Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials
Mahmoud Saghaei, Sara Saghaei
Abstract
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Mahmoud Saghaei, Sara Saghaei
Abstract
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Current minimization programs do not permit full control over different aspects of minimization algorithm such as distance or probability measures and may not allow for unequal allocation ratios. This article describes the implementation of “MinimPy” an open-source minimization program in Python programming language, which provides full customizetion of minimization features. MinimPy supports naive and biased coin minimization together with various new and classic distance measures. Data syncing is provided to facilitate minimization of multicenter trial over the network. MinimPy can easily be modified to fit special needs of clinical trials and in particular change it to a pure web application, though it currently supports network syncing of data in multi-center trials using network repositories.
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Current minimization programs do not permit full control over different aspects of minimization algorithm such as distance or probability measures and may not allow for unequal allocation ratios. This article describes the implementation of “MinimPy” an open-source minimization program in Python programming language, which provides full customizetion of minimization features. MinimPy supports naive and biased coin minimization together with various new and classic distance measures. Data syncing is provided to facilitate minimization of multicenter trial over the network. MinimPy can easily be modified to fit special needs of clinical trials and in particular change it to a pure web application, though it currently supports network syncing of data in multi-center trials using network repositories.
Key concepts: Minification, Computer science, Python (programming language), Open source, Data center, Clinical trial, Computer network, Programming language