Literature DB >> 26121088

The support of human genetic evidence for approved drug indications.

Matthew R Nelson1, Hannah Tipney2, Jeffery L Painter1, Judong Shen1, Paola Nicoletti3, Yufeng Shen4, Aris Floratos4, Pak Chung Sham5, Mulin Jun Li6, Junwen Wang6, Lon R Cardon7, John C Whittaker2, Philippe Sanseau2.   

Abstract

Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we investigated how well the current archive of genetic evidence predicts drug mechanisms. We found that, among well-studied indications, the proportion of drug mechanisms with direct genetic support increases significantly across the drug development pipeline, from 2.0% at the preclinical stage to 8.2% among mechanisms for approved drugs, and varies dramatically among disease areas. We estimate that selecting genetically supported targets could double the success rate in clinical development. Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs.

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Year:  2015        PMID: 26121088     DOI: 10.1038/ng.3314

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  20 in total

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Journal:  Nucleic Acids Res       Date:  2011-12-01       Impact factor: 16.971

7.  Genic intolerance to functional variation and the interpretation of personal genomes.

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Journal:  Nature       Date:  2013-12-25       Impact factor: 49.962

9.  The NHGRI GWAS Catalog, a curated resource of SNP-trait associations.

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10.  Mapping the genetic architecture of gene expression in human liver.

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  426 in total

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Review 5.  Drug development in the era of precision medicine.

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Review 6.  The genetics revolution in rheumatology: large scale genomic arrays and genetic mapping.

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Review 7.  Mendelian randomization in cardiometabolic disease: challenges in evaluating causality.

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8.  Quantitative and systems pharmacology 4. Network-based analysis of drug pleiotropy on coronary artery disease.

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Review 9.  Genetic underpinnings of cerebral edema in acute brain injury: an opportunity for pathway discovery.

Authors:  Elayna Kirsch; Natalia Szejko; Guido J Falcone
Journal:  Neurosci Lett       Date:  2020-05-26       Impact factor: 3.046

10.  Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes.

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