A commercial biologic may be protected by patents covering formulations, dosing regimens, methods of treatment, manufacturing and purification processes, delivery systems, and other product attributes. That means for biologics, expiration of the foundational composition-of-matter patent rarely determines when patent protection effectively ends or biosimilar competition can begin. This makes a comprehensive patent landscape.

Today, AI is changing the scale and speed patent landscape analysis. Used thoughtfully, AI-assisted tools can help teams identify related patent families, organize claims by subject matter, compare claim scope, track legal status and expiration dates, and uncover relationships that might otherwise remain buried in large datasets. But faster analysis is not necessarily more reliable analysis. Incomplete data, inconsistent family relationships, jurisdictional differences, and poorly framed questions can produce results that appear comprehensive while overlooking patents or claims that materially affect strategy.

Join us on Thursday, November 19, at 12 PM ET, for a substantive discussion about how originator companies, biosimilar developers, and their counsel can use AI for decision-ready intelligence. Panelists will examine what AI has changed in practice, where it can make the greatest difference, and how organizations can validate the resulting analysis before relying on it for consequential legal and business decisions.

Following introductory remarks from IPWatchdog Founder and CEO Gene Quinn, Edmund Koundakjian*, J.D., Ph.D., of Mintz, and Sunny Malhotra, Ph.D., J.D., Senior Counsel, IP, Novo Nordisk will provide outside-counsel and in-house perspectives. The conversation will be co-moderated by Josephine Garban, Ph.D., Legal Engineer and IP Counsel at Patlytics, and Candice Kwark, Legal Engineer and IP Counsel at Patlytics.

Topics will include:

• Constructing a comprehensive biologics patent landscape that extends beyond composition-of-matter protection;
• Using AI to identify and map patent families, organize claims, compare scope, track legal status, and monitor an evolving global portfolio;
• Distinguishing patents that may materially affect a commercial product or proposed biosimilar from results that are merely technically related;
• Adapting the analysis to different objectives, including lifecycle management, loss-of-exclusivity planning, freedom to operate, biosimilar entry, licensing, and dispute preparation;
• Identifying where AI can materially reduce manual effort and where legal, scientific, and technical judgment remains indispensable;
• Evaluating how data quality, verification, and human review affect the reliability of AI-assisted conclusions; and
• Translating patent landscape intelligence into actionable portfolio and commercial strategy.

Attendees will leave with a practical framework for evaluating AI-assisted biologics patent analysis and incorporating verified results into life sciences IP strategy.

*Edmund Koundakjian’s views are his own and not those of Mintz.