Indu
Behera

Pharma marketing teams couldn't produce compliant content fast enough. Off-the-shelf AI tools didn't understand review constraints, approved source material, or the logic of regulated pharmaceutical communication. Every content cycle was a bottleneck.

Worked end-to-end with the tech team, from project scoping and PRD writing through to GTM launch. Defined the content workflow architecture, the messaging logic layer, and the SmPC-to-content generation pipeline. Led stakeholder enablement, sales narrative development, and commercial launch positioning for medical affairs and marketing audiences.

Medical Science Liaisons were walking into HCP visits under-prepared. They didn't know what was discussed last quarter, which channel the HCP preferred, or where their own performance gaps were. CRM data existed but wasn't being activated at the point of need.

Scoped and executed end-to-end with the tech team. Defined the KPI architecture, the Databricks data pull logic, the prep note structure, and the WhatsApp notification channel design. Owned the GTM narrative, sales enablement story, and commercial launch positioning for medical affairs audiences.

Pharma medical affairs teams had hundreds of publications but no structured way to query them. Evidence gaps went undetected. Insights sat in PDFs. Field teams re-commissioned the same research repeatedly because no one could access what already existed. The problem wasn't a lack of data. It was a lack of activation.

Scoped and executed end-to-end with the tech team. Translated medical affairs requirements into PRDs defining the query architecture, evidence gap detection logic, and the insight-to-competitor-card conversion workflow. Owned the GTM narrative, target audience positioning for medical affairs and evidence teams, and all sales enablement assets for commercial launch.

Forecasting teams rebuilt patient-based epidemiological models from scratch in Excel for every asset, market, and indication. Slow, inconsistent, hard to audit, impossible to compare across a portfolio. Erosion and risk surfaced late, buried in tabs.

Translated forecasting-lead requirements into an interactive prototype and proposal. Defined the two-builder architecture (epidemiology bottom-up plus market top-down), a live model-flow builder that generates formula-wired Excel templates, a portfolio Model Library, and a signal-to-explanation AI layer that flags rule-based risks without prescribing. Kept Excel as the calculation engine of record. Owned the GTM narrative and enablement assets.

Commercial teams already had Power BI dashboards and IQVIA MIDAS market tracking across countries, brands, and competitors. But leadership still had to manually interpret what changed, why it mattered, and what action should follow. The dashboards reported. They didn't decide.

Built the Market Intelligence scope that upgraded existing dashboards into a signal-to-action framework. Defined country summaries, brand and competitor movement, growth momentum, share shifts, rank-gap interpretation, rep visibility, leadership quick takes, and recommended action prompts. Kept the existing BI infrastructure intact and layered decision support on top.

Medical affairs teams spend weeks manually mapping KOL influence across therapy areas. Signals sit scattered in publications, conference presentations, trial investigators, guidelines, and social. No unified view. No ranking logic. Every launch team rebuilds the map from scratch.

Built a live prototype from scoping to shipped demo. Defined the multi-source signal architecture (publications, congresses, trials, guidelines, social), the KOL ranking logic, the network visualisation, and the search and filter workflow. Owned the positioning, buyer narrative, and enablement story for medical affairs and commercial launch teams.