“Biogen is constantly striving to build a future in which multidimensional data will be used to improve the characterization of the disease and the monitoring of its progression and to predict the therapeutic response at the individual level. The data presented this year at Ectrims outline the progress made in our research activity in the field of digital health and emphasize the extent of innovations in the development of advanced measurement methods, aimed at facilitating the development of personalized drugs and treatments, to improve patient outcomes. ” Shibeshih Belachew, Md, Ph.D., Head of Science at Biogen Digital Healthcomments on the presentation of new data relating to the measurement and advanced analysis systems of Multiple Sclerosis (Sm), which took place at the 38th congress of the European Committee for the Treatment and Research in Multiple Sclerosis (Ectrims), which took place in Amsterdam from 26 to 28 October 2022.
The multiple presentations seen at the Ectrims congress – reads a note – highlight the potential of technology to offer new ways of measuring disease through the technological tools of digital health. The first is dedicated to new measurements that can be obtained thanks to the application of technology in relation to the nine-pin test called Manual dexterity test (MDT) and conducted on 3,525 patients for a total of 44,394 MDT observations. The results suggest that the overall time taken to complete the MDT test is a reliable parameter that can be correlated with changes in the progression of disability and quality of life in people with multiple sclerosis; a new parameter – the speed in the MDT test – offers better predictive models for disease progression with respect to the overall time to complete MDT.
Three presentations at Ectrims illustrated the most recent research resulting from Biogen’s collaboration with TheraPanacea, aimed at developing computer-assisted diagnosis software solutions with the aim of accelerating drug development and developing more effective treatments using machine learning, artificial intelligence and radiomics. A presentation demonstrates that the machine learning and the radiomics they allow to extrapolate more in-depth information on the heterogeneity found in lesions caused by MS than is currently possible with a traditional reading. Almost 2,400 MRI scans acquired in Phase III Advance and Ascend clinical trials were retrospectively analyzed, identifying clusters of acute SM lesions with well-defined spatial, geometric and structural patterns. Two other presentations are dedicated to improvement of the technical capabilities of conventional magnetic resonance through innovative algorithms based on Ml-Ai for the segmentation of lesions typical of Sm.
The ability to predict with greater precision the response of individuals to a treatment – concludes the note – is necessary for the progress of personalized therapies and for better outcomes in people with multiple sclerosis. One of the presentations at the congress illustrated real-world data-based analyzes of 1,600 patients included in the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS Paths) network. The researchers were able to replicate the results of the two-stage precision medicine models already present in the literature and applied to the data acquired in clinical studies, validating this analytical methodology through the use of real-world data. The use of two-stage precision medicine models could offer a framework for predicting and choosing specific treatments in clinical practice based on the stage of disease in each patient.
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