Galmed is Using AI to Conduct PSC Trials for Underserved Communities
References: galmedpharma & clinicaltrialsarena
Galmed Pharmaceuticals has entered a new partnership with OnKai to use artificial intelligence (AI) models to execute and include underserved communities in clinical trials. This project will begin with a Phase IIa trial, which will be conducted at Virginia Commonwealth University and will feature a detailed enrolment plan and five participation models. The first of the five models will be TrialBridge, a service that connects clinics with patients seeking specialists.
Galmed will also make use of OnKai's Smart-Grid AI Platform, which will continually support the trial at local clinics. About 15 PSC patients will participate in the experiment and receive therapy for 24 weeks. The trial will also assess histological fibrosis, molecular assessment, and biomarkers of disease and fibrosis.
Image Credit: Magic Mine
Galmed will also make use of OnKai's Smart-Grid AI Platform, which will continually support the trial at local clinics. About 15 PSC patients will participate in the experiment and receive therapy for 24 weeks. The trial will also assess histological fibrosis, molecular assessment, and biomarkers of disease and fibrosis.
Image Credit: Magic Mine
Trend Themes
1. AI-powered Clinical Trials - Opportunity for using AI models to improve the execution and inclusivity of clinical trials.
2. Underserved Community Outreach - Opportunity to reach and include underserved communities in clinical trial participation.
3. Patient-clinic Connection - Opportunity to connect clinics with patients seeking specialist care for better trial enrollment.
Industry Implications
1. Pharmaceuticals - Disruptive innovation opportunity to leverage AI models in clinical trials for improved drug development and patient outcomes.
2. Healthcare Technology - Opportunity to develop AI platforms that support clinical trials and assist clinics in patient enrollment and management.
3. Medical Research - Opportunity to use AI to enhance the assessment of disease markers and fibrosis in clinical trials, leading to more accurate results and insights.
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