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Unify commercial, medical, clinical, regulatory, supply, and manufacturing data with Tandem prescriber intelligence and Komodo patient journeys under one governed semantic layer.
1 in 5
life sciences leaders believe their operating model enables timely decision-making
50%
of commercial pharma activities are expected to be outsourced within five years
67%
of drug launches underperform expectations
Across R&D, clinical, medical, commercial, access, and supply, teams often work from different views of the same molecule. Research decisions may not inform commercial planning. Clinical site selection may not reflect prior Medical Affairs insight. Launch plans may rely on syndicated data without visibility into access considerations. Supply forecasts may sit apart from these decisions.
The result is often delay, not error. Analysis is requested, decisions move to the next cycle, and the window to act gets smaller.
Value is shifting from studies, dashboards, and reports to the decisions they support. Speed, quality of evidence, and measurable impact will matter more than volume of deliverables.
Syndicated data is widely available. Differentiation comes from connecting it with enterprise data across prescriber behavior, patient journeys, medical insights, content performance, and investigator history.
Agents depend on the context they can access. Without connected, governed data, they inherit existing silos and work from incomplete evidence. The data foundation will determine how far AI can scale.
Analytics partnerships are moving beyond headcount and output-based models toward measurable outcomes such as decision cycle time, workflow adoption, and realized value.
Across all four shifts, the priority is the same: connect data and intelligence directly to the decisions that drive enterprise outcomes.
Unify commercial, medical, clinical, regulatory, supply, and manufacturing data with Tandem prescriber intelligence and Komodo patient journeys under one governed semantic layer.
Each decision outcome improves the next cycle of connected intelligence.
Discover how advanced analytics helped a global biotech identify, prioritize, and engage KOLs with a data-driven strategy.
See how ML-powered recommendation engines helped personalize HCP engagement and increase new HCP leads by 10-15%.
Explore how life sciences organizations can build and scale enterprise data governance to improve quality, trust, and AI readiness.
Unifies commercial, medical, clinical, regulatory, supply, and manufacturing data on one governed foundation with a shared semantic layer and consistent metric definitions.
Connects Tandem prescriber intelligence and Komodo patient journeys to enterprise data at the individual prescriber and patient level.
Connects customer, key opinion leader and investigator, regulatory, quality, and Patient 360 relationships beyond individual records.
Supports numerous decisions with dedicated models, thresholds, and delivery within the relevant workflow.
Generates evidence-backed recommendations with human approval gates, permissions, and a complete audit trail.
Measures incrementality against matched controls, cycle time against baseline, and value against the business case, with pipelines, models, and governance managed as a service.
Decision intelligence connects governed data, therapy-literate analytics, and live signals directly to business decisions, then measures the outcomes.
Indegene builds and runs it on Cortex, its connected intelligence engine for life sciences.
Indegene brings Tandem, 3.5M prescriber profiles built on 15 years of engagement behavior, and through its Komodo partnership, 330M longitudinal patient journeys, linked at the individual prescriber.
The combination surfaces switch risk, eligibility triggers, and channel affinity that syndicated data alone never shows.
Closed-loop measurement replaces quarterly, channel-level marketing mix with weekly HCP-level incrementality against matched controls, tied directly to spend and effort decisions.
Indegene runs it as an operating cadence, with attribution from linked claims and engagement data.
One truth requires a unified data foundation with a governed semantic layer that defines every metric once, and the operating discipline to hold those definitions across teams and tools.
Indegene builds the layer and runs the governance.
Connected enterprise data can reveal gaps and bring decision-ready intelligence into the workflows where critical decisions are made.