ReviewJournal of clinical pharmacology2026
Quantitative Systems Pharmacology (QSP): Bridging Biology and Mechanism with Clinical Drug Development Decisions.
Review in Journal of clinical pharmacology, 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
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative systems pharmacology (QSP) integrates mechanistic representations of biology with quantitative pharmacology to support decision‑making across the drug development continuum. Over the past two decades, QSP has evolved from an exploratory research activity into an established component of model‑informed drug development (MIDD), particularly in settings where system‑level interactions complicate the interpretation of exposure-response relationships or where direct clinical data are limited. This review outlines the historical development and conceptual foundations of QSP and summarizes representative clinical applications spanning early, mid, and late development. Examples highlight how QSP is used to support mechanism-based dose and regimen selection, optimization of combination strategies, biomarker‑informed patient stratification, and lifecycle management decisions. We also discuss considerations for rigor, credibility, and trustworthiness in alignment with the ICH M15 framework, emphasizing clearly defined questions of interest, context of use, and proportional, decision-driven evaluation of assumptions and uncertainty. Finally, we consider emerging challenges and opportunities for QSP adoption, including reuse of platform models, integration of multi-omics data, and selective incorporation of AI-enabled methods within mechanistically interpretable frameworks.
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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.