In the dynamic world of clinical trials, Gen Li of Phesi offers a unique perspective on the industry’s challenges and innovations. As trials face increased attrition rates post-pandemic, AI and data analytics become crucial. Gen Li discusses these issues, the promise of biomarker-specific studies, and the future of clinical trials, providing valuable insights into the evolving landscape.
Moe: With rising attrition rates in phase two trials post-pandemic, what factors drive this trend, and how can AI and data analytics mitigate these risks?
Gen Li: The increase in attrition rates is concerning. Pre-pandemic, rates were stable at 20%, but they have since risen to 25-30%. This shift is largely due to the COVID-19 pandemic, which disrupted the industry’s long-standing ecosystem. Despite advancements in centralized trials and digital data collection, these have not fully addressed the complexities. Issues such as overly complicated trial designs, burdens on patients and sites, and misinterpreting results, especially in oncology, contribute to this crisis. AI and data analytics can play a pivotal role by refining trial designs and improving site selection, ensuring trials are more patient-centric and aligned with specific patient populations. Sponsors can leverage data from millions of patients to refine trial designs and improve site selection, ensuring trials are more patient-centric and aligned with specific patient populations.
Moe: Biomarker-specific studies in NSCLC show promise. What challenges remain in scaling these approaches across other areas, and how can Sponsors overcome these challenges?
Gen Li: Clinical development doesn’t exist in a vacuum; it relies on a broader understanding of diseases. For instance, the progress in cancer treatment has evolved from primitive methods to more specific biomarker-driven approaches. However, scaling these advancements requires a concerted effort across medical and scientific communities. Sponsors can leverage data science to provide tools that help clinical development teams solve complex problems. Such approaches integrate external insights and foster innovation, which is crucial for advancing biomarker-specific studies across various therapeutic areas. For example, the evolution of CAR-T therapies from blood cancers to solid tumors exemplifies the potential for biomarker-driven approaches to revolutionize treatment across different cancer types. This collaborative effort is essential for translating these advancements into other therapeutic areas, ensuring that the benefits of biomarker-specific studies are realized across the board.
Moe: Breast cancer is heavily researched. How can these insights be applied to less studied diseases to drive innovation and reduce attrition rates?
Gen Li: While breast cancer research has seen breakthroughs, it still faces high attrition rates, particularly in areas like triple-negative breast cancer. The key is to move beyond the negatives and identify more positive markers. This approach can be generalized to other diseases, where innovation is driven by both the dire needs of the disease and advancements in medical understanding. For instance, the progress in non-small cell lung cancer through biomarker identification can be a model for other areas, including neuroscience. The challenge lies in translating these insights into actionable strategies for diseases with less research focus, ensuring that the methodologies developed in well-studied areas can be adapted to new contexts. Applying these insights can drive innovation and reduce attrition rates in less-studied diseases, ultimately improving outcomes.
Moe: Investigator site selection is crucial. How can sponsors optimize sites for robust recruitment and retention, especially in underrepresented regions?
Gen Li: Site selection has evolved significantly. Historically, a few investigators contributed to most trials, leading to overburdened sites. We aim to change this by focusing on medium-tier capable yet less burdened investigators. We also emphasize aligning investigators with the specific patient populations targeted by trials. Our platform constructs digital patient profiles to ensure precise alignment, essential for successful recruitment and retention. For example, in acute ischemic stroke trials, identifying neurologists who can recruit patients within a critical 24-48 hour window is crucial. Sponsors can leverage such platforms to facilitate this level of precision. By ensuring that investigators are well-matched to the patient populations they serve, they can improve recruitment and retention metrics, particularly in underrepresented regions, ultimately enhancing the success of clinical trials.
Moe: Given the financial burden of failed trials, what are key missteps in trial design or execution, how can sponsors address these inefficiencies?
Gen Li: Clinical trials inherently involve unknowns, but we can utilize existing data to simulate and foresee potential outcomes. Some platforms allow for precise simulation of trial designs, site selection, and patient composition, helping to mitigate risks and reduce attrition rates. This approach is crucial for phase two and phase three trials, where attrition can be even more costly. By simulating trial scenarios, sponsors can better anticipate challenges and adjust their strategies accordingly, reducing the likelihood of costly failures. Our platform’s ability to simulate and predict outcomes provides sponsors with the tools to make informed decisions, ultimately improving clinical trial efficiency and success rate.
Moe: With COVID-19 no longer a top study focus, what does this shift tell us about sponsor priorities post-pandemic, and how are you leveraging these trends?
Gen Li: The shift from COVID-19 reflects a return to focusing on other pressing medical needs and innovations. However, the emergence of GLP-1 as a significant area of interest highlights the unpredictable nature of medical innovation. We aim to position ourselves to embrace such disruptive forces, ensuring we remain adaptable and responsive to new trends and priorities in clinical research. This adaptability is crucial as the industry navigates post-pandemic priorities, balancing the need for innovation with the realities of resource allocation. By staying attuned to these shifts, we can leverage emerging trends to influence future trial strategies, ensuring we remain at the forefront of clinical research innovation.
Moe Alsumidaie is Chief Editor of The Clinical Trial Vanguard. Moe holds decades of experience in the clinical trials industry. Moe also serves as Head of Research at CliniBiz and Chief Data Scientist at Annex Clinical Corporation.