Innovations in artificial intelligence (AI) and machine learning (ML) are poised to revolutionize the biopharmaceutical industry by integrating laboratory processes. A webinar scheduled for November 5, 2025, will feature experts discussing the vital connection between wet lab experimentation and dry lab modeling. The event is set to commence at 08:00 PST (11:00 EST, 16:00 GMT) and aims to address challenges that hinder the effective application of AI in life sciences research and development.
Milton Yu, PhD, who leads the automation and analytics strategy at Benchling, and Sandy Li, PhD, who oversees scientific AI and ML market strategy at the same company, will share insights on how to create robust data foundations essential for AI applications. Both experts bring extensive backgrounds in biotechnology and data management to the discussion. Yu has a PhD in cell biology from Baylor College of Medicine and previously held significant roles at AWS and Microsoft, while Li earned her PhD in chemical and biomolecular engineering from UCLA and has held leadership positions at Baidu Ventures.
The core challenge for many biopharma organizations is the fragmentation of data systems, which leads to inefficient manual processes that limit scientists’ access to high-quality data. This barrier prevents wet lab scientists from effectively testing insights generated from computational models. The upcoming webinar aims to demonstrate how Benchling’s technology can transform raw instrument outputs into structured, contextualized data that is ready for analysis and AI model training.
Key Learning Objectives for Attendees
Participants will gain critical knowledge on several key topics during the webinar. These include:
– **Requirements for Automating AI-Ready Wet Lab Data**: Understanding how to streamline data collection to enhance model accuracy.
– **Embedding Dry Lab Models into Experimental Workflows**: Learning methods for integrating computational models directly into laboratory practices.
– **Creating a Continuous Wet Lab/Dry Lab Feedback Loop**: Exploring practical approaches to ensure seamless communication between experimental and computational teams.
– **Insights from Leading Biopharma Organizations**: Hearing real-world examples of how companies are advancing AI-driven research and development with Benchling’s support.
The session will conclude with a live Q&A, allowing attendees to engage directly with the expert panelists and deepen their understanding of AI integration in biopharma.
By addressing the challenges of disconnected data systems and manual processes, this initiative represents a significant step towards a more integrated approach in biopharma research. The collaboration between wet lab scientists and computational experts is crucial for leveraging AI to enhance drug discovery and development processes, ultimately improving outcomes in patient care.
This webinar is expected to attract a diverse audience from the life sciences field, providing valuable insights into the future of research and development in biopharma. Those interested in participating can register for the event and take part in discussions that could shape the future of AI in the industry.
