A Framework for quantifying the influence of adherence and dose individualization

Aims: The property of a drug that signifies the likelihood of therapeutic success to imperfect adherence is termed forgiveness. Recently forgiveness has been quantified as relative forgiveness (RF) [1] which describes the times more likely  a drug is forgiving under imperfect adherence compared to perfect adherence (typically RF < 1). RF does not account, however, for the underlying probability of therapeutic success. The aims of this work were to (1) introduce an extension to this concept that accounts for the underlying probability of therapeutic success both without individualization a priori relative forgiveness and after dose individualization a posteriori relative forgiveness and (2) illustrate cases for interpreting these measures.    

 

Methods: (1) Defining a priori and a posteriori RF. In both cases RF  is scaled by the probability of therapeutic success based on using the standard dose, a priori (RF×Pprior), or after doses have been individualized, a posteriori (RF×Ppost). (2) Application of a priori and a posteriori forgiveness to examples of atorvastatin and omeprazole. We consider atorvastatin in the presence or absence of physician-led individualization of the dosing regimen; and omeprazole in the presence and absence of patient-led symptom control of gastroesophageal reflux disease. For both cases, a population pharmacokinetic-pharmacodynamic (PKPD) model was identified. Subsequently, the clinical utility of a priori forgiveness and a posteriori forgiveness were explored using three dose levels of each drug. Five thousand sets of individual PKPD parameters were simulated under perfect adherence and imperfect adherence. For both cases a series of imperfect adherence scenarios constructed were 1, 10, 20, 30, 40, 50, 60, 70, 80, and 89 missed doses out of 90. Because missed doses were generated randomly, each virtual patient would have had a different profile of imperfect adherence. A priori RF and a posteriori RF were then plotted against the series of imperfect adherence scenarios to evaluate the influence of missed doses compared to individualization.

 

Results: Atorvastatin Three doses considered were 10 mg, 40 mg, and 80 mg. For atorvastatin we see that a posteriori RF is always greater than a priori RF for all levels of missing doses (up to 80 missing doses out of 90). In addition higher doses were always more forgiving. For instance at 45 missed doses (half of the total number of doses) the a priori RF of the 10 mg dose is approximately half that of a posteriori RF. This indicates that dose individualization is important irrespective of the underlying adherence in terms of the relative forgiveness. Hence dose individualization provides both a higher probability of therapeutic success as well as inherently making atorvastatin more forgiving. Omeprazole Three doses considered were 10 mg, 20 mg, and 40 mg. The influence of individualization in adherent patients makes a marked difference in a posteriori forgiveness compared to a priori forgiveness for up to about 30 missed doses (per 90 days of treatment). After this level of missed doses the RF for both a priori and a posteriori RF declines rapidly to close to zero and overlap. It is clear for omeprazole, that adherence is the primary factor of interest for those who are likely to be poorly adherent and should be the primary goal.

 

Conclusion:  The concept of a priori forgiveness and a posteriori forgiveness provides a quantitative measure that allows the influence of adherence to be disentangled from dose individualization and could be used to provide clear guidelines about the relative importance of each in clinical practice.

 

References:

1. Assawasuwannakit P et al. Quantification of the forgiveness of drugs to imperfect adherence. CPT Pharmacometrics Syst Pharmacol. 2015;4(3):204-11.