Flagship program
Diploma in Pharma GenAI, Analytics & Consulting
A comprehensive, one-year transformation program covering pharma domain knowledge, commercial operations, forecasting, market access, competitive intelligence, and executive-level presentation skills.
1 YearDuration
5Applicable domains
B.Pharm / M.PharmCore intake
What learners build
A full transformation track
Across the program, learners build capability across pharma domain knowledge, commercial operations, forecasting, market access, competitive intelligence, and the executive-level presentation skills needed to communicate findings to senior stakeholders.
FormatLive / hybrid / online
LevelBeginner to advanced
Core intakeB.Pharm, M.Pharm
Also open toLife science graduates, working professionals
Career switch friendlyIT professionals entering healthcare
CertificationIncluded
Placement supportIncluded
Applicable domains
Relevant across five functional domains
The diploma is structured to be relevant across five major functional domains within a pharma organization.
01
Pharmacovigilance
02
R&D
03
Regulatory
04
Sales & marketing
05
QA / QC / Production
Pharmacovigilance is the discipline of monitoring the safety of medicines after they reach the market — collecting, assessing, and reporting adverse events, and watching for safety signals across a drug's lifecycle. AI is increasingly used here to triage incoming case reports, flag potential signals in large volumes of literature and social data, and draft first-pass narrative summaries that a qualified safety physician then reviews, since regulatory reporting timelines are strict and case volumes can be very high.
Research and development covers everything from early discovery through clinical trials. Analytics and AI applications here include using machine learning to help prioritize drug candidates, applying natural language processing to scan scientific literature and patent filings, and building models that help design more efficient clinical trials — for example, predicting patient recruitment rates or identifying likely trial sites.
Regulatory affairs manages the submission and approval process with authorities such as the FDA, EMA, or India's CDSCO, and the ongoing compliance obligations after approval. GenAI is being adopted for drafting regulatory documents, comparing submission dossiers against changing guidance, and summarizing regulatory intelligence — always with mandatory expert human review before anything is filed.
This is the commercial engine of a pharma company — brand strategy, field force execution, and promotional messaging to healthcare professionals. Analytics here spans prescription and market share analysis, segmentation and targeting, and increasingly using GenAI to accelerate content creation for approved promotional material, always inside medical-legal review processes.
Quality assurance, quality control, and production/manufacturing keep drug batches consistent, safe, and compliant with Good Manufacturing Practice (GMP). Data analytics is used for statistical process control, predictive maintenance on manufacturing equipment, and deviation/root-cause analysis, while AI-assisted computer vision is emerging for visual inspection tasks such as detecting defects in packaging or tablets.
Skills covered
Eight tools and skill areas
SQL
Power BI
Excel
Python
Prompt engineering
Pharma GPT use cases
Medical writing automation
Structured problem solving
Each skill maps onto specific day-to-day work in pharma commercial and medical teams:
Querying sales, claims, and market data warehouses that sit behind most commercial dashboards; the baseline skill for pulling your own data instead of waiting on a BI team.
Building and maintaining the commercial dashboards that brand and sales leadership review weekly, from prescription trends to territory performance.
Still the working backbone of ad hoc forecasting models, budget scenarios, and quick analyses in commercial teams, even where more advanced tools exist.
Used for larger-scale analysis, automation, and building forecasting or NLP models, such as models that scan medical literature or adverse-event text at volume.
The practical skill of getting reliable, checkable output from GenAI tools, which matters more in pharma than most industries because outputs often need to be traceable and defensible.
Applied patterns such as medical-information Q&A support, first-pass competitive intelligence briefs, and literature summarization, each with its own review and validation step.
Using AI to draft first versions of regulatory or medical documents (e.g., slide decks, standard responses, literature summaries) that a qualified medical writer then reviews and finalizes.
Consulting-style frameworks (issue trees, hypothesis-driven analysis, MECE structuring) for breaking down ambiguous business questions, such as "why did share drop in this region."
Career outcomes
Typical roles after completing the diploma
Graduates of programs with this scope typically move into roles such as commercial analytics analyst, forecasting analyst, market access analyst, competitive intelligence associate, business intelligence/reporting analyst, or analyst-level roles within pharma-focused consulting firms.
Career switchers from IT or general analytics backgrounds most often land in roles that value their existing technical depth combined with the pharma domain layer the diploma adds — for example, moving from a generic BI developer role into a pharma commercial analytics role at similar seniority.
Ready to apply for the diploma?
Applications for the next cohort are open — or book a free counseling call first.