Toward a new paradigm for the efficient in vitro–in vivo extrapolation of metabolic clearance in humans from hepatocyte data

体内 肝细胞 体外 外推法 代谢清除率 化学 细胞生物学 生物 计算生物学 药理学 生物化学 药代动力学 遗传学 数学 数学分析
作者
Patrick Poulin,Sami Haddad
出处
期刊:Journal of Pharmaceutical Sciences [Elsevier]
卷期号:102 (9): 3239-3251 被引量:47
标识
DOI:10.1002/jps.23502
摘要

The objective of this study was to follow up a previous study on a comparative analysis of diverse in vitro-in vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs from intrinsic clearance (CLint ) data determined in microsomal incubations, but using hepatocyte data instead. Six IVIVE methods were compared: the "conventional and conventional bias-corrected methods," the "regression equation method," the "direct scaling method," the "Berezhkovskiy's method," and the "novel IVIVE method of Poulin et al." offering a new paradigm. A large and diverse dataset of 49 drugs were collected from the literature for hepatocyte data in human. Based on all statistical parameters, this study confirms that the novel IVIVE method of Poulin et al. shows the greatest prediction performance among the IVIVE methods tested by using hepatocyte data. The superior prediction performance of this novel IVIVE method is again most pronounced for (a) drugs highly bound in blood, (b) drugs bound to albumin, and (c) low CL drugs. Because the novel IVIVE method has been developed particularly to improve the prediction accuracy for drugs with such properties, this study confirms its utility. Furthermore, the results of the current comparative analysis performed using hepatocyte data confirm the findings of a previous analysis made with microsomal data. Overall, the proposed novel IVIVE method offers a new paradigm for the prediction of hepatic metabolic CL particularly for drugs, which have the aforementioned properties, and, hence, this would contribute to a more accurate CL prediction for small molecules in drug discovery and development, interspecies scaling, and can potentially be used for the optimization of driving factors of CL in an attempt to facilitate the simulation of drug disposition by using the physiologically based pharmacokinetics (PBPK) model.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
陈陈发布了新的文献求助10
刚刚
刚刚
1秒前
2秒前
tang完成签到,获得积分20
2秒前
2秒前
reflux应助辣辣采纳,获得10
2秒前
lenglin完成签到,获得积分10
3秒前
念念发布了新的文献求助10
5秒前
5秒前
5秒前
唔西迪西关注了科研通微信公众号
6秒前
ccc发布了新的文献求助10
7秒前
Gengar发布了新的文献求助10
7秒前
7秒前
dushicheng完成签到,获得积分20
8秒前
yuxin发布了新的文献求助10
9秒前
科研通AI5应助m1采纳,获得10
9秒前
9秒前
lenglin发布了新的文献求助10
9秒前
在水一方应助熊二浪采纳,获得10
10秒前
dushicheng发布了新的文献求助10
10秒前
飞飞完成签到,获得积分10
10秒前
小蘑菇应助xiaoxiao采纳,获得10
11秒前
苏格拉要有底完成签到 ,获得积分20
11秒前
所所应助木木采纳,获得10
11秒前
感谢超级沁转发科研通微信,获得积分50
11秒前
Millian完成签到 ,获得积分10
12秒前
liu完成签到 ,获得积分10
13秒前
科研通AI2S应助ChenZhangyang采纳,获得30
13秒前
14秒前
感谢悟空转发科研通微信,获得积分50
14秒前
666发布了新的文献求助10
14秒前
酷酷薯片发布了新的文献求助10
15秒前
大个应助小吃货采纳,获得10
15秒前
小马甲应助米莉采纳,获得10
16秒前
兴奋一斩完成签到,获得积分10
16秒前
感谢优秀如雪转发科研通微信,获得积分50
17秒前
huoyan2006发布了新的文献求助10
18秒前
DZQ发布了新的文献求助10
18秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Conference Record, IAS Annual Meeting 1977 610
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3542598
求助须知:如何正确求助?哪些是违规求助? 3119973
关于积分的说明 9341143
捐赠科研通 2818043
什么是DOI,文献DOI怎么找? 1549287
邀请新用户注册赠送积分活动 722093
科研通“疑难数据库(出版商)”最低求助积分说明 712928