- Biotech think tank expects technologies to optimize patient screening, clinical trials
Artificial intelligence such as rote learning is expected to boost success rates in clinical trials.
The Research Institute for Biological Science and Technology recently said in a report that “machine learning and Robotics Processes Automation(RPA) will optimize clinical trials in the future."
Processing new information and RPAs that were once a responsibility for humans are now being applied to clinical trials. Automated selections of appropriate patient groups for clinical trials will lower the costs and efficiently manage scheduling.
"Inappropriate selection of patients for the clinical trials is one of the main causes of failure. How many patients should participate for a clinical trial is a key factor determining the success of the study," the research institute said in the report. “A delay in clinical recruitment leads to a delay of
It is estimated that demand will rise for AI technologies to process the complex data from the beginning of the research to the end. In particular, machine learning and RPA could increase the likelihood of clinical engagement and increase the probability of success, by picking the right patient groups and increasing patient recruitment rates.
Machine learning and RPA can be applied to processes of clinical trials such as patient matching, site selection, analyzing competitive products and environment and cost control.
"Clinical trials are complex, full of technical issues, business and other factors. The pharmaceutical industry needs a learning model to improve clinical efficiency," the research institute said. “We will increase the rate of clinical success by applying machines and RPAs to optimize these processes."