A vast majority of researchers and specialized tech startup companies have started investing in developing Big Data and Artificial Intelligence (AI) tools to serve the pharmaceutical and medical devices companies, which is believed to transform the clinical trial process. But what exactly is the main outcome of AI?
The buzz around AI in clinical trials is due to its potential as the lynchpin for dramatically improving the probability of success and reducing the timelines.
How does AI really increase Clinical Trial Success Rates?
The answer lies in predictive analysis from available historical data. The main idea of the AI revolution is to bring about “efficient and faster decision making,” provide precision in clinical trials and to bring an effective product from the lab-to-market. The average timeline for a drug molecule to be released from lab-to-market is 9 years with a median development cost of $2 billion. The objective of AI implementation is to eliminate unnecessary repeated clinical evaluations, save costs & time and thereby ensure successful clinical trials.
AI based Clinical Trial transformation process can be divided into three main components: