Literature DB >> 8719238

Perspectives in pharmacokinetics. Physiologically based pharmacokinetic modeling as a tool for drug development.

S B Charnick1, R Kawai, J R Nedelman, M Lemaire, W Niederberger, H Sato.   

Abstract

Since the pioneering work of Haggard and Teorell in the first half of the 20th century, and of Bischoff and Dedrick in the late 1960s, physiologically based pharmacokinetic (PBPK) modeling has gone through cycles of general acceptance, and of healthy skepticism. Recently, however, the trend in the pharmaceuticals industry has been away from PBPK models. This is understandable when one considers the time and effort necessary to develop, test, and implement a typical PBPK model, and the fact that in the present-day environment for drug development, efficacy and safety must be demonstrated and drugs brought to market more rapidly. Although there are many modeling tools available to the pharmacokineticist today, many of which are preferable to PBPK modeling in most circumstances, there are several situations in which PBPK modeling provides distinct benefits that outweigh the drawbacks of increased time and effort for implementation. In this Commentary, we draw on our experience with this modeling technique in an industry setting to provide guidelines on when PBPK modeling techniques could be applied in an industrial setting to satisfy the needs of regulatory customers. We hope these guidelines will assist researchers in deciding when to apply PBPK modeling techniques. It is our contention that PBPK modeling should be viewed as one of many modeling tools for drug development.

Mesh:

Year:  1995        PMID: 8719238     DOI: 10.1007/BF02354273

Source DB:  PubMed          Journal:  J Pharmacokinet Biopharm        ISSN: 0090-466X


  55 in total

1.  Application of neural computing in pharmaceutical product development.

Authors:  A S Hussain; X Q Yu; R D Johnson
Journal:  Pharm Res       Date:  1991-10       Impact factor: 4.200

2.  Precision and sensitivity of pharmacokinetic models for cancer risk assessment: tetrachloroethylene in mice, rats, and humans.

Authors:  F Y Bois; L Zeise; T N Tozer
Journal:  Toxicol Appl Pharmacol       Date:  1990-02       Impact factor: 4.219

3.  Physiological pharmacokinetic parameters for cis-dichlorodiammineplatinum(II) (DDP) in the mouse.

Authors:  F G King; R L Dedrick
Journal:  J Pharmacokinet Biopharm       Date:  1992-02

4.  Variability in biological monitoring of solvent exposure. I. Development of a population physiological model.

Authors:  P O Droz; M M Wu; W G Cumberland; M Berode
Journal:  Br J Ind Med       Date:  1989-07

5.  Feasibility of developing a neural network for prediction of human pharmacokinetic parameters from animal data.

Authors:  A S Hussain; R D Johnson; N N Vachharajani; W A Ritschel
Journal:  Pharm Res       Date:  1993-03       Impact factor: 4.200

6.  A multi-organ, axially distributed model of capillary permeability for a magnetic resonance imaging contrast agent.

Authors:  S M Eaton; P Wedeking; M F Tweedle; W C Eckelman
Journal:  J Pharm Sci       Date:  1993-05       Impact factor: 3.534

Review 7.  Physiological pharmacokinetics and cancer risk assessment.

Authors:  M E Andersen; D Krewski; J R Withey
Journal:  Cancer Lett       Date:  1993-04-15       Impact factor: 8.679

8.  Physiological pharmacokinetic modeling of cis-dichlorodiammineplatinum(II) (DDP) in several species.

Authors:  F G King; R L Dedrick; F F Farris
Journal:  J Pharmacokinet Biopharm       Date:  1986-04

9.  Noninvasive measurement of portal venous blood flow in patients with cirrhosis: effects of physiological and pharmacological stimuli.

Authors:  D Alvarez; R Mastai; A Lennie; G Soifer; D Levi; R Terg
Journal:  Dig Dis Sci       Date:  1991-01       Impact factor: 3.199

10.  Pharmacokinetics and expert systems as aids for risk assessment in reproductive toxicology.

Authors:  D R Mattison; F R Jelovsek
Journal:  Environ Health Perspect       Date:  1987-12       Impact factor: 9.031

View more
  14 in total

1.  BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems.

Authors:  John F Graf; Bernhard J Scholz; Maria I Zavodszky
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-12-10       Impact factor: 2.745

Review 2.  Whole body pharmacokinetic models.

Authors:  Ivan Nestorov
Journal:  Clin Pharmacokinet       Date:  2003       Impact factor: 6.447

Review 3.  Pharmacokinetic-pharmacodynamic guided trial design in oncology.

Authors:  Ch van Kesteren; R A A Mathôt; J H Beijnen; J H M Schellens
Journal:  Invest New Drugs       Date:  2003-05       Impact factor: 3.850

4.  Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model.

Authors:  Feng Yang; Xianping Tong; D Gail McCarver; Ronald N Hines; Daniel A Beard
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-06-07       Impact factor: 2.745

5.  Physiologically based pharmacokinetic modelling of the three-step metabolism of pyrimidine using C-uracil as an in vivo probe.

Authors:  Suminobu Ito; Takeshi Kawamura; Makoto Inada; Yoshiharu Inoue; Yukihiro Hirao; Toshihisa Koga; Jun-ichi Kunizaki; Takefumi Shimizu; Hitoshi Sato
Journal:  Br J Clin Pharmacol       Date:  2005-12       Impact factor: 4.335

6.  Lumping of whole-body physiologically based pharmacokinetic models.

Authors:  I A Nestorov; L J Aarons; P A Arundel; M Rowland
Journal:  J Pharmacokinet Biopharm       Date:  1998-02

7.  Commentary on "Physiologically based pharmacokinetic modeling as a tool for drug development".

Authors:  T M Ludden; W R Gillespie; W J Bachman
Journal:  J Pharmacokinet Biopharm       Date:  1995-04

8.  Physiological modeling for indirect evaluation of drug tissular pharmacokinetics under non-steady-state conditions: an example of antimicrobial prophylaxis during liver surgery.

Authors:  Franck Lagneau; Jean Marty; Pascale Beyne; Michel Tod
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-02       Impact factor: 2.745

Review 9.  The role of population pharmacokinetics in drug development in light of the Food and Drug Administration's 'Guidance for Industry: population pharmacokinetics'.

Authors:  P J Williams; E I Ette
Journal:  Clin Pharmacokinet       Date:  2000-12       Impact factor: 6.447

10.  Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models.

Authors:  Sven Björkman
Journal:  J Pharmacokinet Pharmacodyn       Date:  2003-08       Impact factor: 2.745

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.