During our recent webinar, Bridging the Gap to the New Clinical Trial Landscape, Life Sciences Industry Expert, Dean Gittleman, and CDS’ Jeff Rogers and Cody Wilke explored how advanced technology, including the use of native mobile technology as an integrated data source and management tool, empowers research professionals to optimally manage not only clinical data but also the study as a whole. In this blog post, we recap the top three tips our panelists provided throughout the presentation to confront the hurdles in today’s clinical trial landscape and achieve efficient study execution.
1. Utilize data from a variety of sources
For a number of years, the clinical trials industry relied on case report forms (CRFs) and a select few non-CRF sources (i.e., labs) to gather data. Today, clinical data comes in different forms from a plethora of sources: electronic patient-reported outcomes (ePRO), wearables/internet of medical things (IoMT), imaging, biologics, genomics, and more. While these data sources are not necessarily new, the COVID-19 pandemic has created a shift in how they’re perceived and adopted. The FDA’s recently updated Guidance for the Conduct of Clinical Trials has prompted greater interest in minimizing face-to-face interactions with trial participants and increasing the use of remote site and participant-entered data collection and electronic informed consent (eSource, ePRO, and eConsent) with an expanded focus on patient centricity.
As traditional site visits by participants have become more difficult to carry out due to the circumstances of the pandemic, there’s more pressure than ever to take advantage of any and all pertinent data- particularly real-world data (RWD) – to continue progressing studies with minimal interruption. Although this has taken many organizations out of their technological comfort zones, the change will be beneficial for sponsors and patients alike in the long run. By centralizing the storage and accessibility of all these data, sponsors may see shorter study durations and reduced costs, and patients may receive therapies and treatments much quicker. But getting the data into one location is just the first step – for the data to be useful, they should also be actionable.
2. Implement an integrated approach to data management and operational management
Effective access and use of both clinical data and operational data have long been a challenge in clinical research as a result of departmental silos within companies and disparate data collection and storage tools. It’s common for departments to “own” sets of data; for example, one department may be particularly interested in genomic data and therefore have exclusive access and use of that data, while another department responsible for the operational health of a clinical trial has sole control of the operational data. But by centralizing and integrating the wealth of data collected during a trial, they can be leveraged by the entire research team and further drive collaboration across departments.
Transitioning away from traditional, siloed eClinical systems is often perceived as a risk by some organizations due to budgetary, regulatory, and technical barriers. However, these hurdles are easily overcome today as more flexible, cost-friendly technologies emerge and as regulatory agencies adjust guidance according to changes in the industry.
To successfully execute the transition toward an integrated approach to data management and operational management, we suggest the adoption of a hosted cloud-based platform with a centralized data repository. This solution allows for invaluable real-time data collection from a variety of modalities. More importantly, it gives research professionals the ability to analyze and draw inferences from the data as quickly as possible. In turn, discoveries can be made early on and appropriate changes or action may be taken to correct problem areas in the study.
3. Leverage advanced analytics and reporting tools
In order to gain insights from the data that are needed to make important decisions in clinical trials, organizations can take advantage of sophisticated business intelligence (BI) technologies. The increasing complexity of study protocols and influx of data, however, has generated a heightened demand for solutions that help research teams efficiently centralize and analyze data.
Recognizing the industry’s need for this technology, Crucial Data Solutions recently released TrialKit BI, an advanced analytics and reporting tool that provides a dynamic visual analysis and dashboard view of clinical data, operational data, and metadata from studies being conducted with TrialKit. The system produces highly configurable near-real-time reports based on 120 different metrics and data variables. TrialKit BI can be leveraged throughout the course of the study, fully enabling data analysis when it matters most.
Of course, there are many other considerations to take into account as the industry collectively continues to bridge the gap to the new clinical trial landscape during the pandemic and beyond. To learn more from our panelists, view the full, on-demand recording of the webinar and contact us with any questions you may have that we didn’t address.
