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Latent-Y: The Autonomous AI Agent for Drug Design at Scale

Today, Latent Labs launches Latent-Y, an AI agent that autonomously designs therapeutic antibodies from a text prompt, compressing weeks of expert work into hours. Powered by Latent-X2, Latent Labs' f...

Immagine
  • Scalable, parallel drug design: one researcher can run multiple campaigns simultaneously across targets and modalities
  • From research goal to lab-ready sequences in hours: Latent-Y compresses weeks of expert work into autonomous design campaigns
  • Lab-validated results across three antibody design campaigns: achieving a 67% target-level success rate with single-digit nanomolar affinities-without human filtering or intervention
  • Powered by Latent-X2: drug-like antibodies with drug-like developability, enabling difficult targets and complex designs

LONDON & SAN FRANCISCO: Today, Latent Labs launches Latent-Y, an AI agent that autonomously designs therapeutic antibodies from a text prompt, compressing weeks of expert work into hours. Powered by Latent-X2, Latent Labs' frontier model for drug-like antibody and peptide design, Latent-Y brings structural drug design to any researcher - no specialist infrastructure required. Latent Labs is opening access to selected partners.

Latent-Y is a force multiplier for drug discovery teams. It operates in the same environment as protein design experts, with access to bioinformatics tools, biological databases, and external publications, applying expert-level reasoning to navigate from research objective to lab-ready candidates. A single researcher can now run multiple design campaigns in parallel, across targets and modalities, each progressing autonomously.

How Latent-Y Works

Give Latent-Y a therapeutic goal specified in natural language, a research work plan, or even a scientific publication, and it proceeds from there. The agent analyses the target molecules, applies biological reasoning to identify viable epitopes, designs antibody candidates using Latent-X2, validates them computationally, and iterates until the design goals are met.

Scientists remain in control throughout. Latent-Y can run fully autonomously end-to-end or pause at each stage to surface progress summaries and recommended next steps for expert review. Every design decision is recorded reasoning that scientists can evaluate, challenge, and build on.

Lab-Validated Results

Latent-Y has demonstrated biological reasoning with lab-validated success across three distinct antibody design campaigns, without human filtering or intervention:

  • Epitope discovery: Applying biological reasoning to identify epitopes matched to therapeutic specifications, yielding lab-confirmed VHH binders with single-digit nanomolar affinities.
  • Cross-species binder design: Generating antibodies that bind homologous targets across species for translational studies. To execute this campaign, Latent-Y autonomously extended its own capabilities, implementing a custom generative method from a brief natural language description to solve a design challenge it had not been explicitly built for.
  • Design from publication: Processing a peer-reviewed scientific paper to autonomously design antibodies targeting human transferrin receptor (hTFR1) for blood-brain barrier crossing.

In each case, Latent-Y handled the full workflow autonomously, representing the first demonstration of a generalizable protein design agent with lab-validated results across diverse campaign types.

Productivity at Scale

Latent-Y compresses what would take expert teams weeks into hours of autonomous work. In user studies, PhD-level experts working with Latent-Y completed design campaigns 56 times faster than independent expert time estimates. Unlike manual workflows, it can run many campaigns simultaneously. Drug discovery organisations can now pursue more targets, more design strategies, more exploration, with the same resources.

"Latent-X2 gave us the breakthrough: antibodies designed computationally with drug-like developability. Latent-Y builds on that foundation with an expert reasoning layer that handles the full workflow autonomously. The result is speed and scale that weren't possible before - a single researcher running dozens of campaigns in parallel. This is what it looks like when AI becomes a true force multiplier for discovery teams," said Simon Kohl, CEO and founder of Latent Labs.

Access

Latent-Y will be available to selected partners through the Latent Labs platform. Interest for access can be expressed at partnerships@latentlabs.com.

You can read the full technical report here.

Fonte: Business Wire

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