Johnson Dale E, Rodgers Amie D
Emiliem Inc, 6027 Christie Avenue PO Box 99200, Emeryville, CA 94608, USA.
Curr Opin Drug Discov Devel. 2006 Jan;9(1):29-37.
Computational tools for predicting toxicity have been envisioned to have the potential to broadly impact the attrition rate of compounds in early research and development, and prove successful in predicting adverse drug reactions (ADRs) in patients enrolled in clinical trials, and particularly prior to the marketing of drugs. The impact of such tools to date, however, has been modest and relatively narrow in scope. It is important to note that advances within medical science and newer approaches in clinical development will require predictive toxicology applications to be viable, and therefore efforts must be directed into making these tools relevant to the goal of preventing undesired toxicity in patients. In this Editorial Opinion, the current status of computational toxicology within industry is reviewed and areas in which advances can be made are highlighted. While predicting the potential of a compound to induce specific ADRs continues to be a formidable task, the field of computational biology is now heading in a direction more relevant to human disease and adverse outcomes.
人们设想,用于预测毒性的计算工具有可能广泛影响早期研发中化合物的淘汰率,并在预测参与临床试验的患者,特别是在药物上市前的患者的药物不良反应(ADR)方面取得成功。然而,迄今为止,此类工具的影响较为有限,范围也相对较窄。需要注意的是,医学科学的进步和临床开发中的新方法将要求预测毒理学应用切实可行,因此必须致力于使这些工具与预防患者不良毒性这一目标相关。在这篇编辑意见中,回顾了行业内计算毒理学的现状,并强调了可以取得进展的领域。虽然预测化合物诱发特定ADR的可能性仍然是一项艰巨的任务,但计算生物学领域目前正朝着与人类疾病和不良后果更相关的方向发展。