Data, Analytics, and AI

From Data Universe To Decision Advantage

Across the enterprise, critical decisions shape commercial, clinical, and patient outcomes: which prescriber to engage, which site to open, which submission to prioritize, and which patient may be at risk of discontinuing therapy. These decisions often draw on function-specific views of available evidence. Indegene connects that evidence and brings decision-ready insights into the workflows where decisions are made.

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

Fragmented Evidence Slows Enterprise Decisions

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.

When Decisions Stay Disconnected

Average annual cost of poor data quality$12.9M
Brands citing slow delivery of decision-grade insights as a major gap64%
Companies that have not successfully scaled AI initiatives89%
Where the shortfall landsLaunch uptake, trial timelines, and next year's guidance

Four Shifts Shaping The Next Five Years

  1. 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.

  2. 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.

  3. 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.

  4. 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.

The Connected Decision Universe

Four layers run on Cortex to connect data, add context, support decisions, and learn from outcomes.

Connect

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.

Featured Insights

Capabilities Behind Connected Decision Intelligence

The connected universe


Unifies commercial, medical, clinical, regulatory, supply, and manufacturing data on one governed foundation with a shared semantic layer and consistent metric definitions.

Proprietary data assets


Connects Tandem prescriber intelligence and Komodo patient journeys to enterprise data at the individual prescriber and patient level.

Enterprise knowledge graphs


Connects customer, key opinion leader and investigator, regulatory, quality, and Patient 360 relationships beyond individual records.

Decision products by function


Supports numerous decisions with dedicated models, thresholds, and delivery within the relevant workflow.

Agentic decision support


Generates evidence-backed recommendations with human approval gates, permissions, and a complete audit trail.

Outcome measurement and run


Measures incrementality against matched controls, cycle time against baseline, and value against the business case, with pipelines, models, and governance managed as a service.

Frequently Asked Questions

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.

Connect Data to the Decisions That Matter

Connected enterprise data can reveal gaps and bring decision-ready intelligence into the workflows where critical decisions are made.