As a high-metabolic-rate organ, the kidney exhibits metabolic reprogramming (MR) in various disease states. Given the 860.8 million cases of kidney disease worldwide in 2017, understanding the specific bioenergetic pathways involved and developing targeted interventions are vital needs. The reprogramming of metabolic pathways (glucose metabolism, amino acid metabolism, etc.) has been observed in kidney disease. Therapies targeting these specific pathways have proven to be an efficient approach for retarding kidney disease progression. In this review, we focus on potential pharmacological interventions targeting MR that have advanced through Phase III/IV clinical trials for the management of kidney disease and promising preclinical studies laying the groundwork for future clinical investigations.

Cryptides are a subfamily of bioactive peptides embedded latently in their parent proteins and have multiple biological functions. Cationic cryptides could be used as modern drugs in both infectious diseases and cancers because their mechanism of action is less likely to be affected by genetic mutations in the treated cells, therefore addressing a current unmet need in these two areas of medicine. In this review, we present the current understanding of cryptides, methods to mine them sustainably using available online databases and prediction tools, with a particular focus on their antimicrobial and anticancer potential, and their potential applicability in a clinical setting.

Pharmaceutical co-crystals represent a growing class of crystal forms in the context of pharmaceutical science. They are attractive to pharmaceutical scientists because they significantly expand the number of crystal forms that exist for an active pharmaceutical ingredient and can lead to improvements in physicochemical properties of clinical relevance. At the same time, machine learning is finding its way into all areas of drug discovery and delivers impressive results. In this review, we attempt to provide an overview of machine learning, deep learning and network-based recommendation approaches applied to pharmaceutical co-crystallization. We also present crystal structure prediction as an alternative to machine learning approaches.

The suitability of small molecules as oral drugs is often assessed by simple physicochemical rules, the application of ligand efficiency scores or by composite scores based on physicochemical compound properties. These rules and scores are empirical and typically lack mechanistic background, such as information on pharmacokinetics (PK). We introduce new types of Compound Quality Scores (CQS, specifically called dose scores and cmax scores), which explicitly include predicted or, when available, experimental PK parameters and combine these with on-target potency. These CQS scores are surrogates for an estimated dose and corresponding cmax and allow prioritizing of compounds within test cascades as well as synthesis. We demonstrate the complementarity and, in most cases, superior performance relative to existing efficiency metrics by project examples.

Medication adherence in pediatric patients is a key factor in drug development and dosage form design. High medication adherence is not only important to achieve the expected treatment effects but can also effectively reduce medical costs. It is an ongoing task to accurately identify differences in medication adherence between children and adults and analyze the factors related to pediatric medication adherence. This is necessary to guide the development of pediatric drugs. This review focuses on factors that influence medication adherence as well as pharmaceutical design strategies to improve adherence. Current and new dosage forms, new technologies, and new devices are comprehensively summarized in terms of their advantages and limitations.

Recently, targeted protein degradation technologies based on lysosomal pathways have been developed. Lysosome-based targeted protein degradation technology has a broad range of substrates and the potential to degrade intracellular and extracellular proteins, protein aggregates, damaged organelles and non-protein molecules. Thus, they hold great promise for drug R&D. This study has focused on the biogenesis of lysosomes, their basic functions, lysosome-associated diseases and targeted protein degradation technologies through the lysosomal pathway. In addition, we thoroughly examine the potential applications and limitations of this technology and engage in insightful discussions on potential avenues for future research. Our primary objective is to foster preclinical research on this technology and facilitate its successful clinical implementation.

Affinity selection mass spectrometry (AS-MS) has gained momentum in drug discovery. This review summarizes how this technology has slowly risen as a new paradigm in hit identification and its potential synergy with DNA encoded library technology. It presents an overview of the recent results on challenging targets and perspectives on new areas of research, such as RNA targeting with small molecules. The versatility of the approach is illustrated and strategic drivers discussed in terms of the experience of a small-medium CRO and a big pharma organization.

Current treatment strategies for triple-negative breast cancer (TNBC) are based upon conventional chemotherapy, immunotherapy, or a combination of both. The treatment regimen for chemotherapy is often a combination of two or more drugs, either dose dense or low dose for synergy. Anthracyclines, alkylating agents, antimicrotubule agents, and antimetabolites for early-stage TNBC; and antimetabolites, non-taxane microtubule inhibitors, and cross-linker platinums for late-stage TNBC are usually administered in the clinical setting. Newer options for patients with advanced TNBC, such as poly (ADP-ribose) polymerase (PARP) inhibitors and immune checkpoint inhibitors, have recently emerged for cases where surgery is not a viable option and the disease has metastasized. This review outlines the current trends in hypoxia-inspired treatment strategies for TNBC with a focus on clinical trials.

