Cambridge Healthtech Institute’s 4th Annual

Machine Learning for Protein Engineering Part 1

Advancing Protein Engineering with AI: Next-Generation Models, Data Strategies, and Applications

12 November 2025


The 2025 Machine Learning for Protein Engineering Part 1 conference will explore the expanding role of AI and ML in revolutionising protein design and optimisation. This conference will cover key advancements in algorithm development, model evaluation, and data-driven decision-making, providing researchers with tools to enhance predictive accuracy and experimental efficiency. Attendees will gain insights into the challenges of working in low-data environments, the integration of active learning strategies, and the evolution of multimodal models. Discussions will also extend to cutting-edge applications, from clinical biology to modeling undruggable targets, highlighting how ML is shaping the future of biologic discovery and therapeutic development.

Coverage will include, but is not limited to:

The ML Model and Algorithm Toolkit

  • Dashboards and ecosystems for model deployment
  • Experiment tracking for AI/ML projects
  • Method development for new models and algorithms
  • Models 101: evaluation, evolution, architecture, training, and validation
  • Multimodal models
  • The value of adopting (or not) new foundation models and versions

Active Learning and Training Data Generation

  • Achieving biological ML in a low-data environment
  • Design of active learning experiments (design-build-test-learn)
  • Evaluating data needs; how much and what kind, how much is enough
  • Fine-tuning models with training data
  • The roles of public domain, consortia, and internally developed datasets
  • Use cases of closed loop data and model evolution for de novo design and optimisation projects

Next Generation Applications of AI/ML

  • Design and engineering of complex antibody modalities
  • Enabling applications in clinical biology
  • Extending de novo design and optimisation to non-antibody biologics
  • Knowledge graphs for predicting target combinations
  • Modeling with cryoEM structure data
  • Solving undruggable targets
  • Target identification and validation

The deadline for priority consideration is 28 March 2025.

All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Healthtech Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.

Opportunities for Participation:


For more details on the conference, please contact:

Kent Simmons
Senior Conference Director
Cambridge Healthtech Institute
Phone: (+1) 207-329-2964
Email: ksimmons@healthtech.com

For sponsorship information, please contact:

Companies A-K
Jason Gerardi
Sr. Manager, Business Development
Cambridge Healthtech Institute
Phone: (+1) 781-972-5452
Email: jgerardi@healthtech.com

Companies L-Z
Ashley Parsons
Manager, Business Development
Cambridge Healthtech Institute
Phone: (+1) 781-972-1340
Email: ashleyparsons@healthtech.com