Quantifying Sex-and-Age-Related Differences in Antiretroviral Exposure and Adverse Effects in the MACS/WIHS Combined Cohort Study

摘要 拟议工作的长期目标是提供基于证据的建议，以尽量减少 在不同的艾滋病毒感染者（PLWH）人群中，代谢不良事件，特别是体重增加 识别和量化可能增加患者亚组风险的药物暴露变异性。我们会 考虑药物暴露的一系列广泛的改变因素，包括人口特征、之前 实验室值、身体人体测量学、虚弱表型和药物基因组学。我们的重点是 整合酶链转移抑制剂 (INSTI) 多替拉韦 (DTG) 和比克替拉韦 (BIC)，以及替诺福韦 艾拉酚胺（TAF）。 MWCCS 包括在 III 期临床试验中代表性不足的各种 PLWH，因此， 在申办者开发的药物群体药代动力学模型中。在 AIM 1 中，我们将招募不同的 PLWH 从四个 MWCCS 站点收集药代动力学数据并进一步完善影响因素的知识 DTG、BIC 和 TAF 药代动力学。将测量血浆和外周血中的药物浓度 北卡罗来纳大学艾滋病研究临床药理学和分析中心的血液单核细胞（仅 TAF） 化学实验室（CFAR CPAC）。非线性混合效应模型将用于开发综合的 每种感兴趣药物的 PK 模型。然后，使用这些模型，在 AIM 2 中，我们将回顾性地测量药物 储存库标本中的浓度（使用与 AIM 1 相同的方法和实验室，并预测药物 男性和女性从开始 DTG、BIC 和/或 TAF 起的清除期。这些药物的清除率预计为 每个参与者多次访问，然后将被分析为体重增加、腰臀围增加的预测因素 比率，以及在药物治疗过程中胰岛素抵抗增加（通过 HOMA-IR 测量） 兴趣，并采用多种药物暴露测量方法。假设是那些药物暴露量较高的感染者 （通过减慢药物清除）将更有可能经历这些药物的代谢不良事件。之上 完成后，我们期望为进一步开发基于模型的风险估计器奠定基础 前瞻性验证。

ABSTRACT The long-term objective of the proposed work is to provide evidenced-based recommendations for minimizing metabolic adverse events, particularly weight gain, in a diverse population of people living with HIV (PLWH) by identifying and quantifying variability in drug exposure that may increase risk in patient subgroups. We will consider a broad array of modifying factors of drug exposure, including demographic characteristics, prior laboratory values, body anthropometrics, frailty phenotype, and pharmacogenomics. Our focus is on the integrase strand transfer inhibitors (INSTIs) dolutegravir (DTG) and bictegravir (BIC), as well as tenofovir alafenamide (TAF). The MWCCS includes diverse PLWH underrepresented in Phase III clinical trials and thus, in the sponsor-developed population pharmacokinetic models of the drug. In AIM 1, we will enroll diverse PLWH from four MWCCS sites to collect pharmacokinetic data and further refine the knowledge of factors that influence DTG, BIC, and TAF pharmacokinetics. Drug concentrations will be measured in blood plasma and peripheral blood mononuclear cells (TAF only) in the UNC Center for AIDS Research Clinical Pharmacology and Analytical Chemistry Laboratory (CFAR CPAC). Nonlinear mixed effects models will be used to develop a comprehensive PK model for each drug of interest. Using these models, then, in AIM 2, we will retrospectively measure drug concentrations in repository specimens (using the same methods and laboratory as AIM 1, and predict drug clearance in men and women from initiation of DTG, BIC, and/or TAF. These drug clearances, predicted for multiple visits per participant, will then be analyzed as the predictors of body weight gain, increased waist to hip ratio, and increased insulin resistance (as measured by HOMA-IR) over the course of treatment on the drug of interest, with multiple measures of drug exposure. The hypothesis is that those PLWH with higher drug exposure (via slower drug clearance) will be more likely to experience the metabolic adverse events of these drugs. Upon completion, we expect to have the underpinnings of a model-based risk estimator developed for further prospective validation.