AI and Predictive Modeling in Small Molecule Formulation and Process Development

Is AI truly accelerating small molecule manufacturing, or are most teams still chasing the hype?

Register Free: https://www.pharmtech.com/pt_w/predictive-modeling

Event Overview:

This conversation will explore the real-world impact of AI in small molecule formulation and process development, separating tangible progress from industry hype. The discussion will focus on where AI is genuinely accelerating timelines, the data requirements needed to make it effective, and how its outputs can be justified in a GMP and regulatory context. It will also examine the most practical use cases emerging today, common pitfalls companies encounter when adopting AI, and how organizations can integrate these tools without disrupting established workflows. Ultimately, the conversation will look ahead to what will distinguish companies that successfully operationalize AI from those still struggling to translate potential into meaningful results.

Key Learning Objective:

• Understand where AI is delivering real, measurable value in small molecule formulation and process development and where is not
• Recognize the data requirements and limitations that determine whether AI models succeed or fail in CMC environments
• Learn how AI-driven insights can be justified, documented, and defended within GMP and regulatory frameworks
• Identify the most actionable and "AI-ready" use cases across formulation , process development, and scale-up
• Avoid common implementation pitfalls that slow adoption or lead to wasted investment without disruption
• Anticipate the capabilities and organizational approaches that will define successful AI adoption over the next 3-5 years

Who Should Attend:
This Drug Digest episode is best suited for professionals directly involved in small molecule development and manufacturing, especially those evaluating or implementing new technologies

• Formulation scientists and process development chemists working on optimization and scale-up
• CMC leaders and technical operations teams responsible for development strategy and execution
• Manufacturing and plant managers focused on efficiency, robustness, and tech transfer
• Quality and regulatory professionals navigating GMP expectations for emerging technologies
• Data scientists and digital/innovation leads supporting AI modeling initiatives in pharma
• CDMO executives and business development teams looking to align capabilities with sponsor demand
• R&D and portfolio strategy leaders assessing where AI can create competitive advantage

Register Free: https://www.pharmtech.com/pt_w/predictive-modeling