{
  "id": 652614,
  "title": "AI brings savings to clinical trials: study",
  "url": "https://urgent.news/2026/08/12/ai-brings-savings-to-clinical-trials-study",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-12T09:40:06.000Z",
  "source": {
    "name": "Axios",
    "slug": "axios",
    "url": "https://www.axios.com/2026/08/12/ai-clinical-trials-cost-savings"
  },
  "original_language": "en",
  "account": "Artificial intelligence is not only hastening the early stages of drug discovery, but it is also beginning to unveil millions of dollars in operational efficiencies for clinical trials targeting cancer treatments, according to research initially shared with Axios. The significance lies in the potential for AI-powered tools to slash months off labor-intensive procedures such as patient recruitment and enrollment, result monitoring, and data interpretation. This could free up resources for more clinical studies and possibly reduce the high failure rate of new drugs. The findings come from a recent analysis by the Tufts Center for the Study of Drug Development, which revealed that AI agents can expedite the development of cancer drugs by roughly 10 weeks and cut direct operating costs by up to $5.6 million in late-stage trials. The benefits increase with the number of tumors the drug can treat; an experimental treatment with 50 active uses could yield net benefits of up to $565 million, as per Tufts. The analysis was conducted by applying a clinical monitoring agent from Medable, a platform supporting clinical trials, to an unspecified oncology drug development program in phase 2 and 3 trials. Ken Getz, executive director of the Tufts center, stated that deploying the agent led to new efficiencies, including a reduction in on-site visits, accelerated trial enrollment, and accurate data tracking. This marks the first time predictive modeling based on actual use and benchmark data has been utilized to quantify the net financial impact of an agentic AI solution in a drug development program, according to Getz. Industry experts anticipate AI agents could become commonplace in clinical trials within three to five years, functioning akin to self-driving cars by streamlining the time-consuming record-keeping associated with new drug approval applications. They also highlight the potential for tracking trial population diversity, a crucial concern to ensure experimental treatments work for the broader population. Medable officials assert that the technology will enable clinical trial researchers to grasp the safety and efficacy of a drug earlier, allowing them to concentrate on more strategic aspects of drug development. However, it's essential to note that AI alone cannot guarantee clinical trial success. Key challenges remain in patient identification, consent acquisition, drug distribution, and human verification of AI agent performance, which may diminish some of the time savings achieved through AI implementation.",
  "summary": "Artificial intelligence isn't just speeding up early-stage drug development, it's starting to unlock millions of dollars' worth of new efficiencies in clinical trials on cancer treatments, research shared first with Axios shows. Why it matters: AI-powered tools could shave months off time-consuming processes like recruiting and enrolling patients, monitoring results and interpreting data. That…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}