If you hadn’t already noticed, the clinical research enterprise has well and truly entered the era of “big data,” artificial intelligence (AI), and machine learning. One needs only to look at the industry press to see many recent examples of stakeholders making deals and rearranging assets in order to capitalize on what they hope will be breakthrough technologies and practices in terms of increasing efficiencies in drug and device research and development. At the same time, thought leaders in the field are endeavoring to ensure that real people—the ultimate beneficiaries of these rapidly evolving capabilities for clinical trial design and management—are not getting lost in the shuffle.

The forthcoming June issue of ACRP’s Clinical Researcher journal will feature submissions with a variety of perspectives on where these trends are taking us, and how research participants fit into the big picture. For example, in a special feature on “Personalization of Drug Development and the Transition to Precision Medicine,” Christian Olsen, Associate Vice President and Industry Principal of Biologics at Dotmatics, writes about how, “While the pharmaceutical industry has produced some incredible blockbuster medications, it has largely remained unremarkable at the individual patient level….” Olsen goes on to note that, in precision medicine, each patient’s treatment is personalized “using accurate diagnosis, a thorough understanding of disease mechanisms and treatment options, and a multitude of individual patient factors, such a patient’s genetic and metabolic makeup, lab and test results, and even environmental conditions, lifestyle, and treatment preferences. In other words, it’s about delivering ‘the right treatment to the right patient at the right time.’”

Among other topics, Olsen describes such elements of precision medicine as the growing development and use of biomarkers toward its goals; how data from wearable devices can help inform and monitor treatment choices, as well as influence preventative care measures; and the field’s expansion from oncology to “other treatment areas—including notoriously difficult-to-treat rare diseases—thanks to better access to and application of ‘big data,’ as well as increased accessibility of advanced technologies like genetic sequencing, artificial intelligence, and spatial genomics.”

“Undoubtedly, the expectations for precision medicine are high,” Olsen adds. “Many believe that in addition to improving individual patient outcomes, precision medicine holds promise to reduce overall treatment costs by eliminating ineffective or unnecessary medical care and by identifying high-risk patients who need early targeted care. …However, shifting paradigms to precision medicine will necessitate overcoming many challenges, including those related to technology and data integration; racial bias in genetic population data; privacy, cost, and accessibility concerns; and policy change, oversight, and adoption logistics.”

Elsewhere in the June issue, Londa Ritchey, MS, MBA, Quality Director with the Quality Management and Compliance group at PharmaLex, writes about how “Putting the Patient First is Integral to Building a Strong Quality Culture.” She notes that a strong quality culture “focuses on assessing patient safety in all aspects and decisions of the company, not just within the quality department. Patient safety should be paramount in all decisions, big and small.” Further, “[t]eam members across all levels of the organization should be capable of making decisions on patient safety or raising concerns about it,” she urges.

Meanwhile, in “Designing High-Impact Clinical Trials That Serve Patients, Clinical Centers, and Industry Sponsors,” Erin Leckrone, MFA, MBA, Senior Director of Clinical Trials at the CIBMTR^® (Center for International Blood and Marrow Transplant Research), writes about how “[a] collaborative approach to cell therapy clinical trial challenges pushes the boundaries of discovery and speeds life-saving treatments to patients. When organizations collaborate, sponsors can leverage unique expertise, unparalleled resources, and an established, stable infrastructure, including research, sites, donors, partnerships, and scientific and operational expertise. As a result, the time required to design, launch, and execute high-impact clinical trials is significantly reduced.”

Leckrone goes on to note how “[t]his collaboration can span the clinical trials continuum that starts with clinical trial design and management focused on the patient experience and ends with outcomes collection, research, and long-term follow-up. It also includes search and support services that help patients understand, find, and enroll in clinical trials.”

Going online on or near June 20, the new issue of Clinical Researcher will also include a peer-reviewed article by a trio of San Jose State University authors on “Forward Thinking for the Integration of AI into Clinical Trials” and columns on “Data-Driven Science: How Artificial Intelligence and Open Data Will Revolutionize Scientific Discovery,” “Going Beyond the Guidance: Getting Business Benefit from Change Management,” “Improving Access and Participation in Clinical Trials Using a Patient-Centered Digital Health Platform,” “How Sponsors Can Support Sites with Data Analytics,” “Focus Investigator Meetings to Make the Most of Decentralized Clinical Trials,” “How Social Determinants of Health Affect Clinical Trials and What eClinical Solutions Can Do to Help Level the Playing Field,” and more.

Edited by Gary Cramer

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• Source: https://acrpnet.org/2023/06/07/recognizing-the-real-people-behind-the-big-data-and-artificial-intelligence-in-clinical-research/