The Future of Clinical Trial Modernization: What’s to Come in 2018

2017 has been an exciting year for the clinical trials industry on many fronts, driven by new methods, regulation, and technology. The FDA has made advancements by laying out the foundation for digital health, patient centricity is evolving to include study site-centric approaches, Quality Management systems are starting to leverage predictive modeling and adaptive governance and oversight models, and industry consortia continue to support and invest in standardization.

Digital Health Gains Some Footing

FDA recently released several draft guidance documents that lay the groundwork for advancements in digital health. Specifically, there were changes to Existing Medical Software Policies Resulting from Section 3060 21st-Century Cures Act, and Clinical and Patient Decision Support Software (CDS). In the Cures Act, FDA repositions app regulation by separating software from medical devices, and the draft CDS guidance offers the basis for regulating software that enhance physician decision-making efficiency (i.e., using aggregated big data sets to generate insights from literature, which can be used to facilitate treatment decisions). Although these draft guidances do not directly define digital health use in clinical trials, the release of the guidances can facilitate digital health device validation for disease-specific indications, which can then be used to objectively measure outcomes in clinical trial endpoints.

The biopharmaceutical industry, however, has not shied away from implementing new digital health initiatives, despite vague FDA guidances. Novartis, for example, is using “around the pill” applications to support drug efficacy (i.e., medication adherence), and “beyond the pill” initiatives that incorporate digital therapeutics (i.e., clinically validated interventions, either standalone or in combination with medical products). Moreover, Novartis incorporates digital health in clinical operational execution; for instance, leveraging compliance apps, clinical endpoint and data capture tools, and remote trial delivery systems. On the other hand, enterprises, such as Amgen, have launched digital health data collection studies to validate objective measures in migraine.

Other consortia, such as the Duke-Margolis Center for Health Policy, have collaborated with FDA to release their own papers to help guide the clinical trials industry in digital health. These papers dissect digital health data collection methodologies, and have offered recommendations to encourage study teams to embark on digital health initiatives in their trials.

Despite these advancements, digital health still has a long way to go before researchers can consistently and reliably leverage data collected from digital devices to support study endpoints in regulatory submissions, as many devices must still undergo validation for specific therapeutic indications.

Patient Centricity: More than Convenience

Patient centricity is becoming more explicit, as patients voice their perspectives on patient centricity to the industry. According to some patients, patient centricity is about empowering patients by treating them as a partner, and incorporating their perspective during study design and implementation to attract, engage, and retain patients throughout study duration and after study termination. Sponsors have aligned their approaches with the patient’s voice by not only incorporating patient perspectives during study design, but also by opening communications channels with patients during study execution.  To elaborate, some sponsors are piloting ‘give back’ initiatives where sponsors are sending communications directly to study participants through technology portals. Other sponsors are focusing on establishing methods to execute remote trials, which includes use of patient recruitment technologies, eConsenting, use of digital health to continually and objectively collect data, eMonitoring, and engaging patients.

The convenience and personalized aspects of patient centricity continue to evolve and adapt to support the patient.  To elaborate, Continuum Clinical collaborated with Lyft to assist study patients with transportation needs to reduce missed study visits. Other enterprises are taking an unconventional approach towards patient enrollment by incorporating a site-centric approach; specifically using technology and operational support systems to bring studies to trial-naïve physicians and sites that have access to study patient populations, thereby, maintaining the relationship between the patient and their physician. 

It appears that Patient Centricity has more room for refinement and exploration, as the term continues to evolve, and new patient-centric concepts form.

Study Oversight Models and Quality/Risk Management Systems

Clinical trial technology systems are aggregating data, and comprehensive quality analytics are starting to form. With newly-aggregated datasets, clinical trial risk management models are morphing to include technology-driven approaches towards improving quality and vendor oversight. Pfizer is using customized quality analytics to establish program-specific and study-specific KPIs/KRIs, then monitor and predict significant quality events, such as protocol deviations and GCP performance. Once identified, quality events are quantified (given risk scores), and then analyzed by experts through quality governance models, and issues repository systems.

Janssen is taking an integrated approach towards quality management and vendor oversight through technology system integration and analytics visualization dashboards. In such cases, quality is addressed through CRO vendor performance meetings, where specific KPIs/KRIs are discussed with the CRO, and data transparency is used as a tool to facilitate discussions, and collaboratively enhance study vendor performance.

Industry Consortia Continue to Invest in Collaboration

Industry consortia, such as TransCelerate, have spearheaded several industry initiatives led by biopharmaceutical enterprise shapers. Initiatives include collaborations with FDA/NIH to generate a common protocol template, quantitative metrics toolkit, an investigative medical product comparator network, and clinical research access and information exchange. Some biopharmaceutical companies, such as Johnson & Johnson, have launched their own collaborative initiatives with academia focused on data sharing;  this initiative offers data from previous clinical trials to the research community for analysis.

What’s to Come in 2018?

We expect to see several advancements in 2018. From the digital health front, we anticipate more pilots and investments in validating digital measures. In the time being, digital health will likely be used primarily to support clinical operations and study adherence. With patient centricity, we will likely see growth in virtual trials and site-centric approaches towards clinical trial execution, as well as new concepts involving patients as drivers for study design. It is possible that biopharmaceutical enterprises will also leverage the patient’s perspective when generating digital health validations and new digital health applications. With study oversight and quality risk management, since technology systems are starting to aggregate, we’ll likely see innovative ways of viewing risk analytics, new perspectives on KPIs/KRIs, enhancements in quality, and improvements in vendor oversight communication, efficiency and performance. It is possible that the future for quality management will also include information automation, and subsequently, self-improving quality management systems.

Moe Alsumidaie, MBA, MSF is Chief Data Scientist at Annex Clinical, and Editorial Advisory Board member for and regular contributor to Applied Clinical Trials.