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Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval


Autoři: Emily A. King aff001;  J. Wade Davis aff001;  Jacob F. Degner aff001
Působiště autorů: Department of Computational Genomics, AbbVie, North Chicago, Illinois, United States of America aff001
Vyšlo v časopise: Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. PLoS Genet 15(12): e32767. doi:10.1371/journal.pgen.1008489
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1008489

Souhrn

Despite strong vetting for disease activity, only 10% of candidate new molecular entities in early stage clinical trials are eventually approved. Analyzing historical pipeline data, Nelson et al. 2015 (Nat. Genet.) concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. Taking advantage of recent clinical development advances and rapid growth in GWAS datasets, we extend the original work using updated data, test whether genetic evidence predicts future successes and introduce statistical models adjusting for target and indication-level properties. Our work confirms drugs with genetically supported targets were more likely to be successful in Phases II and III. When causal genes are clear (Mendelian traits and GWAS associations linked to coding variants), we find the use of human genetic evidence increases approval by greater than two-fold, and, for Mendelian associations, the positive association holds prospectively. Our findings suggest investments into genomics and genetics are likely to be beneficial to companies deploying this strategy.

Klíčová slova:

Drug discovery – Drug research and development – Gene mapping – Genetic linkage – Genetics of disease – Genome-wide association studies – Human genetics – Catalogs


Zdroje

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Genetika Reprodukční medicína

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PLOS Genetics


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