fold) or not affected (< 1.25-fold), regardless of CYP2C19 phenotype. In conclusion, a fit-for-purpose PBPK model was developed and verified, which accurately predicted the available clinical data and was used to simulate the potential impact of CYP induction and inhibition on mavacamten PKs, stratified by CYP2C19 phenotype.

Methotrexate polyglutamates (MTX-PG) concentrations in red blood cells (RBCs) have been suggested as a biomarker of response in patients with rheumatoid arthritis (RA) receiving low-dose MTX therapy. We investigated the association and interpatient variability between RBC-MTX-PG3-5 -exposure and response in patients with RA starting MTX. Data of three prospective cohorts were available. The relationship between exposure and Disease Activity Score in 28 joints (DAS28) was analyzed using a population pharmacokinetic-pharmacodynamic model. Relevant covariates were tested using full covariate modeling and backward elimination. From 395 patients, 3,401 MTX-PG concentrations and 1,337 DAS28 measurements were available between 0 and 300 days after MTX treatment onset. The developed model adequately described the time course of MTX-PG3-5 and DAS28. The median MTX-PG3-5 level at month 1 was 30.9 nmol/L (interquartile range (IQR): 23.6-43.7; n = 41) and at month 3: 69.3 nmol/L (IQR: 17.9-41.2; n = 351). Clearance of MTX-PG3-5 from RBCs was 28% lower (95% confidence interval (CI): 23.6-32.8%) in a woman and 10% lower (95% CI: 7.7-12.4%) in a 65-year-old compared with a 35-year-old patient. MTX-PG3-5 concentrations associated with DAS28: half-maximal effective concentration (EC50 ) was 9.14 nmol/L (95% CI: 4.2 nmol/L-14.1 nmol/L). EF at 80% (EC80 ) above 47 nmol/L was regarded as the optimal response. Independent of the MTX-PG 3-5 - response association, co-administration of disease-modifying antirheumatic drugs and corticosteroids improved response (additive effect on maximum effect (Emax )), whereas smoking, high body mass index and low albumin decreased Emax . In patients with RA starting MTX, RBC-MTX-PG3-5 was associated with clinical response. A dose increase is suggested when MTX-PG3-5 at month 1 is below 9.15 nmol/L, continued with the same dose when the concentration is above 47 nmol/L, and consider other treatment options above 78 nmol/L from 3 months onwards.

Congress mandated the creation of a postmarket Active Risk Identification and Analysis (ARIA) system containing data on 100 million individuals for monitoring risks associated with drug and biologic products using data from disparate sources to complement the US Food and Drug Administration's (FDA's) existing postmarket capabilities. We report on the first 6 years of ARIA utilization in the Sentinel System (2016-2021). The FDA has used the ARIA system to evaluate 133 safety concerns; 54 of these evaluations have closed with regulatory determinations, whereas the rest remain in progress. If the ARIA system and the FDA's Adverse Event Reporting System are deemed insufficient to address a safety concern, then the FDA may issue a postmarket requirement to a product's manufacturer. One hundred ninety-seven ARIA insufficiency determinations have been made. The most common situation for which ARIA was found to be insufficient is the evaluation of adverse pregnancy and fetal outcomes following in utero drug exposure, followed by neoplasms and death. ARIA was most likely to be sufficient for thromboembolic events, which have high positive predictive value in claims data alone and do not require supplemental clinical data. The lessons learned from this experience illustrate the continued challenges using administrative claims data, especially to define novel clinical outcomes. This analysis can help to identify where more granular clinical data are needed to fill gaps to improve the use of real-world data for drug safety analyses and provide insights into what is needed to efficiently generate high-quality real-world evidence for efficacy.