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#FutureReadyHealthcare
Japanese biopharma implements AI/ML on RWD to predict chronic kidney disease diagnosis and prognosis​
Challenges
Need to leverage real-world data, in predicting diagnosis, and disease progression in chronic kidney disease (CKD) patients​
Lack of a standardized process for data management, cleaning, analysis, reporting, and visualization​
The Solution
Indegene’s team of subject matter experts (SMEs) helped establish risk predictors, diagnosis, disease stages, and progression for CKD. The research included a comprehensive literature review across credible sources such as PubMed, KIDGO, and National Kidney Foundation. A statistical analysis plan (SAP), and a standard operating procedure (SOP) were set up for management, cleaning, analysis, reporting, and visualization of the real-world data (RWD). Data analytics and AI/ML predictive models were created to arrive at baseline profiles, disease landscape, and risk segmentation
Outcomes
Indegene helped the client implement AI/ML technologies on RWD, to curate, statistically analyze, and predict CKD diagnosis and progression in patients. Using the SOP, client was able to standardize processes and achieve operational efficiencies around data management.
