Shots:  

• Raviv Pryluk, CEO and Co-Founder of PhaseV, in a stimulating conversation with PharmaShots, sheds light on the company’s recent partnership with 9xchange Biopharma   

• The partnership aims to bring Phase V’s proprietary machine learning (ML) technology to ecosystem members, enabling them, to retrospectively analyze and optimally design and execute advanced clinical studies  

• Raviv highlights the importance of machine learning in clinical trial optimization and significantly reducing cost and time  

Saurabh: Congratulations on your partnership with 9xchange Biopharma. Can we first talk about the details of the collaboration? 

Raviv: The partnership with 9xchange is part of our long-term strategy to collaborate with leading platforms and organizations that are working to advance data-driven decision-making in drug development. 

9xchange is an active marketplace that enables interaction and transactions between pharma, biotech, investors, academic centers, entrepreneurs, and technology providers. 

This partnership brings our proprietary machine learning (ML) technology to ecosystem members, enabling them to retrospectively analyze and optimally design and execute advanced clinical studies. 

Saurabh: How do you think the partnership with 9xchange biopharma marketplace help/ support PhaseV in optimizing ML-Powered Clinical Trial Technology for Ecosystem Members? Please tell us about the strategy behind this collaboration. 

Raviv: This collaboration supports our core vision of enabling clinical trial sponsors to not only effectively leverage their own data, but also access our expanded data, expertise, and unique tools in order to design and conduct the right trial to succeed.  
By combining the 9xchange marketplace for drug assets with our causal ML solution, retrospective analysis and prospective optimal design, we can significantly increase the return on investment (ROI) for both sellers and buyers of drug assets in the marketplace. It is a win-win collaboration. 
Saurabh: What are the services offered by PhaseV? 

Raviv: PhaseV offers two main services: 

The first service is retrospective analysis of Phase 2 and Phase 3 trials in order to either 'rescue' failed assets or to optimize the analysis to better prepare for the next trial. Our proprietary technology leverages tools at the intersection of causal inference and machine learning. It has proven to be accurate and robust in identifying the right subgroup of patients and dramatically increasing the probability that successful results will replicate in the next trial. 

The second service is for prospective design and execution of dynamic, innovative and adaptive clinical trials. Our platform allows users to quickly evaluate millions of options, helping them to select the optimal choice while considering their unique considerations and constraints. The platform then supports set up of the trial and ongoing adaptation to dramatically increase efficiency and effectiveness utilizing previously established regulatory frameworks. 

Saurabh: PhaseV raised $15M in Oct 2023 to upgrade Machine learning for Clinical Trial Optimization. How do you plan to utilize these funds?  

Raviv: First and foremost, we are using the majority of the funds to improve the technology, ensuring that sponsors receive the most accurate, robust, and reliable insights and results. Secondly, we are expanding our business teams, mainly in the U.S. and Europe. 
Saurabh: As you said clinical trials are costly & time-consuming stages of drug development so, please explain how Machine learning for Clinical Trial Optimization helps companies cut down the cost & time of the drug development process.  

Raviv: Machine learning can be used to help streamline costs and timelines in clinical trials in several ways. 

One approach is the concept of "failing fast," emphasizing the importance of stopping trials at the earliest indication of non-responsive biology.  

Another critical factor is the selection of the appropriate dose, drug regime, or combination, which can significantly boost the probability of trial success.  
Additionally, achieving success hinges on identifying the precise subset of patients, underscoring the significance of precision medicine. The implementation with the right subset should already start in Phase 2 trials. 

Saurabh: From the above-explained applications, which features are being offered by PhaseV ? 

Raviv: Our adaptive trials platform and Causal-ML retrospective services can help achieve all of the above. Our technology uncovers hidden signals in clinical and real-world data, enabling us to analyze a multitude of covariates using causal-ML to evaluate the most advantageous next steps and decisions in the clinical development process. To that end, we provide a range of tools and features that help biostatisticians and trial teams understand all options so they can make joint optimal decisions at any point during the trial. 

Saurabh: Recently "Oramed Pharmaceuticals" used your “retrospective service” for the P-III clinical study evaluating ORA-D-013-1 to treat type 2 diabetes. What were the problems solved by PhaseV?  

Raviv: In short, one of the reasons the original study failed was because the treatment's effectiveness was not observed across the entire population. 
PhaseV applied our causal-ML pipeline for retrospective analysis and discovered a substantial subgroup of patients who responded well to the treatment. This group was statistically significant, clinically relevant and business viable, allowing the company to focus on the subset of patients. They are now planning additional Phase-3 trials. 

Saurabh: Are there any more collaborations similar to Oramed ongoing? Where pharma companies are using PhaseV’s services?  

Raviv: We have many partnerships at various stages and are receiving significant interest from sponsors who want to better understand how our tools help increase trial success rates and reduce costs and time-to-market.  

We work with companies across the world in a variety of therapeutic areas including oncology, endocrinology, autoimmune diseases, rare diseases, and more. PhaseV is proud to support all of these important sponsors, including pharma companies, biotech innovators, and CROs, on the journey to bring new drugs to patients who need them the most.  

Image Source: Canva 

About the Author: 

Raviv Pryluk 

B.Sc. and M.Sc. in engineering from the Technion (Cum Laude) and Ph.D. in computational neuroscience from the Weizmann Institute (Magna Cum Laude, John F. Kennedy Prize). Raviv was a technological leader and commander in the IDF, and in his last role was head of a technological branch (LtCol), and won a number of prestigious awards. In 2021 Raviv decided to transition into the healthcare industry and joined Immunai where he was the SVP of Operations and Analytics. In his spare time, Raviv loves running long distances and has completed a few full marathons and triathlons. 

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