Bortezomib (Velcade®) is a reversible proteasome inhibitor that shows potent antineoplastic activity, by inhibiting the constitutively increased proteasome activity in myeloma cells, and is approved as a first-line therapy for multiple myeloma (MM). Although clinically successful, bortezomib exhibits a relatively narrow therapeutic index and can induce dose-limiting toxicities such as thrombocytopenia. This study aims to develop a quantitative and predictive pharmacodynamic model to investigate bortezomib dosing-regimens in a rational and efficient manner. Mean temporal profiles of bortezomib pharmacokinetics, proteasome activity, M-protein concentrations, and platelet counts following bortezomib monotherapy were extracted from published clinical studies. A population–based meta-analysis of bortezomib anti-myeloma activity and thrombocytopenia was conducted sequentially with a Stochastic Approximation Expectation Maximization algorithm in Monolix. The final pharmacodynamic model integrates drug-target interactions and cell signaling dynamics with temporal biomarkers of clinical efficacy and toxicity. Bortezomib pharmacokinetics, disease progression, and platelet dynamic profiles were well characterized in MM patients, and a local sensitivity analysis of the final model suggests that increased proteasome concentration could ultimately attenuate bortezomib antineoplastic activity in MM patients. In addition, model simulations confirm that a once-weekly dosing schedule represents an optimal therapeutic regimen with comparable antineoplastic activity but significantly reduced risk of thrombocytopenia. In conclusion, a pharmacodynamic model was successfully developed, which provides a quantitative, mechanism-based platform for probing bortezomib dosing-regimens. Further research is needed to determine whether this model could be used to individualize bortezomib regimens to maximize antineoplastic efficacy and minimize thrombocytopenia during MM treatment.

中文翻译：

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基于人群的多发性骨髓瘤患者硼替佐米暴露-反应关系的荟萃分析。

Bortezomib (Velcade®) 是一种可逆的蛋白酶体抑制剂，通过抑制骨髓瘤细胞中组成性增加的蛋白酶体活性，显示出有效的抗肿瘤活性，并被批准作为多发性骨髓瘤 (MM) 的一线治疗药物。虽然在临床上取得了成功，但硼替佐米的治疗指数相对较窄，并且会引起剂量限制性毒性，例如血小板减少症。本研究旨在开发一种定量和预测药效学模型，以合理有效的方式研究硼替佐米给药方案。从已发表的临床研究中提取硼替佐米单药治疗后硼替佐米药代动力学、蛋白酶体活性、M 蛋白浓度和血小板计数的平均时间分布。使用 Monolix 中的随机近似期望最大化算法顺序进行基于人群的硼替佐米抗骨髓瘤活性和血小板减少症的荟萃分析。最终的药效学模型将药物-靶标相互作用和细胞信号动力学与临床疗效和毒性的时间生物标志物相结合。硼替佐米的药代动力学、疾病进展和血小板动力学特征在 MM 患者中得到了很好的表征，最终模型的局部敏感性分析表明，蛋白酶体浓度的增加最终会减弱 MM 患者的硼替佐米抗肿瘤活性。此外，模型模拟证实，每周一次的给药方案代表了一种最佳治疗方案，具有相当的抗肿瘤活性，但显着降低了血小板减少症的风险。总之，成功开发了药效学模型，为探索硼替佐米给药方案提供了一个定量的、基于机制的平台。需要进一步研究以确定该模型是否可用于个性化硼替佐米方案，以最大限度地提高抗肿瘤疗效并最大限度地减少 MM 治疗期间的血小板减少症。