ReviewESMO open2026
Personalized medicine, scientific revolution or self-serving illusion: viewpoint from EORTC-PAMM Group.
Review in ESMO open, 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
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Personalized medicine has redefined oncology by tailoring treatments to molecular and clinical characteristics. However, despite remarkable advances in biomarker discovery and targeted therapy, the integration of pharmacological principles into precision oncology remains limited. The resulting discrepancy between biological innovation and therapeutic optimization contributes to high attrition rates in drug development, inconsistent real-world efficacy, and escalating financial toxicity. The European Organisation for Research and Treatment of Cancer Pharmacology and Molecular Mechanisms Group explored how pharmacology can bridge the gap between molecular precision and clinical reality. Although understanding mechanisms of action is a critical first step, the subsequent translation of this knowledge into individualized dosing and scheduling strategies and rational drug combinations is equally essential. Achieving this requires the use of quantitative tools, such as pharmacokinetic/pharmacodynamic modeling, therapeutic drug monitoring, and real-world evidence (RWE). These patient-centered approaches enable continuous learning from patient data, refine our understanding of exposure-response relationships, and support adaptive treatment strategies across diverse populations. We also discuss the rise of tumor-agnostic approvals, which transcend histological boundaries yet expose disparities in national regulatory and reimbursement frameworks. Ensuring equitable access to mechanism-driven therapies requires harmonized policies integrating pharmacological, clinical, and ethical perspectives. True personalization in oncology requires moving beyond target selection to delivering the right dose to the right patient at the right time. Embedding holistic pharmacology approaches into the design, evaluation, and postmarketing use of anticancer therapies will improve efficacy, minimize toxicity, and promote value-based care. Integrating mechanistic understanding with quantitative pharmacology and RWE represents the next frontier of precision oncology, transforming innovation into sustainable, patient-centered benefit.
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What OpenQuestion holds
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.