» Articles » PMID: 38632401

Refining the Impact of Genetic Evidence on Clinical Success

Overview
Journal Nature
Specialty Science
Date 2024 Apr 17
PMID 38632401
Authors
Affiliations
Soon will be listed here.
Abstract

The cost of drug discovery and development is driven primarily by failure, with only about 10% of clinical programmes eventually receiving approval. We previously estimated that human genetic evidence doubles the success rate from clinical development to approval. In this study we leverage the growth in genetic evidence over the past decade to better understand the characteristics that distinguish clinical success and failure. We estimate the probability of success for drug mechanisms with genetic support is 2.6 times greater than those without. This relative success varies among therapy areas and development phases, and improves with increasing confidence in the causal gene, but is largely unaffected by genetic effect size, minor allele frequency or year of discovery. These results indicate we are far from reaching peak genetic insights to aid the discovery of targets for more effective drugs.

Citing Articles

Integration of functional genomics and statistical fine-mapping systematically characterizes adult-onset and childhood-onset asthma genetic associations.

Zhong X, Mitchell R, Billstrand C, Thompson E, Sakabe N, Aneas I medRxiv. 2025; .

PMID: 40034789 PMC: 11875274. DOI: 10.1101/2025.02.11.25322088.


Genome-wide association study of Idiopathic Pulmonary Fibrosis susceptibility using clinically-curated European-ancestry datasets.

Chin D, Hernandez-Beeftink T, Donoghue L, Guillen-Guio B, Guillen-Uio B, Leavy O medRxiv. 2025; .

PMID: 39974050 PMC: 11838657. DOI: 10.1101/2025.01.30.25321017.


Drug-target Mendelian randomisation applied to metabolic dysfunction-associated steatotic liver disease: opportunities and challenges.

Luo S, Zheng M, Wong V, Au Yeung S eGastroenterology. 2025; 2(4):e100114.

PMID: 39944268 PMC: 11770435. DOI: 10.1136/egastro-2024-100114.


Specificity, length, and luck: How genes are prioritized by rare and common variant association studies.

Spence J, Mostafavi H, Ota M, Milind N, Gjorgjieva T, Smith C bioRxiv. 2025; .

PMID: 39935885 PMC: 11812597. DOI: 10.1101/2024.12.12.628073.


UK Biobank-A Unique Resource for Discovery and Translation Research on Genetics and Neurologic Disease.

Taylor H, Lewins M, Foody M, Gray O, Besevic J, Conroy M Neurol Genet. 2025; 11(1):e200226.

PMID: 39911793 PMC: 11796045. DOI: 10.1212/NXG.0000000000200226.


References
1.
DiMasi J, Grabowski H, Hansen R . Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016; 47:20-33. DOI: 10.1016/j.jhealeco.2016.01.012. View

2.
Hay M, Thomas D, Craighead J, Economides C, Rosenthal J . Clinical development success rates for investigational drugs. Nat Biotechnol. 2014; 32(1):40-51. DOI: 10.1038/nbt.2786. View

3.
Wong C, Siah K, Lo A . Estimation of clinical trial success rates and related parameters. Biostatistics. 2018; 20(2):273-286. PMC: 6409418. DOI: 10.1093/biostatistics/kxx069. View

4.
Nelson M, Tipney H, Painter J, Shen J, Nicoletti P, Shen Y . The support of human genetic evidence for approved drug indications. Nat Genet. 2015; 47(8):856-60. DOI: 10.1038/ng.3314. View

5.
Diogo D, Tian C, Franklin C, Alanne-Kinnunen M, March M, Spencer C . Phenome-wide association studies across large population cohorts support drug target validation. Nat Commun. 2018; 9(1):4285. PMC: 6191429. DOI: 10.1038/s41467-018-06540-3. View