Clinical trial optimization: Monte Carlo simulation Markov model for planning clinical trials recruitment.
BACKGROUND
The patient recruitment process of clinical trials is an essential element which needs to be designed properly.


METHODS
In this paper we describe different simulation models under continuous and discrete time assumptions for the design of recruitment in clinical trials.


RESULTS
The results of hypothetical examples of clinical trial recruitments are presented. The recruitment time is calculated and the number of recruited patients is quantified for a given time and probability of recruitment. The expected delay and the effective recruitment durations are estimated using both continuous and discrete time modeling.


CONCLUSIONS
The proposed type of Monte Carlo simulation Markov models will enable optimization of the recruitment process and the estimation and the calibration of its parameters to aid the proposed clinical trials. A continuous time simulation may minimize the duration of the recruitment and, consequently, the total duration of the trial.
Abbas
Ismail
I
Universitat Politècnica de Catalunya, Facultat d'Informàtica de Barcelona, Laboratori de Càlcul, Barcelona, Spain. ismail.abbas@fib.upc.edu
Rovira
Joan
J
Casanovas
Josep
J
D002986:Clinical Trials as Topic / Q000379:methods*; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method; D018579:Patient Selection