In the pharmaceutical industry, it is essential to ensure the safety and efficacy of medicinal products. Therefore a robust quality assurance framework is needed. This manuscript examines the impact of GAMP 5 and data integrity (DI) on quality assurance, while also highlighting the role of quality by design (QbD) principles. GAMP 5 is a widely used framework for validating automated systems that establishes quality assurance practices. DI guarantees the reliability of data collected throughout various stages of drug development. The integration of QbD principles promotes a systematic approach to development that emphasizes a deep understanding of critical quality attributes, risk management, and continuous improvement. With their implementation, organizations are able to meet regulatory requirements and provide safe medications to patients worldwide.

Certain mono-infections of influenza viruses and novel coronaviruses, including severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) are significant threats to human health. Concurrent infections by influenza viruses and coronaviruses increases their danger. Influenza viruses have eight manipulations capable of assisting SARS-CoV-2 and other coronaviruses, and several of these manipulations, which are not specific to viruses, can also directly or indirectly boost dangerous secondary bacterial pneumonias. The influenza virus manipulations include: inhibiting transcription factors and cytokine expression; impairing defensive protein expression; increasing RNA viral replication; inhibiting defenses by manipulating cellular sensors and signaling pathways; inhibiting defenses by secreting exosomes; stimulating cholesterol production to increase synthesized virion infectivities; increasing cellular autophagy to assist viral replication; and stimulating glucocorticoid synthesis to suppress innate and adaptive immune defenses by inhibiting cytokine, chemokine, and adhesion molecule production. Teaser: Rapidly spreading multidrug-resistant respiratory bacteria, combined with influenza virus's far-reaching cellular defense manipulations benefiting evolving SARS-CoV-2 or other coronaviruses and/or respiratory bacteria, can enable more severe pandemics or co-pandemics.

Glutaminyl cyclase (QC) activity has been identified as a key effector in distinct biological processes. Human glutaminyl-peptide cyclotransferase (QPCT) and glutaminyl-peptide cyclotransferase-like (QPCTL) are considered attractive therapeutic targets in many human disorders, such as neurodegenerative diseases, and a range of inflammatory conditions, as well as for cancer immunotherapy, because of their capacity to modulate cancer immune checkpoint proteins. In this review, we explore the biological functions and structures of QPCT/L enzymes and highlight their therapeutic relevance. We also summarize recent developments in the discovery of small-molecule inhibitors targeting these enzymes, including an overview of preclinical and clinical studies.

N-of-1 strategies can provide high-quality evidence of treatment efficacy at the individual level and optimize evidence-based selection of off-label treatments for patients with rare diseases. Given their design characteristics, n-of-1 strategies are considered to lay at the intersection between medical research and clinical care. Therefore, whether n-of-1 strategies should be governed by research or care regulations remains a debated issue. Here, we delineate differences between medical research and optimized clinical care, and distinguish the regulations which apply to either. We also set standards for responsible optimized clinical n-of-1 strategies with (off-label) treatments for rare diseases. Implementing clinical n-of-1 strategies as defined here could aid in optimized treatment selection for such diseases.

Cystic fibrosis (CF), a fatal genetic condition, causes thick, sticky mucus. It also causes pancreatic dysfunction, bacterial infection, and increased salt loss. Currently available treatments can improve the patient's quality of life. Drug delivery aided by nanotechnology has been explored to alter the pharmacokinetics and toxicity of drugs. In this short review, we aim to summarize various conventional formulations and highlight advanced formulations delivered via the pulmonary route for the treatment of CF. There is considerable interest in advanced drug delivery formulations addressing the various challenges posed by CF. Despite their potential to be translated for clinical use, we anticipate that a significant amount of effort may still be required for translation to the clinic.

