Literature DB >> 28028770

On the Nature of Physiologically-Based Pharmacokinetic Models -A Priori or A Posteriori? Mechanistic or Empirical?

Ken Korzekwa1, Swati Nagar2.   

Abstract

Physiologically-based pharmacokinetic (PBPK) models explicitly incorporate tissue-specific blood flows, partition coefficients, and metabolic processes. Since PBPK models are derived using physiologic parameters and interactions of the compound with tissue components, these models are considered to be "bottom up" as opposed to "top down". Modeling approaches can be characterized as either a posteriori (observational) or a priori (based solely on theory). Furthermore, approaches can be mechanistic (structure and components based on mechanisms) or empirical (based on observations alone). Both "bottom up" and "top down" approaches can incorporate either empirical or mechanistic components. In this perspective, we discuss some of the methods and assumptions of current PBPK modeling approaches. Specifically, we discuss drug partitioning into phospholipids and neutral lipids, use of blood-plasma ratios to estimate basic drug tissue partitioning, and clearance of neutral and acidic drugs. Based on these discussions, we believe that current PBPK models are mechanistic but a posteriori and semi-empirical.

Entities:  

Keywords:  PBPK; clearance; tissue partitioning

Mesh:

Substances:

Year:  2016        PMID: 28028770      PMCID: PMC5469509          DOI: 10.1007/s11095-016-2089-8

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  20 in total

1.  Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution.

Authors:  Patrick Poulin; Frank-Peter Theil
Journal:  J Pharm Sci       Date:  2002-01       Impact factor: 3.534

2.  Partition coefficients and the structure-activity relationship of the anesthetic gases.

Authors:  C Hansch; A Vittoria; C Silipo; P Y Jow
Journal:  J Med Chem       Date:  1975-06       Impact factor: 7.446

3.  Application of PBPK modelling in drug discovery and development at Pfizer.

Authors:  Hannah M Jones; Maurice Dickins; Kuresh Youdim; James R Gosset; Neil J Attkins; Tanya L Hay; Ian K Gurrell; Y Raj Logan; Peter J Bungay; Barry C Jones; Iain B Gardner
Journal:  Xenobiotica       Date:  2011-10-30       Impact factor: 1.908

Review 4.  Modeling kinetics of subcellular disposition of chemicals.

Authors:  Stefan Balaz
Journal:  Chem Rev       Date:  2009-05       Impact factor: 60.622

5.  Phosphatidylserine as a determinant for the tissue distribution of weakly basic drugs in rats.

Authors:  N Yata; T Toyoda; T Murakami; A Nishiura; Y Higashi
Journal:  Pharm Res       Date:  1990-10       Impact factor: 4.200

6.  Lipid solubility and drug penetration of the blood brain barrier.

Authors:  W H Oldendorf
Journal:  Proc Soc Exp Biol Med       Date:  1974-12

7.  Effects of phosphatidylserine and phosphatidylethanolamine content on partitioning of triflupromazine and chlorpromazine between phosphatidylcholine-aminophospholipid bilayer vesicles and water studied by second-derivative spectrophotometry.

Authors:  Shigehiko Takegami; Keisuke Kitamura; Tatsuya Kitade; Miwa Takashima; Mika Ito; Eiko Nakagawa; Midori Sone; Rie Sumitani; Yumiko Yasuda
Journal:  Chem Pharm Bull (Tokyo)       Date:  2005-01       Impact factor: 1.645

Review 8.  Prediction of in vivo drug disposition from in vitro data based on physiological pharmacokinetics.

Authors:  T Iwatsubo; N Hirota; T Ooie; H Suzuki; Y Sugiyama
Journal:  Biopharm Drug Dispos       Date:  1996-05       Impact factor: 1.627

9.  Structural determinants of drug partitioning in surrogates of phosphatidylcholine bilayer strata.

Authors:  Viera Lukacova; Senthil Natesan; Ming Peng; Roman Tandlich; Zhanbin Wang; Sandra Lynch; Rajesh Subramaniam; Stefan Balaz
Journal:  Mol Pharm       Date:  2013-09-11       Impact factor: 4.939

10.  A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

Authors:  Min Ye; Swati Nagar; Ken Korzekwa
Journal:  Biopharm Drug Dispos       Date:  2016-04       Impact factor: 1.627

View more
  8 in total

Review 1.  Drugs in Lactation.

Authors:  Philip O Anderson
Journal:  Pharm Res       Date:  2018-02-06       Impact factor: 4.200

2.  Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution.

Authors:  Estelle Yau; Andrés Olivares-Morales; Michael Gertz; Neil Parrott; Adam S Darwich; Leon Aarons; Kayode Ogungbenro
Journal:  AAPS J       Date:  2020-02-03       Impact factor: 4.009

3.  Prediction of Tissue-Plasma Partition Coefficients Using Microsomal Partitioning: Incorporation into Physiologically based Pharmacokinetic Models and Steady-State Volume of Distribution Predictions.

Authors:  Kimberly Holt; Min Ye; Swati Nagar; Ken Korzekwa
Journal:  Drug Metab Dispos       Date:  2019-07-19       Impact factor: 3.922

Review 4.  Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.

Authors:  Neil A Miller; Micaela B Reddy; Aki T Heikkinen; Viera Lukacova; Neil Parrott
Journal:  Clin Pharmacokinet       Date:  2019-06       Impact factor: 6.447

5.  Methods to Predict Volume of Distribution.

Authors:  Kimberly Holt; Swati Nagar; Ken Korzekwa
Journal:  Curr Pharmacol Rep       Date:  2019-06-06

6.  Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data.

Authors:  Jaydeep Yadav; Mehdi El Hassani; Jasleen Sodhi; Volker M Lauschke; Jessica H Hartman; Laura E Russell
Journal:  Drug Metab Rev       Date:  2021-05-25       Impact factor: 6.984

7.  A permeability- and perfusion-based PBPK model for improved prediction of concentration-time profiles.

Authors:  Ken Korzekwa; Casey Radice; Swati Nagar
Journal:  Clin Transl Sci       Date:  2022-05-31       Impact factor: 4.438

8.  Streamlining physiologically-based pharmacokinetic model design for intravenous delivery of nanoparticle drugs.

Authors:  Anh-Dung Le; Helen J Wearing; Dingsheng Li
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-02-07
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.