Training course · Claude Code · Pharma & Life Sciences

Claude Code for Pharma and Life Sciences

Agentic coding with Claude Code in the terminal and IDE: CLAUDE.md, subagents, hooks, MCP, CI pipelines and secure permissions.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Claude Code with the everyday processes of Pharma & Life Sciences. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Claude Code is not only for professional developers. Business users with no programming background can use it to analyse data, clean up Excel and CSV files, generate reports or build small internal tools, all in plain language. You describe what should happen, and Claude Code writes and runs the necessary scripts itself. This course variant shows you how to put these capabilities to work in your daily job without needing to understand code, and how to check the results reliably before anyone relies on them.

You will work through realistic office scenarios: merging exports from several systems, producing analyses with charts, generating documents and mail merges automatically, or turning repetitive file chores into a single command. Working safely is a central theme: which data may be processed, how you stay in control of approvals, and when to involve your IT department. The result is a set of useful helpers that take load off your team while remaining transparent and easy to hand over.

Pharmaceutical, biotech and medtech companies operate in one of the most heavily regulated environments of all. Documentation, validation and traceability shape daily work from research and clinical trials to manufacturing. Generative AI offers significant potential: AI assistants review scientific literature, help draft study protocols, regulatory documents and SOPs, summarise deviation reports, support pharmacovigilance case processing and prepare medical information for healthcare professionals. Automation supports change control, CAPA tracking and regulatory intelligence. At the same time, as soon as AI touches GxP-relevant processes, validation, data integrity according to ALCOA+ and clear accountability are mandatory. Adoption succeeds when companies clearly separate non-regulated support from GxP use and involve quality assurance early.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Regulatory affairs professionals
  • Quality assurance and Qualified Persons
  • Clinical operations and medical writers
  • Pharmacovigilance and drug safety teams
  • Medical affairs and R&D scientists

Typical challenges we address

  • Producing extensive regulatory and scientific documents to a high standard
  • Processing deviations, CAPAs and change controls on time
  • Systematically evaluating growing volumes of literature and regulation
  • Using AI tools in a GxP-compliant, validatable way

What you will be able to do

  • You commission data analyses and file tasks from Claude Code in plain language.
  • You clean and combine Excel and CSV data and check the results for plausibility.
  • You automate recurring document and reporting tasks with reusable instructions.
  • You have small internal helper tools built and refine them step by step.
  • Use AI for literature review, medical writing and regulatory intelligence.
  • Distinguish non-regulated AI use from GxP-relevant applications and understand validation requirements.
  • Safeguard data integrity, confidentiality and patient data protection when using AI.

Course outline

Day 1

Module 1 Getting started without coding skills
  • What a coding agent is and what it is allowed to do on your computer
  • Launching Claude Code and setting up a protected working folder
  • Describing tasks in everyday language: goal, input files, expected result
  • Understanding approval prompts and consciously accepting or declining them
Module 2 Analysing data in Excel and CSV files
  • Cleaning exports: duplicates, date formats, missing values
  • Combining several tables and calculating key figures
  • Producing charts and summaries as Excel files or images
  • Sanity-checking results with spot checks and cross-calculations
Module 3 Automating documents and routine tasks
  • Generating reports, minutes and mail merges from templates and data
  • Renaming, sorting and converting files automatically
  • Saving recurring procedures as reusable instructions
  • Writing a simple team guide in CLAUDE.md
Module 4 Building small scripts and internal tools
  • From idea to working helper: stating requirements clearly
  • Having simple input forms or local web interfaces created
  • Improving step by step: describing problems instead of debugging yourself
  • Documenting results so colleagues can use them

