Tenofovir diphosphate (TFVdp; an active metabolite of oral HIV pre-exposure prophylaxis (PrEP)) is measured in dried blood spots (DBS) to estimate adherence. However, TFVdp's long half-life in whole blood may lead to misclassification following a recent change in adherence. PrEP's other metabolite, emtricitabine triphosphate (FTCtp), has a shorter half-life in whole blood but adherence thresholds are undefined. We characterized DBS TFVdp and FTCtp concentrations across many dosing scenarios. Population pharmacokinetic models were fit to TFVdp and FTCtp DBS concentrations from a directly observed therapy study (NCT03218592). Concentrations were simulated for 90 days of daily dosing followed by 90 days of 1 to 7 doses/week and for event-driven PrEP (edPrEP) scenarios. Thresholds of 1,000 and 200 fmol/punch, for TFVdp and FTCtp, respectively, were reflective of taking 4 doses/week (a minimum target for effective PrEP in men). TFVdp was < 1,000 fmol/punch for 17 days after initiating daily PrEP and > 1,000 fmol/punch for 62 days after decreasing to 3 doses/week. Respectively, FTCtp was < 200 fmol/punch for 4 days and > 200 fmol/punch for 6 days. Accuracy of edPrEP adherence classification depended on duration between last sex act and DBS sampling for both measures with misclassification ranging from 9-100%. These data demonstrate adherence misclassification by DBS TFVdp for 2 months following a decline in adherence, elucidating the need for FTCtp to estimate recent adherence. We provide proof of principle that individualized interpretation is needed to support edPrEP adherence monitoring. Our collective approach facilitates clinicians' ability to interpret DBS results and administer patient-centric interventions.

Prediction of treatment responses is essential to move forward translational science. Our question was to identify patient-based variables that predicted responses to treatments. We conducted secondary analyses on pooled data from two randomized phase III clinical trials (NCT02697773 and NCT02709486) conducted in participants with moderate to severe osteoarthritis randomized to subcutaneous placebo (n = 514) or tanezumab 2.5 mg (n = 514). We used gradient boosted regression trees to identify variables that predicted Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain subscale scores at Week 16 and marginal plots to determine the directional relationship between each variable category and responses to placebo or tanezumab within the models. We also used Virtual Twins models to identify potential subgroups of response to the active treatment vs. placebo. We found that responses to placebo were predicted by baseline WOMAC Physical Function, baseline WOMAC Pain, the radiographic classification of the index joint, and the standard deviation of diary pain scores at baseline. In contrast, baseline WOMAC Pain along with failure of prior medications, duration of disease, and standard deviation of diary pain scores at baseline were predictive of tanezumab responses as expressed by the WOMAC Pain scores at Week 16. Those who responded to tanezumab vs. placebo were identified based on the radiographic classification of the index joint and either age or smoking status. These secondary-data analyses identified distinct and common patient-based variables to predict response to placebo or tanezumab. These findings will inform the design of future clinical trials, helping to move forward clinical pharmacology and translational science.

Self-perceived statin-associated muscle symptoms (SAMS) are prevalent, but only a minority is drug-dependent. Diagnostic biomarkers are not yet identified. The local statin exposure in skeletal muscle tissue may correlate to the adverse effects. We aimed to determine whether atorvastatin metabolites in blood reflect the corresponding metabolite levels in skeletal muscle, and whether genetic variants of statin transporters modulate this relationship. We also addressed atorvastatin metabolites as potential objective biomarkers of SAMS. Muscle symptoms were examined in patients with coronary disease and self-perceived SAMS during 7 weeks of double-blinded treatment with atorvastatin 40 mg/day and placebo in randomized order. A subset of 12 patients individually identified with more muscle symptoms on atorvastatin than placebo (confirmed SAMS) and 15 patients with no difference in muscle symptom intensity (non-SAMS) attended the present follow-up study. All received 7 weeks of treatment with atorvastatin 40 mg/day followed by 8 weeks without statins. Biopsies from the quadriceps muscle and blood plasma were collected after each treatment period. Strong correlations (rho > 0.7) between muscle and blood plasma concentrations were found for most atorvastatin metabolites. The impact of the SLCO1B1 c.521T>C (rs4149056) gene variant on atorvastatin's systemic pharmacokinetics was translated into muscle tissue. The SLCO2B1 c.395G>A (rs12422149) variant did not modulate the accumulation of atorvastatin metabolites in muscle tissue. Atorvastatin pharmacokinetics in patients with confirmed SAMS were not different from patients with non-SAMS. In conclusion, atorvastatin metabolite levels in skeletal muscle and plasma are strongly correlated, implying that plasma measurements are suitable proxies of atorvastatin exposure in muscle tissue. The relationship between atorvastatin metabolites in plasma and SAMS deserves further investigation.

