NEW DRUG R&D OF TRADITIONAL CHINESE MEDICINE: ROLE OF DATA MINING APPROACHES
NEW DRUG R&D OF TRADITIONAL CHINESE MEDICINE: ROLE OF DATA MINING APPROACHES
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新药研发
DOI：
10.1142/s0218339009002971
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发表时间：
2009-09-01
影响因子：
1.6
通讯作者：
Yi, Jianqiang
中科院分区：
文献类型：
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作者：
Yang, Hongjun;Chen, Jianxin;Yi, Jianqiang
中医 (TCM) 在过去 2500 年间记录了大约 100,000 个方剂。为了适应现代制药行业的使用和定制，我们通过引入数据挖掘方法，跨学科地研究中药新药研发（R＆D）活动。我们使用偏头痛公式作为训练集，研究通过数据挖掘开发新处方的可能性。中药新药研发活动分为两个步骤。第一步是从偏头痛配方中发现新的处方（候选药物）。我们提出了一种基于数据挖掘理论的无监督聚类方法来解决第一步的问题，并从公式数据中自动发现十个新处方。第二步是开发和优化当前生物医学方法发现的处方。由于川芎这种药草常用于治疗偏头痛并出现在新方中，因此我们以川芎为例，应用基于数据挖掘理论的监督回归方法来研究中药的药物研发活动。我们修改了两种线性回归方法，以建立 LCH 的三种化学成分与相应药理活性之间的非线性关联，并用它来预测活性。这种关联通过体外实验得到验证，我们发现实验结果与预测一致。无监督聚类和监督回归涵盖了数据挖掘理论的大部分内容，这意味着数据挖掘方法在中药新药研发中发挥着至关重要的作用，为建立中药新药研发平台提供了更好的解决方案。
Traditional Chinese Medicine (TCM) documented about 100,000 formulae during past 2500 years. To use and customize them by modern pharmaceutical industry, we make an interdisciplinary effort to study the activity of new drug research and development (R&D) in TCM by introducing data mining approaches to it. We used the migraine formulae as a training set to investigate the possibility of developing new prescription by means of data mining. The activity of new drug R&D of TCM consists of two steps. The first step is to discover new prescriptions (candidates for drugs) from migraine formulae. We present an unsupervised clustering approach based on data mining theory to address the problem in the first step and automatically discover ten new prescriptions from the formulae data. The second step is to develop and optimize the prescriptions discovered by current biomedical approaches. Since Ligusticum chuanxiong Hort (LCH), a kind of herb, is often used to treat migraine and appears in the new prescriptions, we use it as an example and apply supervised regression method based on data mining theory to study the drug R&D activity of TCM. We revised two linear regression methods in order to establish the nonlinear association between three chemical ingredients of LCH and corresponding pharmacological activity and used it to predict the activities. The association is validated by in vitro experiments and we found that the experimental results are consistent with the prediction. Unsupervised clustering and supervised regression cover most part of data mining theory, which means that data mining approaches play a crucial role in new drug R&D in TCM and present a better solution to establish the platform of drug R&D in TCM.