A crucial part of setting up a clinical trial is establishing various controlled groups to determine a drug’s efficacy. The process is quite sensitive and has many built-in safety practices. An AI-powered solution can help ensure that patient safety data is more accurate and has the ability to warn medical monitors of potential adverse events or risk.
While medical monitors evaluate all processes and ensure patient safety, they could use some help in sifting through data and identifying patterns not immediately visible to the human eye. An AI-powered solution can perform a deep dive into any data system, harmonize it to adhere to the Industry standards – Study Data Tabulation Model (SDTM) – and then extract insights quickly and accurately. These insights may have been otherwise unidentifiable, and even if a group of analysts had been able to draw the same conclusions, they would not have been able to do so as quickly.
LSAC can ensure protocol adherence, keep data records standardized and free of error, monitor inclusion/exclusion criteria, keep a constant check on all regulations, and generate near real-time analysis of data. With real-time insights at your fingertips, it is possible to have a comprehensive view of how a drug or treatment is performing across patient pools and sites on a global level. Since clinical data is standardized near-real time using a metadata based approach, it allows sponsors to standardize the clinical data management, review, and monitoring process. This approach enables the submission pathway to be faster and more efficient.
LSAC also offers a virtual assistant interface that provides access to results from the Drug Efficacy and Patient Safety Analytics capability. As a result, activities such as the review of clinical data, troubleshooting sites with a high number of adverse events, and performing patient-level safety analysis, become more accurate and efficient.