Axios – Artificial intelligence is not only accelerating the early stages of drug development, but is also starting to generate tangible savings in clinical trials for oncology treatments. According to research anticipated by Axios, AI-based tools could significantly reduce the time and costs of crucial activities such as patient recruitment, outcome monitoring, and data interpretation.
An analysis by the Tufts Center for the Study of Drug Development estimates that AI agents could shorten the clinical development of cancer drugs by approximately 10 weeks and cut up to $5.6 million in direct operating costs in late-stage trials. The economic benefits would also grow as the number of tumor types treated by the same drug increases: for a candidate with 50 possible active indications, the net benefit could reach up to $565 million.
The study applied a clinical monitoring agent developed by Medable, a company that provides a trial support platform, to an unspecified oncology program in Phases 2 and 3. According to Ken Getz, executive director of the Tufts Center, the use of the agent has generated efficiencies such as reduced in-person visits, accelerated participant enrollment, and faster data closure and validation.
According to Medable, within three to five years, these agents could become a standard component of some clinical trials, playing a role similar to that of semi-autonomous systems in managing the administrative and documentation tasks required for the approval of new drugs. They could also help monitor the diversity of the enrolled population, an aspect considered important for verifying the effectiveness of a treatment across a broad patient population.
The company also claims that the technology will allow researchers to understand the safety and efficacy of drugs earlier, allowing human efforts to be more focused on the strategic aspects of development. This would be particularly important in oncology trials, which are among the most complex and expensive to monitor.
However, one important limitation remains: AI does not guarantee the success of a trial. Many crucial challenges still involve identifying the right patients, obtaining consent, and manufacturing and distributing the drug. Furthermore, the work performed by the agents will likely need to be verified by humans, at least partially reducing the promised time savings.
AI brings savings to clinical trials: study
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