Literature DB >> 10214560

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

W Krzyzanski1, W J Jusko.   

Abstract

Direct pharmacologic effects are known to recede over time with largely linear slopes (Levy's k.m product, J. Pharm. Sci. 53:342, 1964) and indirect responses have similar behavior. Pharmacodynamic slope properties were examined mathematically for the Hill function with monoexponential drug disposition and simulations were carried out for other pharmacokinetic functions. Both types of pharmacodynamic profiles exhibit a single terminal inflection point (fp) when drug concentrations exceed the EC50 (that concentration causing one-half maximum effect, Emax). For direct effects it was found that Cfp (the drug concentration at fp) = EC50, the determinants of inflection time were identified, and Slopefp = -lambda z gamma Emax/4 where lambda z is the terminal disposition slope and gamma is the Hill coefficient. These characteristics were explored for the four basic indirect response models which also exhibit recession profiles with slight sigmoidity and a single terminal inflection point at higher doses. The drug concentration at inflection Cfp is < or = IC50 or SC50 (drug concentrations causing half-maximal inhibition or stimulation), while the inflection response (Rfp) attains constant values at larger doses. Indirect Response Models I, III, and IV have nearly linear return slopes for a wide range of doses which are governed by the disposition slope lambda z of the drug, loss constant kout of the response, maximum inhibition (Imax) or stimulation (Smax) factors, and a unique fractional constant (0 < G < or = 1). Model II exhibits more complex behavior with recession slopes which are less likely to be parallel for various doses. Most indirect responses are expected to show nearly linear recession slopes which are parallel for moderate to large doses and mainly governed by an identical combination of pharmacokinetic (lambda z), system (kout), and dynamic capacity factors (Imax or Smax).

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Year:  1998        PMID: 10214560     DOI: 10.1023/a:1021012117627

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


  11 in total

1.  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

2.  RELATIONSHIP BETWEEN ELIMINATION RATE OF DRUGS AND RATE OF DECLINE OF THEIR PHARMACOLOGIC EFFECTS.

Authors:  G LEVY
Journal:  J Pharm Sci       Date:  1964-03       Impact factor: 3.534

Review 3.  Characteristics of indirect pharmacodynamic models and applications to clinical drug responses.

Authors:  A Sharma; W J Jusko
Journal:  Br J Clin Pharmacol       Date:  1998-03       Impact factor: 4.335

4.  Integrated functions for four basic models of indirect pharmacodynamic response.

Authors:  W Krzyzanski; W J Jusko
Journal:  J Pharm Sci       Date:  1998-01       Impact factor: 3.534

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

Authors:  W Krzyzanski; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1997-02

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

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

7.  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

8.  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

9.  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

10.  Kinetics of pharmacologic effects.

Authors:  G Levy
Journal:  Clin Pharmacol Ther       Date:  1966 May-Jun       Impact factor: 6.875

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  2 in total

1.  Assessment of pharmacologic area under the curve when baselines are variable.

Authors:  Jeremy D Scheff; Richard R Almon; Debra C Dubois; William J Jusko; Ioannis P Androulakis
Journal:  Pharm Res       Date:  2011-01-14       Impact factor: 4.200

Review 2.  Pharmacodynamic model of slow reversible binding and its applications in pharmacokinetic/pharmacodynamic modeling: review and tutorial.

Authors:  Tianjing Ren; Xu Zhu; Natalie M Jusko; Wojciech Krzyzanski; William J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2022-08-30       Impact factor: 2.410

  2 in total

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