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Management of complex randomisation methodologies

Edited by the Laboratorytalk editorial team Feb 3, 2006

In a recent poll by ClinPhone, over half of the respondents said that the biggest challenge facing randomisation and blinding in clinical trials was the management of complex statistical methodologies

A further 35% of poll respondents indicated another problem area was ensuring that randomisation processes are followed correctly.

The opinion poll was conducted as part of ClinPhone's recent webinar series, 'Demystifying the black box: basic and advanced randomisation methodologies'.

These webcasts, attended by over 300 biopharmaceutical experts, discussed how ClinPhone's interactive voice response (IVR) and interactive web response (IWR) can overcome these challenges.

During the webinar, Graham Nicholls, product manager at ClinPhone, presented various methodologies to address these issues.

IVR and IWR offer easy access to a variety of validated randomisation algorithms, ensuring that treatment allocations are completed immediately and providing study sites and end users with a very practical and easy-to-use technique.

This allows sponsors to select complex techniques that would be difficult to administer in any other way.

Using ClinPhone's centralised randomisation services, pharmaceutical clients can effectively tackle the problem areas such as obtaining treatment group balance for baseline clinical variables and safeguarding that randomisation algorithms are implemented correctly across all study sites.

ClinPhone's team of statistical experts, headed by Damian McEntegart, provides a unique consultative service, offering advice on the randomisation methodology for any given trial, from simple non-stratified schemes to more complex allocation methods including stratification, biased coin minimisation, dynamic hierarchical algorithm, and client-specific algorithms.

In addition to double-blind trials, ClinPhone's services are also valuable in open-label studies where computerised treatment allocation provides protection against potential selection bias.