Challenges with sirolimus experimental data to inform QSP model of post‐transplantation cyclophosphamide regimens

Author:

Mohanan Ezhilpavai1ORCID,Shen Guofang1ORCID,Ren Suping1ORCID,Fan Hsuan‐Hao2ORCID,Moua Kao Tang Ying3ORCID,Karolak Aleksandra14ORCID,Rockne Russell C.4ORCID,Nakamura Ryotaro15ORCID,Horne David A.6ORCID,Kanakry Christopher G.7ORCID,Mager Donald E.28ORCID,McCune Jeannine S.15ORCID

Affiliation:

1. Department of Hematologic Malignancies Translational Sciences City of Hope Duarte California USA

2. Department of Pharmaceutical Sciences University at Buffalo, SUNY Buffalo New York USA

3. Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences University of Southern California Los Angeles California USA

4. Department of Computational and Quantitative Medicine City of Hope Duarte California USA

5. Department of Hematopoietic Cell Transplantation City of Hope Medical Center Duarte California USA

6. Department of Cancer Biology and Molecular Medicine City of Hope Duarte California USA

7. Center for Immuno‐Oncology, Center for Cancer Research, National Cancer Institute National Institutes of Health Bethesda Maryland USA

8. Enhanced Pharmacodynamics, LLC Buffalo New York USA

Abstract

AbstractDose optimization of sirolimus may further improve outcomes in allogeneic hematopoietic cell transplant (HCT) patients receiving post‐transplantation cyclophosphamide (PTCy) to prevent graft‐versus‐host disease (GVHD). Sirolimus exposure–response association studies in HCT patients (i.e., the association of trough concentration with clinical outcomes) have been conflicting. Sirolimus has important effects on T‐cells, including conventional (Tcons) and regulatory T‐cells (Tregs), both of which have been implicated in the mechanisms by which PTCy prevents GVHD, but there is an absence of validated biomarkers of sirolimus effects on these cell subsets. Considering the paucity of existing biomarkers and the complexities of the immune system, we conducted a literature review to inform a quantitative systems pharmacology (QSP) model of GVHD. The published literature presented multiple challenges. The sirolimus pharmacokinetic models insufficiently describe sirolimus distribution to relevant physiological compartments. Despite multiple publications describing sirolimus effects on Tcons and Tregs in preclinical and human ex vivo models, consistent parameters relating sirolimus concentrations to circulating Tcons and Tregs could not be found. Each aspect presents a challenge in building a QSP model of sirolimus and its temporal effects on T‐cell subsets and GVHD prevention. To optimize GVHD prevention regimens, phase I studies and systematic studies of immunosuppressant concentration–effect association are needed for QSP modeling.

Publisher

Wiley

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