Review Article | Published:

The genetics of drug efficacy: opportunities and challenges

Nature Reviews Genetics volume 17, pages 197206 (2016) | Download Citation


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.

Key points

  • To date, there have been at least 76 genome-wide association studies and a large number of candidate gene studies of drug efficacy. From these, there are at least 12 drugs with high-confidence genetic predictors of drug efficacy.

  • Genetic predictors of drug efficacy are mostly common variants with a range of effect sizes; most have been discovered through studies of sensitive quantitative measures of drug response, and all but one were discovered following drug approval.

  • Less than 20% of drugs are estimated to have common genetic predictors of efficacy that are large enough to inform clinical decision making.

  • There are limited scenarios in which genetics can 'rescue' a trial that fails owing to lack of efficacy. However, advances in genetic technologies can allow for cost-effective screening for genetic predictors with potential clinical utility during the course of clinical development.

  • Pharmaceutical and academic researchers should combine resources to study the efficacy pharmacogenetics of marketed drugs.

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The authors thank S. Ghosh, L. Hosking, C. Cox, S. Stinnett and three anonymous reviewers for valuable discussions and input.

Author information

Author notes

    • Liling Warren

    Present address: Acclarogen, Cambridge CB4 0WS, UK.

    • Matthew R. Nelson
    •  & Toby Johnson

    These authors contributed equally to this work.


  1. Target Sciences, GlaxoSmithKline, King of Prussia, Pennsylvania 19406, USA.

    • Matthew R. Nelson
    •  & Dawn M. Waterworth
  2. Target Sciences, GlaxoSmithKline, Stevenage SG1 2NY, UK.

    • Toby Johnson
    •  & Chun-Fang Xu
  3. GlaxoSmithKline, Durham, North Carolina 27713, USA.

    • Liling Warren
  4. PAREXEL International, Research Triangle Park, North Carolina 27713, USA.

    • Arlene R. Hughes
  5. Target Sciences, GlaxoSmithKline, Seattle, Washington 98107, USA.

    • Stephanie L. Chissoe


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Competing interests

M.R.N., T.J., A.R.H., S.L.C., C.-F.X. and D.M.W. are all full-time employees of GlaxoSmithKline. L.W. is a former employee of GlaxoSmithKline.

Corresponding author

Correspondence to Dawn M. Waterworth.

Supplementary information

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    Supplementary information S1 (table)

    In format provided by Nelson et al. (April 2016); doi:10.1038/nrg.2016.12

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    Supplementary information S3 (table)

    In format provided by Nelson et al. (April 2016); doi:10.1038/nrg.2016.12

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    Supplementary information S2 (figure)

    Relationship between minor allele frequency and effect size to achieve statistical power to detect a pharmacogenetic effect.

  2. 2.

    Supplementary information S5 (figure)

    GWAS statistical power (alpha = 5 × 10−8) for efficacy pharmacogenetics based on a range of potential trial outcomes. Power to detect association with time to event efficacy outcome.


Companion diagnostics

Diagnostic tests used to determine the applicability of a therapeutic drug to a specific patient.


The branch of pharmacology concerned with the movement of drugs within the patient's body.

Drug efficacy

The ability of a drug to achieve the desired effect.


Measurable indicators of a given biological state or condition.

Prognostic effects

Effects that may be independent of the drug or treatment received.

Predictive effects

Effects that depend on the drug or treatment received, and therefore predict which patients are most likely to respond.

Clinical Pharmacogenetics Implementation Consortium

(CPIC). A shared project between the Pharmacogenomics Knowledge Base (PharmGKB) and the Pharmacogenomics Research Network, whose goal is to address some of the barriers to the implementation of pharmacogenetic tests into clinical practice.

Pharmacogenomics Knowledge Base

(PharmGKB). A database of comprehensively collected information about genes and response to drugs and/or disease.


(Soliris; Alexion Pharmaceuticals). A humanized monoclonal antibody that is a terminal complement inhibitor and the first agent approved for the treatment of atypical haemolytic uraemic syndrome.


A class of cholesterol-lowering drugs that inhibit the enzyme 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR).

Poly(ADP-ribose) polymerase 1

(PARP1). An enzyme involved in DNA repair. A PARP1 inhibitor, olaparib (Lynparza; AstraZeneca), is an approved targeted therapy for ovarian cancer.


Widely used anti-diabetic drugs that act by increasing insulin release from the β-cells in the pancreas.

Clinical end point

The occurrence of a disease or symptom that constitutes one of the target outcomes of a clinical trial.


Relating to the mechanism of action of a drug and its effects on the patient.

Surrogate end point

A biomarker intended to substitute for a clinical end point.

Primary end point

The measure for which subjects are randomized and for which a clinical trial is powered, and which determines primary success or failure of the trial.

BRACAnalysis CDx

An FDA (US Food and Drug Administration)-approved companion diagnostic test for breast cancer 1 (BRCA1) and BRCA2 that is intended to be used as an aid in treatment decision making for olaparib (Lynparza; AstraZeneca), a PARP1 inhibitor.

Bayesian prior

A prior belief that is incorporated into a probability distribution before specific evidence is taken into account.

Alpha allocation

A strategy for performing analyses that outlines the false-positive rate that will be used for each analysis to achieve an overall desired false-positive rate (for example, 0.05).

Bonferroni principle

A statistical approach that controls for multiple testing.


Biorepositories that store human samples.

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