Simulating sequential multiple assignment randomized trials to generate optimal personalized warfarin dosing strategies.
BACKGROUND
Due to the cost and complexity of conducting a sequential multiple assignment randomized trial (SMART), it is desirable to pre-define a small number of personalized regimes to study.


OBJECTIVE
We proposed a simulation-based approach to studying personalized dosing strategies in contexts for which a therapeutic agent's pharmacokinetic and pharmacodynamics properties are well understood. We take dosing of warfarin as a case study, as its properties are well understood. We consider a SMART in which there are five intervention points in which dosing may be modified, following a loading phase of treatment.


METHODS
Realistic SMARTs are simulated, and two methods of analysis, G-estimation and Q-learning, are used to assess potential personalized dosing strategies.


RESULTS
In settings where outcome modelling may be complex due to the highly non-linear nature of the pharmacokinetic and pharmacodynamics mechanisms of the therapeutic agent, G-estimation provides for which the more promising method of estimating an optimal dosing strategy. Used in combination with the simulated SMARTs, we were able to improve simulated patient outcomes and suggest which patient characteristics were needed to best individually tailor dosing. In particular, our simulations suggest that current dosing should be determined by an individual's current coagulation time as measured by the international normalized ratio (INR), their last measured INR, and their last dose. Tailoring treatment only based on current INR and last warfarin dose provided inferior control of INR over the course of the trial.


CONCLUSIONS
The ability of the simulated SMARTs to suggest optimal personalized dosing strategies relies on the pharmacokinetic and pharmacodynamic models used to generate the hypothetical patient profiles. This approach is best suited to therapeutic agents whose effects are well studied.


CONCLUSIONS
Prior to investing in a complex randomized trial that involves sequential treatment allocations, simulations should be used where possible in order to guide which dosing strategies to evaluate.
Division of Clinical Epidemiology, McGill University Health Centre, Montreal, QC, Canada.
Benjamin
B
Rich
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada erica.moodie@mcgill.ca.
Erica Em
EE
Moodie
Department of Mathematics and Statistics, McGill University, Montreal, QC, Canada.
David A
DA
Stephens