Miedel Mark T, Varmazyad Mahboubeh, Xia Mengying, Brooks Maria Mori, Gavlock Dillon C, Reese Celeste, Behari Jaideep, Soto-Gutierrez Alejandro, Gough Albert, Taylor D Lansing, Schurdak Mark E
Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Cell Rep Methods. 2025 Apr 21;5(4):101028. doi: 10.1016/j.crmeth.2025.101028. Epub 2025 Apr 14.
Multi-cell-type, 3D microphysiological systems (MPS) that recapitulate normal organ/organ system functions and the progression of diseases are being applied in drug discovery and development programs to enable precision medicine. A critical step for this application is to demonstrate the reproducibility of the MPS and its ability to identify biologic/clinical heterogeneity from experimental variability, which requires capturing detailed metadata associated with MPS studies as well as a strong analytical approach for assessing reproducibility. Detailed metadata ensure that identical study parameters are being compared when evaluating reproducibility. We have developed the Pittsburgh reproducibility protocol (PReP), which uses a set of common statistical metrics, the coefficient of variation (CV), ANOVA, and intraclass correlation coefficient (ICC), in a pipeline as a standard approach to evaluate the intra- and interstudy reproducibility of MPS performance. The PReP can be employed to identify biological/clinical heterogeneity relevant to precision medicine.
能够重现正常器官/器官系统功能以及疾病进展的多细胞类型三维微生理系统（MPS）正被应用于药物发现和开发项目中，以实现精准医疗。此应用的关键一步是证明MPS的可重复性及其从实验变异性中识别生物学/临床异质性的能力，这需要捕获与MPS研究相关的详细元数据以及用于评估可重复性的强大分析方法。详细的元数据可确保在评估可重复性时比较相同的研究参数。我们开发了匹兹堡可重复性协议（PReP），该协议在一个流程中使用一组常见的统计指标，即变异系数（CV）、方差分析（ANOVA）和组内相关系数（ICC），作为评估MPS性能的研究内和研究间可重复性的标准方法。PReP可用于识别与精准医疗相关的生物学/临床异质性。
