The clinical trials industry is beginning to reemerge from the pandemic and is taking a new direction in the new post-pandemic reality. The pandemic has forced the clinical trials industry to adapt to new ways of thinking around patient-centricity; politicization seemed to have generated a renewed interest in clinical trial diversity inclusion, surging demand in decentralized technologies is transforming research, and advances in artificial intelligence (AI) and data access are allowing for new opportunities in RWE predictive research and early patient engagement. These were the main themes discussed at Disruptive Innovations to Advance Clinical Trials (DPHARM) 2021.
One of the main topics included recruitment challenges with COVID vaccine development during the pandemic. Diane Montross, Sr. Director of Patient Recruitment and Retention at Moderna, discussed that while the COVE study initially saw many volunteers, enrolling 30,000 patients in a short timeframe and ensuring diversity inclusion was a big challenge. Accordingly, Moderna needed to expand its recruitment vendor access; however, another challenge included vendor onboarding. To elaborate, specific vendor qualification and onboarding stages took time, such as the request for proposal (RFP) process, bid defenses, procurement and contracting, relationship building, vendor management, and governance, and performance tracking analysis. Hence, they partnered with Citeline Connect, which centralized the process, enabling Moderna to rapidly engage and ramp up numerous recruitment vendors. As a result, within two months, Hispanic/Latinx patients increased from 14% to 20% of the entire study population, and African American patients increased from 5% to 10%, helping to achieve its diversity inclusion and recruitment goals.
This year, diversity inclusion has been an essential topic within the biopharmaceutical industry, as evangelized by Eli Lilly and Genentech/Roche. Lloyd Miller, VP of Immunodermatology Disease at Janssen, discussed his organization’s approaches towards enhancing diversity, equity, and inclusion in clinical trials. Miller indicated that while FDA advises the biopharmaceutical industry to improve diversity by including patients who will use’ medication post-approval, safety and efficacy differences between patient populations are often not explored in datasets because of lacking statistical power. Nevertheless, the industry has made strides in clinical trial diversity inclusion; for example, from 1995-1999, white patient populations represented 83% of trials, whereas, in 2019, they represented 72%. Of particular note, Latinx patient populations increased from 3% to 18% in clinical trials, respectively, which is close to diversity representation figures in the US.
Miller mentioned several challenges to enrolling diverse patient populations, including socioeconomic factors (i.e., education, culture, age, and race/ethnicity), awareness factors (i.e., health literacy), opportunity (i.e., geography and poor dissemination of information, and various communication methods), and decision factors (i.e., lacking trust in the industry and investigators, and negative preconceived notions about research). Janssen included diversity elements in feasibility assessments and segmented sites into diversity enrollment categories to overcome these challenges. However, selecting sites that can enroll diverse patients is not enough; hence, Janssen implemented educational programs, such as investigator meeting workshops, training materials, and highlighting diversity in study communications.
Moreover, other recruitment initiatives included targeted social media campaigns, local community outreach, and advocacy group outreach. Additional diversity inclusion strategies included easing the socioeconomic burden by offering patients door-to-door car service and meal stipends. These strategies contributed towards improving diversity inclusion in Janssen’s clinical trial programs.
The pandemic has unleashed demand offered by eClinical technologies that support decentralized clinical trial conduct to expand diversity inclusion in hard-to-reach communities. Amidst this unprecedented demand, the clinical trials industry is known to resist novel eClinical technologies and methodologies to innovate. Accordingly, Ken Getz, Professor, and Director of Tufts CSDD, aimed to answer that question by discussing preliminary study results on the innovation process and opportunities to optimize drug development operations. This study aimed to “characterize and measure primary process and mechanisms that sponsors use in adopting innovations supporting clinical development operations and to identify best practices and shortcomings.” Preliminary results indicate that economic risk, regulatory risk, lack of trust in solutions, and lack of commitment contributed towards adoption barriers. The study showed a straightforward four-step process towards new technology adoption (mainly by the biopharmaceutical industry and CROs), which includes the initiation phase (i.e., identifying a need, gauging interest and initial planning), the evaluation phase (assessing and piloting), the adoption decision phase (deciding whether to adopt the technology enterprise-wide), and the full implementation phase (i.e., broad rollout, communication, and training).
