2007 - KÝbenhavn - Denmark

PAGE 2007: Methodology- Other topics
Stacey Tannenbaum

A Comparison of Fixed Dose-Controlled (FD) versus Pharmacokinetic Modified Dose-Controlled (PKMD) Clinical Study Designs

Stacey Tannenbaum (1), Gene Williams (2), He Sun (3), I. Peter Lee (2), Lawrence Lesko (2), and Robert Temple (2)

(1) Novartis Pharmaceuticals Corp. Pharmacology Modeling and Simulation, (2) Center for Drug Evaluation and Research, US Food and Drug Administration, (3) Clinical Pharmacology, SunTech Research Institutes

Objectives: When pharmacokinetics (PK) is a known function of covariates such as age and weight, individualizing doses according to these covariates may reduce variability in drug exposure. The objective of this study was to determine the extent to which dose individualization based upon patient characteristics (PK modified dosing, PKMD) results in increased trial success, compared to a fixed dosing (FD) design. Trial success is assessed by the percentage of patients (%P) whose exposure falls within a target range, determined from the exposure-safety and exposure-efficacy relationships. A number of scenarios were examined to determine under what circumstances the benefits of PKMD outweigh the costs.

Methods: The change in %P between a FD and PKMD design was examined as a function of three factors: the unexplained variability in clearance (CLvar), the width of the target exposure range (ERW), and the available dosage strengths. Simulations were performed for all combinations of ERW (2-10), CLvar (10-100% CV), and dosage strength (20, 25 mg) with 1000 subjects per scenario. The doses required to obtain a target exposure (AUCtarget, fixed for all scenarios) were calculated as follows: FD = AUCtarget*CLpop, and PKMD = AUCtarget*CLpred,i, where CLpred,i is the individual predicted CL, based on covariates. Doses were then rounded to the nearest available dosage strength. The individual exposure was determined using this rounded dose and the true (simulated) individual CL. The difference in %P between FD and PKMD was calculated for each scenario.

Results: A multi-panel nomogram was created to observe the effects of the three variables (CLvar, ERW, and dosage strength) on the trend in %P for FD and PKMD. The results suggest that the extent of improvement with PKMD versus FD is reduced with increased CLvar; a less accurate prediction of individual CL may lead to a PKMD inappropriate to determine the target exposure. Smaller dosage strengths are superior in both FD and PKMD, as there is a smaller difference between the rounded (administered) dose and the calculated (“ideal”) dose. Finally, exposure ranges that are sufficiently large will offset the variability in exposure with FD, making the extent of improvement with PKMD minimal.

Conclusions: By assigning individual doses to account for the variability in PK, the variability in exposure can be reduced. The degree of this reduction, in combination with a known target exposure range and dosage strength, can be used to determine how much a PKMD design would increase %P compared to a FD design, and thus improve the probability of trial success. Quantifying the extent of this improvement should allow drug developers to discern if a PKMD strategy will improve the trial results sufficiently to offset the additional effort of designing and implementing a PKMD-controlled study.




Reference: PAGE 16 (2007) Abstr 1187 [www.page-meeting.org/?abstract=1187]
Poster: Methodology- Other topics
Click to open PDF poster/presentation (click to open)
Top