2022 - Leveraging AI to Improve the Financial, Operational and Scientific ROI of Clinical Research

Clinical research is a core component of academic medical centers’ identity and mission, but increasingly complex trial designs and staffing challenges make it difficult to deliver results while managing a budget. Highly targeted inclusion criteria require research teams to complete time-intensive chart reviews and use unreliable recruiting strategies, often to find that patients are not available or have already been enrolled on a competing trial. This leads to hidden costs borne by research sites for patient recruitment and ongoing study management, which often are not reimbursed by study sponsors. A single trial can cost $70,000 per year or more in unreimbursed expenses when recruitment isn’t moving forward.
By making full use of a wealth of unstructured patient data, which is typically hard to search through standard reporting processes, research sites can better manage their study portfolio by selecting the right trials and then finding patients faster.
Using artificial intelligence (AI) and natural language processing (NLP), sites increase the accuracy of feasibility checks up front, turning down studies where the patient population is too small. Better data means sites avoid failing or stalled trials and can put their resources to studies that will be able to gather sufficient data to push the research forward. Once a trial is open, sites can use precision-matching technology to quickly identify matching patients, speeding time to recruitment.
Join this webinar to understand the hidden costs of stalled trials and strategies to use technology to mitigate risk, increase efficiency and improve the return of investment (ROI) of clinical research operations.