PhaseV to push boundaries of machine learning with $15 million funding

By Liza Laws

- Last updated on GMT

© Getty Images
© Getty Images

Related tags funding Investment machine learning Research Clinical trial optimization

Advanced tech company, PhaseV, has raised $15 million in funding that it says it will use to ‘push the boundaries of machine learning for clinical trial optimization’.

The company uses causal machine learning (ML) technology that optimizes clinical trial design and analysis – its funding round was led by Viola Ventures and Exor Ventures and included participation from LionBird and a group of prominent angel investors.

Causal ML tries to identify the causes underlying the data and can be a technique to increase the personalization of our users.

A recent Deloitte study​ estimates the average cost of developing a single new drug at $2.3 billion in 2022, with an average 7.1 year deployment time. Moreover, most drug candidates do not reach the finish line, and many fail the clinical phase even though the biology works.

PhaseV said it tackles this challenge by using its ML technology providing clinical development teams an advanced ability to retrospectively analyze and optimally design studies, as well as adapt in real-time throughout the trial.

PhaseV said this ML-driven adaptive process has the ability to significantly accelerate the clinical drug development process and increase certainty along the way, resulting in more efficient, targeted, and ultimately more successful clinical trials.

Costly drug development

“Clinical trials are the most time-consuming and costly stages of drug development, and many trials fail due to inherent uncertainties and complexities in trial design and execution,” said Noam Ohana, managing director at Exor Ventures.

“PhaseV has demonstrated its technological prowess and commitment to reshaping the landscape of clinical trial design and analysis to ensure that promising drugs reach their full potential.”

PhaseV offers two distinct service lines for AI clinical trial optimization. The first includes assessing the potential impact of adaptive trial design on the proposed study, followed by optimal design and execution. The second involves retrospective analysis that detects hidden signals in clinical trial data and evaluates endpoints and subpopulations to redefine success or failure of a trial.

Raviv Pryluk, CEO and co-founder of PhaseV, said: “Our platform excels at uncovering 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.”

“This investment provides us with the resources to further advance our platform and expand our reach to additional pharma, CRO and biotech companies in Europe and the U.S., bringing new needed treatments to patients.”

Multifaceted approach

Using a wide range of parameters, the company says the multifaceted approach is also valuable for drug repurposing efforts. The company's approach has proven valuable in a variety of therapeutic areas including oncology, endocrinology, autoimmune diseases, rare diseases and more.

Oramed Pharmaceuticals Inc., a protein oral drug platform, is one company that has utilized PhaseV's retrospective services.

"PhaseV played a vital role in the analysis of our Phase 3 trial in the US, ORA-D-013-1, for the treatment of type 2 diabetes. The analysis found subpopulations of patients that responded very well to oral insulin,” said Miriam Kidron, CSO at Oramed.

“Over the last decade, new technologies have disrupted the way drugs are discovered, but unfortunately the drug development and clinical trial process has largely lagged behind,” said Zvika Orron, general partner at Viola Ventures.

“With precision medicine widely acknowledged as the next frontier, drug development stands to gain tremendously from personalized technology capabilities that have proven successful in other industries. We are excited by the promise of PhaseV, combining advanced algorithmic capabilities with drug development expertise to facilitate an important change in the pharma and biotech industries.” 

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