Transforming Diabetes Care with AI-Powered Patient Identification

A leading pharmaceutical company faced a serious challenge in expanding access to its CD3-directed monoclonal antibody (mAB) therapy for Type 1 Diabetes (T1D). Many high-risk patients remained undiagnosed due to the lack of widespread screening for asymptomatic Stage 2 T1D. Without early intervention, these patients progressed to Stage 3, missing the opportunity for preventive treatment and limiting the commercial impact of the therapy.

Axtria leveraged advanced machine learning and AI-driven predictive modeling to identify at-risk individuals before symptoms appeared. By integrating traditional machine learning techniques with a deep neural network BERT model, Axtria analyzed real-world medical data to enhance patient identification. This approach enabled healthcare providers to focus education, screening, and treatment efforts on those who would benefit most.

The impact was significant - a 350% increase in identifying at-risk patients, expanding the potential market for the client’s therapy. This breakthrough improved patient outcomes, optimized resource allocation, strengthened payer engagement, and increased commercial success.

Download the case study to learn how Axtria’s AI-driven approach is transforming patient identification and market access.

Contact us at connect@axtria.com with any questions.