Medical Affairs in modern pharmaceutical companies ensure that the company's products are supported by sound scientific evidence, are used safely and effectively, and that the company maintains a positive relationship with the wider medical community.

Its activities range from clinical development support to health economics and outcomes research (HEOR), medical information and advocacy and stakeholder relations, requiring a wide range of professional skills and experience.

This course offers an exploration of the use of Artificial Intelligence, specifically Large Language Models (LLMs) such as ChatGPT, within the field of Medical Affairs. As technology continues to evolve, there's a growing interest in understanding how AI tools can be integrated into traditional medical processes.

Attendees will gain insight into how AI can process and present scientific data, potentially opening up new avenues for medical education and real-world data analysis. The course will also address the challenges associated with these models, including data reliability and ethical considerations.

By the end of the course, participants should have a clearer understanding of the benefits and limitations of using AI and LLMs in Medical Affairs, enabling them to make informed decisions about their potential application.

Module 1: Introduction and Key Applications

  • Welcome and Introduction to the Course
  • Basics of AI, Machine Learning, and LLMs
  • Overview of Medical Affairs and AI’s Potential Role
  • Prompt engineering: basic concepts
  • Case Presentation: AI in Scientific Communication and Engagement
  • Hands-on Session: using ChatGPT for Medical Information Retrieval
  • Group Discussion and Q&A

Module 2: Advanced Applications and Considerations

  • Recap of Day 1 and Introduction to Day 2
  • Case Presentation: AI in Health Economics and Outcomes Research
  • Prompt engineering: more advanced applications
  • Hands-on Session: Customizing ChatGPT for Personalized Medical Learning
  • Roundtable Discussion: ethical and operational considerations in AI for Medical Affairs
  • Course Conclusion, Feedback, and Closing Remarks

Medical director, Medical Advisor, Medical Science Liaison, Clinical development, health economics and outcomes research (HEOR), medical information and advocacy and stakeholder relations.

Interactive hands-on training.

Marco Anelli

Marco Anelli

Medical Affairs and Pharmacovigilance consultant

Marco has a medical degree from the University of Milan, specializations in Medical Statistics and Clinical Pharmacology from the University of Pavia and an international master’s degree in health economics and pharmacoeconomics from the University of Pompeu Fabra in Barcelona, plus formal training in Data Science and Artificial Intelligence.
In the last few years, he has extensively worked in the fields of pharmacoeconomics and health technology assessment.
Marco has been a free-lance consultant in Medical Affairs and Pharmacovigilance/ Drug Safety since 2022.

Before that, he has been “Head of Pharmacovigilance and Medical Affairs Advisory Services” at ProductLife Group (PLG).
As “Deputy Chief Scientific Officer”, always at PLG, Marco has also coordinated all delivery and research projects (internal and on behalf of clients) linked to Big Data, Knowledge Management, Artificial Intelligence and Machine Learning.
Previously, Marco was R&D Director at Keypharma, an Italy-based consultancy company (later acquired by PLG), where was responsible for the oversight of all clinical and preclinical aspects of projects run internally and on behalf of clients.
Drawing on a career in the pharmaceutical industry that spans more than 30 years, Marco provides expert oversight on a wide range of R&D and Medical Affairs related activities.
Marco has participated in and supervised all stages of drug development – from formulation to Phase I-IV and pharmacovigilance.
In addition, Marco is a qualified QPPV and has prepared and overseen more than 200 non-clinical and clinical overviews and summaries.
Before joining Keypharma and PLG, Marco was Medical Affairs Director at Eurand.

This online training is divided in 2 modules:

Module 1 | 13 March 2024 from 09:00 am to 01:00 pm CET
Module 2 | 15 March 2024 from 09:00 am to 01:00 pm CET

Some days before the online training you will receive all details about the connection.

The course will proceed with a minimum number of participants. Should this number not be reached the registered participants will be notified one week prior to the commencement of the course.

Early Bird: € 895,00* (until 21 February 2024)

Ordinary: € 1.085,00*

Freelance – Academy – Public Administration**: € 580,00*

*for Italian companies: +22% VAT

**Early Bird discount not applicable to Freelance – Academy – Public Administration fee

The fee includes: tuition, organizational office assistance, teaching materials and attendance certificate that will be sent after the training via e-mail.


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Versione Stampabile
Cosa saprai fare dopo il corso
Risultato atteso
Grasp the basic concepts related to Artificial Intelligence and Machine Learning
Risultato atteso
Get some knowledge of ChatGPT and of the other Large Language Models (Bard, Bing AI, etc.)
Risultato atteso
Grasp the basics of “prompt engineering”
Risultato atteso
Apply what you have learnt to real life Medical Affairs activities
Risultato atteso
Make informed decision about the choice and the implementation of LLM based approaches to Medical Affairs

<p><span>Online interactive training on Zoom platform. </span></p>
<p><em>LS Academy will provide the access link to the virtual platform a few days before the training.</em></p>

Online interactive training on Zoom platform. 

LS Academy will provide the access link to the virtual platform a few days before the training.

<p><span>Online interactive training on Zoom platform. </span></p>
<p><em>LS Academy will provide the access link to the virtual platform a few days before the training.</em></p>