RBQM Ops 2022 - How do we get to zero SDV?
How do we get to Zero SDV?
data, SDV, SDR, monitoring, trial, risk assessment, critical, rbqm, protocol, remote, source, important, clinical trials, quality, identified, processes, central, supported
Our next speaker is again someone I've had the pleasure of knowing for many years now. Jonathan Rowe has worked in the sector for more than 25 years, including two stints at Pfizer. Jonathan is now the head of r&d quality operations and risk management at ZS, the management consulting and technology company. Jonathan's a well-known industry speaker and blogger, and today he's going to be talking about a topic which is important to lots of us. Judging by the number of people that have asked us to make sure that we cover this topic at the RBQM event this year. The topic is all about SDV. And specifically, how do we get to zero SDV? So, Jonathan, thank you very much for agreeing to talk to us. I'll hand over to you.
And thank you, Duncan, for the introduction. I'm really happy to be here at RBQM Operations 2022. And talk a little bit about getting to zero STD. I always think that clarity is a good thing. And we'll talk obviously about SDV and SDR. SDV is a transcription checking process. Its intent is to compare critical data within the case report form, and your original source of information to confirm that it was transcribed accurately.
SDR is a different type of review. It's a site level review, to assess the quality source documentation and the performance of the critical processes that get that information into the documentation. It's a very valuable quality management activity that requires experience understanding of what goes on on-site, GCP requirements and understand the protocol. And it's, it's more than just checking for a transcription error. Its intent is to ensure that critical processes are followed. So, we'll talk a bit about SDV and SDR.
Now the literature is clear about how we in the industry feel about SDV. Even more than 10 years ago, there was a paper looking at the value of source data verification and a cancer clinical trial. And as you can see by the conclusion, quality assurance methods used in clinical trials should be informed by empirical evidence. And in this empirical comparison, SDV was expensive and identified random errors that made little impact on results and clinical conclusions of the trial.
They went on to say central monitoring using external data source was a more efficient approach at least for the primary outcome which was overall survival in this trial. And for subjective outcome, objective response and independent blinded review committee a tracking system to monitor missing scan data and trawling scanning as an out as an outcome could be more efficient than SDV...
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