Evidence map›Paper›PMID 31830040›Full record

ArticlePLoS genetics2019

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.

Emily A King, J Wade Davis, Jacob F Degner

Abstract read
In one paragraph

Article in PLoS genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 351 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
351citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

351 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  3. IBDTransDB: a manually curated transcriptomic database for inflammatory bowel disease.Database : the journal of biological databases and curation · 2024
    Pooled it
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  7. Positive selection screen identifies natural product β-catenin inactivators.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  8. Genome-scale perturbation signatures from primary human CD4bioRxiv : the preprint server for biology · 2026
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291 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Emily A KingDepartment of Computational Genomics, AbbVie, North Chicago, Illinois, United States of America.ORCID 0000-0003-1877-8673
J Wade DavisDepartment of Computational Genomics, AbbVie, North Chicago, Illinois, United States of America.
Jacob F DegnerDepartment of Computational Genomics, AbbVie, North Chicago, Illinois, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Databases, GeneticDrug ApprovalGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansModels, StatisticalPharmacogenomic VariantsPhenotypePrecision MedicineQuantitative Trait Loci

Identifiers

PMID31830040
PMCPMC6907751

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.