ReviewNature reviews. Genetics2016
The genetics of drug efficacy: opportunities and challenges.
Review in Nature reviews. Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 2 of them syntheses that pooled 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.
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
68 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Role of Mitochondrial DNA Variation in Drug Response: A Systematic Review.Frontiers in genetics · 2021Pooled it
- Pooled it
- Pharmacogenomics polygenic risk score for drug response prediction using PRS-PGx methods.Nature communications · 2022Trial
- Pharmacogenetic investigation of efficacy response to mepolizumab in eosinophilic granulomatosis with polyangiitis.Rheumatology international · 2020Trial
- Pharmacogenomic predictors of drug response and choice in dyslipidemia and hypertension.medRxiv : the preprint server for health sciences · 2026Article
- Pre-emptive pharmacogenetic testing in Italy: a review of evidence and multidisciplinary consensus on key priorities for implementation.Frontiers in public health · 2026Review
- Artificial intelligence in precision medicine: transforming disease subtyping, medical imaging, and pharmacogenomics.Emerging topics in life sciences · 2025Article
- Multiomics integration prioritizes potential drug targets for multiple sclerosis.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Genome-wide enhancer-gene regulatory maps of liver reveal novel regulatory mechanisms underlying NAFLD pathogenesis.BMC genomics · 2025Article
- Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications.Nature communications · 2025Article
- Decoding uncertainty for clinical decision-making.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- AI-Based Drug Discovery and Design for Different Genetic Designs.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Characterizing the genetic architecture of drug response using gene-context interaction methods.Cell genomics · 2024Article
- Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications.medRxiv : the preprint server for health sciences · 2024Article
- Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia.European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology · 2024Article
- Analysis of the Relationship between Rheumatoid Arthritis and Osteoporosis Based on Mendelian Randomization.Current rheumatology reviews · 2024Article
- Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Pharmacogenomics: current status and future perspectives.Nature reviews. Genetics · 2023Review
- Examining the shared etiology of psychopathology with genome-wide association studies.Physiological reviews · 2023Review
- Single-cell-led drug repurposing for Alzheimer's disease.Scientific reports · 2023Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lack of sufficient efficacy is the most common cause of attrition in late-phase drug development. It has long been envisioned that genetics could drive stratified drug development by identifying those patient subgroups that are most likely to respond. However, this vision has not been realized as only a small proportion of drugs have been found to have germline genetic predictors of efficacy with clinically meaningful effects, and so far all but one were found after drug approval. With the exception of oncology, systematic application of efficacy pharmacogenetics has not been integrated into drug discovery and development across the industry. Here, we argue for routine, early and cumulative screening for genetic predictors of efficacy, as an integrated component of clinical trial analysis. Such a strategy would identify clinically relevant predictors that may exist at the earliest possible opportunity, allow these predictors to be integrated into subsequent clinical development and provide mechanistic insights into drug disposition and patient-specific factors that influence response, therefore paving the way towards more personalized medicine.
Indexed as
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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.