ReviewACS pharmacology & translational science2026
Biography as Biology in Drug Development: Bio-Biographical Response States for Translational Pharmacology.
Review in ACS pharmacology & translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular stratification has improved drug development, yet treatment effects remain heterogeneous within apparently similar patients. We propose that selected lived exposures be studied as bio-biographical response states: prospectively measured combinations of experience, candidate mediator biology, and treatment context that may modify efficacy, toxicity, adherence, or end point ascertainment. This Perspective translates the concept into a falsifiable development framework. It defines pathway-specific hypotheses, consolidates trial-feasible measures, uses immuno-oncology as an implementation test case, and specifies stage-appropriate evidentiary gates. The framework does not treat adversity as destiny or assume that association establishes causation. It requires reliable measurement, formal interaction estimates, competing-explanation analyses, independent replication, and a defined decision consequence. Used with these guardrails, biography can complement molecular pharmacology by revealing reproducible host states that otherwise appear as unexplained response heterogeneity.
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Registered trials
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.