Accelerating drug discovery with mass spectrometry-driven bioanalytical innovations and beyond.

Authors

Joseph N Mwangi, Ryan Hill, Avery Runnebohm, Gregg Czerwieniec, Michael Berna

Published in

Bioanalysis. Pages 1-20. Jun 21, 2026. Epub Jun 21, 2026.

Abstract

The emergence of structurally complex therapeutic modalities, including bispecific antibodies, antibody-drug conjugates, fusion proteins, incretins, radioligand therapeutics, antibody-oligonucleotide conjugates, and small interfering RNAs, demands advanced mass spectrometry workflows across the ADME pipeline. This forward-looking perspective examines the bioanalytical challenges these next-generation therapeutics present, from absorption and distribution through metabolism and elimination. Current MS platforms, LC-MS/MS, high-resolution MS, quantitative mass spectrometry imaging, and ICP-MS, while highly capable, present opportunities for sensitivity enhancement to fully characterize low-dose therapeutics through the elimination phase. To quantify this need, we developed a pharmacokinetic-driven prediction framework and applied it to FDA-approved complex therapeutics, demonstrating that enhanced sensitivity would enable comprehensive metabolite characterization, particularly during the elimination phase. We identify five convergent innovation priorities: (1) addressing modality complexity through integrated ADME workflows; (2) continued advancement of instrument sensitivity for low-dose therapeutics; (3) resolving biotransformation challenges through enhanced analytical resolution; (4) improving qMSI capabilities for therapeutic-level tissue detection; and (5) implementing AI/ML-driven automation for data complexity management. Rather than advocating for MS-only solutions, we recommend integration of mass spectrometric structural specificity with complementary high-throughput technologies; immunoassays, hybridization ELISA, qPCR, and element-specific detection, to enable comprehensive bioanalysis across all modalities, accelerating the path from discovery to development.

PMID:
42324885
Bibliographic data and abstract were imported from PubMed on 22 Jun 2026.

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