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Considerations for Physiologically Based Modeling in Liver Disease: From Nonalcoholic Fatty Liver (NAFL) to Nonalcoholic Steatohepatitis (NASH)

基于生理学的药代动力学模型 非酒精性脂肪肝 广告 药理学 药效学 医学 药代动力学 人口 肝病 脂肪肝 生物信息学 内科学 疾病 生物 环境卫生
作者
William A. Murphy,Jeffry Adiwidjaja,Noora Sjöstedt,Kyunghee Yang,James J. Beaudoin,Jessica Spires,Scott Q. Siler,Sibylle Neuhoff,Kim L. R. Brouwer
出处
期刊:Clinical Pharmacology & Therapeutics [Wiley]
卷期号:113 (2): 275-297 被引量:19
标识
DOI:10.1002/cpt.2614
摘要

Nonalcoholic fatty liver disease (NAFLD), representing a clinical spectrum ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), is rapidly evolving into a global pandemic. Patients with NAFLD are burdened with high rates of metabolic syndrome‐related comorbidities resulting in polypharmacy. Therefore, it is crucial to gain a better understanding of NAFLD‐mediated changes in drug disposition and efficacy/toxicity. Despite extensive clinical pharmacokinetic data in cirrhosis, current knowledge concerning pharmacokinetic alterations in NAFLD, particularly at different stages of disease progression, is relatively limited. In vitro ‐to‐ in vivo extrapolation coupled with physiologically based pharmacokinetic and pharmacodynamic (IVIVE‐PBPK/PD) modeling offers a promising approach for optimizing pharmacologic predictions while refining and reducing clinical studies in this population. Use of IVIVE‐PBPK to predict intra‐organ drug concentrations at pharmacologically relevant sites of action is particularly advantageous when it can be linked to pharmacodynamic effects. Quantitative systems pharmacology/toxicology (QSP/QST) modeling can be used to translate pharmacokinetic and pharmacodynamic data from PBPK/PD models into clinically relevant predictions of drug response and toxicity. In this review, a detailed summary of NAFLD‐mediated alterations in human physiology relevant to drug absorption, distribution, metabolism, and excretion (ADME) is provided. The application of literature‐derived physiologic parameters and ADME‐associated protein abundance data to inform virtual NAFLD population development and facilitate PBPK/PD, QSP, and QST predictions is discussed along with current limitations of these methodologies and knowledge gaps. The proposed methodologic framework offers great potential for meaningful prediction of pharmacological outcomes in patients with NAFLD and can inform both drug development and clinical practice for this population.

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