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Prerna Kaul is a product and platform leader who has spent over 14 years turning machine-learning research into consumer and B2B products at Amazon Alexa, AGI, Moderna, and now Panasonic Well. In today’s episode, she explains how she’s using AI to slash some of the most time-consuming, expensive tasks in life sciences—from generating 60,000-page FDA submissions to crafting communication frameworks that help product managers navigate complex stakeholder dynamics. Her innovations are saving millions of dollars and helping lifesaving treatments reach the market faster.
What you’ll learn:
—
Brought to you by:
CodeRabbit—Cut code review time and bugs in half. Instantly: https://lovable.dev/
Lovable—Build apps by simply chatting with AI: https://lovable.dev/
—
Where to find Prerna Kaul:
LinkedIn: https://www.linkedin.com/in/prernakkaul/
—
Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
—
In this episode, we cover:
(00:00) Introduction to Prerna
(03:01) The FDA submission challenge: 60,000 pages, months of work, millions in costs
(05:20) Getting started in Claude: from prompt to production-ready prototype
(10:13) How Claude selected the right models for medical entity recognition
(12:04) Using Streamlit to create accessible UIs for non-technical users
(16:04) Detecting and redacting PHI in unstructured clinical notes
(18:44) Generating the Common Technical Document (CTD) for FDA submission
(21:54) Tracking and displaying AI operation costs for stakeholder buy-in
(24:38) Real-world impact on vaccine development timelines and costs
(26:12) Creating an AI communication coach for product managers
(30:22) Training Claude on classic literature and persuasion techniques
(31:53) Analyzing a complex stakeholder scenario with multiple competing priorities
(34:40) Getting personalized communication strategies inspired by tech leaders
(35:40) Summarizing strategic approaches
(38:26) Conclusion and final thoughts
—
Tools referenced:
• Claude: https://claude.ai/
• Streamlit: https://streamlit.io/
• Anthropic Console: https://console.anthropic.com/
• Claude Sonnet 4: https://www.anthropic.com/claude/sonnet
—
Other references:
• Claude project chat (AI Product Management Stakeholder Challenges): https://claude.ai/share/caba4ab0-b28a-480c-8633-71920b12999e
• XML: https://www.w3.org/XML/
• Python: https://www.python.org/
• RegEx: https://regex101.com/
• Moderna: https://www.modernatx.com/
• FDA: https://www.fda.gov/
• Project Gutenberg: https://www.gutenberg.org/
• FDA Biologics License Application: https://www.fda.gov/vaccines-blood-biologics/development-approval-process-cber/biologics-license-applications-bla-process-cber
• Protected health information (PHI): https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Prerna Kaul is a product and platform leader who has spent over 14 years turning machine-learning research into consumer and B2B products at Amazon Alexa, AGI, Moderna, and now Panasonic Well. In today’s episode, she explains how she’s using AI to slash some of the most time-consuming, expensive tasks in life sciences—from generating 60,000-page FDA submissions to crafting communication frameworks that help product managers navigate complex stakeholder dynamics. Her innovations are saving millions of dollars and helping lifesaving treatments reach the market faster.
What you’ll learn:
—
Brought to you by:
CodeRabbit—Cut code review time and bugs in half. Instantly: https://lovable.dev/
Lovable—Build apps by simply chatting with AI: https://lovable.dev/
—
Where to find Prerna Kaul:
LinkedIn: https://www.linkedin.com/in/prernakkaul/
—
Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
—
In this episode, we cover:
(00:00) Introduction to Prerna
(03:01) The FDA submission challenge: 60,000 pages, months of work, millions in costs
(05:20) Getting started in Claude: from prompt to production-ready prototype
(10:13) How Claude selected the right models for medical entity recognition
(12:04) Using Streamlit to create accessible UIs for non-technical users
(16:04) Detecting and redacting PHI in unstructured clinical notes
(18:44) Generating the Common Technical Document (CTD) for FDA submission
(21:54) Tracking and displaying AI operation costs for stakeholder buy-in
(24:38) Real-world impact on vaccine development timelines and costs
(26:12) Creating an AI communication coach for product managers
(30:22) Training Claude on classic literature and persuasion techniques
(31:53) Analyzing a complex stakeholder scenario with multiple competing priorities
(34:40) Getting personalized communication strategies inspired by tech leaders
(35:40) Summarizing strategic approaches
(38:26) Conclusion and final thoughts
—
Tools referenced:
• Claude: https://claude.ai/
• Streamlit: https://streamlit.io/
• Anthropic Console: https://console.anthropic.com/
• Claude Sonnet 4: https://www.anthropic.com/claude/sonnet
—
Other references:
• Claude project chat (AI Product Management Stakeholder Challenges): https://claude.ai/share/caba4ab0-b28a-480c-8633-71920b12999e
• XML: https://www.w3.org/XML/
• Python: https://www.python.org/
• RegEx: https://regex101.com/
• Moderna: https://www.modernatx.com/
• FDA: https://www.fda.gov/
• Project Gutenberg: https://www.gutenberg.org/
• FDA Biologics License Application: https://www.fda.gov/vaccines-blood-biologics/development-approval-process-cber/biologics-license-applications-bla-process-cber
• Protected health information (PHI): https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].