PhaseV Unveils Innovative AI/ML Solutions for Clinical Trials at CMO Summit 360⁰

PhaseV to Showcase Innovative AI/ML Solutions at CMO Summit 360⁰



PhaseV, a pioneering company in AI and machine learning for clinical development, is set to reveal its latest advancements in clinical trial design and analysis at the upcoming CMO Summit 360⁰ in Boston, Massachusetts. This event, held from April 7-8, 2025, will provide an excellent platform for PhaseV to demonstrate how its technology could revolutionize the clinical trial process.

At this year’s summit, PhaseV will introduce its new capabilities that leverage causal machine learning to enhance clinical trial design, enabling clinical leaders—such as Chief Medical Officers (CMOs) and biostatisticians—to merge insights from historical trials with real-world data seamlessly. Traditionally, trial design and execution have been siloed processes, but PhaseV's innovative platform bridges this gap, allowing clinical teams to work in a more integrated manner.

Dr. Raviv Pryluk, CEO and Co-Founder of PhaseV, states, “For the first time, clinical teams can leverage causal ML-driven insights from prior trials and real-world data to inform the design of future trials, all within a single end-to-end multi-modal platform. This enables real-time evaluation of various parameters, significantly enhancing the likelihood of trial success.”

This breakthrough approach means that biotech and pharmaceutical companies can not only reduce trial failure rates but also maximize their investments in trials, ultimately leading to improved outcomes for patients.

One of the key features highlighted by PhaseV is the Causal to Adaptive capability, which combines real-world and clinical trial data to streamline planning and decision-making in future clinical trials. Another notable feature is the Clinical Trial Success Prediction tool. This innovative mechanism allows trial sponsors to calculate the probability of success by analyzing past trial data, specific trial parameters, and existing real-world evidence. By employing PhaseV’s proprietary statistical and AI methodologies, this tool generates a probability score to support informed decision-making, which in turn helps to mitigate failure rates and enhance patient outcomes.

Brad Carlin, Senior Director of Data Science and Statistics at PhaseV, highlights the uniqueness of this integration, saying, “Integrating causal ML and AI capabilities with Bayesian adaptive tools is significantly more advanced than existing solutions currently available on the market. Our platform is a true game-changer for the industry.”

Attendees at the CMO Summit 360⁰ in Boston will have the opportunity to participate in live demonstrations of both the Causal to Adaptive and the Clinical Trial Success Prediction capabilities at Booth #11. This breakdown of advanced systems will showcase how they can be implemented in real-world situations, providing invaluable insights to clinical leaders within the industry.

PhaseV has already made significant waves in the clinical development sphere, credited with reducing trial costs by 25%, shortening enrollment sizes and durations by as much as 40%, and enhancing the likelihood of clinical trial success by 30%. To date, its platform has generated impressive results for over 30 leading biotech and pharmaceutical entities across various therapeutic areas such as oncology, neurology, immunology, and rare diseases.

For those looking to learn more or to schedule a meeting with PhaseV representatives during the conference, detailed inquiries can be directed to [email protected].

In summary, PhaseV’s commitment to developing advanced AI/ML solutions signifies a monumental shift in how clinical trials can operate, with the potential to dramatically improve the landscape of clinical research. By harnessing the power of causal machine learning and integrating it with traditional methodologies, PhaseV not only paves the way for more effective clinical trials but also opens doors to better treatments and health outcomes for patients worldwide.

Topics Health)

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