Predictive drug supply modelling in clinical trials
Vladimir Anisimov
Presented at PSI conference, Manchester, 18 May 2010
Drug Supply Modeling Software: User Manual
Vladimir Anisimov, Valerii Fedorov, Richard Heiberger, Sourish Saha and Mark Kothapalli
Published as GSK DDS Technical Report 2010-01
Abstract: The design of multicentre clinical studies consists of several interconnected stages including patient recruitment prediction, choosing a randomization scheme and a statistical model for analyzing patient responses, and drug supply planning. The Research Statistics Unit (RSU) at GlaxoSmithKline (GSK) has developed a risk-based supply modeling tool using statistical principles. The tool predicts drug supply needed to cover patient’s demand in a single study with a given risk of running out of stock for a patient. In order to support Clinical Trials Supply and Global Supplies Operations teams at GSK, the RSU created a user-friendly RExcel interface embedding the risk-based supply modeling tool into the Excel environment. This manual discusses screenshots to guide the user through using the interface.
Comparisons of minimisation and Atkinson’s algorithm
Stephen Senn, Vladimir Anisimov and Valerii Fedorov
Published in Statistics in Medicine, 2010, V. 29, 7/8, pp. 721-730
Abstract: Some general points regarding efficiency in clinical trials are made. Reasons as to why fitting many covariates to adjust the estimate of the treatment effect may be less problematic than commonly supposed are given. Two methods of dynamic allocation of patients based on covariates, minimization and Atkinson’s approach, are compared and contrasted for the particular case where all covariates are binary. The results of Monte Carlo simulations are also presented. It is concluded that in the cases considered, Atkinson’s approach is slightly more efficient than minimization although the difference is unlikely to be very important in practice. Both are more efficient than simple randomization, although it is concluded that fitting covariates may make a more valuable and instructive contribution to inferences about treatment effects than only balancing them.
Predictive modelling of patient recruitment in clinical trials
Vladimir Anisimov
Presented at 3rd Annual Effective Patient Recruitment in Clinical Trials Conference, Vienna, 26 April 2010 (via broadcast from UK)
Sergei Leonov
Presented at ENAR, New Orleans, 22 Mar 2010
Adjustment of patient recruitment in the Bayesian setting
Frank Mannino
Presented at ENAR, New Orleans, 22 Mar 2010
Vladimir Anisimov
Presented at PSI Statistical Interest Group on Modelling & Simulation, Cambridge, UK, 31 March 2010
