Tanmay Sharma is a senior commercial analytics and data leader whose work spans enterprise analytics, forecasting, and the design of scalable commercial data architectures for pharmaceutical and biotechnology organizations. Across his career, Tanmay has operated at the intersection of commercial strategy, advanced analytics, and data platform design—helping organizations translate complex data into durable, decision-ready systems, particularly in oncology.
At Gilead Sciences, Tanmay helped build and evolve large-scale commercial analytics and data ecosystems supporting global HIV and oncology portfolios, combining forecasting, performance analytics, and platform design at enterprise scale. Earlier, at ZS Associates, he advised life sciences clients on commercial analytics, sales operations, forecasting, and data strategy, gaining exposure to how architectural and analytical choices directly affect execution.
In his current role at Corcept Therapeutics, Tanmay has been responsible for shaping the end-to-end commercial data and analytics foundation supporting oncology launch readiness and long-term growth. His work reflects a consistent philosophy: in oncology, analytics and data architecture are strategic assets that must be designed deliberately and early.
That perspective is increasingly critical. Oncology success is rarely defined by a single launch. Therapies often begin in narrow indications and expand across tumor types, lines of therapy, and patient populations. Yet many small biotechs still design analytics and data systems as if each launch were a one-time event, resulting in infrastructure that struggles to scale.
Based on experience across multiple oncology launches, Tanmay has observed that traditional commercial data models are poorly suited for oncology markets.
Products progress from one indication to many. Treatment paradigms change quickly. Stakeholders extend beyond individual physicians to include academic centers, integrated delivery networks, specialty pharmacies, and hospital-based teams. Commercial questions shift rapidly—from identifying initial targets to understanding variation by indication, line of therapy, and site of care.
Most legacy data environments were not designed for this complexity. They are often fragmented, rely on inconsistent provider and account definitions, embed logic directly in dashboards, and activate CRM systems without sufficient analytical context. While these limitations may be tolerable in stable primary care markets, in oncology they directly impair execution quality.
In response, Tanmay has consistently advocated for treating commercial data architecture as a strategic oncology investment rather than a downstream IT exercise.
In his current role, this meant ensuring architectural design preceded production buildout. Rather than starting with tools, the organization invested time upfront in defining how the commercial data ecosystem would function over time—how it would support multiple indications, which data definitions needed to remain stable, how insights would flow into execution systems, and what governance would prevent future re-engineering.
This design-first approach was shaped by earlier experiences where rushed implementation led to fragmentation, rework, and limited scalability under launch pressure.
A recurring failure mode Tanmay has encountered across small biotechs is attempting to design data architecture without first establishing commercial strategy.
In oncology, effective architecture must be anchored in alignment across Sales, Medical Affairs, and Market Access—addressing physicians, payers, hospitals, and patients as a single ecosystem. A clearly defined distribution strategy, including site-of-care and specialty pharmacy considerations, is equally important.
These strategic decisions determine which data must be captured, how entities should be modeled, and how insights are operationalized. Without this clarity, even technically sophisticated architectures struggle to support execution.
While end-to-end commercial data architectures can become complex, Tanmay’s implementation philosophy emphasizes focus and restraint.
Rather than attempting to solve every future use case upfront, the goal is to deliver a small number of core capabilities exceptionally well:
Standardized ingestion of claims, prescription, field activity, patient services, and market data
A governed commercial data warehouse as the single system of record
Strong master data management for providers, accounts, products, and hierarchies
Shared semantic models for reporting and analysis
Clear pathways for insights to flow into CRM and field execution
A stable foundation for forecasting and advanced analytics
These components must be designed together—but kept intentionally simple.
Artificial intelligence is becoming an increasingly important extension of oncology commercial strategy, but its effectiveness depends far more on architectural discipline than on algorithmic sophistication.
Rather than eliminating foundational systems, AI agents increase the importance of strong data management. In regulated oncology environments, AI systems require explicit context: consistent definitions, clear lineage, usage constraints, and semantic meaning. As a result, metadata and governance become first-class architectural assets.
At the same time, Tanmay emphasizes that organizations cannot afford to wait for these technologies to fully mature. CRM and analytics platforms are already introducing agent-based capabilities and conversational reporting, even if many remain early.
The practical approach is continuous, controlled experimentation - working closely with legal and compliance teams to establish guardrails that enable learning without undue risk. Architectures built with simplicity, semantic clarity, and flexibility allow organizations to adopt AI-enabled capabilities incrementally, without repeated re-engineering.
In oncology commercialization, which grows with every new indication, Tanmay's architectural design is a disciplined, future-proof extension built upon a foundational commitment to getting the architecture correct from the beginning.