19 Apr 2018 Blog
Clinical Data Ecosystem – It’s evolving faster than ever

Since the first few citations of registered and structured clinical data in the 1940s, the methods of capturing clinical data, use and application of clinical data, global inclusions, and role of payers, users and regulators have evolved.

At present, Clinical Data universe comprises of the siloed internal and external data sources within clinical development processes, which is a conceivable evolution; and currently, every other organization across this industry is experiencing similar scenario due to that.

This resulted data universe is primarily due to the strategic decisions made in the interest of business to support organizational consolidations, to manage cost & revenue pressures, to enable focus on core R&D and management, and to ensure continuous compliance to dynamically evolving regulatory guidance.

Staying focused on the core R&D business and continually improving operational & clinical performance have always been the topmost priorities among the business stakeholders; but, a collective and timely insight across the horizontally spread data and information haven’t always been possible. In such cases, the business decisions have often delayed, or relied on outdated information or lacked the cross-functional impact. The resulting outcome has become more like a spider-web with the knots at every corner.

Other reasons for this evolution could also be that for a long time, the conduct of clinical trials and healthcare initiatives have been carried out by separate functional silos within an organization using separate “legacy” applications & cookie-cutter solutions. Such approaches are typically focused on a specific process or function. This has resulted in multiple, disparate, and inefficient solutions that may not work well together. This has deprived organizations of the ability to make timely decisions, as well as increase efficiencies and overall productivity at the corporate portfolio level while controlling costs & mitigating risks involved at a specific study or functional level or at a portfolio level.

However, the adoption of digital means such as electronic patient reported outcome (ePRO) and electronic data capture (EDC) systems in place of paper-based case report form (PCRF) has changed the landscape of clinical data. It has reduced the time taken to collect data and relay into the next stage of the process from five days to fifteen minutes. Also, has aided in expediting the process to develop drugs.

Another milestone is the evolution of data structures. Big Data has allowed management of large volume of data and conversion of the same into comprehensible and insightful visualizations. To realize such benefits, clinical data management processes are compelled to use standardized fields, formats, and forms. This requires the application of the metadata-driven process.

The uprise of Clinical Trial Globalization has eliminated gaps between global study expectations and national standard protocols that lead to many operational complexities. Regulatory bodies like FDA and EMA have come together to synchronize requirements on a protocol-by-protocol basis.

To control financial risks for managing patient populations and to provide continuous access to electronic data, private networks have started building centralized data repositories. This can be further used for a range of analytics, including predictive modeling, quality benchmarking, and risk stratification.

These breakthroughs have eased out many challenges while implementing critical trials but have also increased the responsibility of CROs and Clinical data managers to upgrade and standardize their systems in response to these progressive developments.