In this podcast, we interview Matt Lewis, Chief AI Officer at Inizio Medical, a well-regarded expert in data analytics and augmented intelligence.Â
A Q&A on how Medical Affairs can align on omnichannel for long-term success
This article highlights a collaborative approach to content creation in which insights from MSLs were used to develop concepts for educational tools that were shared with key opinion leaders (KOLs).
In this podcast, MAPS speaks with experts from Virtual Science AI about how the word, “Generative,” has elevated the promise of AI.
In this podcast, the final part of our 3-part series, our experts tackle the question of: “How does a Medical Affairs organization measure the success, or value, of omnichannel activities?”
In this podcast, part 2 of a 3-part series, our experts tackle the question of: “How does a Medical Affairs organization plan for integrating omnichannel activities?”
In this podcast, part 1 of a 3-part series, our experts in the Digital FAWG tackle the question of: “How do you define omnichannel?”
In this podcast, we explore best practices for gathering content (beyond simply creating it yourself!), and making content accessible in modern, personalized platforms.
In this podcast, two data specialists discuss the ways in which Medical Affairs professionals can use this data to discover your next generation of researchers, those influencers whose voices are heard on Twitter, and how your KOLs are interacting with others online.
AI Application in Medical Affairs – Advanced Course
This course includes
What you will learn?
Course description
This comprehensive course is tailored to professionals in the pharmaceutical, biotechnology, and medical device industries who work in Medical Affairs functions. It addresses the impact of technology and automation on Medical Affairs in the post–COVID-19 era, which has been accelerated by the pandemic.
This curriculum delves into the utilization of AI in the creation of personalized content, management of medical queries, and prediction of customer engagement pathways.
Additionally, it examines the use of AI in MLR review processes to allow for a more strategic allocation of resources and highlights current AI applications utilized in MLR reviews.
Furthermore, this curriculum explores the application of AI in personalizing customer interactions and utilizing next-best actions, content affinity, and channel affinity in Medical Affairs interactions, as well as AI’s role in generating insights.
Our on-demand content, which includes animations and rich graphics, is presented in a clear and concise manner, making it easy to understand and apply in real-world scenarios. Upon successful completion of the Certification Quiz, a downloadable version of this curriculum will be made available to users..
Learning activities/assessments: eLearning self-paced modules, knowledge checks, and a brief pre- and post-test
Approximate time to complete the activity: 120 minutes
Prerequisites: The eLearning module “Artificial Intelligence Foundations for Medical Affairs” is highly recommended.
Audience: Intermediate-level content for Medical Affairs professionals who have digital experience
Credits: As an IACET Accredited Provider, Medical Affairs Professional Society offers IACET CEUs for its learning events that comply with the ANSI/IACET Continuing Education and Training Standard. MAPS is authorized by IACET to offer 0.2 CEUs for this program.
Participants/attendees must complete 100% of the program and receive a minimum of 70% on the post program assessment.
At the conclusion of this online learning activity, participants should be able to:
1. Recall the impact of technology and automation across Medical Affairs in a post-Covid-19 world especially accelerated due to the pandemic
2. Articulate the potential business cases for AI within the Medical Affairs function
3. Describe the use of AI in modular content creation to deliver personalized targeted content
4. Explain how AI can help in the content supply chain and query management
5. Identify how the integration of AI and data sources predicts an ideal customer engagement pathway
6. Explain the need for AI in MLR review to allow reviewers to do more strategic work
7. List a few examples of AI applications in MLR review
8. Explain the role of AI in advanced MI portal search
9. Discuss the importance of conversational AI in customer interactions
10. Describe how AI can help in insight generation
11. List a few use cases of insight generation using AI in Medical Affairs