Quantitative Medicine, Critical Path Institute, Tucson, AZ, USA.
Uppsala University, Uppsala, Sweden.
Eur J Pharm Sci. 2017 Nov 15;109S:S65-S71. doi: 10.1016/j.ejps.2017.06.035. Epub 2017 Jul 4.
Sharing of resources across organisations to support open innovation is an old idea, but which is being taken up by the scientific community at increasing speed, concerning public sharing in particular. The ability to address new questions or provide more precise answers to old questions through merged information is among the attractive features of sharing. Increased efficiency through reuse, and increased reliability of scientific findings through enhanced transparency, are expected outcomes from sharing. In the field of pharmacometrics, efforts to publicly share data, models and workflow have recently started. Sharing of individual-level longitudinal data for modelling requires solving legal, ethical and proprietary issues similar to many other fields, but there are also pharmacometric-specific aspects regarding data formats, exchange standards, and database properties. Several organisations (CDISC, C-Path, IMI, ISoP) are working to solve these issues and propose standards. There are also a number of initiatives aimed at collecting disease-specific databases - Alzheimer's Disease (ADNI, CAMD), malaria (WWARN), oncology (PDS), Parkinson's Disease (PPMI), tuberculosis (CPTR, TB-PACTS, ReSeqTB) - suitable for drug-disease modelling. Organized sharing of pharmacometric executable model code and associated information has in the past been sparse, but a model repository (DDMoRe Model Repository) intended for the purpose has recently been launched. In addition several other services can facilitate model sharing more generally. Pharmacometric workflows have matured over the last decades and initiatives to more fully capture those applied to analyses are ongoing. In order to maximize both the impact of pharmacometrics and the knowledge extracted from clinical data, the scientific community needs to take ownership of and create opportunities for open innovation.
跨组织资源共享以支持开放式创新是一个古老的理念，但正被科学界以越来越快的速度所采用，特别是在公共共享方面。通过合并信息来解决新问题或为旧问题提供更精确答案的能力是共享的吸引人之处之一。通过重用提高效率，通过提高透明度提高科学发现的可靠性，是共享的预期结果。在药物代谢动力学领域，最近开始公开共享数据、模型和工作流程。为建模共享个体水平纵向数据需要解决类似于许多其他领域的法律、伦理和专有问题，但也存在与数据格式、交换标准和数据库属性有关的药物代谢动力学特定方面。几个组织（CDISC、C-Path、IMI、ISoP）正在努力解决这些问题并提出标准。还有一些旨在收集特定疾病数据库的倡议——阿尔茨海默病（ADNI、CAMD）、疟疾（WWARN）、肿瘤学（PDS）、帕金森病（PPMI）、结核病（CPTR、TB-PACTS、ReSeqTB）——适合药物疾病建模。过去，药物代谢动力学可执行模型代码和相关信息的有组织共享很少，但最近推出了一个旨在实现这一目标的模型存储库（DDMoRe 模型存储库）。此外，还有其他一些服务可以更普遍地促进模型共享。药物代谢动力学工作流程在过去几十年中已经成熟，并且正在努力更全面地捕捉应用于分析的工作流程。为了最大限度地提高药物代谢动力学的影响力和从临床数据中提取的知识，科学界需要拥有并为开放式创新创造机会。
