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P2· Pharmacy and health sciences

AI Medical Writing & Regulatory Affairs

You learn to draft clinical and regulatory documents with AI, prove every sentence and every reference against its source, and turn approved label text into patient leaflets in Kannada, Hindi and Tulu that a pharmacist signs off.

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Who it is for
PharmD and MPharm students who want to write regulatory and patient-facing documents, and who already know their pharmacology and have finished the common AI core. It adds to, and never replaces, your PCI-mandated practice school or industrial training.
AI core
9 units · 20 h
This course
6 modules · 12 lessons · 4.7 h
Live projects
2, on Professional and Career
01Roles it prepares you for
  • Medical Writer
  • Regulatory Affairs Associate

The skills these roles ask for. Preparation, not a promise of a job.

02Tools you will use
  • Claude (free tier)Free tier
  • ChatGPT (free tier)Free tier
  • Gemini (free tier)Free tier
  • PubMedFree tier
  • Crossref metadata search and REST APIFree tier
  • ZoteroFree tier
  • Google Sheets and DocsFree tier
  • Saarthi sandbox (synthetic CSR, dossier and leaflet packs; metered API credits)Saarthi sandbox

You never pay for a tool subscription. “Verified” means we checked the free access on the vendor’s own site this month. Tool names describe what you learn; no vendor endorses Launchpad.

03Syllabus

What you will learn, in order.

Lesson films are narrated with an AI voice, over visuals made with AI tools and checked by our team. Saarthi, the coach, is an AI. Mentors and reviewers are people.

Part 1 · The AI core, shared by every stream

00Set up your coach1 hLearn how the core works, write the learning-context document that tells every AI tool who you are, and set Saarthi up as a coach that makes you think instead of thinking for you.
  1. How this core works6 min
  2. Write your learning-context document8 min
  3. Seven roles for AI, and study modes7 min
01How LLMs work and fail2.5 hBuild a working mental model of a large language model: tokens, prediction, context windows and memory. Then learn its predictable failures (hallucination, sycophancy, stale knowledge, bad arithmetic) and reproduce them yourself.
  1. Tokens and next-word prediction7 min
  2. Context windows and memory7 min
  3. Hallucination, sycophancy and other failures8 min
  4. Lab: one prompt, three models, five failures8 min
02Description and context engineering3.5 hWrite briefs that get the right output the first time: role, task, context, examples and format. Then make them reusable with Claude and ChatGPT Projects, Gemini Gems, custom GPTs and NotebookLM, and learn to work with PDFs, spreadsheets and images.
  1. The brief: role, task, context, format8 min
  2. Examples and output formats7 min
  3. Projects in Claude and ChatGPT8 min
  4. Gems, custom GPTs and NotebookLM8 min
  5. Working with files: PDFs, spreadsheets, images8 min
03Verify everything2.5 hCheck AI output the way fact-checkers do: lateral reading, tracing citations and numbers to the original, using deep-research modes without trusting them blindly, and testing a prompt properly with a 10-case golden set.
  1. Lateral reading7 min
  2. Checking citations and numbers8 min
  3. Deep-research modes: use and limits7 min
  4. Your first eval: a 10-case golden set8 min
04Connectors and MCP2 hConnect AI to the places your work lives (Drive, Gmail, Sheets, business data) without writing code. Learn what an MCP server is, why a reviewed directory differs from unreviewed community servers, how to grant the least access that works, and how to keep browser extensions on a short leash.
  1. What connectors and MCP are8 min
  2. Trust, least privilege and the reviewed directory8 min
  3. Browser extensions and AI browsers7 min
  4. Lab: ask the seller-data MCP server, check every answer8 min
05Agents and automations3.5 hHand multi-step work to AI safely. Tell an agent from an automation, decide what to delegate, use browser and coding agents with care, and build an n8n workflow that uses AI with a human-approval step before anything leaves the system.
  1. Agents vs automations: what to delegate8 min
  2. Browser agents, safely7 min
  3. Automation basics with n8n and Zapier8 min
  4. Lab: build an automation with a human-approval step8 min
  5. Failure modes and your failure-mode note7 min
06AI for learning and careers1.5 hUse AI to learn faster without outsourcing the learning, write applications that still sound like you, and practise interviews out loud with Saarthi.
  1. Learning with AI, not instead of learning7 min
  2. Applications in your own voice7 min
  3. Mock interview with Saarthi8 min
07Diligence: law, ethics, integrity2.5 hThe rules that apply when you use AI in India: the DPDP Act 2023 and its 2025 Rules, academic integrity and disclosure, copyright (including where Indian law is still unsettled), and bias. You finish by writing your own AI-use policy.
  1. DPDP Act 2023: personal data and AI8 min
  2. Academic integrity and disclosure7 min
  3. Copyright and AI in India8 min
  4. Bias and fairness7 min
  5. Write your personal AI-use policy7 min
08Core capstone1 hPut all four Ds together on one anonymised marketplace settlement file: ask good questions, automate one step, verify every number against Saarthi's P&L engine, and defend your work live in five minutes.
  1. The capstone brief6 min
  2. Lab: ask, automate, verify8 min
  3. Prepare your 5-minute defence7 min

