COURSE
Life Sciences and Pharmaceuticals: Advanced Analytics and Insights
INR 59
Description
Develops expertise in leveraging data science, AI/ML, and advanced analytics for clinical, commercial, supply chain, quality, and patient applications in pharma IT.
Learning Objectives
Learners will deploy analytics for actionable business/clinical insights, improve decision-making, and drive digital transformation.
Topics (8)
1
Advanced Analytics Lifecycles for Pharma
Project framing, pipelines, model governance, value dashboards.
2
AI/ML and Predictive Modeling in R&D and Clinical
Predictive algorithms, deep learning, molecular modeling.
3
Real World Data Analytics and Digital Twins
Data lakes, digital twin build, RWD integration.
4
Personalized Medicine and Data-Driven Patient Engagement
Segmentation, engagement tracking, smart triggers.
5
Supply Chain and Quality Analytics
Quality signal detection, demand forecasting, scorecards.
6
Visual Storytelling and Business Insight Reporting
Visualization libraries, dashboard UX, narrative storytelling.
7
Performance Measurement and Value Tracking
Program KPIs, performance heatmaps, executive reporting.
8
Next-Gen Analytics Governance and Data Ops
Model validation, audit, compliance automation.