This process, however, does not appear to be fast enough for respondents, as 83% believe that their company took ‘somewhat’ or ‘much longer’ to adopt an innovation compared to their peers fully, and 58% believe that their enterprise is ‘late to adopt’ or ‘last to adopt.’ The most significant challenges towards innovation are in the later phases of the process, including the adoption decision and full implementation phases. To elaborate, challenges in the adoption decision phase include insufficient evidence, inability to determine ROI, and vendor/solution uncertainty and volatility; alternatively, contributing factors included quantitative evidence, internal champions, regulatory clarity, and senior management support. In the full implementation phase, major challenges included cross-functional buy-in and support, poor commitment, economic continuity, and lack of senior management support; on the other hand, contributing factors included change management planning, communication and promotion, visible senior management participation, and training and incentive alignment.
Interesting insights that may hinder innovation appeared to be culturally related, as 42% of respondents indicated ‘high’ to ‘moderate’ risk in poor performance reviews when pursuing adoption of new solutions, and 57% mentioned that adoption interferes ‘somewhat’ or ‘greatly’ with their current tasks and project deliverables. Nonetheless, 54% of respondents who rated their enterprise as ‘excellent’ at innovation adoption indicated they were rewarded for taking on innovation initiatives.
Real-World Evidence (RWE), data analytics, and AI was also a topic of discussion at DPHARM, as these topics go hand-in-hand with patient centricity and engagement. Jessica Scott, Head of R&D Patient Engagement at Takeda, and Wendy Sanhai, Specialist Leader at Deloitte, discussed patient experience data (PED) trends in clinical development. There was discussion on regulatory trends with PED; for example, the ICH in 2020 recommends global harmonization in patient inclusion perspectives, and FDA suggested more consistency in patient and caregiver input to inform regulatory decision-making. Asian agencies are also focusing on patient involvement in drug development. As defined by FDA, PEDs contain information that captures patients’ experiences, perspectives, needs, and priorities, including symptoms, impact, treatment experiences, input on study outcomes, preferences, and relative importance of issues. Patient engagement examples include symptoms, the burden of disease, and treatment, to name a few. Sanhai and Scott emphasized that since many regulators across the globe are mandating the use of PEDs, it is vital to increase awareness for PED use within the biopharmaceutical enterprise, and recommended identifying appropriate programs, inviting collaboration both internally and with regulators and patient organizations, and leverage various types of PEDs (i.e., Clinical Outcomes Assessments (COA), Patient-Reported Outcomes (PROs), and qualitative PEDs, such as interviews with patients and caregivers).
Earl Seltzer, Sr. Director of Global Feasibility at Labcorp, discussed how AI and data analytics play a key role in creating better patient experiences through RWE analysis. Seltzer suggested that billions of lab test results in Labcorp’s databases allow for individual and longitudinal data analysis, which can be done with AI and predictive analytics. For example, Labcorp now can predict NASH and use this predictive model to identify and potentially contact patients or their caregivers for health screenings and introduce them to research.
In summary, diversity inclusion, technology adoption, and RWE research were all topics that were linked to patient-centricity at DPHARM 2021. Diversity inclusion has been a regulatory recommendation for several years, and the biopharmaceutical industry is making strides in enhancing diversity in clinical trials via recruitment and site selection strategies, though data on diverse patient populations collected in clinical research is still not large enough to decipher statistical results. In addition, new insights on technology adoption resistance are emerging, and it appears the biopharmaceutical industry can improve and standardize its approaches towards adopting innovation more rapidly. Finally, RWE data collection and analysis are increasing in interest as regulatory authorities are expecting some form of PDEs in submissions, and the increasing availability of data allows for emerging disease prediction and early patient and caregiver clinical trial engagement opportunities.
Moe Alsumidaie, MBA, MSF, is a thought leader and expert in the application of business analytics toward clinical trials, and Editorial Advisory Board member for and regular contributor to Applied Clinical Trials.