9Exchange partners with PhaseV to give its members new opportunities to progress unwanted drugs

By Liza Laws

- Last updated on GMT

© Getty Images
© Getty Images

Related tags Partnership Drug development Drug discovery Research machine learning Artificial intelligence platform

Israeli biopharma marketplace, 9Exchange, has partnered with PhaseV a causal machine learning (ML) company, it was announced yesterday (November 6).

The move is a bid to release drugs from owners unable or unlikely to pursue them further while adding access to PhaseV’s technology adding more ML-powered clinical trial optimization technology to its ecosystem members.

With access to PhaseV’s ML technology, members-only platform 9xchange said pharma, biotech, investors, entrepreneurs, and select academic centers will be able to retrospectively ‘analyze and optimally design and execute advanced clinical trials’.

This announcement follows a recent partnership between 9xchange and BenevolentAI (Euronext Amsterdam: BAI), an AI-enabled drug discovery and development company, using BenevolentAI’s technology to support decision-making related to indication expansion and drug repurposing for assets within the 9xchange platform.

Anat Naschitz, CEO and co-founder at 9xchange said: “Too many deserving drugs never get to patients due to insufficient resource or attention, or objective issues such as suboptimal trial design.

“The seamless, online, and initially anonymous transaction path offered by 9xchange removes friction and unveils unexpected availability and matches while enabling members to tap into new value through a range of AI/ML technologies.”

“For our members, the PhaseV partnership means new opportunities. Owners can chart a new course for assets lost to trial failure, increase the value at sale, and build confidence in a likely outcome.

“Buyers and investors can conduct due diligence on an asset and circumscribe the cost and probability of success. We build partnerships carefully, and are excited to collaborate with PhaseV, whose team and technology we find very impressive.”

PhaseV says its platform offers two distinct service lines for AI clinical trial optimization. The first includes revealing the potential impact of adaptive trial design on the proposed study, followed by optimal trial design and execution.

The second involves advanced retrospective analysis that enables the detection of hidden signals in clinical trial data and evaluates endpoints and subpopulations that will result in a successful next trial. Using a wide range of parameters, this multifaceted approach, it says, has also shown significant value in drug repurposing efforts.

The company said its approach has shown positive results in a variety of therapeutic areas including oncology, endocrinology, autoimmune diseases, rare diseases, and more.

“The latest advancements in causal inference and ML, when used right, enable us to harness available data to make informed and optimal decisions in the clinical development stage.

“One of the benefits of the 9xchange platform is that it helps liberate assets from owners who are unlikely to pursue them further while providing access to the right technologies to unlock the potential of such assets and support the optimal trial to ensure their success,” said Raviv Pryluk, CEO and co-founder of PhaseV.

“We value our partnership with 9xchange, which will bring our novel and proprietary technology and methods to more biopharma innovators looking to uncover the real value of available assets and allow the successful development of new, much-needed treatments that otherwise might be left behind.”

With the power of advanced causal inference and pushing the boundaries of machine learning, PhaseV's mission as a company is to detect hidden signals in clinical data and extract actionable insights for planning the optimal next steps.

The company says its technology enables optimal design and closed-loop execution of adaptive clinical trials, increasing efficiency and success rates.

9xchange releases biopharma assets from owners who are unlikely to develop them, then it aims to progress potential drugs towards transactions through a seamless, online platform while deploying AI/ML technologies to augment their value by adding indications, correcting trial paths, and more.

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