Literature DB >> 9353696

Mathematical formalism for the properties of four basic models of indirect pharmacodynamic responses.

W Krzyzanski1, W J Jusko.   

Abstract

Four basic models for characterizing indirect pharmacodynamic responses were proposed previously and applied using differential equations. These models consider inhibition or stimulation by drug of the production or loss of mediators or response variables. This report develops partially integrated solutions for these models which allow more detailed examination of the roles of model parameters and pharmacokinetic functions in affecting the time course of drug effects. Because of the nonlinear Hill function, the solutions are represented by means of definite integrals containing kinetic and dynamic functions. These solutions allow a qualitative examination, using calculus, of how response is controlled by Dose, IC50 or SC50, Imax or Smax, and kout for drugs exhibiting monotonic or biphasic disposition. Characteristics of the response curves that were identified include shape, maximum or minimum, and changes with the above parameters and time. These relationships, together with simulation studies, provide a fundamental basis for understanding the temporal aspects of the basic indirect response models.

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Year:  1997        PMID: 9353696     DOI: 10.1023/a:1025723927981

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


  4 in total

1.  Characterization of four basic models of indirect pharmacodynamic responses.

Authors:  A Sharma; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1996-12

2.  Convergence of direct and indirect pharmacodynamic response models.

Authors:  W J Jusko; H C Ko; W F Ebling
Journal:  J Pharmacokinet Biopharm       Date:  1995-02

3.  Comparison of four basic models of indirect pharmacodynamic responses.

Authors:  N L Dayneka; V Garg; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1993-08

4.  Physiologic indirect response models characterize diverse types of pharmacodynamic effects.

Authors:  W J Jusko; H C Ko
Journal:  Clin Pharmacol Ther       Date:  1994-10       Impact factor: 6.875

  4 in total
  24 in total

1.  Indirect pharmacodynamic models for responses with multicompartmental distribution or polyexponential disposition.

Authors:  W Krzyzanski; W J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-02       Impact factor: 2.745

2.  Note: caution in use of empirical equations for pharmacodynamic indirect response models.

Authors:  W Krzyzanski; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1998-12

3.  Mathematical formalism and characteristics of four basic models of indirect pharmacodynamic responses for drug infusions.

Authors:  W Krzyzanski; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1998-08

4.  Characterization of pharmacodynamic recession slopes for direct and indirect response models.

Authors:  W Krzyzanski; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1998-08

5.  Basic pharmacodynamic models for agents that alter production of natural cells.

Authors:  W Krzyzanski; R Ramakrishnan; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1999-10

6.  A method of obtaining starting values of k(in) and k(out) for the indirect response models.

Authors:  Debu Mukherjee; Matthew M Hutmacher
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-02       Impact factor: 2.745

Review 7.  Pharmacodynamic models of age-structured cell populations.

Authors:  Wojciech Krzyzanski
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-09-16       Impact factor: 2.745

8.  A dynamical systems analysis of the indirect response model with special emphasis on time to peak response.

Authors:  Lambertus A Peletier; Johan Gabrielsson; Jacintha den Haag
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-08       Impact factor: 2.745

9.  Assessment of dosing impact on intra-individual variability in estimation of parameters for basic indirect response models.

Authors:  Wojciech Krzyzanski; Jacek Dmochowski; Nobuko Matsushima; William J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-08-29       Impact factor: 2.745

10.  Mathematical assessment of properties of precursor-dependent indirect pharmacodynamic response models.

Authors:  Anasuya Hazra; Wojciech Krzyzanski; William J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-10-12       Impact factor: 2.745

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