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Philip Russmeyer: Revolutionising clinical trials with true data anonymization
Manage episode 382347592 series 3526489
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This week we speak to Philip Russmeyer, Founder & CEO of Fitfile, about the promises that true data anonymization holds for transforming clinical trials.
We dive into the differences between tokenization, anonymization and pseudonymisation of data. And how the difference is whether individuals can ever be identified or if the data is masked with a token that can potentially be removed.
The risk of secondary use of data that has been tokenized has held back research and data sharing between healthcare and life sciences. One of the reasons is that collecting consent from individuals costs about 400 USD per consent.
One of the downsides of anonymization is that data cannot be unified across sources for an individual to get a full picture of health data.
We speak about the differences between US and EU attitudes and legislation about personal data protection and how these are converging towards stronger privacy protection. For good reason, since personal health data is worth 10x more on the dark web compared to financial data.
Collection of consent also matters in the sense that 80-90% of a trial is still delayed due to longer recruitment timelines than anticipated. That can be reduced if the trial protocol rests on a larger volume of anonymized relevant data.
Anonymized data can also serve as a larger and more ethical control arm for clinical trials. Same goes for long-term follow up of clinical trials and the potential to re-use data collected once in additional trials.
We speak about the siloed nature of health data between healthcare and life sciences and how Fitfile attempts to work end-to-end between the entire data creation lifecycle. Which is not always simple, but optimises the use of health data.
Guest:
https://www.linkedin.com/in/philiprussmeyer/
Fitfile
https://www.linkedin.com/company/fitfile/
Notes:
GPDPR Program of the NHS: https://digital.nhs.uk/data-and-information/data-collections-and-data-sets/data-collections/general-practice-data-for-planning-and-research
European Journal of Human Genetics:
ADPPA:
https://www.congress.gov/bill/117th-congress/house-bill/8152/text
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