Muliaditan Morris, Teutonico Donato, Ortega-Muro Fatima, Ferrer Santiago, Della Pasqua Oscar
Clinical Pharmacology & Therapeutics Group, University College London, London, UK.
Translational Medicine and Early Development, Sanofi R&D, Chilly-Mazarin, France.
Eur J Pharm Sci. 2022 Jun 1;173:106163. doi: 10.1016/j.ejps.2022.106163. Epub 2022 Mar 4.
The development of novel candidate molecules for tuberculosis remains challenging, as drug distribution into the target tissue is not fully characterised in preclinical models of infection. Often antitubercular human dose selection is derived from pharmacokinetic data in plasma. Here, we explore whether whole-body physiologically-based pharmacokinetic (PBPK) modelling enables the prediction of lung exposure to anti-tubercular drugs in humans. Whole-body PBPK models were developed for rifampicin, isoniazid, pyrazinamide, and ethambutol using plasma data in mice as basis for the prediction of lung exposure. Model parameters were subsequently used to extrapolate disposition properties from mouse and determine lung:plasma ratio in humans. Model predictions were compared to biopsy data from patients. Predictions were deemed adequate if they fell within two-fold range of the observations. The concentration vs time profiles in lung were adequately predicted in mice. Isoniazid and pyrazinamide lung exposures were predicted to be comparable to plasma levels, whereas ethambutol lung exposure was predicted to be higher than in plasma. Lung:plasma ratio in humans could be reasonably predicted from preclinical data, but was highly dependent on the distribution model. This analysis showed that plasma pharmacokinetics may be used in conjunction with PBPK modelling to derive lung tissue exposure in mice and humans during early lead optimisation phase. However, the impact of uncertainty in predicted tissue exposure due to distribution should be always investigated through a sensitivity analysis when only plasma data is available. Despite these limitations, insight into lung tissue distribution represents a critical step for the dose rationale in tuberculosis patients.
开发新型抗结核候选分子仍然具有挑战性，因为在感染的临床前模型中，药物在靶组织中的分布尚未完全明确。通常，抗结核药物的人体剂量选择是根据血浆中的药代动力学数据得出的。在此，我们探讨基于全身生理的药代动力学（PBPK）模型是否能够预测人体肺部对抗结核药物的暴露情况。利用小鼠的血浆数据作为预测肺部暴露的基础，为利福平、异烟肼、吡嗪酰胺和乙胺丁醇建立了全身PBPK模型。随后使用模型参数外推小鼠的处置特性，并确定人体的肺：血浆比值。将模型预测结果与患者的活检数据进行比较。如果预测值落在观察值的两倍范围内，则认为预测是充分的。在小鼠中，肺部的浓度-时间曲线得到了充分预测。异烟肼和吡嗪酰胺的肺部暴露预计与血浆水平相当，而乙胺丁醇的肺部暴露预计高于血浆水平。可以根据临床前数据合理预测人体的肺：血浆比值，但这高度依赖于分布模型。该分析表明，在早期先导优化阶段，血浆药代动力学可与PBPK模型结合使用，以得出小鼠和人体肺部组织的暴露情况。然而，当仅有血浆数据可用时，应始终通过敏感性分析来研究由于分布导致的预测组织暴露不确定性的影响。尽管存在这些局限性，但了解肺部组织分布是确定结核病患者给药剂量的关键步骤。