This proof-of-concept study retrospectively assessed the feasibility of applying a hybrid control arm design to a completed phase III randomized controlled trial (RCT; CheckMate-057) in advanced non-small cell lung cancer using a real-world data (RWD) source. The emulated trial consists of an experimental arm (patients from the RCT experimental cohort) and a hybrid control arm (patients from the RCT and RWD control cohorts). For the RWD control cohort, this study used a nationwide electronic health record-derived de-identified database. Three frequentist statistical borrowing methods were evaluated: a two-step Cox model, a fixed Cox model, and propensity score-integrated composite likelihood ("Methods 1-3"). The experimental treatment effect for hybrid control designs were evaluated using hazard ratios (HRs) with 95% confidence interval (CI) estimated from the Cox models accounting for covariate differences. The reduction in study duration compared to the RCT was also evaluated. All three statistical borrowing methods achieved comparable experimental treatment effects to that observed in the CheckMate-057 clinical trial, with HRs of 0.73 (95% CI: 0.59, 0.92), 0.74 (95% CI: 0.61, 0.91), 0.72 (95% CI: 0.59, 0.88) for Methods 1-3, respectively. Reduction in study duration time was 99-115 days when borrowing 30-38 events for Methods 1-3, respectively. This study demonstrated that it is feasible to emulate an RCT using a hybrid control arm design using three frequentist propensity-score based statistical borrowing methods. Selection of an appropriate, fit-for-use RWD cohort is critical to minimizing bias in experimental treatment effect.

Overall survival is defined as the time since randomization into the clinical trial to event of death or censor (end of trial or follow-up), and is considered to be the most reliable cancer end point. However, the introduction of second-line treatment after disease progression could influence survival and be considered a confounding factor. The aim of the current study was to set up a multistate model framework, using data from the IMpower131 study, to investigate the influence of second-line immunotherapies on overall survival analysis. The model adequately described the transitions between different states in patients with advanced squamous non-small cell lung cancer treated with or without atezolizumab plus nab-paclitaxel and carboplatin, and characterized the survival data. High PD-L1 expression at baseline was associated with a decreased hazard of progression, while the presence of liver metastasis at baseline was indicative of a high risk of disease progression after initial response. The hazard of death after progression was lower for participants who had longer treatment response, i.e., longer time to progression. The simulations based on the final multistate model showed that the addition of atezolizumab to the nab-paclitaxel and carboplatin regimen had significant improvement in the patients' survival (hazard ratio = 0.75, 95% prediction interval: 0.61-0.90 favoring the atezolizumab + nab-paclitaxel and carboplatin arm). The developed modeling approach can be applied to other cancer types and therapies to provide a better understanding of efficacy of drug and characterizing different states, and investigate the benefit of primary therapy in survival while accounting for the switch to alternative treatment in the case of disease progression.

Selective safety data collection may simplify late-stage clinical trials and improve their feasibility. However, the impact on increasing overall drug safety knowledge is unknown. The aim of this study is to evaluate how much safety information is added to the drug label based on large trials after initial authorization. Changes made to the "undesirable effects" section of the drug label of cardiometabolic agents approved between 2000 and 2020 based on the results of large (> 1,000 patient) clinical trials submitted to the European Medicines Agency (EMA) were evaluated. The study focused on glucose lowering, antithrombotic, and lipid-modifying agents. The primary outcome was the number of changes in adverse drug reactions in the drug label. The EMA reviewed 55 large trials concerning 25 cardiometabolic agents after the initial marketing authorization, which included 402,444 patients. Ultimately, 38 trials (69%) resulted in a safety section update, whereas 17 trials (31%) did not. Changes in listed adverse drug reactions were made following 19 trials (35%) for 12 agents: 77 adverse drug reactions were added, 11 were deleted, and the frequencies of 43 were changed. Most changes in adverse drug reactions arose from trials with antithrombotic agents (88%) and trials performed in a new population (92%). Large trials for cardiometabolic agents reported after authorization add limited new safety information on adverse drug reactions, especially when performed in the population studied prior to approval. This suggests that selective safety data collection does not reduce learnings from late stage cardiometabolic trials in populations comprehensively studied before.

