In this new whitepaper published by Medpace and Medidata, experts discuss the recent advances in artificial intelligence and machine learning as well as:
- Benefits for Medical Imaging in Clinical Trials
- Barriers to Uptake
- The Future of AI Imaging in Clinical Trials
- Finding the Right Solution
Why Leverage AI in a Clinical Trial
Boost Speed: AI allows automatic interpretation of images, such as the ability to quickly assess images against eligibility criteria for a trial. This can cut turnaround time from days to milliseconds and shave weeks or months off the timeline for patient enrollment.
Improve Quality: AI soon may be able to identify medically relevant findings, as well as poor quality medical images, helping radiologists avoid missed lesions, misclassifications and flawed measurements.
Ensure Consistency: Without AI, sponsors see up to 40% variability on different radiologists’ readings of scans, as well as significant variability in the same radiologist’s interpretation of the same scan on different occasions.
Medpace Core Labs
Medpace Core Labs is already a leader in the use of ML algorithms for medical imaging assessments in multiple areas, including detection of lesions and infarcts in brain scans, measurement of liver and spleen volume in metabolic disease, with the ability to review every slice of a specimen, scoring of liver biopsy specimens using the NASH Activity Score, and identification, classification and measurement of tumors.
The right solution and partner will save sponsors money; allow central reviewers to work more efficiently and provide better, more accurateresults; and enable sponsors to develop therapies faster for patients
who need them.