Optimizing GVHD Prevention with Systems Pharmacology Models

利用系统药理学模型优化 GVHD 预防

基本信息

批准号：
10652502
负责人：
DAVID A. HORNE
金额：
$ 58.8万
依托单位：
BECKMAN RESEARCH INSTITUTE/CITY OF HOPE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10652502
关键词：
Acute Graft Versus Host Disease Age Allogenic Area Cells Characteristics Cities Clinical Data Complex Computer Models Cyclophosphamide Data Disease Disease Pathway Disease Progression Dose Drug Kinetics Engraftment Enrollment Enzymes Equilibrium FOXP3 gene Goals Graft-Versus-Tumor Induction Human Hybrids IL2RA gene Immune response Immunosuppressive Agents In Vitro Individual Inosine Monophosphate Knowledge Link Malignant Neoplasms Metabolic Metabolic Pathway Modeling Mycophenolic Acid National Cancer Institute Nature Oxidoreductase Pathway interactions Patients Pharmaceutical Preparations Pharmacodynamics Pharmacology Physiological Plasma Population Process Prodrugs Proliferating Prospective cohort Publishing Regimen Regulatory T-Lymphocyte Retrospective cohort Sampling Schedule Severity of illness System T cell response T-Lymphocyte T-Lymphocyte Subsets Tacrolimus Testing Time Translations Transplant Recipients Weight biological systems cohort cytotoxic disorder prevention experience experimental study graft vs host disease hematopoietic cell transplantation high risk immunoreaction improved inter-individual variation mathematical model model building mortality mycophenolate mofetil novel pharmacodynamic model pharmacokinetic model pharmacokinetics and pharmacodynamics physiologically based pharmacokinetics post-transplant pre-clinical prospective standard of care success

项目摘要

PROJECT SUMMARY Quantitative systems pharmacology (QSP) is a rapidly expanding area that integrates available in vitro, preclinical, and clinical data representing existing knowledge to achieve a reverse translation. Reverse translation uses real-time human clinical data to directly inform new discoveries, of existing therapies and attributes of disease progression. Here, we seek to be the first to build a QSP model to, a priori, predict interpatient pharmacokinetics and pharmacodynamics using population priors (population pharmacokinetic or popPK modeling) and physiologic predictions (using physiologically based pharmacokinetic or PBPK modeling) combined with pharmacodynamic models based on in vitro and preclinical data. We will apply this novel hybrid popPK-PBPK-PD QSP model to allogeneic hematopoietic cell transplant (HCT) because its success requires a delicate balance as the grafting of cells from one individual (donor) to another (host, the HCT recipient). Guided by our preliminary data, our working hypothesis is that QSP modeling can minimize interindividual variability of these immunosuppressants, while also optimizing the novel graft versus host disease (GVHD) regimen of post- transplant cyclophosphamide (PTCy). Aim 1 seeks to identify the optimal PTCy dose using popPK and PBPK models. Our preclinical data shows that PTCy has a narrow dose window, with intermediate doses having the lowest GVHD rates. To achieve the optimal PTCy dose in each patient, we seek to develop a validate a popPK- PBPK model building upon our unique expertise in quantitating 4-hydroxycyclophosphamide (4HCY), the primary precursor to the cytotoxic metabolite of CY and personalizing CY using popPK-guided dosing. This hybrid popPK-PBPK CY model will be developed using our retrospective and prospective (n=150) cohort. The prospective cohort will be enrolled at National Cancer Institute (NCI) and City of Hope (COH). The NCI cohort will determine if the PTCy dose and schedule can be reduced (by 75%) without compromising GVHD rates; the COH cohort will use the traditional PTCy dosing. In Aim 2, we will characterize the pharmacokinetics and pharmacodynamics of mycophenolic acid (MPA), the active metabolite of MMF, with its target enzyme inosine monophosphate dehydrogenase (IMPDH). Like CY, MPA has substantive pharmacokinetic variability but different metabolic and transport pathways so separate pharmacokinetic models are needed. We seek to create a popPK-PBPK-PD model to identify the optimal plasma exposure of MPA and IMPDH activity. In Aim 3, we will create a quantitative systems pharmacology (QSP) model of T-cell response and acute GVHD. Our preclinical data show that acute GVHD prevention with PTCy is associated with reduction of CD4+CD25-Foxp3- conventional T-cell (Tcon) proliferation at day +7 followed by the preferential expansion of CD4+CD25+Foxp3+ regulatory T cells (Tregs) at day +21. Building upon fully-integrated immune response model (FIRM), we seek integrate in vitro, preclinical, and clinical data to build a QSP model.

