虚拟双胞胎用于在治疗耐药精神分裂症患者中以模型为基础精确剂量克洛扎宾
Sam Mostafa1,2, Reza Rafizadeh3, Thomas M Polasek1,4,5
1Centre for Medicine Use and Safety, Monash University, Parkville, Victoria, Australia.
CPT: pharmacometrics & systems pharmacology
|January 20, 2024
概括
使用虚拟双胞胎 (MIPD-VTs) 进行基于模型的精确剂量测定,有望预测治疗耐药精神分裂症患者的克洛扎宾度. 虽然对许多人有效,但对药物相互作用的预测需要进一步细化,特别是对流胺.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
- 精神病学是一个精神病学.
背景情况:
- 使用虚拟双胞胎 (MIPD-VTs) 进行基于模型的精确剂量是预测药物度的新兴策略.
- 克洛扎对于耐治疗精神分裂症至关重要,但需要谨慎剂量以控制毒性和疗效.
- 准确预测克洛扎平度对于优化患者的治疗结果至关重要.
研究的目的:
- 评估一个高虚拟化的MIPD-VT方法 (Simcyp v21) 来预测稳定状态的克洛沙平度.
- 确定在住院患者中达到目标度 (350600 ng/mL) 所需的克洛扎宾剂量范围.
- 评估MIPD-VTs在预测克洛扎水平和药物相互作用的影响方面的准确性.
主要方法:
- 在模拟中使用了高虚拟化的MIPD-VT方法 (Simcyp版本21).
- 在11名患有治疗耐药精神分裂症的住院患者中,预测的稳定状态度和最佳剂量范围.
- 分析了预测准确性 (R2值) 和在达到目标度方面的表现,包括增加黄素的情况.
主要成果:
- MIPD-VTs合理地预测了个体患者的克洛扎宾度 (R2:0.290.60).
- 这种方法成功地预测了73%的患者的最终克洛札剂量范围.
- 稳定状态度在接受fluvoxamine增强治疗的三分之二的患者中超预测了24倍.
结论:
- 高虚拟化MIPD-VT方法显示了在临床实践中指导克洛沙平剂量定位的潜力.
- 目前的模型需要改进,以改善药理学药物相互作用的预测,特别是流胺的药物相互作用.
- 进一步开发MIPD-VTs是有必要的,以提高复杂患者群体的精确剂量.
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