Cook David
AstraZeneca plc, Global Safety Assessment, Mereside, Alderley Park, Macclesfield, Cheshire, SK10 4TG, UK.
IDrugs. 2010 Feb;13(2):85-9.
Despite the significant investment made in drug safety testing by the pharmaceutical industry, new drugs continue to experience a substantial failure rate because of unacceptable toxicology in patients. More effective methods of predicting potential safety issues that can be employed during the drug design phase are required to reduce this attrition. Computational biology offers such new approaches, and is a term that includes a wide range of disciplines, the general features of which are the application of computer science and mathematics to biology. The techniques used in computational biology can integrate and analyze large complex sets of data and enable scientists to truly exploit the large amounts of information available to them, both in predicting likely risk and in understanding issues when they arise. These new approaches can only be achieved by embracing in silico experimentation as a valid and equal partner to other forms of experimentation in drug safety, and by integrating these approaches alongside current methods to support better decision-making in R&D that will ultimately result in the production of safer medicines.
尽管制药行业在药物安全性测试方面投入巨大,但由于患者中出现不可接受的毒理学问题,新药的失败率仍然很高。需要更有效的方法来预测药物设计阶段可能出现的潜在安全问题,以减少这种损耗。计算生物学提供了这样的新方法,它是一个涵盖广泛学科的术语,其一般特征是将计算机科学和数学应用于生物学。计算生物学中使用的技术可以整合和分析大量复杂的数据,并使科学家能够真正利用现有的大量信息,无论是预测可能的风险还是在问题出现时理解问题。只有将计算机模拟实验作为药物安全性其他形式实验的有效且平等的伙伴,并将这些方法与当前方法相结合,以支持研发中的更好决策,最终生产出更安全的药物,才能实现这些新方法。