Training Seminars
Training Seminars Will Be Held In-Person Only
To ensure a cohesive and focused learning environment, moving between conference sessions and the training seminars is not allowed
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Training Seminars
Monday, January 19, 2026 8:30 AM – 5:00 PM
TS7A TS7A: AI-Driven Design of Biologics: A Hands-On Guide to Using State-of-the-Art ML Protein Models
Since 2021, artificial intelligence models have revolutionized AI-driven biologics development, enabling breakthroughs in structure prediction, sequence design, and protein engineering. This course equips researchers and professionals with the expertise to leverage cutting-edge tools for structure prediction (AlphaFold, ImmuneBuilder), protein engineering with protein language models (ESM, AntiBERTy), and structure-based design (ProteinMPNN and RFDiffusion). Through a blend of lectures and hands-on exercises, participants will learn best practices for tool selection, method optimization, and design selection. By exploring real-world applications and emerging techniques, such as BindCraft and RFAntibody, attendees will gain a practical understanding of performance capabilities, limitations, and effective workflows.
AI-Driven Design of Biologics: A Hands-On Guide to Using State-of-the-Art ML Protein Models
David P. Nannemann, PhD, Vice President, Rosetta Commons Foundation
Jannis de Riz, Graduate Student, University of Leipzig
Participants are expected to have some prior exposure to computational modelling tools (e.g. Python, R, COOT, Rosetta, AutoDock Vina, etc.) but limited experience applying them to their projects. They should be comfortable using Jupyter notebooks and prepared to explore topics such as evaluating metrics, determining appropriate sampling sizes, and selecting key adjustable parameters. While this seminar does not cover ligand docking or protein-protein docking, it is well-suited for those interested in antibody modeling and, potentially, enzyme design language models.
Hands-on instructional content will be presented as Google Colab notebooks written in python. A basic understanding of general coding principles, such as typing, loops, functions, and classes, will be sufficient. It will not be required to write your own code from scratch, but a sufficient familiarity with python to understand and edit the provided notebooks will be essential to a meaningful experience.
Topics to be covered:
- Building practical experience with AI-based modelling of proteins
- A breakdown of input formats, command lines, and analysis of output
- Hands-on exercises using real-world scenarios in antibody structure prediction, developability pre-screening, immunogen solubilization, and de novo binder design
- Discussion of, and guidance on, questions like: how many models, in silico selection metrics and ranking, and how many to test in the lab
- Pipelining of protein design software and the critical use of an “oracleâ€
INSTRUCTOR BIOGRAPHIES:
David is an expert in protein engineering and computational design, with extensive experience applying AI-driven modeling tools in an industry setting. He serves as Vice President of the Rosetta Commons Foundation and Industry Chair on the Rosetta Commons board, helping bridge academic advancements with industry applications. As Managing Member of Rosetta Design Group, he collaborates with companies of all sizes to tackle complex challenges in biologics design. David's deep expertise in leveraging cutting-edge tools like Rosetta, AlphaFold, and diffusion-based models for protein design make him an invaluable guide for participants looking to apply AI-driven biologics design in real-world settings.
I am a PhD student co-advised by Torben Schiffner and Jens Meiler. I work on Computational and experimental High-Throughput Characterization of Protein-Protein Interactions.
TS8A TS8A: Introduction to Antibody Engineering for ML/AI Scientists
In this training seminar, designed for ML/AI students wishing to learn more about antibodies, students will learn about antibody basics, including the antibody therapeutic market, structure, genetics, and the generation of diversity, as well as the generation of potential therapeutic antibodies. This latter part will include antibody humanization, affinity and specificity maturation, display technologies, creation of naïve libraries, and antibody characterization. The seminar will be fully interactive with students providing ample opportunities to discuss technology with instructors.
Introduction to Antibody Engineering
Andrew R.M. Bradbury, MD, PhD, CSO, Specifica, an IQVIA business
Topics to be covered:
Antibody BackgroundÂ
- StructureÂ
- GenesÂ
- Generation of diversity (recombination, somatic hypermutations)Â
Antibody Humanization​ Â
- Closest human gene approach Â
- Minimal modification approach Â
- VeneeringÂ
Display Technologies OverviewÂ
- Phage Â
- Yeast Â
- Combining phage and yeast display Â
- Ribosome Â
- Others Â
Generation of Naïve Antibody Libraries ​Â
- Natural libraries (methods, quality control)Â Â
- Synthetic libraries (including strategies for generation diversity)Â Â
- Affinity Maturation ​Â
- Error-prone PCRÂ Â
- Chain shuffling Â
- CDR-targeted mutations Â
Next-Generation Sequencing in Antibody EngineeringÂ
- Platforms: advantages and disadvantages Â
- Error rates and why they are important Â
- Naïve library diversity analysisÂ
- Selection analysis Â
Antibody Characterization and Developability ​Â
- Expression Â
- Specificity Â
- Aggregation
- Solubility​
INSTRUCTOR BIOGRAPHIES:
Andrew Bradbury is Chief Scientific Officer of Specifica. He trained in medicine at the universities of Oxford and London and received his PhD from the university of Cambridge at the MRC Laboratory of Molecular Biology under the guidance of Nobel Laureate, Cesar Milstein. He has worked in the fields of phage and yeast display, library generation, antibody engineering and Next Generation Sequencing for over thirty years. He was a Group Leader at Los Alamos National Laboratory before founding Specifica. Specifica's mission is to enable companies developing therapeutic antibodies with the world’s best antibody discovery platform.
Dr. Marks is Professor and Vice-Chairman of the Department of Anesthesia and Perioperative Care at the University of California, San Francisco (UCSF) and Chief of Performance Excellence at Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG). Dr. Marks received his medical degree from UCSF where he also completed residencies in Internal Medicine and Anesthesia and a fellowship in Critical Care Medicine. He received his Ph.D. in molecular biology from the Medical Research Council Laboratory of Molecular Biology in Cambridge, England. Dr. Marks is an internationally recognized pioneer in the field of antibody engineering, has had constant federal funding for 27 years and has authored more than 200 publications and 100 patents. In recognition of these scholarly achievements, he was elected to the National Academy of Medicine. As an entrepreneur, he has co-founded four biotechnology companies and currently serves on three biotechnology corporate boards.