项目概要定量系统药理学 (QSP) 是一个快速扩展的领域，它整合了可用的体外、代表现有知识的临床前和临床数据以实现反向翻译。撤销翻译使用实时人类临床数据直接告知新发现、现有疗法和疾病进展的特征。在这里，我们寻求成为第一个构建 QSP 模型来先验地预测使用群体先验（群体药代动力学或 popPK 模型）和生理学预测（使用基于生理学的药代动力学或 PBPK 模型）结合基于体外和临床前数据的药效学模型。我们将应用这种新颖的混合动力 popPK-PBPK-PD QSP 模型异基因造血细胞移植 (HCT)，因为其成功需要将细胞从一个人（供体）移植到另一个人（宿主、HCT 接受者）时需要保持微妙的平衡。引导根据我们的初步数据，我们的工作假设是 QSP 模型可以最大限度地减少个体间的变异性这些免疫抑制剂，同时还优化了新型移植物抗宿主病（GVHD）治疗后的方案移植环磷酰胺（PTCy）。目标 1 寻求使用 popPK 和 PBPK 确定最佳 PTCy 剂量模型。我们的临床前数据显示 PTCy 的剂量窗口很窄，中间剂量的最低的 GVHD 率。为了使每位患者获得最佳 PTCy 剂量，我们寻求开发一种验证 popPK- PBPK 模型建立在我们定量 4-羟基环磷酰胺 (4HCY) 方面的独特专业知识之上， CY 细胞毒性代谢物的主要前体，并使用 popPK 指导的剂量个性化 CY。这混合 popPK-PBPK CY 模型将使用我们的回顾性和前瞻性 (n=150) 队列来开发。这前瞻性队列将在国家癌症研究所 (NCI) 和希望之城 (COH) 进行招募。 NCI 队列将确定是否可以在不影响 GVHD 率的情况下减少 PTCy 剂量和时间表（减少 75%）；这 COH 队列将使用传统的 PTCy 剂量。在目标 2 中，我们将描述药代动力学和 MMF 的活性代谢物霉酚酸 (MPA) 及其靶酶肌苷的药效学单磷酸脱氢酶（IMPDH）。与 CY 一样，MPA 具有显着的药代动力学变异性，但不同的代谢和转运途径，因此需要单独的药代动力学模型。我们力求创造 popPK-PBPK-PD 模型用于确定 MPA 和 IMPDH 活性的最佳血浆暴露量。在目标 3 中，我们将创建 T 细胞反应和急性 GVHD 的定量系统药理学 (QSP) 模型。我们的临床前数据显示，用 PTCy 预防急性 GVHD 与 CD4+CD25-Foxp3- 的减少有关第 +7 天进行常规 T 细胞 (Tcon) 增殖，随后优先扩增 CD4+CD25+Foxp3+ +21 天的调节性 T 细胞 (Treg)。基于完全集成的免疫反应模型（FIRM），我们寻求整合体外、临床前和临床数据来构建 QSP 模型。

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Haploidentical hematopoietic cell and kidney transplantation for hematological malignancies and end-stage renal failure.

单倍相合造血细胞和肾移植治疗血液恶性肿瘤和终末期肾衰竭。

DOI：
发表时间：
2019
期刊：
影响因子：
20.3
作者：
Chen, Yi;Elias, Nahel;Heher, Eliot;McCune, Jeannine S;Collier, Kerry;Li, Shuli;Del Rio, Candice;El;Williams, Winfred;Tolkoff;Fishman, Jay A;McAfee, Steven;Dey, Bimalangshu R;DeFilipp, Zachariah;O'Donnell, Paul
通讯作者：
O'Donnell, Paul