Part 2 · AI Medical Writing & Regulatory Affairs

01Medical writing foundations2 lessonsThe documents you will write (CSR, CTD, prescribing information, patient leaflets), who reads each one, and where AI helps or hurts.
  1. Documents, readers and the rules that never change14 min
  2. Lab: build a structure map from a public product document25 min
02Grounded drafting with AI2 lessonsSource packs, sentence-level tags and claim tables that stop a model from filling gaps with plausible numbers.
  1. Source packs, tags and claim tables14 min
  2. Lab: draft a CSR synopsis and prove every sentence30 min
03Reference integrity and hallucinated citations2 lessonsFour kinds of reference failure, a verification ladder using PubMed, doi.org and Crossref, and an audit record you can defend.
  1. Fabricated, misattributed, unsupported, retracted13 min
  2. Lab: audit a seeded reference list35 min
04Regulatory affairs in India: the working map2 lessonsCDSCO, the NDCT Rules 2019, SUGAM and CTD in India, with AI used for checklists and label comparisons, never for stating the law from memory.
  1. CDSCO, NDCT Rules and how a submission travels14 min
  2. Lab: submission tracker and label comparison30 min
05Dossier summarisation with traceability2 lessonsChunk, summarise, assemble and prove: anchors, a traceability matrix, a hallucinated-reference audit and three numbers that show quality.
  1. Traceable summaries and how to measure them14 min
  2. Lab: build and test a dossier-section summariser40 min
06Multilingual patient leaflets2 lessonsPlain-language source, forward and back translation into Kannada, Hindi and Tulu, native-speaker review and pharmacist sign-off.
  1. Plain language, translation risk and Tulu13 min
  2. Lab: one leaflet in four languages, with an error log40 min
04Live projects

Two briefs. Real-shaped work.

  1. Project 1

    Dossier-section summariser with a hallucinated-reference audit

    Build a repeatable AI summariser for a CTD Module 2 clinical section and prove how far it can be trusted. You receive a synthetic Clinical Overview (Module 2.5) for a fictional product, its synthetic source study reports and its reference list. Your summariser must produce a summary of at most 800 words in which every statement carries an anchor to document, section and page or table. You then test it: a full traceability matrix, a measured run-to-run comparison after one prompt change, and an audit of every citation in the summary against the source reference list and against PubMed or Crossref. The source contains seeded reference problems that your audit is expected to find. You present the results to a reviewer as a tool tested on synthetic data, not a validated system, and you state clearly what a medical writer must still check.

