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      PhaseV to Present Novel Causal Machine Learning Method for Understanding Patient Treatment Response at ML4H Symposium

      PhaseV-logo (PRNewsfoto/9xchange,PhaseV)

      News provided by

      PhaseV

      Dec 12, 2024, 08:30 ET

      Share this article

      Share this article


      New Method, Applicable to Multiple Therapeutic Areas and Clinical Phases, Can Advance Precision Medicine for Improved Patient Outcomes

      BOSTON, Dec. 12, 2024 /PRNewswire/ -- PhaseV, a pioneer in software and machine learning (ML) for advanced clinical trial optimization, announced today it will present at the AHLI Machine Learning for Health (ML4H) 2024 Symposium, taking place on December 15-16 in Vancouver, Canada. The company has been selected to share a poster session on its novel method for identifying responders in clinical trials and observational studies. PhaseV will also demonstrate the power of its machine learning-driven platform to enhance adaptive clinical trial design in a demo presentation.

      Continue Reading
      PhaseV AdaptV Platfrom Demo: ML Optimization Capabilities
      PhaseV AdaptV Platfrom Demo: ML Optimization Capabilities

      The conference session, Identifying Responders in Randomized Controlled Trials and Observational Studies, will explore PhaseV's novel Causal Responder Detection (CARD) method. Published in a recent research paper, this approach uses advanced machine learning methods, specifically causal tree techniques, to identify individuals who respond to treatments, helping to increase accuracy and reduce false discovery in clinical trials. The method enhances understanding of individual treatment responses and supports the integration of precision medicine across various therapeutic areas and clinical phases to advance clinical development. (Session 2 on December 16, Location ID: 40 Review ID: 68.)

      "We are proud to present our latest findings in applying causal ML to clinical trial optimization," said Raviv Pryluk, PhD, Co-founder and CEO of PhaseV. "Our proprietary Causal Responder Detection method enhances the precision of trials, allowing researchers to develop treatments tailored to patients' individual needs. We remain committed to working with global pharma and biotech companies, using our technology to maximize resources while enabling more effective and personalized healthcare."

      PhaseV will also present a live demo titled Accelerating Adaptive Clinical Trial Design with Machine Learning-Enhanced Simulation Software. Attendees will be introduced to unique ML-optimization capabilities from the company's adaptive trial optimization platform. (Demo Session 1 on December 15, Location ID: D5, Review ID: Demo 9.)

      About PhaseV
      Leveraging the power of advanced causal inference and pushing the boundaries of ML, PhaseV detects hidden signals in clinical data and extracts actionable insights for planning the optimal next steps. The company's technology enables optimal design and closed-loop execution of adaptive clinical trials, increasing efficiency and success rates. PhaseV is advancing paradigm shifts in the clinical trial world in order to bring new treatments to more patients in a more precise and efficient way. Learn more at www.phaseVtrials.com and follow us on LinkedIn.

      Media Contact: 
      Ellie Hanson
      FINN Partners for PhaseV
      [email protected]
      929-588-2008

      Video: https://www.youtube.com/watch?v=emZXO7jP-s0
      Logo:  https://mma.prnewswire.com/media/2267452/5074889/PhaseV_logo.jpg

      SOURCE PhaseV

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