面对改变等离子体蛋白结合的事实:当前的模型是否正确预测特殊人群中未结合部分的变化?
Jokha Al-Qassabi1, Shawn Pei Feng Tan2, Patcharapan Phonboon2
1Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK; University of Technology and Applied Sciences, Oman.
Journal of pharmaceutical sciences
|February 28, 2024
概括
基于生理学的药物动力学模型通常通过调整血蛋白度变化来预测药物未结合分量 (fu). 然而,这种方法无法准确地预测特殊人群之间的变化,因此需要考虑其他约束因素.
科学领域:
- 药理动力学和药物新陈代谢
- 生物化学 生物化学
- 计算生物学 计算生物学
背景情况:
- 精确预测血中未结合的药物分量 (fu) 对生理学基础的药理动力学 (PBPK) 模型至关重要,特别是在特殊人群中.
- 目前的模型经常根据血蛋白度的变化进行调整,但假定结合亲和力是恒定的,这种简化可能会限制预测准确性.
研究的目的:
- 评估单个蛋白质结合模型在各种特殊人群中药物效应的预测性能.
- 为了评估预测相对于参考种群的变的准确性,比绝对预测更严格的指标.
主要方法:
- 预测的fu和在fu的折叠变化超过200种药物在各种人群 (肝脏/脏功能障碍,儿科,老年人,炎症疾病,种族群体) 使用蛋白和α-1-酸糖蛋白结合模型.
- 使用一致性相关系数 (CCC) 进行统计分析,以比较预测和观察值.
主要成果:
- 专蛋白模型显示出对预测的fu (CCC>0.90在16/17种群中) 的强烈一致.
- 然而,在所有种群中,对于所有阿尔伯和α-1-酸糖蛋白模型,预测的变化的CCC始终很低 (<0.38).
- 这表明,仅仅蛋白质度的变化不能解释特殊种群中观察到的变化.
结论:
- 仅仅基于血蛋白度变化的fu的预测对于某些特殊人群来说是不够的.
- 未来的PBPK模型应该包含内源物质的竞争性结合和潜在的白蛋白结构修饰.
- 对于高度结合的药物,建议使用测量后的fu数据或比较人口之间的预测未结合药物暴露,以获得可靠的预测.
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