Modelling and Simulation, Early Oncology, Oncology R&D, AstraZeneca, Cambridge, UK.
Clinical Pharmacology and Quantitative Pharmacology, Biopharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Br J Clin Pharmacol. 2021 Oct;87(10):3988-4000. doi: 10.1111/bcp.14822. Epub 2021 Apr 14.
Herbal products, spices and/or fruits are perceived as inherently healthy; for instance, St. John's wort (SJW) is marketed as a natural antidepressant and patients often self-administer it concomitantly with oncology medications. However, food constituents/herbs can interfere with drug pharmacokinetics, with risk of altering pharmacodynamics and efficacy. The objective of this work was to develop a strategy to prioritize herb- or food constituent-drug interactions (FC-DIs) to better assess oncology drug clinical risk.
Physiologically based pharmacokinetic (PBPK) models were developed by integrating in vitro parameters with the clinical pharmacokinetics of food constituents in grapefruit juice (bergamottin), turmeric (curcumin) or SJW (hyperforin). Perpetrator files were linked to verified victim PBPK models through appropriate interaction mechanisms (cytochrome P450 3A, breast cancer resistance protein, P-glycoprotein) and applied in prospective PBPK simulations to inform the likelihood and magnitude of changes in exposure to osimertinib, olaparib or acalabrutinib.
Reported FC-DIs with oncology drugs were well recovered, with absolute average fold error values of 1.10 (bergamottin), 1.05 (curcumin) and 1.01 (hyperforin). Prospective simulations with grapefruit juice and turmeric showed clinically minor to insignificant changes in exposure (<1.50-fold) to acalabrutinib, osimertinib and olaparib, but predicted 1.57-fold FC-DI risk between acalabrutinib and curcumin. Moderate DDI risk was expected when acalabrutinib, osimertinib or olaparib were dosed with SJW.
A model-informed decision tree based on mechanistic understanding of transporter and/or enzyme-mediated FC-DI is proposed based on bergamottin, curcumin and hyperforin FC-DI clinical data. Adopting this quantitative modelling approach should streamline herbal product safety assessments, assist in FC-DI management, and ultimately promote safe clinical use of oncology drugs.
草药产品、香料和/或水果被认为是天然健康的；例如，贯叶连翘（SJW）被作为天然抗抑郁药销售，患者经常自行将其与肿瘤药物同时使用。然而，食物成分/草药会干扰药物药代动力学，从而改变药效动力学和疗效的风险。这项工作的目的是制定一种策略来优先考虑草药/食物成分-药物相互作用（FC-DIs），以更好地评估肿瘤药物的临床风险。
通过将体外参数与葡萄柚汁（佛手柑素）、姜黄（姜黄素）或 SJW（金丝桃素）中的食物成分的临床药代动力学相结合，开发了基于生理的药代动力学（PBPK）模型。通过适当的相互作用机制（细胞色素 P450 3A、乳腺癌耐药蛋白、P-糖蛋白）将肇事者文件链接到经过验证的受害者 PBPK 模型，并将其应用于前瞻性 PBPK 模拟中，以告知 osimertinib、olaparib 或 acalabrutinib 暴露变化的可能性和程度。
与肿瘤药物相关的报道的 FC-DIs 得到了很好的恢复，绝对平均倍数误差值分别为 1.10（佛手柑素）、1.05（姜黄素）和 1.01（金丝桃素）。与葡萄柚汁和姜黄的前瞻性模拟显示，acalabrutinib、osimertinib 和 olaparib 的暴露变化较小（<1.50 倍），但预测 curcumin 与 acalabrutinib 之间存在 1.57 倍的 FC-DI 风险。当 acalabrutinib、osimertinib 或 olaparib 与 SJW 一起给药时，预计会有中度的 DDI 风险。
基于佛手柑素、姜黄素和金丝桃素 FC-DI 的临床数据，提出了一种基于对转运蛋白和/或酶介导的 FC-DI 的机制理解的基于模型的决策树。采用这种定量建模方法应该简化草药产品安全性评估，有助于 FC-DI 管理，并最终促进肿瘤药物的安全临床使用。