Prioritization of diversity, equity, and inclusion in all facets of our work is long overdue for the clinical pharmacology community. Increasing diversity in clinical research will deepen our understanding of nuanced patient populations and help improve all patient outcomes. Fostering an inclusive and diverse workforce will lead to broader perspectives that can better inform critical decisions and create work environments where everyone can thrive. In this call to action, we invite you to join us.

The most intuitive question for market access for medicinal products is the benefit/risk (B/R) balance. The B/R assessment can conceptually be divided into sub-questions related to establishing efficacy and safety. There are additional layers to the B/R ratio for medical products, including questions related to dose selection, clinical and non-clinical pharmacology, and drug quality. Explicitly stating the actual questions and how they contribute to the overall B/R provides a structure that helps better informed cross-domain discussions. There is currently no systematic approach in the regulatory setting to assess and establish the acceptability of alternative methods and data sources. In most cases, the medicinal product sponsors tend to prioritise traditional data types and methods, which are well accepted by regulators for inclusion in regulatory submissions. This, in addition to the absence of rigour in the use and validation of new data types and methods, and the limited training of assessors in related fields can lead to increased regulatory scepticism toward new data types and methods. A data-knowledge backbone is needed to mitigate the uncertainty in efficacy and safety characterisation. This white paper discusses the value of explicitly redefining and restructuring the regulatory scientific decision-making around the scientific question to be addressed. The ecosystem proposed is based on three pillars: (a) a repository connecting questions, data, and methods; (b) the development and validation of high-quality standards for data and methods; (c) credibility assessment, The ecosystem is applied to four use-cases for illustration. The need for training and regulatory guidance is also discussed.

Hepatotoxicity is a serious adverse drug reaction related to methotrexate (MTX). However, the cause of drug-induced liver injury (DILI) is still unclear and unpredictable. Genetic risk factors may predispose for MTX-DILI. Therefore, we conducted a nested case control genome-wide association study to explore genetic risk factors associated with MTX DILI. Seven international groups contributed blood samples and data of rheumatoid arthritis patients who used MTX. MTX-induced DILI was defined as an ALT level of at least 3X the upper limit of normal (ULN), to increase contrast controls ALT levels did not raise above 2X ULN. Per study site, control and MTX DILI patients (ratio 3:1) were matched for age, gender, and duration of MTX use. Patients were genotyped using Illumina GSA MD-24v1-0 and data were imputed using the 1000Genomes reference panel. SNPs were analyzed using an additive genetic model, corrected for sex, country, and age. A p-value of ≤5x10-8 was considered significant, while a p-value of ≤5x10-6 was considered suggestive. A total of 104 MTX-induced DILI cases and 315 controls were included for association analysis. None of the SNPs were significantly associated with MTX DILI. However, we found seven suggestive genetic variants associated with MTX DILI (p-value 7.43*10-8 to 4.86*10-6 ). Of those, five SNPs were in the intronic protein-coding regions of FTCDNL1, BCOR, FGF14, RBMS3, and PFDN4/DOK5. Investigation of candidates SPATA9 (rs72783407), PLCG2 (rs60427389), RAVER2 (rs72675408), JAK1 (rs72675451), PTPN2 (rs2476601), MTHFR C677T (rs1801133) and into the HLA region did not show significant findings. No genetic variants associated with MTX-DILI were found, while suggestive SNPs need further investigation.

The P-glycoprotein efflux pump, encoded by the ABCB1 gene, has been shown to alter concentrations of various antidepressants in the brain. In this study, we conducted a systematic review and meta-analysis to investigate the association between six ABCB1 SNPs (rs1045642, rs2032582, rs1128503, rs2032583, rs2235015, rs2235040) and antidepressant treatment outcomes in individuals with major depressive disorder (MDD), including new data from the Canadian Biomarker and Integration Network for Depression (CAN-BIND-1) cohort. For the CAN-BIND-1 sample, we applied regression models to investigate the association between ABCB1 SNPs and antidepressant treatment response, remission, tolerability, and antidepressant serum levels. For the meta-analysis, we systematically summarized pharmacogenetic evidence of the association between ABCB1 SNPs and antidepressant treatment outcomes. Studies were included in the meta-analysis if they investigated at least one ABCB1 SNP in individuals with MDD treated with at least one antidepressant. We did not find a significant association between ABCB1 SNPs and antidepressant treatment outcomes in the CAN-BIND-1 sample. A total of 39 studies were included in the systematic review. In the meta-analysis, we observed a significant association between rs1128503 and treatment response (T vs C-allele, OR= 1.30, 95% CI [1.15-1.48], p-value (adjusted)= 0.024, n=2526). We did not find associations between the six SNPs and treatment remission nor tolerability. Our findings provide limited evidence for an association between common ABCB1 SNPs and antidepressant outcomes, which do not support the implementation of ABCB1 genotyping to inform antidepressant treatment at this time. Future research, especially on rs1128503, is recommended.

