Main Conference Day 3Wednesday, 17 December 2025 - PT (Pacific Time, GMT-08:00)

My group engineers genetic systems that dramatically accelerate the speed of mutation and gene evolution in vivo so that we can drive the rapid evolution of new biomolecular functions and prospectively watch (and systematically manipulate) the course of long gene evolutionary processes on laboratory timescales. I will share recent developments in the use of our continuous evolution system, orthogonal DNA replication system (OrthoRep), to evolve antibodies. I will discuss our efforts to affinity mature antibodies at scale along with the intersection of computational antibody design and evolution, including work focusing on prioritizing sequence space exploration to generate data for training computational models.

We developed a novel functional screening method using hyperphage display platform that allows rapid discovery of potent antiviral single domain antibodies. We benchmarked RASP against established phage ELISA and deep sequencing methods. RASP can be used either as a standalone platform or seamlessly integrated with conventional screening methods to accelerate the discovery of antiviral VHHs.

We present JAM, a protein design system capable of designing antibodies de novo with therapeutic-grade affinities, function, and early-stage developability for soluble and multipass membrane protein targets. For GPCRs, we show de novo designed antibodies have single-digit nM to picomolar binding affinities, and while most are functional antagonists, remarkably, a subset are agonists -- marking an important milestone in the field.

Therapeutic protein engineering has been transformed by the incorporation of big data and AI/ML techniques. An emerging challenge for this field is how to efficiently leverage the right data and the best models to drive meaningful results and resolve long-standing bottlenecks. Amgen has incorporated a generative biology approach to tackle complex engineering problems, aiming to deliver better, more effective molecules across every therapeutic program.

This talk will share updates from the AIntibody competition, a benchmarking initiative engaging the biotech, pharma, academia, and AI communities to use AI and other informatic methods to design or identify developable antibodies with high affinities, from curated NGS datasets. Results will compare the properties of these antibodies with those derived using experimental methods, providing insights into the value of AI in antibody discovery. AIntibody announcement manuscript: Erasmus, M. F. et al. Nat Biotechnol 42, 1637-1642 (2024).