AIDDD Summit
Conference dates: October 27-28, 2026
Location: Boston Marriott Copley Place, Boston
Booth: F11-F12
Speaking sessions
Title: Accelerating AIDD Validation: From Sequence to Quality Data in 4 Days
Integrating Rapid Build with Carterra HT-SPR™ Technology for AI-Ready Data
Presenter:
Daniel Bedinger, PhD, Director of Application Science, Carterra
Hanying Luo, PhD, Director of Emerging Applications, GenScript
Date and Time: Wednesday, Oct. 28, 2026 | 12:00 – 12:00 pm
Abstract: The challenge in AI-driven drug discovery is increasingly shifting from designing candidates to generating high-quality experimental data at the speed, scale, and consistency required to learn from them. As design cycles accelerate, wet-lab validation must evolve from a downstream bottleneck into a scalable data engine that continuously feeds the Design–Build–Test–Learn cycle.
GenScript’s high-throughput validation engine integrates rapid protein production with multi-dimensional biological characterization to generate structured, AI-ready experimental data at scale. By combining cell-free protein production with Carterra’s high-throughput SPR technology, AI-designed sequences can progress from sequence to quantitative binding data in as few as 4 days. Carterra’s multiplexed SPR platforms enable label-free, high-throughput characterization of binding affinity and kinetics, supporting large interaction matrices with minimal sample consumption.
Together, ultra-fast protein production and quantitative HT-SPR characterization provide a scalable Sequence-to-Data workflow, enabling faster experimental feedback and more rapid iteration of AI-guided molecular designs.
Poster sessions
Poster Title: : 4 Day Sequence to Data: Accelerating AI Driven Protein Discovery via Integrated Cell Free Workflow
Abstract:
- The Challenge: Experimental Data Generation Lags Behind AI Design
AI driven protein and antibody design platforms can generate large candidate sets in minutes, yet experimental validation remains a major bottleneck in the Design Build Test Learn cycle. Delayed access to consistent,
high quality data slows candidate ranking and limits the iterative feedback needed to train and refine AI models.
- The Solution: 4 Day Sequence to Data with Integrated Cell Free Workflow
To address the expression and validation bottlenecks, we combine our proprietary cell free protein expression system with a comprehensive, integrated assay platform to deliver high quality, AI ready datasets starting within 4 calendar days. The platform provides rapid, multidimensional insights into binding kinetics and affinity, stability (DSF/ and developability (HIC and AC SINS), together with safety and PK relevant assessments such as BVP and ELISA based panels for polyspecificity and FcRn binding. Our digital integration solutions, including API and MCP connectivity, enable standardized data to flow directly into customer platforms and AI workflows. This high throughput workflow transforms sequence inputs into decision ready data for model training, candidate ranking, antibody development feedback, and iterative optimization throughout the AI driven discovery cycle.