Evidence map›Paper›PMID 42907642›Full record

ReviewAdvances in experimental medicine and biology2026

Mass Spectrometry-Based Biomarkers in Drug Development.

Michelle R Robinson, Ronald A Miller, Daniel S Spellman

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Michelle R RobinsonPharmacokinetics, Pharmacodynamics and Drug Metabolism, Merck Research Laboratories, 770 Sumneytown Pike, West Point, PA, 19486, USA.
Ronald A MillerImpact Analytical, 1940 N Stark Road, Midland, MI, 48642, USA.
Daniel S SpellmanPharmacokinetics, Pharmacodynamics and Drug Metabolism, Merck Research Laboratories, 770 Sumneytown Pike, West Point, PA, 19486, USA. daniel_spellman@merck.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in mass spectrometry, proteomics, protein bioanalytical approaches, and biochemistry have led to a rapid evolution and expansion in the area of mass spectrometry-based biomarker discovery and development. The last decade has also seen significant progress in establishing accepted definitions, guidelines, and criteria for the analytical validation, acceptance, and qualification of biomarkers. These advances have coincided with a decreased return on investment for pharmaceutical research and development and an increasing need for better early decision-making tools. Empowering development teams with tools to measure a therapeutic interventions impact on disease state and progression, measure target engagement and confirm predicted pharmacodynamic effects is critical to efficient data-driven decision making. Appropriate implementation of a biomarker or a combination of biomarkers can enhance understanding of a drug mechanism, facilitate effective translation from the preclinical to clinical space, enable early proof of concept and dose selection, and increase the efficiency of drug development. Here, we will provide descriptions of the different classes of biomarkers that have utility in the drug development process, as well as review specific, protein-centric, mass spectrometry-based approaches for the discovery of biomarkers and development of targeted assays to measure these markers in a selective and analytically precise manner.

Indexed as

BiomarkersDrug DevelopmentDrug DiscoveryMass SpectrometryProteomicsAnimalsHumansBiomarkers

Identifiers

PMID42907642

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.