Research press release


Nature Genetics

Predicting drug trial outcomes


開発中の新薬の半数以上は、マウスなどの動物モデルを用いた実験室での研究から予想された治療効果が臨床試験で確認できず、頓挫している。今回、M Nelsonたちは、薬剤開発過程の早い段階で別の情報源を利用することで、その成功率を高められないか検討した。Nelsonたちは、特定の疾患の発症リスクと有意に関連する遺伝子または遺伝子バリアントを同定する遺伝的関連研究に着目した。遺伝的関連が認められても、因果関係が必ず存在することにはならないが、従来から用いられている薬物選定方法と組み合わせて用いることで、正しい薬物標的を選定する確率を高められる可能性がある。


Choosing drug targets based on studies of genetic associations with disease could potentially double the success rate of new drug development, reports a study published online this week in Nature Genetics.

More than half of newly developed drugs fail during clinical trials because they do not have the therapeutic effects expected based on laboratory studies in mice and other animal models. Matthew Nelson and colleagues asked whether other sources of information could be used earlier in the drug development process to increase the rate of success. They looked to genetic association studies, in which particular genes or gene variants are found to be significantly associated with the risk of developing specific diseases. Genetic associations do not always indicate a causative relationship. However, they could potentially increase the chances of selecting a successful drug target when combined with traditional drug selection methods.

The authors created a catalog of gene?disease associations based on genetic studies and correlated this with information about drug trials. They found that successful drugs (those that were eventually approved for treatment of a disease) were more likely to target genes with evidence of association to that disease or a related trait. Based on this information, they estimated that using genetic association data applied to drug target selection could significantly boost the chances of success.

doi: 10.1038/ng.3314

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