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The Role of Statistical Thinking in Biopharmaceutical Research
No full textThe development of new drugs has evolved dramatically over the past decade. Advances in technology enable scientists to generate 'big data' faster than ever before. The availability of complex, high-volume data in turn creates demand for innovative quantitative solutions and tools in a rapidly evolving landscape. As a result, the role of the statistical scientist in collaborative research has never been more important.
Reflecting on these changes, Cox (2012) wrote, “…[A]lthough the tactics of statistical analysis have been utterly changed… the strategy of research design and analysis has been much less affected…” In this paper, we argue that the practice of statistics is built on the foundation of good statistical thinking and consists of a complex combination of problem-solving skills, the essence of what is meant by the “strategy of research.”. Although others have highlighted the role of statistical thinking in research design and analysis, in the age of data science, machine learning and artificial intelligence, it cannot be emphasized enough. We outline four general steps that contribute to good statistical thinking and illustrate them with five use cases (‘vignettes’) as well as a detailed case study discussion from a maintenance therapy clinical trial for depression
Using enhanced development tools offered by analytical Quality by Design to support switching of an analytical quality control method
No full textQuality by Design (QbD) principles play an increasingly important role in pharmaceutical industry. Here, we used an analytical QbD (AQbD) approach to develop a capillary electrophoresis method under reducing conditions (rCE-SDS), with the aim of replacing SDS-PAGE as release and stability test method for a commercialized monoclonal antibody product. Method development started with defining analytical method performance requirements as part of an analytical target profile (ATP), followed by a systematic risk assessment of method input parameters and their relation to defined method outputs. Based on this, design of experiments (DoE) studies were performed to identify a method operable design region (MODR). The MODR could be leveraged to improve method robustness. In a bridging study, it was demonstrated that the rCE-SDS method is more sensitive than the legacy SDS-PAGE method, and a correlation factor could be established to compensate for an off-set due to the higher sensitivity, without losing the correlation to the historical data acquired with the former method. Overall, systematic application of AQbD principles for designing and developing a new analytical method helped to elucidate the complex dependency of method outputs on its input parameters. The link of the method to critical quality attributes and the definition of method performance requirements were found to be most relevant for de-risking the analytical method switch, regarding impact on the control strategy
Computer-aided evaluation and exploration of chemical spaces constrained by reaction pathways
No full textThe processes of molecular design and synthetic route selection are necessarily
intertwined during discovery. Computational tools have been developed to facilitate
synthesis planning, but in a discovery setting, finding a single route to a
single molecule of interest may be less important than finding a route that enables
rapid access to a library of analogs. Here, we demonstrate how we can estimate
diversifiability and use it as a criterion during route selection. We illustrate how
the chemical space of synthetically-accessible analogs is influenced by properties
of alternative starting materials or constraints on their cost. Finally, we integrate
these analyses with a synthesizability-constrained hit expansion workflow
in a virtual screening pipeline for focused library expansion around putative hits
to support molecular optimization. As medicinal chemistry and adjacent fields
shift towards more autonomous design and synthesis of new molecules, it will be
increasingly important to embed considerations of synthesizability into molecular
design to ensure that computational recommendations are actionable
Investigation of the differences in the pharmacokinetics of CYP2D6 substrates, desipramine and dextromethorphan in healthy African subjects carrying the allelic variants CYP2D6*17 and CYP2D6*29 when compared with normal metabolizers
No full textThis study investigated the differences in the pharmacokinetics (PK) of dextromethorphan and desipramine in African healthy volunteers to understand the effect of allelic variants of the human cytochrome-P450(CYP)2D6 enzyme namely, CYP2D6*1/*2 diplotypes, CYP2D6*17*17 and CYP2D6*29*29 genotypes. Overall, 28 adults were included through genotype screening into the three cohorts: CYP2D6*1/*2 (n=12), CYP2D6*17*17 (n=12), and CYP2D6*29*29 (n=4). Each subject received a single oral dose of dextromethorphan 30-mg syrup on Day 1 and desipramine 50-mg tablet on Day 8. The PK parameters, area under plasma concentration-time curve from time of dosing to time of last quantifiable concentration (AUClast) and extrapolated to infinity (AUCinf), and maximum plasma concentration (Cmax) were determined. For both dextromethorphan and desipramine, AUCinf and Cmax were higher in subjects of the CYP2D6*29*29 and CYP2D6*17*17 cohorts as compared with those reported in the CYP2D6*1/*2 diplotype cohort, and for normal metabolizers in literature.
