# A Clinical Indications Prediction (CLIP) Scale for Human Mesenchymal Stem Cells > **NIH NIH R01** · SCRIPPS FLORIDA · 2020 · $760,933 ## Abstract Project Summary Cell-based therapies employing mesenchymal stem cells (MSCs) now cover the spectrum of early to late phase clinical trials in both industry and academic sponsored studies for a broad array of unrelated medical conditions. While MSC-based clinical trials have yielded significant benefits for some patients, other trials have yielded suboptimal outcomes or failed to meet their primary endpoints of efficacy even in cases were the therapy is well justified scientifically. A limiting factor in the development of efficacious MSC-based clinical therapies is the lack of metrics to discriminate clinically relevant differences in the potency of MSC isolates pre- and post- manufacturing, which is necessary to deliver optimized protocols for each patient population. Therefore, the identification and reduction to practice of deployable biomarkers/metrics that define MSC products based on potency rather than phenotype or composition of matter are critically needed to improve the predictability, efficacy, and reproducibility of MSC-based therapies currently in use today. To address this need, we developed a CLinical Indications Prediction (CLIP) scale that simultaneously classifies human MSC donor populations based on their intrinsic biological activity, and predicts how culture- expansion protocols alter the composition and function of these populations. The basis for the CLIP scale is rooted in the activity of the transcription factor TWIST1, which we have shown coordinately regulates stem/progenitor and paracrine functions in MSC. Importantly, intrinsic levels of TWIST1 expression, which vary significantly between human MSC donor populations, predicts differences in the pro-angiogenic, anti- inflammatory and immuno-modulatory activity of these population as determined in relevant cell-based assays and an acute lung injury model. In this application, we propose to directly test the clinical utility of the CLIP scale by demonstrating its ability to reconcile the biological activity of human MSC isolates administered to patients with patient outcomes in three different completed human clinical trials via retrospective analysis. We will also use the CLIP scale to evaluate how cGMP manufacturing protocols alter the composition and biological activity of human MSCs, and exploit these findings to devise novel protocols to generate MSCs of defined potency for different disease indications. Lastly, we propose to identify additional metrics that expand the scope and enhance the predictive value of the CLIP scale. Successful completion of these studies will deliver a potentially transformative metric whose use in the design and manufacture of MSC-based therapies is anticipated to greatly enhance the efficacy and reproducibility of such therapies for a variety of disease indications. ## Key facts - **NIH application ID:** 9999670 - **Project number:** 5R01HL144089-03 - **Recipient organization:** SCRIPPS FLORIDA - **Principal Investigator:** Donald G Phinney - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $760,933 - **Award type:** 5 - **Project period:** 2018-09-01 → 2022-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9999670 ## Citation > US National Institutes of Health, RePORTER application 9999670, A Clinical Indications Prediction (CLIP) Scale for Human Mesenchymal Stem Cells (5R01HL144089-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9999670. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*