Day 2

Module 5 Working safely and responsibly
  • Handling personal and confidential data correctly
  • Limiting permissions and working only in approved folders
  • Recognising limits: when a tool should be handed over to IT
  • Coordinating with IT, data protection and business owners
Module 6 Hands-on project: your own solution for Pharma & Life Sciences
  • Literature extraction table – An app where abstracts are pasted in and study design, population, endpoints and results are turned into an exportable comparison table.
  • CAPA tracker – An internal dashboard for non-GxP preliminary overviews that visualises open CAPAs, due dates and effectiveness checks and sends reminders.
  • Regulatory news feed – A tool that collects authority publications, filters them by topic and produces a weekly annotated overview for the regulatory team.
Module 7 Data protection, quality & transfer to daily work
  • When AI systems are used in GxP-relevant processes, computerised system validation under EU GMP Annex 11 or 21 CFR Part 11 and data integrity according to ALCOA+ must be ensured. Clinical trial and pharmacovigilance data contain health data under Article 9 GDPR and may only be processed in pseudonymised form in approved environments.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Literature review and evidence

An AI assistant summarises scientific publications, extracts study design, endpoints and results into tables and supports systematic reviews, with experts checking every data point against the original source.

Medical writing support

AI creates outlines and first drafts of study protocols, clinical study reports, investigator brochures or modules of the regulatory dossier based on approved templates and source data.

SOPs and training materials

Process descriptions and regulations are turned into draft SOPs, training slides and comprehension questions, which are then reviewed and approved through the validated document management system.

Deviations and CAPA

AI summarises deviation reports, structures root cause analyses, finds similar past cases and suggests CAPAs, which quality assurance evaluates and decides on.

Regulatory intelligence

Automations collect new guidelines and publications from the EMA, national authorities or the FDA; AI summarises changes and maps them to affected products and processes for an impact assessment.

Pharmacovigilance support

AI helps pre-structure case reports from unstructured text, extract relevant information on product, event and patient and detect duplicates, while medical assessment remains with qualified staff.

Possible hands-on projects

Literature extraction table

An app where abstracts are pasted in and study design, population, endpoints and results are turned into an exportable comparison table.

CAPA tracker

An internal dashboard for non-GxP preliminary overviews that visualises open CAPAs, due dates and effectiveness checks and sends reminders.

Regulatory news feed

A tool that collects authority publications, filters them by topic and produces a weekly annotated overview for the regulatory team.

Prerequisites

No programming knowledge is needed; confident use of Excel, files and folders on your own computer is sufficient. You work in the pharmaceutical, biotech or medtech industry and know the GxP basics of your area.

Technical requirements

Your own laptop with admin rights, Git, a Node.js runtime and an up-to-date editor; a Claude subscription or Anthropic API access is required for the exercises.

Data protection & compliance

When AI systems are used in GxP-relevant processes, computerised system validation under EU GMP Annex 11 or 21 CFR Part 11 and data integrity according to ALCOA+ must be ensured. Clinical trial and pharmacovigilance data contain health data under Article 9 GDPR and may only be processed in pseudonymised form in approved environments.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Hanover Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Munich Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Stuttgart Request

Frequently asked questions

How is Claude Code different from traditional code completion?

Code completion suggests the next few lines, whereas Claude Code acts as an agent that handles whole tasks: it searches the repository, plans changes across several files, runs tests and commands, and corrects itself based on the results. You define the goal and review the outcome instead of steering every single line yourself.

Is Claude Code secure enough for enterprise use?

By default, Claude Code asks for approval before editing files or running commands. Permission rules, sandboxing, managed settings and hooks let you define precisely what the agent may do. During the course you learn to configure these mechanisms to match your security and data protection requirements and to assess risks such as prompt injection.

Does Claude Code work with my language and tech stack?

Yes. Claude Code is language-agnostic because it works with files, terminal commands and your existing build and test tooling. Whether you use Python, Java, TypeScript, Go, SAP-related code or infrastructure as code, what matters most is a well-written CLAUDE.md describing your commands and conventions. Each course variant adds the relevant domain focus.

Do AI tools need to be validated in pharma?

It depends on the use. For activities without GxP relevance, such as internal communication or literature overviews, general IT and data protection rules apply. If results feed into GxP-relevant decisions or records, a risk-based validation approach is required. We show you how to classify use cases.

How do we ensure data integrity?

AI output must be attributable, traceable and verifiable. That means documented inputs and prompts, clearly assigned reviewers, versioning and release through your validated systems. In the course we discuss how ALCOA+ principles apply to AI-supported work steps. Clear retention rules complete the picture.

How much does “Claude Code for Pharma and Life Sciences” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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