PhaseV to Present at Upcoming Clinical Trial Events and Scientific Meetings, Highlighting the Value of Machine Learning in Drug Development

PhaseV announced today that company executives will present at five upcoming leading industry events in May and June.

Presentations and Case Studies Showcase Success of Causal ML-Based Technology for Planning and Executing Adaptive Trials for Lupus, Diabetes, and other Clinical Indications

BOSTON, April 8, 2024 /PRNewswire/ -- PhaseV, a pioneer in causal machine learning (ML) for clinical trial analysis and optimization, announced today that company executives will present at five upcoming leading industry events in May and June.

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“Machine learning is becoming an essential tool for data-driven decision-making in drug development,” said Dr. Raviv Pryluk, CEO and Co-founder of PhaseV. “We are proud to have been accepted to present and chair sessions on the use of advanced ML in clinical trials, and to see the rapidly growing interest in the field. Our presentations will demonstrate the tangible impact of our technology for ensuring significantly more precise and efficient clinical trials.”

PhaseV executives, partners and industry leaders will present at the following events:

  • Society for Clinical Trials 45th Annual Meeting
    Date: May 19-22, 2024
    City: Boston, MA
    Presentation: Case Study: Use of an Interactive Adaptive-Trial AI Simulation Tool to Increase Efficiency and Promote Informed Decision-Making Within Clinical Trial Teams
  • Fiscal Year 2024 Generic Drug Science and Research Initiatives Public Workshop
    Date: May 20-21, 2024
    City: FDA White Oak Campus, MD
    Presentation: Integrating AI/ML Tools with Regulatory Information and Data
  • EULAR 2024 Congress
    Date: June 12-15, 2024
    City: Vienna, Austria
    Presentation: Case Study on Use of Proprietary ML-Based Technology for Optimizing Adaptive Trials for Lupus
  • DIA 2024 Global Annual Meeting
    Date: June 16-20, 2024
    City: San Diego, CA
    Chairing Sessions:
    - Machine Learning and Simulations to Facilitate Clinical Trials
    - Recruitment Optimization in Clinical Trials: Looking Towards an Adaptive Future
  • American Diabetes Association 84th Scientific Sessions
    Date: June 21-24, 2024
    City: Orlando, FL
    Presentation: Abstract by Oramed Pharmaceuticals and PhaseV on Machine Learning-Based Optimization of Patient Eligibility for Oral Insulin Treatment: A Post Hoc Analysis of Phase III Trial Results

PhaseV’s platform leverages proprietary causal inference and machine learning tools to enable retrospective analysis of Phase 2 and Phase 3 trials to ‘rescue’ failed assets and/or optimize an analysis in order to better prepare for the next trial. The platform also enables prospective design and execution of dynamic adaptive clinical trials by allowing users to quickly evaluate millions of options—taking specific considerations and constraints into account—and select the optimal choice. This ML-driven adaptive process can significantly accelerate the clinical drug development process and increase certainty along the way, resulting in more efficient, targeted, and ultimately more successful clinical trials.

PhaseV’s solutions are used by global pharma companies, biotech innovators, and CROs across a wide range of therapeutic indications, including oncology, endocrinology, autoimmune diseases, rare diseases, and more.

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:
FINN Partners for PhaseV
Aviva Sapir
aviva.sapir@finnpartners.com
929-588-2014

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SOURCE PhaseV

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