Developability assessment in discovery is crucial and requires different combinations of tools
Affinity on-demand: hitting your desired affinity while maintaining crucial properties – now possible with our AI-centric workflow
Get to any affinity you want -- up or down from the parental molecule
Maintain/optimize developability/immunogenicity profiles
Fast turn-around
Proprietary AI model that can search an ultra-large mutant space in the 1025
High-accuracy affinity & developability prediction algorithms
High-throughput make & test system that gives quick feedback
Case 1
Improving the affinity of an undisplayable proteinGoal: affinity maturation for a modular protein that's not compatible with display systems
Optimized affinity by 13-fold with 2 mutants that contain 3-4 point mutations
2 rounds of design-make-test of 60 mutants to obtain 9 with >3-fold improved affinity
Case 2
Bi-directional affinity tuning of a lead antibodyGoal: tuning the affinity of a lead antibody both upwards and downwards to provide more options for bispecifics development
Our AI model generated 3 buckets of designed mutants with predicted affinities of:
1) significant increase (target: 10x),
2) mild increase (target: 3x) and
3) mild decrease (target: -3x) vs. WT
1) significant increase (target: 10x),
2) mild increase (target: 3x) and
3) mild decrease (target: -3x) vs. WT
When expressed and tested, these mutants show affinities that correspond to their targeted ranges. (Shown on the right)
1 round of design-make-test of 96 mutants to arrive at a panel of highly optimized leads with KD that span 3 orders of magnitude and optimal developability profiles
XtalPi is keenly aware that every research partner has unique needs and priorities, and is happy to create a customized solution to optimize your research program
