Are we too slavish to the guidance and interpretation of GCP?
Written by Ian Macholl
This was one of several deliberately thought-provoking questions raised in our webinar last month, “COVID-19: The catalyst for long overdue change in clinical trial technologies and processes”.
In the first session, Gurpal Ahluwalia (Partner at BDO Life Sciences) assessed the disruptive impact of COVID-19 on clinical trials and the reasons why the industry has found itself in such difficulty. Cmed CEO, David Connelly, then shared some further perspective on the shortcomings of existing technologies and processes and suggested these contributed to the degree of disruption caused by the pandemic. One of the perspectives discussed was while completely accepting the need for regulation and guidance via Good Clinical Practice (GCP), is it now time to go back and look at the basics?
The thalidomide tragedy led to much greater regulation of drug testing and licensing which ultimately went further and led to GCP. GCP is needed to regulate clinical trials to help ensure data integrity and quality, as well as uphold safety and ethical standards. No question.
GCP has been developed, expanded and modified over the years. The Regulatory Authorities also acted swiftly to temporarily introduce some relaxation, greater flexibility and pragmatism in response to the COVID-19 pandemic. Is the need for such relaxation a symptom of an underlying problem? Have we, as an industry, become obsessed with following the rules? Do we now need to consider instead our basic aim to develop effective and safe treatments as quickly and efficiently as possible to help and save lives.
GCP emerged at a time of very different technologies to today. Have we built up a legacy of regulations that were right for the technologies and knowledge in our society at the time, but their legacy now hinders our progress in some areas? Are we trying to fit new technologies and the new processes that they allow onto old rules and thinking?
Dr Connelly went on to highlight the process of source data verification as an example. 72% of our webinar audience agreed with this position, at least to some extent.
To listen to the entire webinar, please access this link
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