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Applications of the microphysiology systems database for experimental ADME-Tox and disease models.
Lab on a Chip ( IF 6.1 ) Pub Date : 2020-03-25 , DOI: 10.1039/c9lc01047e
Mark Schurdak 1 , Lawrence Vernetti 1 , Luke Bergenthal 2 , Quinn K Wolter 2 , Tong Ying Shun 2 , Sandra Karcher 2 , D Lansing Taylor 1 , Albert Gough 1
Affiliation  

To accelerate the development and application of Microphysiological Systems (MPS) in biomedical research and drug discovery/development, a centralized resource is required to provide the detailed design, application, and performance data that enables industry and research scientists to select, optimize, and/or develop new MPS solutions, as well as to harness data from MPS models. We have previously implemented an open source Microphysiology Systems Database (MPS-Db), with a simple icon driven interface, as a resource for MPS researchers and drug discovery/development scientists (https://mps.csb.pitt.edu). The MPS-Db captures and aggregates data from MPS, ranging from static microplate models to integrated, multi-organ microfluidic models, and associates those data with reference data from chemical, biochemical, pre-clinical, clinical and post-marketing sources to support the design, development, validation, application and interpretation of the models. The MPS-Db enables users to manage their multifactor, multichip studies, then upload, analyze, review, computationally model and share data. Here we discuss how the sharing of MPS study data in the MS-Db is under user control and can be kept private to the individual user, shared with a select group of collaborators, or be made accessible to the general scientific community. We also present a test case using our liver acinus MPS model (LAMPS) as an example and discuss the use of the MPS-Db in managing, designing, and analyzing MPS study data, assessing the reproducibility of MPS models, and evaluating the concordance of MPS model results with clinical findings. We introduce the Disease Portal module with links to resources for the design of MPS disease models and studies and discuss the integration of computational models for the prediction of PK/PD and disease pathways using data generated from MPS models.

中文翻译:

微生理学系统数据库在实验 ADME-Tox 和疾病模型中的应用。

为了加速微生理系统 (MPS) 在生物医学研究和药物发现/开发中的开发和应用,需要集中资源来提供详细的设计、应用和性能数据,使行业和研究科学家能够选择、优化和/或开发新的 MPS 解决方案,以及利用 MPS 模型中的数据。我们之前实现了一个开源微生理学系统数据库 (MPS-Db),具有简单的图标驱动界面,作为 MPS 研究人员和药物发现/开发科学家的资源 (https://mps.csb.pitt.edu)。MPS-Db 捕获并聚合来自 MPS 的数据,范围从静态微孔板模型到集成的多器官微流体模型,并将这些数据与来自化学、生化、临床前、临床和上市后来源的参考数据相关联,以支持模型的设计、开发、验证、应用和解释。MPS-Db 使用户能够管理他们的多因素、多芯片研究,然后上传、分析、审查、计算模型和共享数据。在这里,我们讨论 MS-Db 中 MPS 研究数据的共享如何在用户控制下进行,并且可以对个人用户保密、与选定的合作者组共享,或者可供一般科学界访问。我们还以我们的肝腺泡 MPS 模型 (LAMPS) 为例介绍了一个测试用例,并讨论了 MPS-Db 在管理、设计和分析 MPS 研究数据、评估 MPS 模型的再现性以及评估MPS 模型结果与临床发现。我们介绍了疾病门户模块,其中包含用于设计 MPS 疾病模型和研究的资源链接,并讨论了使用 MPS 模型生成的数据预测 PK/PD 和疾病途径的计算模型的集成。
更新日期:2020-04-24
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