通过使用PBTK建模促进的逆剂量测量方法,从体外毒性数据中预测利摩尔的体内发育毒性
Manisha Bhateria1, Isha Taneja2, Kajal Karsauliya1
1Toxicokinetics Laboratory, ASSIST and REACT Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Lucknow, India.
Toxicology and applied pharmacology
|March 2, 2024
概括
以生理学为基础的毒动力学 (PBTK) 建模为辅助的反向剂量计 (PBTK-RD) 从体外数据预测了体内毒性. 这项研究开发了利的PBTK模型,成功地将体外发育毒性转化为体内剂量,用于风险评估.
科学领域:
- 毒理学 毒理学 毒理学
- 药理动力学 药理动力学
- 计算生物学 计算生物学
背景情况:
- 实验室中毒学测试至关重要,但在风险评估中缺乏直接应用.
- 基于生理学的毒动力学 (PBTK) 建模-辅助逆剂量测量 (PBTK-RD) 桥梁体外数据和体外风险评估.
- 预测跨物种和种群的化学动力学和毒性对于准确的风险评估至关重要.
研究的目的:
- 构建一个最小的PBTK模型,用于预测鼠和人类体内林醇 (FNL) 的动态特征.
- 利用PBTK-RD将FNL的体外发育毒性数据转化为体内剂量反应数据.
- 为了推导出化学特异性调整因子 (CSAFs) 对FNL的物种间和个体间的毒动因子变异性.
主要方法:
- 开发一个最小的PBTK模型为fenarimol.
- 使用大鼠药理动力学数据验证PBTK模型.
- 应用PBTK-RD来预测测定量对应的口服剂量在老鼠和人类.
- 蒙特卡洛模拟人口变异性和CSAF导出.
主要成果:
- 该PBTK模型准确地预测了大鼠和人类的FNL药理动力学.
- 预测测定量相当于大鼠口服剂量 (36.46 mg/kg) 与文献值 (BMD10 = 22.8 mg/kg) 相比.
- 与默认不确定性因子相比,针对物种间和主体间变化的衍生CSAF被发现具有足够的保护作用.
结论:
- 该PBTK-RD方法是有效的预测体内毒性从体外数据为利.
- 开发的PBTK模型提供了一种有价值的工具,用于评估fenarimol的毒动力学,并推导出适当的安全因子.
- 该方法通过整合体外和体内数据,支持可靠的化学风险评估.
相关概念视频
Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance
Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion, mediated...
A recent model describes pravastatin's hepatobiliary excretion, mediated...
Toxicity Testing in Animals
Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...


