Wilkins J J, Chan Pls, Chard J, Smith G, Smith M K, Beer M, Dunn A, Flandorfer C, Franklin C, Gomeni R, Harnisch L, Kaye R, Moodie S, Sardu M L, Wang E, Watson E, Wolstencroft K, Cheung Sya
Occams, Amstelveen, The Netherlands.
Pharmacometrics, Global Clinical Pharmacology, Pfizer, Sandwich, UK.
CPT Pharmacometrics Syst Pharmacol. 2017 May;6(5):285-292. doi: 10.1002/psp4.12171. Epub 2017 May 15.
Pharmacometric analyses are complex and multifactorial. It is essential to check, track, and document the vast amounts of data and metadata that are generated during these analyses (and the relationships between them) in order to comply with regulations, support quality control, auditing, and reporting. It is, however, challenging, tedious, error-prone, and time-consuming, and diverts pharmacometricians from the more useful business of doing science. Automating this process would save time, reduce transcriptional errors, support the retention and transfer of knowledge, encourage good practice, and help ensure that pharmacometric analyses appropriately impact decisions. The ability to document, communicate, and reconstruct a complete pharmacometric analysis using an open standard would have considerable benefits. In this article, the Innovative Medicines Initiative (IMI) Drug Disease Model Resources (DDMoRe) consortium proposes a set of standards to facilitate the capture, storage, and reporting of knowledge (including assumptions and decisions) in the context of model-informed drug discovery and development (MID3), as well as to support reproducibility: "Thoughtflow." A prototype software implementation is provided.
药代动力学分析复杂且涉及多因素。在这些分析过程中（以及它们之间的关系），检查、跟踪和记录大量数据及元数据以符合法规要求、支持质量控制、审计和报告至关重要。然而，这具有挑战性、乏味、容易出错且耗时，还会使药代动力学家偏离更有意义的科学研究工作。自动化这一过程将节省时间、减少转录错误、支持知识的保留和传递、鼓励良好实践，并有助于确保药代动力学分析对决策产生适当影响。使用开放标准记录、交流和重建完整的药代动力学分析的能力将带来巨大益处。在本文中，创新药物倡议（IMI）药物疾病模型资源（DDMoRe）联盟提出了一套标准，以促进在模型引导的药物发现和开发（MID3）背景下知识（包括假设和决策）的获取、存储和报告，并支持可重复性：“思维流程”。还提供了一个原型软件实现。
