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Recent lessons learned from population pharmacokinetic studies of mycophenolic acid: physiological, genomic, and drug interactions leading to the prediction of drug effects

霉酚酸 药代动力学 药理学 人口 药品 药效学 医学 药物开发 移植 内科学 环境卫生
作者
Yan Rong,Vrunda Patel,Tony K. L. Kiang
出处
期刊:Expert Opinion on Drug Metabolism & Toxicology [Taylor & Francis]
卷期号:17 (12): 1369-1406 被引量:10
标识
DOI:10.1080/17425255.2021.2027906
摘要

Introduction Mycophenolic acid (MPA) is a widely used immunosuppressant in transplantation and autoimmune disease. Highly variable pharmacokinetics have been observed with MPA, but the exact mechanisms remain largely unknown.Areas covered The current review provided a critical, comprehensive update of recently published population pharmacokinetic/dynamic models of MPA (n = 16 papers identified from PubMed and Embase, inclusive from January 2017 to August 2021), with specific emphases on the intrinsic and extrinsic factors influencing the pharmacology of MPA. The significance of the identified covariates, potential mechanisms, and comparisons to historical literature have been provided.Expert opinion While select covariates affecting the population pharmacokinetics of MPA are consistently observed and mechanistically supported (e.g. cyclosporine and post-transplant time on MPA clearance), some variables have not been regularly reported and/or lacked mechanistic explanation (e.g. diarrhea and several genetic polymorphisms). Very few pharmacodynamic models were available, pointing to the need to extrapolate pharmacokinetic findings. Ideal models of MPA should consist of: i) utilizing optimal sampling points to allow the characterizations of absorption, re-absorption, and elimination phases; ii) characterizing unbound/total MPA, MPA metabolites, plasma/urinary concentrations, and genetic polymorphisms to facilitate mechanistic interpretations; and iii) incorporating actual outcomes (e.g. rejection, leukopenia, infections) and pharmacodynamic data (e.g. inosine-5′-monophosphate dehydrogenase activities) to establish clinical relevance. We anticipate the field will continue to expand in the next 5 to 10 years.
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