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药物代谢动力学和药代动力学的计算机模拟预测。由欧洲科学与技术合作组织B15行动组组织的专家会议报告。

In silico prediction of ADME and pharmacokinetics. Report of an expert meeting organised by COST B15.

作者信息

Boobis Alan, Gundert-Remy Ursula, Kremers Pierre, Macheras Panos, Pelkonen Olavi

机构信息

Section on Clinical Pharmacology, Imperial College, London, UK.

出版信息

Eur J Pharm Sci. 2002 Dec;17(4-5):183-93. doi: 10.1016/s0928-0987(02)00185-9.

Abstract

The computational approach is one of the newest and fastest developing techniques in pharmacokinetics, ADME (absorption, distribution, metabolism, excretion) evaluation, drug discovery and toxicity. However, to date, the software packages devoted to ADME prediction, especially of metabolism, have not yet been adequately validated and still require improvements to be effective. Most are 'open' systems, under constant evolution and able to incorporate rapidly, and often easily, new information from user or developer databases. Quantitative in silico predictions are now possible for several pharmacokinetic (PK) parameters, particularly absorption and distribution. The emerging consensus is that the predictions are no worse than those made using in vitro tests, with the decisive advantage that much less investment in technology, resources and time is needed. In addition, and of critical importance, it is possible to screen virtual compounds. Some packages are able to handle thousands of molecules in a few hours. However, common experience shows that, in part at least for essentially irrational reasons, there is currently a lack of confidence in these approaches. An effort should be made by the software producers towards more transparency, in order to improve the confidence of their consumers. It seems highly probable that in silico approaches will evolve rapidly, as did in vitro methods during the last decade. Past experience with the latter should be helpful in avoiding repetition of similar errors and in taking the necessary steps to ensure effective implementation. A general concern is the lack of access to the large amounts of data on compounds no longer in development, but still kept secret by the pharmaceutical industry. Controlled access to these data could be particularly helpful in validating new in silico approaches.

摘要

计算方法是药代动力学、ADME(吸收、分布、代谢、排泄)评估、药物发现和毒性研究领域中最新且发展最快的技术之一。然而,迄今为止,专门用于ADME预测(尤其是代谢预测)的软件包尚未得到充分验证,仍需改进才能有效。大多数是“开放”系统,处于不断发展中,能够快速且通常很容易地纳入来自用户或开发者数据库的新信息。现在可以对几个药代动力学(PK)参数进行定量的计算机模拟预测,特别是吸收和分布。新出现的共识是,这些预测并不比使用体外试验做出的预测差,其决定性优势在于所需的技术、资源和时间投入要少得多。此外,至关重要的是,可以筛选虚拟化合物。一些软件包能够在几小时内处理数千个分子。然而,常见的经验表明,至少部分原因是基本不合理的,目前人们对这些方法缺乏信心。软件生产商应努力提高透明度,以增强用户的信心。计算机模拟方法很可能会像过去十年中的体外方法那样迅速发展。后者的过往经验应有助于避免重复类似错误,并采取必要措施确保有效实施。一个普遍关注的问题是无法获取大量关于已停止研发但仍被制药行业保密的化合物的数据。对这些数据的可控访问对于验证新的计算机模拟方法可能会特别有帮助。

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