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Mendelian randomisation applied to drug development in cardiovascular disease: a review
  1. Lauren E Mokry1,2,
  2. Omar Ahmad3,
  3. Vincenzo Forgetta1,
  4. George Thanassoulis4,5,6,
  5. J Brent Richards1,2,5,7
  1. 1Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada
  2. 2Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
  3. 3Division of Internal Medicine, McGill University, Montreal, Canada
  4. 4Preventive and Genomic Cardiology, McGill University Health Centre, McGill University, Montreal, Canada
  5. 5Department of Medicine, McGill University, Montreal, Canada
  6. 6The Research Institute of McGill University Health Centre, McGill University, Montreal, Canada
  7. 7Department of Twin Research, King's College London, London, UK
  1. Correspondence to Dr Brent Richards, Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, 3755 Côte Ste Catherine Road, Montreal, Quebec, Canada J3T 1E2; brent.richards{at}mcgill.ca

Abstract

Despite increased expenditure, productivity of the pharmaceutical industry has decreased and currently 90% of developed molecules entering phase II and phase III clinical trials fail to gain regulatory approval. Most of these failures are due to lack of therapeutic efficacy rather than lack of safety, suggesting that drug development failures may often be due to poor drug target validation. Currently, drug targets are largely validated using in vitro assays and animal models which may not translate well to human disease. Emerging methods from human genetics, such as Mendelian randomisation (MR), can enable the validation of putative biomarker drug targets in humans prior to the initiation of clinical trials. MR studies can provide evidence as to whether genetically determined levels of a biomarker influence disease aetiology, enabling investigators to infer whether the biomarker is causal. We review the extent to which MR techniques may be helpful in biomarker validation by assessing the concordance between the results from MR studies and phase III clinical trials for lipid therapy in cardiovascular disease. Our findings show that concordance is highest when MR provides evidence suggesting that a biomarker is not causal. In contrast, there are many examples of clinical trials that still failed despite targeting confirmed causal biomarkers. We discuss why such trials may not succeed, despite evidence for causality in MR studies, and outline important limitations when using MR for biomarker validation in drug development. Nonetheless, given the current inefficiencies in drug development, MR methods have potential to improve the success rate of drug development and ultimately the delivery of new molecules to clinical care.

  • Mendelian randomization
  • Drug development
  • Genetic epidemiology
  • Cardiovascular disease

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