PRADA innovation project to improve Arthritic treatment selections
Published:
A new project, PRADA (Precise Rheumatoid Arthritis Drug Assessment), is funded to by the Research Council of Norway, applying machine learning and molecular biomarkers to one of the biggest challenges in rheumatology: selecting the right treatment for the right patient.
Rheumatoid arthritis (RA) is a painful and disabling disease affecting between 1-1.5% of the global population. Finding the right medication is a major struggle, as the current approach is trial and error, with around 30% of patients intolerant to the current first-line treatment, and second-line treatments having insufficient effect on more than half of patients. The process of switching drugs due to side effects or lack of effect delays proper treatment and is expensive.
The PRADA project
PRADA aims to develop and validate a licensable diagnostic test for Rheumatoid Arthritis (RA) treatment selection, with a high-quality, standardised dataset to support future product development.
Recent research suggests that clues to the solution exist within our molecular biology, and how these markers are expressed (epigenetics), may help us determine what drugs are effective for each individual. By combining molecular data with advanced machine learning, PRADA seeks to move treatment selection away from trial-and-error and toward more precise, data-guided decisions.
Collaboration
Age Labs, a Norwegian life science company developing precision diagnostics, is project lead. Simula has an R&D partner role and will contribute to the development of a ML based approach for assessing the efficacy of rheumatoid arthritis drugs based on molecular biomarkers. The goal is to develop a validated test that can help patients get the right treatment faster. From Simula, the main contact is Omar Richardson.
Impact
This innovation effort addresses a significant clinical need within the field of rheumatology, that is reducing the quality of life for millions of patients living with RA. At the same time, it can reduce healthcare costs by limiting the use of ineffective and costly therapies and strengthen the Norwegian diagnostics industry through new collaborations.
Regarding the PRADA project, Omar commented,“This is an exciting application that shows how machine learning and AI have the potential to improve people’s physical lives. The human body is incredibly complex, and using data in the right way can help us make medical treatment both better and more resource-efficient.”