With the 14th annual DPHARM® wrapping up, we talked to our peers across the industry to find out what the big themes and takeaways were from this year’s conference.
Medable showcases Studio to a live audience, building an eCOA solution in minutes
Andrew Mackinnon, Executive GM of Customer Value, demonstrated to the crowd how Studio enables users to build custom eCOA assessments, instruments, and diaries using a simple drag-and-drop interface in minutes. This simplicity in ease of use starkly contrasts the traditional way of building COAs, which requires programmers to code them and several back-and-forth rounds of reviews.
The crowd was impressed with Studio's instant edit and preview functionality, which Mackinnon showcased by editing translations in real time.
"Impressive in how quickly you can deploy,” stated one Head of Business Performance & Analytics.
“The real-time previews is what stood out to me the most,” a Senior Director of Strategy stated.
More than a builder, Medable Studio delivers unprecedented control over the study creation and launch process, freeing users from the roadblocks associated with study startup.
Andrew Mackinnon showcases Medable Studio to the DPHARM crowdArtificial intelligence continues to gain traction across our industry
With two tracks dedicated to artificial intelligence (AI) in clinical trials, DPHARM 24 proved that AI uptake in research will only continue as its capabilities mature.
Multiple sponsors and vendors such as Amgen, Merck, Regeneron, Johnson and Johnson, and more discussed how they are using AI today and showed potential use cases for the technology in the near future.
On Wednesday, Tufts CSDD announced they would release an updated report on AI adoption in clinical trials. Speaking on the report, Mary Jo Lamberti, Research Associate Professor and Director of Sponsored Research at Tufts CSDD stated that "AI adoption has matured since our earlier study, and we will examine which approaches are most effective and impactful within clinical development."
Some of the highlights included sponsors using AI to drive site selection, author clinical protocols, optimize protocols, better find patients for recruitment, and generate documents like training materials and informed consent documents.
For instance, Amgen is leveraging advanced platforms such as ATOMIC (an internal platform built by Amgen) to revolutionize patient recruitment and trial site selection, potentially slashing years off drug development timelines. By harnessing the power of machine learning to analyze vast troves of unstructured medical data, Amgen believes it can streamline trial processes, enhance patient engagement, and foster more diverse and representative study cohorts.
One clinical trial vendor highlighted how teams are witnessing a staggering 85% reduction in the effort required to produce initial drafts by leveraging AI-assisted generation. This dramatic efficiency boost allows professionals to redirect their focus to the sections requiring expertise and attention.
Digital and DCT trial elements continue to prove their ROI
In his keynote speech, Kenneth Getz, MBA, Executive Director of Tufts CSDD, kicked off the conference by presenting the return on investment that decentralized clinical trials and digital trials provide. The initial Tufts CSDD report showcased ROI of 5x for Phase II trials and 13x for Phase III trials. As Getz notes, ROI “an extremely important way that we persuade and ultimately drive adoption.” Going forward, the PACT Consortium, a group of companies including Medable, are working to update the research by “scaling the data set and conducting much more granular analysis.”
Throughout the conference, organizations presented on how eCOA, ePRO, televisit, and more are making game-changing differences in how we conduct clinical research, with almost one-third of all topics touching on the importance and effectiveness of digital and DCT elements.
Technology will be vital in helping sponsors address the FDA’s DEI requirements
With an entire DPHARM track dedicated to diversity, equity, and inclusion (DEI), multiple companies showcased how they’ll use new trial technologies to help facilitate the FDA’s newest guidance.
Companies like Gilead are deploying machine learning models to predict patient enrollment diversity at clinical sites with unprecedented accuracy. These AI-driven approaches surpass traditional demographic data, leveraging diverse data sources to enhance site selection and quantify critical factors influencing site diversity.
Merck is pioneering risk-based quality management (RBQM) tools to track progress on diversity action plans, enabling targeted messaging and sophisticated visibility into DEI goals. The company recently announced that it’d partnered with Acclinate, using its e-DICT (Enhanced Diversity in Clinical Trials) platform, which “provides real-time reporting on community access and engagement activities and insights into potential participants.” Meanwhile, AbbVie is utilizing data analytics to assess clinical researchers, demonstrating their positive effect on research inclusivity.
Through predictive modeling, tailored outreach strategies, and culturally competent engagement initiatives, these technological advancements are fostering trust and increasing the willingness of diverse communities to participate in clinical trials, ultimately driving better DEI outcomes in pharmaceutical research.
