Mosaic Biosciences Launches SortAI, a Purpose-Built Wet Lab Validation Service for AI-Designed Antibody Libraries

Yeast-based screening platform closes the AI-to-candidate gap by delivering training-ready biological data before a single recombinant protein is produced

BOULDER, CO, UNITED STATES, May 26, 2026 /EINPresswire.com/ -- Mosaic Biosciences, a consultative contract research organization (CRO) specializing in antibody and protein discovery and engineering, today announced the commercial launch of SortAI, a yeast display-based validation service designed specifically for AI-generated antibody sequence panels. SortAI enables AI drug discovery companies to screen model derived libraries, before committing full recombinant protein production, and returns structured experimental data that feeds directly back into model retraining.

The Bottleneck AI Drug Discovery Can't Ignore

Generative AI platforms are transforming antibody drug design, producing campaigns of hundreds of thousands to millions of computationally designed sequences per cycle. Yet the infrastructure built to validate those sequences was designed around traditional single-candidate drug programs: full recombinant expression on every sequence, one at a time.

The result is a compounding problem: slow cycles, wasted production budget, and models that cannot improve until the wet lab catches up. Typical CROs produce and characterize whatever sequence list arrives in their inbox. SortAI filters it first.

"Generative models can produce thousands of antibody candidates. Wet labs can validate a fraction of them. Sort AI triages AI-generated libraries at scale so your best sequences get tested first and nothing falls through."

- Eric Furfine, PhD, Chief Scientific Officer, Mosaic Biosciences

One Engagement. The Full Triage Picture. SortAI delivers a complete triage picture in a single defined engagement:

- Sequence liability review at intake: Mosaic scientists screen panels for CDR liabilities, aggregation motifs, poor expression signals, and other flags. Bad
sequences are removed before they waste wet lab capacity.

- Yeast-based selection at library scale: Multi-round selection across panels ranging from hundreds to over millions of sequences, with next-generation
sequencing (NGS) at each round to track full population dynamics.

- Negative data returned as a deliverable: Every selection round generates a negative population. SortAI sequences and returns those alongside ranked
positive binders because what didn't bind is half the training signal.

- Function pulled forward: Candidates that pass binding are immediately pressure-tested through cell-based functional screening, before expensive
downstream development work begins.

- Binding, affinity, epitope binning, developability, and function together: A complete discovery funnel in a single engagement, with deliverables
structured for model retraining rather than drug program documentation.

Faster Cycles. A Fraction of the Cost.
A production-centric competitor workflow covering binding and affinity alone requires approximately 7 weeks and costs significantly more than a full SortAI engagement which extends through developability profiling and cell-based functional screening. Sequence enrichment for model training is available as early as 6 weeks from project initiation; a full engagement completes in approximately 14 weeks.

The yeast display platform underpinning SortAI scales to 107 sequence diversity: three orders of magnitude beyond the throughput of production-centric validation workflows enabling functional triage at the true scale of AI-generated libraries.

"The value of AI-driven antibody discovery ultimately depends on the quality of the experimental data used to refine subsequent design cycles. SortAI was designed to maximize signal quality at true library scale, enabling rapid iterative learning without compromising throughput."

- Tracey Mullen, Chief Strategy Officer, Mosaic Biosciences

Built on Demonstrated Capability.
SortAI is backed by Mosaic's team of 50+ scientists, 80% holding advanced degrees and more than 216 completed discovery programs. The yeast display workflow that powers SortAI has already demonstrated results in library-based screening engagements that competing CROs were unable to accommodate.

The platform was first introduced publicly at PEGS Boston 2026 and is now available as a defined commercial service. Detailed pricing and scope information is available upon request under NDA.

More information is available at mosaicbio.com/see-sortai

About Mosaic Biosciences
Mosaic Biosciences is a consultative, end-to-end antibody and protein discovery CRO headquartered in Boulder, CO. With fully integrated in vivo and in vitro discovery capabilities including the Atlas FHD™ mouse platform, phage and yeast display, and Tessaic™ fully human VHH libraries. Mosaic partners with biotechs, pharmaceutical companies, and AI drug design platforms to deliver decision-grade candidates with predictable outcomes. 100% of Mosaic's research is conducted in the United States.

Chrissy Conti
Mosaic Biosciences
chrissy@mosaicbio.com
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