Predicting human pharmacokinetics from preclinical data: absorption.

IF 1.1 Q4 PHARMACOLOGY & PHARMACY Translational and Clinical Pharmacology Pub Date : 2020-09-01 Epub Date: 2020-09-21 DOI:10.12793/tcp.2020.28.e14
Dong-Seok Yim, Suein Choi, Soo Hyeon Bae
{"title":"Predicting human pharmacokinetics from preclinical data: absorption.","authors":"Dong-Seok Yim,&nbsp;Suein Choi,&nbsp;Soo Hyeon Bae","doi":"10.12793/tcp.2020.28.e14","DOIUrl":null,"url":null,"abstract":"<p><p>Predicting the rate and extent of oral absorption of drugs in humans has been a challenging task for new drug researchers. This tutorial reviews <i>in vitro</i> and PBPK methods reported in the past decades that are widely applied to predicting oral absorption in humans. The physicochemical property and permeability (typically obtained using Caco-2 system) data is the first necessity to predict the extent of absorption from the gut lumen to the intestinal epithelium (F<sub>a</sub>). Intrinsic clearance measured using the human microsome or hepatocytes is also needed to predict the gut (F<sub>g</sub>) and hepatic (F<sub>h</sub>) bioavailability. However, there are many issues with the correction of the inter-laboratory variability, hepatic cell membrane permeability, CYP3A4 dependency, etc. The bioavailability is finally calculated as F = F<sub>a</sub> × F<sub>g</sub> × F<sub>h</sub>. Although the rate of absorption differs by micro-environments and locations in the intestine, it may be simply represented by k<sub>a</sub>. The k<sub>a</sub>, the first-order absorption rate constant, is predicted from <i>in vitro</i> and <i>in vivo</i> data. However, human PK-predicting software based on these PBPK theories should be carefully used because there are many assumptions and variances. They include differences in laboratory methods, inter-laboratory variances, and theories behind the methods. Thus, the user's knowledge and experiences in PBPK and <i>in vitro</i> methods are necessary for proper human PK prediction.</p>","PeriodicalId":23288,"journal":{"name":"Translational and Clinical Pharmacology","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/2e/f3/tcp-28-126.PMC7533162.pdf","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational and Clinical Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12793/tcp.2020.28.e14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/9/21 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 5

Abstract

Predicting the rate and extent of oral absorption of drugs in humans has been a challenging task for new drug researchers. This tutorial reviews in vitro and PBPK methods reported in the past decades that are widely applied to predicting oral absorption in humans. The physicochemical property and permeability (typically obtained using Caco-2 system) data is the first necessity to predict the extent of absorption from the gut lumen to the intestinal epithelium (Fa). Intrinsic clearance measured using the human microsome or hepatocytes is also needed to predict the gut (Fg) and hepatic (Fh) bioavailability. However, there are many issues with the correction of the inter-laboratory variability, hepatic cell membrane permeability, CYP3A4 dependency, etc. The bioavailability is finally calculated as F = Fa × Fg × Fh. Although the rate of absorption differs by micro-environments and locations in the intestine, it may be simply represented by ka. The ka, the first-order absorption rate constant, is predicted from in vitro and in vivo data. However, human PK-predicting software based on these PBPK theories should be carefully used because there are many assumptions and variances. They include differences in laboratory methods, inter-laboratory variances, and theories behind the methods. Thus, the user's knowledge and experiences in PBPK and in vitro methods are necessary for proper human PK prediction.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
从临床前数据预测人体药代动力学:吸收。
预测药物在人体口服吸收的速度和程度对新药研究人员来说是一项具有挑战性的任务。本教程回顾了在过去几十年中广泛应用于预测人体口服吸收的体外和PBPK方法。物理化学性质和渗透性(通常使用Caco-2系统获得)数据是预测从肠腔到肠上皮吸收程度(Fa)的首要必要条件。使用人体微粒体或肝细胞测量内在清除率也需要预测肠道(Fg)和肝脏(Fh)的生物利用度。然而,在校正实验室间变异性、肝细胞膜通透性、CYP3A4依赖性等方面存在许多问题。生物利用度最终计算为F = Fa × Fg × Fh。虽然吸收率因微环境和肠内位置的不同而不同,但它可以简单地用ka表示。一阶吸收速率常数ka是根据体内和体外数据预测的。然而,基于这些PBPK理论的人类pk预测软件应该谨慎使用,因为有许多假设和方差。它们包括实验室方法的差异、实验室间差异和方法背后的理论。因此,用户在PBPK和体外方法方面的知识和经验对于正确的人类PK预测是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Translational and Clinical Pharmacology
Translational and Clinical Pharmacology Medicine-Pharmacology (medical)
CiteScore
1.60
自引率
11.10%
发文量
17
期刊介绍: Translational and Clinical Pharmacology (Transl Clin Pharmacol, TCP) is the official journal of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT). TCP is an interdisciplinary journal devoted to the dissemination of knowledge relating to all aspects of translational and clinical pharmacology. The categories for publication include pharmacokinetics (PK) and drug disposition, drug metabolism, pharmacodynamics (PD), clinical trials and design issues, pharmacogenomics and pharmacogenetics, pharmacometrics, pharmacoepidemiology, pharmacovigilence, and human pharmacology. Studies involving animal models, pharmacological characterization, and clinical trials are appropriate for consideration.
期刊最新文献
Development of in-silico drug cardiac toxicity evaluation system with consideration of inter-individual variability. Enhancing drug administration flexibility: evaluation of pharmacokinetic properties of tegoprazan orally disintegrating tablet (ODT) administered via nasogastric tube or oral dosing. Pharmacokinetics and bioequivalence study of candesartan cilexetil tablet in Chinese volunteers under fasting condition: an open-label, randomized-sequence, 2-period crossover study. Data science through natural language with ChatGPT's Code Interpreter. Emerging and upcoming therapies in insomnia.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1