2025 White Paper on Recent Issues in Bioanalysis: What is the Future of Bioanalytical LIMS? AI/ML Integration in Bioanalysis; Tear Sample Collection; Radiolabeled Mass Balance Studies; Chiral Assays; Bioanalysis of Antibody-Oligonucleotide & Bicycle Drug Conjugates ( <u>PART 1A</u> – Recommendations on Mass Spectrometry Assays, Chromatography, Sample Preparation and Regulated Bioanalysis Sampling, Validating, Analyzing & Reporting <u>PART 1B</u> – Regulatory Agencies’ Input on Regulated Bioanalysis/BMV)
Bibliographic record
Abstract
The 19th Workshop on Recent Issues in Bioanalysis (19th WRIB) took place in New Orleans, LA, USA on April 7-11, 2025. Over 1200 professionals representing pharma/biotech companies, CROs, and multiple regulatory agencies convened to actively discuss the most current topics of interest in bioanalysis. The 19th 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 “Implementation Practice for the Newest ELN/LIMS Systems” and on “Vaccine Cell-Based/Functional & Molecular Assays as part of the harmonization of vaccine clinical assays global initiative” were the special features of the 19th edition. As in previous years, WRIB continued to gather a wide diversity of international, industry opinion leaders and Regulatory Agency 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 2025 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 2025 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 1) covers in the Part 1A the recommendations on Mass Spectrometry Assays and Regulated Bioanalysis/BMV and in Part 1B the Regulatory Inputs on these topics. Part 2 (Biomarkers/BAV, IVD/CDx, Ligand-Binding Assays and Cell-Based Assays) and Part 3 (Gene Therapy, Cell therapy, Vaccines and Biotherapeutics Immunogenicity) are published in volume 18 of Bioanalysis, issues 1 and 2 (2026), respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.056 | 0.046 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".