Leading pharmaceutical companies and Clinical Research Organizations (CROs) are already leveraging the nascent concepts of managed data lakes to accelerate patient recruitment and reduce costs by implementing risk-based monitoring approaches. In order for drug companies and associated partner, clinical research organizations to prevail in the competitive process of getting FDA approval for a drug, the data management function has to become lean and agile compared to the time-honored but inefficient practices of previous decades.
Implementing such comprehensive end-to-end harmonization and integration of data requires a number of capabilities that are enabled by nascent concepts such as managed data lakes. Data security, data traceability, data provenance and clinical concept semantics will all be key facets and functions that this foundational data infrastructure will need to provide ubiquitously and reliably.
Some implications of the rapid acceleration and adoption of data-driven evidence-based medicine:
The beginning of the arduous drug approval process is usually conducted in labs and research institutions, called Academic and Laboratory Research Phase or the Pre Clinical phase. This is followed by Clinical Trials Phases I through IV culminating in FDA approval for the drug or not (usually resulting in termination of further interest in drug development).
Consider the case of a new special purpose hypertension drug under clinical development where the stringent inclusion and exclusion criteria for patient recruitment must be managed across multiple sites and countries.
Inclusion:
Exclusion:
A representative illustration of pharmacy drug fill history data that could be leveraged for patient recruitment is provided as an example below:
In the past, the techniques for accelerating drug development used to hinge primarily on the identification of key physicians (principal investigators) and key hospitals (sites) where patients go for treatment. This implied an often misplaced reliance on the accuracy and currency of provider, hospital, or CRO databases or public health records to identify the candidate patient pools. The attendant process and paperwork to get such information often proved to be very onerous and expensive.
However, with the advent of managed data lakes and patient recruitment analytics, the existing data from diverse hospitals, practices, retail pharmacies, and social media sites can be leveraged to address time-sensitive patient recruitment challenges and to lock-in competitive advantage. What could only have been achieved by paying for access to expensive patient registries and CRO databases is now becoming commoditized by the foundational data management platforms that offer these facilities as platform services.
To learn more about managed data lakes, foundational data management platforms for health and life sciences, watch our on-demand webinar on Health Informatics and Managed Data Lakes.
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