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Physiologically based pharmacokinetic modeling of small molecules: How much progress have we made?

基于生理学的药代动力学模型 药代动力学 化学 计算生物学 药理学 医学 生物
作者
Nina Isoherranen
出处
期刊:Drug Metabolism and Disposition [American Society for Pharmacology and Experimental Therapeutics]
卷期号:53 (1): 100013-100013 被引量:17
标识
DOI:10.1124/dmd.123.000960
摘要

Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and in academic research. The use of PBPK models is continuously expanding, with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiologic changes into the models. Because of the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series of gut compartments allowing modeling of physiologic blood flow distribution within an organ and zonation of metabolic enzymes and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This Minireview suggests that awareness of the need for predefined criteria for model acceptance has increased, but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance. SIGNIFICANCE STATEMENT: Physiologically based pharmacokinetic (PBPK) modeling has become a mainstream application in academic literature and is broadly used for predictions, analysis, and evaluation of pharmacokinetic data. Significant progress has been made in developing advanced PBPK models that better capture human physiology, but oftentimes sufficient justification for the chosen model acceptance criterion and model structure is still missing. This Minireview provides a summary of the current landscape of PBPK applications used and highlights the need for advancing PBPK modeling science and training in academia.
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