Recommendations for Development and Validation of a Fit-For-Purpose Biomarker Assays Using Western Blotting; An-AAPS Sponsored Initiative to Harmonize Industry Practices.

Western blot (WB) assays are routinely used for detection and quantification of biomarkers. Although assay validation to measure biomarkers in complex matrices has become a mainstay process for ligand binding assays (LBA) and mass spectrometry (MS), no guidelines exist yet validate biomarker methods using WB techniques. In this cross-industry white paper, we outlined in detail the key steps for development and for validation of WB assays for protein biomarkers under different contexts of use (COU). In addition, we described how to determine the level of assay validation needed for biomarker assays using Western blotting. For simplicity, we described two paths of WB assay validation. The first path (Path 1) is for biomarkers being analyzed for exploratory research or for internal go- or no/go- decision making. The second path (Path 2) is for clinical decision making such as dose determination or drug response that need to be run in a regulated environment. This work is supported through AAPS Biomarkers and Precision Medicine subteam and represents AAPS members opinion.

2023 White Paper on Recent Issues in Bioanalysis: EU IVDR 2017/746 Implementation/Impact, IVD/CDx/CLIA Approved Assays, High Dimensional Cytometry, Multiplexing Technologies, LBA Tissue Analysis, Vaccine Study Endpoints, Cell-Based Assays for Biomarkers, Cell Therapy and Vaccines (PART 2 - Recommendations on Development & Validation of Biomarkers, IVD, CDx, Cell-Based, Flow Cytometry, Ligand-Binding and Enzyme Assays; Advanced Critical Reagents Strategies).

The 17th Workshop on Recent Issues in Bioanalysis (17th WRIB) took place in Orlando, FL, USA on 19-23 June 2023. 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 17th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week to allow an exhaustive and thorough coverage of all major issues in bioanalysis of biomarkers, immunogenicity, gene therapy, cell therapy and vaccines.Moreover, in-depth workshops on "EU IVDR 2017/746 Implementation and impact for the Global Biomarker Community: How to Comply with these NEW Regulations" and on "US FDA/OSIS Remote Regulatory Assessments (RRAs)" were the special features of the 17th 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 2023 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 2023 edition of this comprehensive White Paper has been divided into three parts for editorial reasons.This publication (Part 2) covers the recommendations on Biomarkers, IVD/CDx, LBA and Cell-Based Assays. Part 1A (Mass Spectrometry Assays and Regulated Bioanalysis/BMV), P1B (Regulatory Inputs) and Part 3 (Gene Therapy, Cell therapy, Vaccines and Biotherapeutics Immunogenicity) are published in volume 16 of Bioanalysis, issues 9 and 7 (2024), respectively.

LipidSIM: Inferring mechanistic lipid biosynthesis perturbations from lipidomics with a flexible, low-parameter, Markov modeling framework.

Lipid metabolism is a complex and dynamic system involving numerous enzymes at the junction of multiple metabolic pathways. Disruption of these pathways leads to systematic dyslipidemia, a hallmark of many pathological developments, such as nonalcoholic steatohepatitis and diabetes. Recent advances in computational tools can provide insights into the dysregulation of lipid biosynthesis, but limitations remain due to the complexity of lipidomic data, limited knowledge of interactions among involved enzymes, and technical challenges in standardizing across different lipid types. Here, we present a low-parameter, biologically interpretable framework named Lipid Synthesis Investigative Markov model (LipidSIM), which models and predicts the source of perturbations in lipid biosynthesis from lipidomic data. LipidSIM achieves this by accounting for the interdependency between the lipid species via the lipid biosynthesis network and generates testable hypotheses regarding changes in lipid biosynthetic reactions. This feature allows the integration of lipidomics with other omics types, such as transcriptomics, to elucidate the direct driving mechanisms of altered lipidomes due to treatments or disease progression. To demonstrate the value of LipidSIM, we first applied it to hepatic lipidomics following Keap1 knockdown and found that changes in mRNA expression of the lipid pathways were consistent with the LipidSIM-predicted fluxes. Second, we used it to study lipidomic changes following intraperitoneal injection of CCl4 to induce fast NAFLD/NASH development and the progression of fibrosis and hepatic cancer. Finally, to show the power of LipidSIM for classifying samples with dyslipidemia, we used a Dgat2-knockdown study dataset. Thus, we show that as it demands no a priori knowledge of enzyme kinetics, LipidSIM is a valuable and intuitive framework for extracting biological insights from complex lipidomic data.