NeuroSense and PhaseV partner to optimise ALS Phase III trial using causal machine learning

Published: 15-May-2024

PhaseV's causal machine learning predicts high probability of success in multiple ALS subgroups for NeuroSense's Phase II trial

NeuroSense Therapeutics,  a company developing novel treatments for severe neurodegenerative diseases, has partnered with PhaseV, a company specialising in causal machine learning (ML) for clinical trial analysis and optimisation, with respect to the planned Phase III trial of PrimeC as a treatment for amyotrophic lateral sclerosis (ALS).


Utilising causal ML to enhance the clinical trial process

As part of the collaboration, PhaseV conducted an independent analysis of NeuroSense's PARADIGM Phase IIb study using a causal ML and predicts a high probability of success in multiple subgroups for the planned Phase III trial of PrimeC as a treatment for ALS.  The external results provide important insights that will significantly inform study design, patient enrollment and ensure cost-effectiveness.

"There remains a critical need for new approaches to address this neurodegenerative disease," said Alon Ben-Noon, CEO of NeuroSense. "Our recently announced subgroup analysis from the PARADIGM study is very encouraging and suggests the potential of PrimeC to change this reality. Through our initial collaboration with PhaseV, we gained an even greater understanding of the effect of PrimeC across multiple patient subgroups. We will apply these insights to optimise the design of our Phase III study with the aim of maximising meaningful clinical results that will differentiate PrimeC in the market."

"Although there is an improved understanding of the underlying mechanisms of ALS, therapeutic options remain limited due to the complexity and heterogeneity of the disease," said Dr Raviv Pryluk, CEO and Co-founder of PhaseV. "NeuroSense's ALS drug candidate PrimeC showed great promise in its Phase IIb study. Through a unique combination of causal-ML, real-world data and advanced statistical methods, we confirmed the potential clinical benefit of PrimeC and provided actionable insights for the Phase III study. Our analysis predicted a high rate of success for PrimeC in the Phase III clinical trial for multiple recommended subgroups."      


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