Adaptyx Biosciences, a next-generation biotech startup pushing the boundaries of antibody discovery, has raised $14 million in Seed funding to expand its AI-driven molecular discovery platform and accelerate therapeutic antibody development. The round was led by Interlagos, with participation from Overwater Ventures, Starbloom Capital, Stanford University, Chan Zuckerberg Biohub, Hyperlink Ventures, Cantos Ventures, Humba Ventures, and Seaside Ventures.

This new capital will empower Adaptyx to scale its platform  -  which blends computational modeling, adaptive learning, and wet-lab validation  -  enabling a faster, smarter, and more efficient pipeline for therapeutic discovery.

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Engineering the Next Evolution of Antibody Discovery

At its core, Adaptyx Biosciences is reimagining how scientists discover antibodies  -  moving from slow, linear experimentation to a closed-loop adaptive AI model that continuously learns and refines hypotheses. This shift doesn’t just speed up the process; it reshapes how biological data interacts with machine intelligence.

Traditional antibody discovery often involves months of lab work, uncertain success rates, and limited scalability. Adaptyx’s platform, on the other hand, uses predictive modeling and generative AI to design optimal antibody candidates, simulate their structure and binding properties, and prioritize high-probability candidates for physical testing.

This integration of AI with molecular biology has the potential to reduce discovery timelines from years to months, accelerating how new treatments are found and brought to patients.

“Our goal is simple yet ambitious  -  to make therapeutic antibody discovery as programmable and adaptive as modern software engineering,” said Vijit Sabnis, Founder and CEO of Adaptyx Biosciences. “We’re entering an age where biology and computation converge, and our platform sits at that intersection.”

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The Rise of Adaptive Intelligence in Biotech

Adaptyx’s approach represents a broader trend reshaping biotechnology: the rise of adaptive intelligence  -  systems that learn dynamically from experimental feedback.

Unlike static machine learning models, adaptive AI continuously incorporates new data to improve accuracy in real-time. In the context of antibody engineering, that means every failed experiment becomes a new source of learning, making the next iteration smarter and more efficient.

This concept is transforming how biotech startups think about data pipelines, model tuning, and molecular iteration. Instead of massive one-off training datasets, the future lies in adaptive, self-improving loops  -  exactly what Adaptyx has built.

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The Power of Tight Loops

Many early-stage biotech founders over-index on building the “perfect” dataset before deploying AI. What makes Adaptyx stand out  -  and what others can learn from  -  is the focus on iterative velocity over data volume.

By designing feedback loops that constantly refine both biological data and model weights, Adaptyx has achieved compounding improvement instead of static accuracy.

For founders across any sector  -  biotech, AI, or deep tech  -  this principle is gold: shorten your feedback loops, and you accelerate both learning and product-market fit.

Adaptyx’s structure mirrors how elite software teams operate  -  deploy, test, learn, and refine rapidly. In biotech, that mindset could compress timelines from a decade to just a few years.

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A Strategic Web of Investors with Deep Scientific Roots

The diversity of investors in this Seed round signals confidence not just in Adaptyx’s tech, but in its scientific and translational potential.

• Stanford University and Chan Zuckerberg Biohub bring research credibility and direct access to top-tier academic collaboration.
  
• Interlagos, Overwater Ventures, and Starbloom Capital provide deep capital and expertise in AI, life sciences, and scaling deep-tech startups.
  
• Cantos Ventures and Hyperlink Ventures add early-stage support networks experienced in high-risk, high-reward frontier innovation.
  

This mix of academic partnerships and venture capital positions Adaptyx as one of the most promising biotech entrants of 2025  -  blending rigorous science with scalable business execution.

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Building a Smarter Biotech Future

At a time when drug development costs exceed $2.6 billion per approved therapy (Tufts Center for the Study of Drug Development), and timelines average 10–15 years, innovation like Adaptyx’s is not just valuable  -  it’s essential.

The company’s platform represents a structural shift in how life sciences can operate: combining AI’s predictive power with human intuition and biological insight. By making discovery faster, cheaper, and more precise, Adaptyx is helping to democratize innovation  -  unlocking opportunities for smaller labs, academic teams, and mid-market biopharma players.

In a field where inefficiency often kills innovation before it matures, Adaptyx is rewriting the rules of what’s possible.

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Industry Outlook: The AI-Biotech Convergence Accelerates

The intersection of artificial intelligence and biotechnology is now one of the most transformative arenas in global innovation. According to McKinsey, the AI-biotech market is projected to surpass $130 billion by 2030, growing at a CAGR of 35%, driven by demand for faster drug discovery and precision medicine.

Major pharmaceutical companies like Pfizer, Novartis, and Amgen have already established internal AI discovery divisions or partnerships with AI-first biotech startups. Yet, smaller, agile companies like Adaptyx are setting the pace  -  unburdened by legacy systems and able to build AI-native workflows from the ground up.

Additionally, antibody therapeutics continue to dominate the biotech pipeline, representing over 20% of all new biologic approvals in 2024 (Evaluate Pharma). As biologics expand into autoimmune, oncology, and rare disease markets, platforms like Adaptyx’s adaptive engine could cut preclinical discovery times by over 60%, redefining the economics of therapeutic innovation.

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What’s Next for Adaptyx Biosciences

With its new funding, Adaptyx plans to:

• Expand its computational biology team and deepen its AI discovery capabilities.
  
• Launch strategic collaborations with academic and pharma partners.
  
• Advance its antibody discovery pipeline targeting high-impact therapeutic areas.
  
• Build automated wet-lab infrastructure to scale its feedback-driven R&D engine.
  

This next phase will position Adaptyx not just as a biotech startup, but as a full-stack molecular intelligence company capable of transforming the entire discovery-to-delivery pipeline.

“Our vision is to create an ecosystem where every experiment teaches the system something new,” said Sabnis. “That’s how biology should work  -  adaptive, efficient, and deeply intelligent.”

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Final Thoughts: Rewriting the Code of Discovery

Adaptyx Biosciences is not simply another biotech venture; it represents the evolution of scientific thinking  -  merging computational power with biological intuition to create a new paradigm of discovery.

By focusing on adaptive intelligence, the company has positioned itself to lead the next wave of biotech  -  one where algorithms don’t replace scientists, but augment their creativity and speed.

As the biotech industry enters this new phase of convergence, Adaptyx’s story underscores a timeless lesson: innovation happens fastest when feedback loops are shortest and learning never stops.

This $14 million Seed round marks the beginning of that revolution  -  and Adaptyx is at the forefront.