A review article published today in Trends in Pharmacological Sciences examines how artificial intelligence (AI) could affect drug development in the coming decade.
Although AI has not yet had a significant impact on clinical trials, AI-based models are helping trial design, AI-based techniques are being used for patient recruitment, and AI-based monitoring systems aim to boost study adherence and decrease dropout rates.
"AI is not a magic bullet and is very much a work in progress, yet it holds much promise for the future of healthcare and drug development," says lead author Stefan Harrer, a researcher at IBM Research-Australia.
As part of the review and based on their research, Harrer and colleagues reported that AI can potentially boost the success rate of clinical trials by:
- Efficiently measuring biomarkers that reflect the effectiveness of the drug being tested
- Identifying and characterizing patient subpopulations best suited for specific drugs.
Start-ups, large corporations, regulatory bodies, and governments are all exploring and driving the use of AI for improving clinical trial design, Harrer says. "What we see at this point are predominantly early-stage, proof-of-concept, and feasibility pilot studies demonstrating the high potential of numerous AI techniques for improving the performance of clinical trials," Harrer says.
The authors also identify several areas showing the most real-world promise of AI for patients. For example:
- AI-enabled systems might allow patients more access to and control over their personal data.
- Coaching via AI-based apps could occur before and during trials.
- AI could monitor individual patients' adherence to protocols continuously in real time.
- AI techniques could help guide patients to trials of which they may not have been aware
In particular, Harrer says, the use of AI in precision-medicine approaches, such as applying technology to advance how efficiently and accurately professionals can diagnose, treat and manage neurological diseases, is promising. "AI can have a profound impact on improving patient monitoring before and during neurological trials," he says.
Because AI methods have only begun to be applied to clinical trials in the past 5 to 8 years, it will most likely be another several years in a typical 10- to 15-year drug-development cycle before AI's impact can be accurately assessed.