Drug-target-drug complexes (DTDCs) are phenomena newly observed in patients who switch from the complement component 5 (C5) inhibitor eculizumab to crovalimab, a novel, anti-C5 antibody in development for paroxysmal nocturnal hemoglobinuria (PNH), because these agents bind to different C5 epitopes. In Part 3 of the four-part, phase I/II COMPOSER study, 19 patients with PNH switching from eculizumab received 1,000-mg crovalimab intravenously, then subcutaneous maintenance doses from Day 8 (680 mg every 4 weeks (q4w), 340 mg every 2 weeks, or 170 mg every week). Crovalimab exposure was transiently reduced, and size-exclusion chromatography and crovalimab-specific enzyme-linked immunosorbent assays revealed DTDCs in all 19 patients' sera. Additionally, self-limiting mild to moderate symptoms suggestive of type III hypersensitivity reactions occurred in two patients. Mathematical modeling simulations of DTDC kinetics and effects of dosing on DTDC size distribution using Part 3 data predicted that increased crovalimab concentrations could reduce the proportion of large, slow-clearing DTDCs in the blood. A simulation-guided, optimized crovalimab regimen (1,000 mg intravenously; four weekly, subcutaneous 340-mg doses; then 680 mg q4w from Day 29) was evaluated in Part 4. Confirming the model's predictions, mean proportions of large DTDCs in patients who switched from eculizumab to this optimized regimen decreased by > 50% by Day 22, and target crovalimab concentrations were maintained. No type III hypersensitivity reactions occurred in Part 4. Optimizing crovalimab dosing thus reduced the proportion of large DTDCs, ensured adequate complement inhibition, and may improve safety. Model-based dosing optimization to mitigate DTDC formation offers a useful strategy for patients switching to novel antibody treatments targeting soluble epitopes.

Despite the requirement of routine blood tests during thiamazole treatment in Japan, granulocytopenia among patients treated with thiamazole has been occasionally reported to the Pharmaceuticals and Medical Devices Agency (PMDA). To characterize granulocytopenia in patients with thiamazole in Japan, the effects of routine blood tests were examined in a cohort of new users of thiamazole or propylthiouracil utilizing the MID-NET. The occurrence of granulocytopenia (neutrophil count ≤ 1,500/μL) in a given period was compared between patients with and without blood test results prior to the period. The trend in neutrophil count during thiamazole treatment was also compared between patients with and without granulocytopenia. A nested case-control study based on the cohort was conducted to identify potential risk factors for granulocytopenia during thiamazole treatment. In the new user cohort including 4,371 patients treated with thiamazole, the occurrence of granulocytopenia in patients who had undergone blood tests at all previous periods was similar or higher than that among those who had not undergone blood test in all previous periods (e.g., adjusted odds ratio in period 2 was 1.63). The neutrophil count was relatively lower in the group of patients with granulocytopenia even before the occurrence of granulocytopenia. In a nested case-control study, an upward tendency of the risk was observed when a patient was co-prescribed anti-arrhythmic drugs or antiulcer drugs with thiamazole. The characteristics of granulocytopenia during thiamazole treatment elucidated in this study should be recognized in clinical practice for the proper use of thiamazole.

The US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have robust collaboration and dialogue around the need for data and the inclusion of pregnant and lactating individuals in clinical trials. Despite this collaboration, the two agencies have their own standards for the format and content of labeling for these populations. To understand these differences, the pregnancy and lactation labeling sections for 31 approved drugs were compared, and trends were assessed for use of language concordance and discordance related to use during pregnancy and lactation between the 2 agencies. Further analysis evaluated the presence of human data included in the labeling. The EMA and the FDA had high discordance between pregnancy and lactation labeling language, in 68% and 71% of labeling, respectively, and only 10% of pregnancy labeling and 16% of lactation labeling include human data. Concordance in labeling language is not the norm but occurs when there is a sizeable body of human data, animal data suggesting a particular safety issue, drug mechanism of action information, or disease-specific considerations. This study highlights the need for more human data to inform prescribing decisions in these populations. The results also suggest that there is an opportunity for alignment in labeling across regions.