All PK parameters including AUCinf, Cmax, and elimination half-life followed a similar trend: CYP2D6*17*17 >CYP2D6*29*29 >CYP2D6*1/*2. The plasma and urinary drug/metabolite exposure ratios of both drugs were higher in subjects of the CYP2D6*17*17 and CYP2D6*29*29 cohorts when compared with those in the CYP2D6*1/*2 diplotype cohort. All adverse events were mild, except for one subject with CYP2D6*17*17 who had moderately severe headache with desipramine. These results indicated that subjects with CYP2D6*17*17 and CYP2D6*29*29 genotypes were 5–10 times slower metabolizers than those with CYP2D6*1/*2 diplotypes. These findings suggest that dose optimization may be required when administering CYP2D6 substrate drugs in African patients. Larger studies can further validate these findings
STREAMLINING FOOD EFFECT ASSESSMENT – ARE REPEAT FOOD EFFECT STUDIES NEEDED? AN IQ ANALYSIS
No full textCurrent regulatory guidelines on drug-food interactions recommend an early assessment of food effect to inform clinical dosing instructions, as well as conducting a pivotal food effect study on the to-be-marketed formulation if different from that used in pivotal trials. Study waivers are currently only granted for BCS Class 1 drugs. Thus, repeated food effect studies are very common in clinical development, with the initial evaluation conducted as early as the first-in-human studies. Information on such repeated food effect studies is not common in the public domain. The goal of the work presented in this manuscript from the Food Effect PBPK IQ Working Group was to compile a dataset with experience on these studies across pharmaceutical companies and provide recommendations on their conduct. Based on 53 studies collected, we report here that the majority of the repeat food effect studies do not result in meaningful differences in the assessment of food effect. Seldom changes observed were more than 2-fold. There was no clear relationship between the change in food effect and the formulation change, indicating that in the majority of cases the food effect is primarily driven by inherent compound properties, and not formulation,. Representative examples of PBPK models demonstrate that following appropriate validation of the model with the initial food effect study, the models can be applied to future formulations. We recommend that repeat food effect studies should be approached on a case-by-case basis taking into account the totality of evidence including use of PBPK modeling as appropriate
2022 White Paper on Recent Issues in Bioanalysis: ICH M10 BMV Guideline & Global Harmonization; Hybrid Assays; Oligonucleotides & ADC; Non-Liquid & Rare Matrices; Regulatory Inputs (Part 1A - Recommendations on Mass Spectrometry, Chromatography and Sample Preparation, Novel Technologies, Novel Modalities, and Novel Challenges, ICH M10 BMV Guideline & Global Harmonization Part 1B - Regulatory Agencies' Inputs on Regulated Bioanalysis/BMV, Biomarkers/CDx/BAV, Immunogenicity, Gene & Cell Therapy and Vaccine).
No full textThe 16th Workshop on Recent Issues in Bioanalysis (16th WRIB) took place in Atlanta, GA, USA on September 26-30, 2022. Over 1000 professionals representing pharma/biotech companies, CROs, and multiple regulatory agencies convened to actively discuss the most current topics of interest in bioanalysis. The 16th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on the ICH M10 BMV final guideline (focused on this guideline training, interpretation, adoption and transition); mass spectrometry innovation (focused on novel technologies, novel modalities, and novel challenges); and flow cytometry bioanalysis (rising of the 3rd most common/important technology in bioanalytical labs) were the special features of the 16th edition. As in previous years, WRIB continued to gather a wide diversity of international, industry opinion leaders and regulatory authority experts working on both small and large molecules as well as gene, cell therapies and vaccines to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance, and achieving scientific excellence on bioanalytical issues. This 2022 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2022 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 1A) covers the recommendations on Mass Spectrometry and ICH M10. Part 1B covers the Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine. Part 2 (LBA, Biomarkers/CDx and Cytometry) and Part 3 (Gene Therapy, Cell therapy, Vaccines and Biotherapeutics Immunogenicity) are published in volume 15 of Bioanalysis, issues 15 and 14 (2023), respectively
Antifibrotic Drug Nintedanib Inhibits CSF1R to Promote IL-4-associated Tissue Repair Macrophages.
No full textProfibrotic and prohomeostatic macrophage phenotypes remain ill-defined, both and , impeding the successful development of drugs that reprogram macrophages as an attractive therapeutic approach to manage fibrotic disease. The goal of this study was to reveal profibrotic and prohomeostatic macrophage phenotypes that could guide the design of new therapeutic approaches targeting macrophages to treat fibrotic disease. This study used nintedanib, a broad kinase inhibitor approved for idiopathic pulmonary fibrosis, to dissect lung macrophage phenotypes during fibrosis-linked inflammation by combining and bulk and single-cell RNA-sequencing approaches. In the bleomycin model, nintedanib drove the expression of IL-4/IL-13-associated genes important for tissue regeneration and repair at early and late time points in lung macrophages. These findings were replicated in mouse primary bone marrow-derived macrophages exposed to IL-4/IL-13 and nintedanib. In addition, nintedanib promoted the expression of IL-4/IL-13 p
Chemoproteomics-enabled discovery of a covalent molecular glue degrader targeting NF-κB.
No full textTargeted protein degradation has arisen as a powerful therapeutic modality for degrading disease targets. While proteolysis-targeting chimera (PROTAC) design is more modular, the discovery of molecular glue degraders has been more challenging. Here, we have coupled the phenotypic screening of a covalent ligand library with chemoproteomic approaches to rapidly discover a covalent molecular glue degrader and associated mechanisms. We have identified a cysteine-reactive covalent ligand EN450 that impairs leukemia cell viability in a NEDDylation and proteasome-dependent manner. Chemoproteomic profiling revealed covalent interaction of EN450 with an allosteric C111 in the E2 ubiquitin-conjugating enzyme UBE2D. Quantitative proteomic profiling revealed the degradation of the oncogenic transcription factor NFKB1 as a putative degradation target. Our study thus puts forth the discovery of a covalent molecular glue degrader that uniquely induced the proximity of an E2 with a transcription factor to induce its degradation in cancer cells