Janiszewski John S, Liston Theodore E, Cole Mark J
Pfizer Global Research and Development, Eastern Point Road, Groton, CT 06340, USA.
Curr Drug Metab. 2008 Nov;9(9):986-94. doi: 10.2174/138920008786485173.
The use of high speed synthesis technologies has resulted in a steady increase in the number of new chemical entities active in the drug discovery research stream. Large organizations can have thousands of chemical entities in various stages of testing and evaluation across numerous projects on a weekly basis. Qualitative and quantitative measurements made using LC/MS are integrated throughout this process from early stage lead generation through candidate nomination. Nearly all analytical processes and procedures in modern research organizations are automated to some degree. This includes both hardware and software automation. In this review we discuss bioanalytical mass spectrometry and automation as components of the analytical chemistry infrastructure in pharma. Analytical chemists are presented as members of distinct groups with similar skillsets that build automated systems, manage test compounds, assays and reagents, and deliver data to project teams. The ADME-screening process in drug discovery is used as a model to highlight the relationships between analytical tasks in drug discovery. Emerging software and process automation tools are described that can potentially address gaps and link analytical chemistry related tasks. The role of analytical chemists and groups in modern 'industrialized' drug discovery is also discussed.
高速合成技术的应用使得处于药物发现研究流程中的活性新化学实体数量稳步增加。大型机构每周在众多项目中会有数千种处于不同测试和评估阶段的化学实体。从早期的先导化合物发现到候选药物提名,整个过程都整合了使用液相色谱/质谱进行的定性和定量测量。现代研究机构中几乎所有的分析流程和程序都在一定程度上实现了自动化。这包括硬件和软件自动化。在本综述中,我们将讨论生物分析质谱和自动化,它们是制药分析化学基础设施的组成部分。分析化学家被视为具有相似技能集的不同团队成员,这些团队构建自动化系统、管理测试化合物、分析方法和试剂,并向项目团队提供数据。药物发现中的ADME筛选过程被用作模型,以突出药物发现中分析任务之间的关系。还描述了新兴的软件和过程自动化工具,它们可能解决差距并连接与分析化学相关的任务。此外,还讨论了分析化学家及其团队在现代“工业化”药物发现中的作用。