Literature DB >> 35156179

A pharmacokinetic and pharmacodynamic analysis of drug forgiveness.

Noel P McAllister1, Sean D Lawley2.   

Abstract

Nonadherence to medication is a major public health problem. To combat nonadherence, some clinicians have suggested using "forgiving" drugs, which maintain efficacy in spite of delayed or missed doses. What pharmacokinetic (PK) and pharmacodynamic (PD) factors make a drug forgiving? In this paper, we address this question by analyzing a linear PK/PD model for a patient with imperfect adherence. We assume that the drug effect is far from maximal and consider direct effect, effect compartment (biophase), and indirect response PD models. We prove that the average drug effect relative to the clinically desired effect is simply the fraction of prescribed doses actually taken by the patient. Hence, under these assumptions, drug forgiveness cannot be defined in terms of the average effect. We argue that forgiveness should instead be understood in terms of effect fluctuations. We prove that the rates of PK absorption, PK elimination, and PD elimination are exactly equivalent for determining effect fluctuations. We prove all the aforementioned results for any pattern of nonadherence, including late doses, missed doses, drug holidays, extra doses, etc. To obtain quantitative estimates of effect fluctuations, we consider a simple statistical pattern of nonadherence and analytically calculate the coefficient of variation of effect. We further show how effect fluctuations can be reduced by taking an extra "make up" dose following a missed dose if any one of the aforementioned PK/PD rates is sufficiently slow. We illustrate some of our results for a nonlinear indirect response model of metformin.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Forgiveness; Medication adherence; Missed doses; Stochastics

Mesh:

Substances:

Year:  2022        PMID: 35156179     DOI: 10.1007/s10928-022-09808-w

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  28 in total

1.  Use of sensitivity functions to characterise and compare the forgiveness of drugs.

Authors:  Patrice Nony; Jean-Pierre Boissel
Journal:  Clin Pharmacokinet       Date:  2002       Impact factor: 6.447

2.  Pharmacodynamics of variable patient compliance: implications for pharmaceutical value.

Authors: 
Journal:  Adv Drug Deliv Rev       Date:  1998-09-07       Impact factor: 15.470

3.  Understanding forgiveness: minding and mining the gaps between pharmacokinetics and therapeutics.

Authors:  L G Osterberg; J Urquhart; T F Blaschke
Journal:  Clin Pharmacol Ther       Date:  2010-10       Impact factor: 6.875

4.  Effects on blood pressure and cardiovascular risk of variations in patients' adherence to prescribed antihypertensive drugs: role of duration of drug action.

Authors:  A Lowy; V C Munk; S H Ong; M Burnier; B Vrijens; E P Tousset; J Urquhart
Journal:  Int J Clin Pract       Date:  2010-11-22       Impact factor: 2.503

5.  Use of computer simulations to test the concept of dose forgiveness in the era of extended-release (XR) drugs.

Authors:  John M Pellock; Scott T Brittain
Journal:  Epilepsy Behav       Date:  2015-12-24       Impact factor: 2.937

Review 6.  Adherence to medication.

Authors:  Lars Osterberg; Terrence Blaschke
Journal:  N Engl J Med       Date:  2005-08-04       Impact factor: 91.245

Review 7.  Using pharmacokinetic-pharmacodynamic relationships to predict the effect of poor compliance.

Authors:  Jean-Pierre Boissel; Patrice Nony
Journal:  Clin Pharmacokinet       Date:  2002       Impact factor: 6.447

8.  A framework for quantifying the influence of adherence and dose individualization.

Authors:  P Assawasuwannakit; R Braund; S B Duffull
Journal:  Clin Pharmacol Ther       Date:  2015-11-19       Impact factor: 6.875

9.  Relationship Between Adherence Rate Threshold and Drug 'Forgiveness'.

Authors:  Alan Morrison; Melissa E Stauffer; Anna S Kaufman
Journal:  Clin Pharmacokinet       Date:  2017-12       Impact factor: 6.447

Review 10.  A new taxonomy for describing and defining adherence to medications.

Authors:  Bernard Vrijens; Sabina De Geest; Dyfrig A Hughes; Kardas Przemyslaw; Jenny Demonceau; Todd Ruppar; Fabienne Dobbels; Emily Fargher; Valerie Morrison; Pawel Lewek; Michal Matyjaszczyk; Comfort Mshelia; Wendy Clyne; Jeffrey K Aronson; J Urquhart
Journal:  Br J Clin Pharmacol       Date:  2012-05       Impact factor: 4.335

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