US-based data software provider Phesi has announced a new free-of-charge service that aims to rescue at-risk trials, identify potential “zombie” studies, and help bring drugs to the market faster.

The Health Check and Trial Rescue Service will enable sponsors to submit their protocols to Phesi, which will provide real-time insights and forecasting. The company has said that it aims to provide feedback to sponsors within 10 working days.

According to Phesi, it is able to provide this trial rescue service as it leveraged by its artificial intelligence (AI)-driven Trial Accelerator Platform to assess protocols. It draws on Phesi’s data from 90,000 updated sources, including more than 4,000 indications and 70.8 million patients alongside methods and AI models created and validated over the past 15 years.

Phesi’s CEO Gen Li said: “Once a trial is underway, sponsors are often forced to amend the protocol to better align with the targeted patient population, often with millions of dollars on the line. We know around a fifth of trials designed today will fail and that many “zombie” trials continue to run, mostly caused by inadequate protocol design.”

Phesi estimates that the average protocol amendment costs around $500,000 and is likely to add on an additional 5.2 months of implementation time.

Phesi’s chief operating officer Jonathan Peachey added: “We’re launching this new service at the time of year when we know sponsors are considering budgets, reviewing what’s been successful over the past year, and creating their portfolios for 2024.”

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Peachey detailed how the service is intended for staff at multiple levels within the trial process, from heads of clinical operations to heads of portfolios. The service then aims to provide them with insights about the likely outcome of a trial as well as its indication or stage in the trial process.

Phesi is not the only company using digital systems as a tool to streamline clinical trials. Earlier this year, Clinical Trials Arena investigated the use of digital and AI tools in patient selection and enrolment. Whereas New York-based H1 suggests using AI to find the right principal investigators and sites.