N1 -methylnicotinamide (NMN) has been proposed as endogenous biomarker for drug-drug interactions mediated by inhibition of multidrug and toxin extrusion proteins (MATEs) at the renal proximal tubule. We analyzed NMN in plasma and urine samples of two clinical trials investigating a new probe drug cocktail (consisting of digoxin, metformin, furosemide, and rosuvastatin) dedicated to clinically relevant drug transporters. In trial 1, NMN was investigated after single-dose treatment with individual cocktail components or after cocktail treatment. In trial 2, NMN was investigated after treatment with cocktail alone or with cocktail + inhibitor (cimetidine, a MATE inhibitor; or rifampin, verapamil, or probenecid, inhibitors of other transporters). In trial 1, NMN kinetics in plasma and urine were essentially not affected by individual cocktail components or after cocktail treatment. In trial 2, NMN renal clearance from 0 to 12 hours (CLR,0-12 ) geometric mean ratio (GMR) after cocktail + cimetidine vs. cocktail alone was 75% (90% confidence interval (CI): 65-87%). NMN CLR GMR after cocktail + verapamil, + rifampin, or + probenecid vs. cocktail alone was 99% (90% CI: 81-121%), 91% (90% CI: 75-111%), and 107% (90% CI: 91-126%), respectively. Compared with creatinine CLR and creatinine area under the plasma-concentration time curve, NMN CLR was more specific and more sensitive for renal MATE inhibition. Absence of impact of the cocktail on NMN in trial 1 allows for utilization of NMN in studies using this transporter cocktail. Trial 2 data support that NMN CLR is a specific and sensitive marker for MATE-mediated renal drug-drug interactions.

Drug-drug interaction (DDI) assessments are well defined in health authority guidelines for small molecule drugs, and US Food and Drug Administration (FDA) draft guidance is now available for therapeutic proteins. However, there are currently no regulatory guidelines outlining DDI assessments for therapeutic peptides, which poses significant uncertainty and challenges during drug development for this heterogenous class of molecules. A cross-industry peptide DDI working group consisting of experts from 10 leading companies was formed under the sponsorship of the European Federation of Pharmaceutical Industries and Associations. We aimed to capture the range of DDI studies undertaken for peptide drugs by (i) anonymously surveying relevant companies involved in peptide drug development to better understand DDI study type/timing currently performed and (ii) compiling a database containing in vitro / clinical DDI data from submission packages for recently approved peptide drugs. Our analyses highlight significant gaps and uncertainty in the field. For example, the reported timing of in vitro peptide DDI studies, if performed, vary substantially across responding companies from early research to phase III. Nearly all in vitro cytochrome P450 / transporter inhibition studies reported in the survey were negative. For the few positive hits reported, no clinical follow-up studies were performed, questioning the clinical relevance of these findings. Furthermore, available submission packages reveal DDI likelihood is low for peptides >2 kDa, making it reasonable to adopt a risk-based approach during drug development for larger peptides. By benchmarking the landscape of peptide DDI activities across the industry, we set the stage for future discussions with health authorities on harmonizing peptide DDI approaches.

The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (N = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (N = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (N = 287, N = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (ρ = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (N = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R2 ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.

Women and people from most racial and ethnic groups in the United States have historically been under-represented in clinical trials of investigational medical products. Inadequate representation of these groups may lead to an incomplete understanding of the safety and efficacy of new drugs, devices, biologics, and vaccines, and limit the generalizability of trial findings. As a result, new medical products may not be beneficial to all people who need them, and existing inequities in outcomes among various population groups may remain unchanged or worsen, or new disparities may arise. Although much work has focused on study-level strategies, research organizations must make systemic changes to how clinical trials are envisioned and implemented to achieve sustainable support for diversity and inclusion in clinical trials. The Clinical Trials Transformation Initiative (CTTI) conducted interviews with leaders at institutions that conduct clinical trials to explore perspectives on organizational-level practices that promote diversity and inclusion in clinical trials. Leaders described motivations, such as an ethical and moral imperative; organizational practices, such as staff investment and resource allocation; perceived return on investments, such as better science; and deterrents, such as cost and time. The CTTI also convened an expert meeting to discuss the interview findings and provide guidance. We present the interview findings and expert guidance in a framework that describes four key areas-commitment, partnerships, accountability, and resources-on sustaining organizational-level approaches for improving diversity and inclusion in clinical trials, with the ultimate goal of advancing health equity. Institutions who conduct and support clinical trials should implement organizational-level approaches to improve equitable access and diverse patient participation in clinical trials.