This report focuses on small non-coding RNA molecules (miRNAs), which have emerged as potential biomarkers with variable diagnostic values and false-positives in different conditions that limit their clinical preference. Current investigations focus on small non-coding RNA molecules (miRNAs), which have emerged as potential biomarkers with variable diagnostic values and false-positives in different conditions that limit their clinical preference. We thoroughly scrutinize the leading pathology of myocardial infarction and contemporary alterations in miRNAs for their specificity, stability and significant prognostic value at the early stage of acute myocardial infarction (AMI). Based on secondary data analysis, we explore common biomarkers and further investigate included miRNA biomarkers for their specificity, stability and area under the curve (AUC) values. We conclude that a group of novel biomarkers, including miRNA-1, miRNA-208a/b and miRNA-499, could help predict the emergence of AMI at an early stage.

The cytochrome P450 (CYP450) enzyme system is responsible for the metabolism of more than two-thirds of xenobiotics. This review summarizes reports of a series of in silico tools for CYP450 enzyme-drug interaction predictions, including the prediction of sites of metabolism (SOM) of a drug and the identification of inhibitor/substrates for CYP subtypes. We also evaluated four prediction tools to identify CYP inhibitors utilizing 52 of the most frequently prescribed drugs. ADMET Predictor and CYPlebrity demonstrated the best performance. We hope that this review provides guidance for choosing appropriate enzyme prediction tools from a variety of in silico platforms to meet individual needs. Such predictions are useful for medicinal chemists to prioritize their designed compounds for further drug discovery.

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) main protease has an essential role in viral replication and has become a major target for coronavirus 2019 (COVID-19) drug development. Various inhibitors have been discovered or designed to bind to the main protease. The availability of more than 550 3D structures of the main protease provides a wealth of structural details on the main protease in both ligand-free and ligand-bound states. Therefore, we examined these structures to ascertain the structural features for the role of the main protease in the cleavage of polyproteins, the alternative conformations during main protease maturation, and ligand interactions in the main protease. The structural features unearthed could promote the development of COVID-19 drugs targeting the SARS-CoV-2 main protease.

R&D productivity continues to be the industry's grand challenge. We analyzed the R&D input, output, and outcome of 16 leading research-based pharmaceutical companies over 20 years (2001-2020). Our analysis shows that pharma companies increased their R&D spending at a compound annual growth rate of 6% (2001-2020) to an average R&D expenditure per company of $6.7 billion (2020). The companies in our investigation launched 251 new drugs representing 46% of all CDER-related FDA approvals in the past 20 years. The average R&D efficiency of big pharma was $6.16 billion total R&D expenditures per new drug. Almost half of the leading companies needed to compensate for their negative R&D productivity through mergers and acquisitions.

The quality of biopharmaceuticals is carefully monitored by manufacturers and regulators to ensure safety and efficacy throughout the entire product life cycle. Quality defects can lead to post-approval regulatory actions (RAs) to inform healthcare professionals (HCPs). The present study identified quality-related RAs for biopharmaceuticals approved in the European Union and United States between 1995 and 2019. Quality-related RAs were issued due to various quality defects and required different actions by HCPs. The quality defects were not identified due to a negative impact on efficacy and/or safety, which is reassuring. The findings reflect the capability of the stringent regulatory system and quality control to capture and counter various quality defects before the affected product and batches can harm patients.

Spinal cord injury (SCI) culminates in chronic inflammation and glial scar formation driven by the activation of microglia and astrocytes. Current anti-inflammatory strategies to treat glial activation associated with SCI have several limitations. Existing in vitro and ex vivo models studying molecular mechanisms associated with inflammation focus only on the acute phase. However, the progression of glial cell-derived inflammation over the acute-to-chronic phases has not been assessed. Understanding this progression will help establish a framework for evaluating therapeutic strategies. Additionally, new models could be useful as high-throughput screening (HTS) platforms. This review aims to highlight currently available models and future methods that could facilitate screening of novel therapeutics for SCI.

Over 3 years, the SARS-CoV-2 pandemic killed nearly 7 million people and infected more than 767 million globally. During this time, our very small company was able to contribute to antiviral drug discovery efforts through global collaborations with other researchers, which enabled the identification and repurposing of multiple molecules with activity against SARS-CoV-2 including pyronaridine tetraphosphate, tilorone, quinacrine, vandetanib, lumefantrine, cetylpyridinium chloride, raloxifene, carvedilol, olmutinib, dacomitinib, crizotinib, and bosutinib. We highlight some of the key findings from this experience of using different computational and experimental strategies, and detail some of the challenges and strategies for how we might better prepare for the next pandemic so that potential antiviral treatments are available for future outbreaks.