Knockouts model the 100 best-selling drugs—will they model the next 100? is a research paper published in Nature Reviews Drug Discovery (2003). On theSindex it has a DataRank of 0.896. It has been cited 392 times.
The biopharmaceutical industry is currently faced with a tremendous number of potential drug targets identified through the sequencing of the human genome. The challenge ahead is to delineate those targets with the greatest value for therapeutic intervention. Here, we critically evaluate mouse-knockout technology for target discovery and validation. A retrospective evaluation of the knockout phenotypes for the targets of the 100 best-selling drugs indicates that these phenotypes correlate well with known drug efficacy, illuminating a productive path forward for discovering future drug targets. Prospective mining of the druggable genome is being catalysed by large-scale mouse knockout programs combined with phenotypic screens focused on identifying targets that modulate mammalian physiology in a therapeutically relevant manner.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.896
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.