    You hand in

    • Versioned prompt recipe (chunk, assemble, citation-list prompts) with change notes
    • Final summary (max 800 words) with anchors on every statement
    • Traceability matrix for every statement with verdicts
    • Reference audit sheet covering every citation in the summary, with evidence for each verdict
    • Before-and-after metrics as counts: anchor accuracy, number fidelity, coverage, references flagged
    • One-page reviewer handover and a 5-minute recorded walkthrough for the viva

    Data: Saarthi sandbox synthetic dossier pack: fictional product Clinical Overview (about 25 pages), three synthetic study reports and a 30-item reference list mixing real public papers with seeded errors (wrong details, unsupported citations, non-existent papers). No real trial or patient data.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

  2. Project 2

    Patient counselling leaflets in Kannada, Hindi and Tulu with pharmacist review

    Produce a set of patient counselling leaflets for three common, well-known generic medicines (fictional brand names, label text supplied) in English, Kannada, Hindi and Tulu. You write a plain-language English source from the label text only, get it approved by a pharmacist, translate it with AI, back-translate it with a different tool, have a native speaker review each language, and get pharmacist sign-off on every final version. You measure how often AI translation changed the meaning in each language and compare Tulu, a low-resource language, with Kannada and Hindi. The leaflets add no clinical advice beyond the label and the prescriber's instructions, and none is used or shared without sign-off.

    You hand in

    • Pharmacist-approved plain-English source for each medicine
    • Final leaflets in Kannada, Hindi and Tulu for each medicine, each with a signed review record (name, date, version)
    • Translation error log with issue type, severity, fix and who fixed it
    • Per-language counts: lines translated, issues caught by back-translation, issues caught only by native review, critical issues, lines changed at pharmacist review
    • Comprehension check notes from at least two lay readers per language
    • A one-page reflection on where AI translation can and cannot be trusted for patient materials

    Data: Saarthi sandbox synthetic leaflet briefs: three fictional brand names for common generic medicines with approved-style label text. No real prescriptions, patients or brand labels.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

05Practise out loud

In voice mock interviews and client calls, Saarthi plays: Dr. Meera Rao, medical-writing lead at a mid-size contract research organisation in Bengaluru, interviewing you for a medical-writing role. She has reviewed hundreds of CSRs and CTD summaries, is friendly but exacting, and will ask you to walk her through one of your traceability matrices, explain how you caught a hallucinated reference, and explain what you would never let an AI write. She probes for honesty about errors, care with patient data under the DPDP Act, and respect for reviewer sign-off, and she pushes back if you call anything 'validated'.

On plans that include mock interviews. You get written feedback after every call.

06Enrol

Pick a plan for AI Medical Writing & Regulatory Affairs.

One payment. The access deadline for each plan is shown before you pay.

  • Foundation

    01

    Learn the AI your field now runs on.

    ₹2,999

    One payment. GST included.

    • Access for 120 days (about 4 months) from the day you pay
    • No 1:1 mentor sessions
    • The common AI core and your domain course
    • Saarthi, your AI coach, any hour
    • Hands-on labs on free tools
    • Verifiable certificate
    Enrol on Foundation

  • Professional

    02

    Prove it on real work.

    ₹7,999

    One payment. GST included.

    • Access for 180 days (about 6 months) from the day you pay
    • One 1:1 session with a mentor
    • Everything in Foundation
    • Two live projects, reviewed by Saarthi and a mentor
    • Public portfolio page of verified work
    • Voice mock interviews
    • One 1:1 coaching session
    Enrol on Professional

  • Career

    03

    Work alongside our team.

    ₹14,999

    One payment. GST included.

    • Access for 240 days (about 8 months) from the day you pay
    • Four 1:1 sessions with a mentor
    • One 1:1 call with an industry expert
    • Everything in Professional
    • Four-week supervised practicum with the Saarthi team
    • Four 1:1 coaching sessions with your mentor
    • An exclusive 1:1 call with an industry expert in your field
    • CV and LinkedIn review
    • Priority mentor replies
    Enrol on Career

Your access period starts the day you pay and is shown before you pay. One exam pause per enrolment, for up to 15 days. When access ends the course locks, and your portfolio page and certificate stay live. Full refund within 7 days, pro-rata after that, and an automatic refund for any practicum, 1:1 mentor or expert session we do not deliver. Refund policy