Neurophet Launches Joint Study with VHIR on ‘Neurophet AQUA MS’, Accelerating AI Algorithm Validation

Neurophet Launches Joint Study with VHIR on ‘Neurophet AQUA MS’, Accelerating AI Algorithm Validation

Neurophet Launches Joint Study with VHIR on ‘Neurophet AQUA MS’, Accelerating AI Algorithm Validation

https://www.prnewswire.com/news-releases/neurophet-launches-joint-study-with-vhir-on-neurophet-aqua-ms-accelerating-ai-algorithm-validation-302778771.html

Publish Date: 2026-05-26 09:00:00

Source Domain: www.prnewswire.com

  • Collaboration Announcement: Neurophet, an AI solution company, announced a joint research partnership with Vall d’Hebron Institut de Recerca (VHIR) to develop AI diagnostics for multiple sclerosis.
  • Focus on AI Algorithms: The collaboration aims to leverage large-scale clinical brain MRI datasets to develop AI algorithms that can detect key lesion biomarkers in multiple sclerosis.
  • Development of AQUA MS Software: Neurophet aims to use VHIR’s datasets to integrate and enhance its AQUA MS software, which is designed for analyzing brain images of multiple sclerosis patients.
  • Key Biomarker Detection: The project will focus on creating detection algorithms for the Central Vein Sign (CVS) and Paramagnetic Rim Lesions (PRL), which are important imaging biomarkers for multiple sclerosis.
  • Market Focus: The enhanced AI technology from Neurophet aims to establish a strategic foothold in the U.S. and European markets, where the prevalence of multiple sclerosis is higher.
  • Leveraging VHIR’s Expertise: VHIR will contribute de-identified MRI datasets and expertise, with Dr. Alex Rovira Cañellas leading this effort in enhancing the clinical reliability of Neurophet’s AI technology.
  • Product Background: Neurophet’s AQUA MS received FDA 510(k) clearance in October 2024 and is part of a suite of AI-driven products for brain disorder diagnosis and treatment solutions.
  • Strategic Focus: Neurophet, founded in 2016, is dedicated to developing AI solutions for brain disorders, emphasizing the importance of clinical data in enhancing the efficacy of its technologies.