Clinical trials that function on a global magnitude have clinical sites and patients across multiple geographies. The very nature of clinical trials brings opportunities as well as some challenges, wherein the clinical data spread across the globe adds more complexities to this. Amid these convoluted multiplicities, the element of BYOD, wearable technology, and mHealth applications may seem overwhelming. However, they partially resolve the issue of multiplicity.
Let me explain how.
On time Data
The dispersed patient population refrains researchers and clinical trial practitioners from collecting real-time and on-time data necessary to draw timely insights for the drug development process. Eliminating follow-up visits to research centers, seamless clinical data collection, and reduced clinical data cost per patient are some of the advantages that have brought these personalized technologies accepted in the clinical trial process by practitioners, patients, and also the regulatory authorities such as the FDA.
In August 2017, the National Institutes of Health’s clinical trial database returned over 170 results for the search term ‘Fitbit’, over 300 for ‘wearable’ and over 440 studies 76 for ‘mobile app.’ This justifies the acceptance of BYOD, wearable technology, and mHealth applications in the clinical data collection process during clinical trials by the entire ecosystem.
While this is comforting news on one side; the researchers, investors and practitioners must deal with a different challenge when they step over to the other side. These technologies have led to device diversity which is followed by data diversity during clinical trials. With high diversity, the information systems and insight machines experience a continuous flow of data. By 2021, 504.65 million wearable devices are expected to be sold. Extremely useful clinical data can be derived and made available through them, but again not in a consumable form.
Many legal standards, statutory guidelines and recommendations for clinical data formats are already in place to resolve the issue of clinical data diversity and complexity. However, it is also a matter of transparency, speed to deploy meta-schema and the maintenance of clinical data repositories for the same. For future inquiry and research, maintaining a metadata repository is imperative. Apart from that delays and gaps in updating researchers and scientists of the new development and data points during the clinical trials would slow down the process drastically. It obviously has further adverse cost implications for both the investors and patients.
Clinical data diversity also brings in the complexity of managing a variety of clinical data formats. This creates heavy volume of clinical data which gets unmanageable in the absence of a robust statistical computational environment for clinical reporting.
Instead of going back and forth to verify clinical data quality and timeliness out of a clinical trial, on-time clinical data renders necessary information to eliminate expensive iterations. On-time data facilitates in-time action; and in-time action helps fulfilling regulatory compliance and shortening the cycle of each clinical trial, while reducing costs.
A single platform that integrates, comprehends and interprets a variety of clinical data and clinical devices can turn such clinical data into insights. Seamless, transparent, and on-time insights into clinical data based on an aggregation and standardization across the clinical studies in a cloud-based clinical data repository, backed by AI and built around SCE, will enable all stakeholders involved in the clinical trial to act in-time. This would mitigate all risk and shorten your time to market.
At MaxisIT, we clearly understand strategic priorities within clinical R&D, and we can resonate that well with our similar experiences of implementing solutions for improving Clinical Development Portfolio via an integrated platform-based approach; which delivers timely access to study specific as well as standardized and aggregated clinical data, allows efficient data quality management, clinical reviews, and statistical computing.
Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring. MaxisIT’s Integrated Technology Platform is purpose-built solution, which helps Pharmaceutical & Life sciences industry by “Empowering Business Stakeholders with Integrated Computing, and Self-service Analytics in the strategically externalized enterprise environment with major focus on the core clinical operations data as well as clinical information assets; which allows improved control over externalized, CROs and partners driven, clinical ecosystem; and enable in-time decision support, continuous monitoring over regulatory compliance, and greater operational efficiency at a measurable rate.”