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Online

2026 年 04 月 21 日 11:00 上午 - 2026 年 04 月 21 日 12:00 下午

(US Eastern Standard Time)

DIA Direct: From AI Experiment to Strategic Advantage: Future-Proofing MSL Engagement

概览

Generative AI (GenAI) is no longer an experiment: it is becoming a strategic advantage for Medical Affairs teams that know how to use it effectively. Organizations that continue using AI in random or unstructured ways risk being left behind, while those that adopt a structured, scalable approach can transform how MSLs prepare, engage, and follow up with healthcare providers. This interactive workshop equips participants with a practical prompting framework and a set of plug-and-play prompts aligned to the full MSL engagement process. Attendees will gain hands-on experience across three stages of the workflow:

Strategic preparation: Using AI for strategic rapid literature reviews, transforming scientific papers into digestible formats (such as podcasts), and researching KOL priorities.

Engagement planning: Applying prompts to set clear agendas, uncover what matters to an HCP, anticipate objections, and generate high-value questions that lead to insights

Follow-up and continuity: Using AI to help secure the next meeting, effectively follow up, and coach teams on writing insights that help drive strategy

Participants will practice adapting prompts in small groups, see live demonstrations of GenAI in action, and explore how these applications can be implemented responsibly within existing guardrails. In parallel, Medical Affairs leaders will consider strategies to scale adoption, through shared frameworks and training programs that turn AI from a collection of experiments into an enterprise-level capability.

谁应该参加?

Who should attend: The webinar is designed for Field Medical professionals, Med Info Professionals, Med Comm Professionals

学习目标

  • Apply a structured prompting framework to Medical Affairs use cases
  • Practice creating and adapting plug-and-play prompts for MSL engagement scenarios
  • Identify strategies for leaders to scale AI adoption into enterprise-level capability

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