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Red Queen Bio

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  • QualityRated 55 but structure suggests 87 (underrated by 32 points)
DimensionAssessmentEvidence
Focus AreaAI-enabled biothreat countermeasuresMaps AI-enabled biothreats with frontier labs and pre-builds medical countermeasures1
Founded2025 (launched November 2025)Spun out of HelixNano, a clinical-stage mRNA therapeutics company2
StructurePublic Benefit Corporation (PBC)Governance ensures mission precedence over individual partnerships1
Funding$15M seed round led by OpenAIAdditional investors: Cerberus Ventures, Fifty Years, Halcyon Futures, Dhuna Ventures, LongeVC23
Core Thesis”Defensive co-scaling”Scale biological defenses proportionally with advancing AI capabilities1
HeadquartersBoston, MACo-located with HelixNano operations4

Red Queen Bio is an AI biosecurity Public Benefit Corporation founded in 2025 by Nikolai Eroshenko and Hannu Rajaniemi, who previously spent nearly a decade together as co-founders of HelixNano, a clinical-stage mRNA therapeutics company.12 The company emerged from a collaboration with OpenAI in which the founders observed that frontier AI models displayed “remarkable biological creativity” — leading them to conclude that safe scaling of AI biology required new defensive infrastructure.1

The company’s core thesis is defensive co-scaling for biology: rather than merely using AI for biodefense, Red Queen Bio aims to couple “defensive compute and funding to the same technological and financial forces that drive the capability race.”1 The name derives from the Red Queen hypothesis in evolutionary biology (proposed by Leigh Van Valen in 1973 and named after Lewis Carroll’s character), which holds that species must constantly adapt and evolve just to maintain their relative fitness against ever-evolving opponents.5

Red Queen Bio launched in November 2025 with a $15 million seed round led by OpenAI, making it one of the first major investments by an AI lab directly in biosecurity infrastructure.2 The company is structured as a Public Benefit Corporation with governance designed to ensure its mission takes precedence over any individual partnership, and it is committed to open collaboration with all AI labs, biopharma companies, and governments.1

HelixNano was founded in 2013 by Hannu Rajaniemi and Nikolai Eroshenko to develop next-generation mRNA technologies, initially focused on cancer vaccines.6 The company pivoted to COVID-19 vaccine development in March 2020 and advanced to clinical-stage mRNA therapeutics.7

During their work at HelixNano, the founders increasingly incorporated AI into drug-design workflows. A collaboration with OpenAI to develop tests for evaluating AI-related biological risks proved pivotal: the founders saw firsthand how capable frontier models had become at biological reasoning, and recognized that the defensive side of the equation was not keeping pace.2

Red Queen Bio was spun out of HelixNano in 2025, with the founders retaining their HelixNano roles while launching the new biosecurity venture.1 The spin-out was motivated by the recognition that:

  1. Frontier AI models demonstrate significant biological capability that will continue to advance
  2. Defensive biological infrastructure (countermeasures, surveillance, response) lags behind
  3. The business model for biosecurity needed innovation — borrowing from frameworks like catastrophic risk insurance8
  4. Defensive capabilities needed to be structurally linked to the same scaling dynamics driving AI advancement

The concept of defensive co-scaling represents Red Queen Bio’s central strategic framework. OpenAI Chief Strategy Officer Jason Kwon described it as “scaling the defensive capabilities of complementary technologies by linking them to the scaling of AI.”9

The approach has three key elements:

1. Threat Mapping: Working directly with frontier AI labs to identify emerging biological threats that advanced AI could enable. This means understanding not just current risks but anticipating how capability improvements could create new threat vectors.1

2. Pre-built Countermeasures: Rather than responding to biological threats after they emerge, Red Queen Bio aims to pre-build medical countermeasures against threats identified through the mapping process. The countermeasure design pipeline uses leading AI models, lab automation, and reinforcement learning.1

3. On-demand Manufacturing: Together with on-demand biologics manufacturing capabilities, the full technology stack aims to provide the foundation for matching defensive capability growth to offensive capability growth.1

Red Queen Bio’s technical approach integrates:

ComponentFunction
Frontier AI modelsBiological threat identification and countermeasure design
Lab automationExperimental validation and rapid prototyping
Reinforcement learningIterative optimization of countermeasure candidates
On-demand biologics manufacturingRapid production of validated countermeasures

The company is expanding into an integrated AI-wet lab pipeline aimed at detecting vulnerabilities earlier, validating them experimentally, and strengthening the broader biodefense ecosystem.10

On January 8, 2026, Red Queen Bio announced a therapeutic antibody discovery partnership with AbTherx, combining AbTherx’s Atlas Full Human Diversity Transgenic Mouse platform with Red Queen Bio’s vaccination and AI-driven antibody development pipeline.11

Key details:

  • Partnership generated “high-quality, AI-ready data in less than three months”
  • Focuses on antibodies against targets selected by Red Queen Bio
  • Red Queen Bio retains rights to develop and commercialize resulting therapeutic antibodies
  • AbTherx receives research payments and is eligible for development milestones and royalties11

The Atlas mouse platform was engineered to capture >99% of the expressed human VH and VK allele repertoire, generating broadly human-like antibody responses.11

InvestorRoleDetails
OpenAILead investorFirst major AI lab biosecurity investment2
Cerberus VenturesParticipantMission-aligned investor2
Fifty YearsParticipantImpact-focused VC2
Halcyon FuturesParticipantMission-aligned investor2
Dhuna VenturesParticipantMiami-based VC (founded 2021)3
LongeVCParticipantDC-based VC focused on regenerative medicine and AI drug discovery (founded 2020)3
Total$15,000,0002

The OpenAI investment is notable for several reasons. It represents a direct financial commitment by a frontier AI lab to building defensive biological infrastructure against risks that its own technology could create. Jason Kwon and other OpenAI executives with prior exposure to the founders through Y Combinator held indirect stakes valued at less than $2,500 and recused themselves from the investment decision; OpenAI’s chief compliance officer and unconflicted board members reviewed and approved the investment.12

Legal counsel for the round was provided by Goodwin Procter LLP.13

Leadership Team
NE
Nikolai Eroshenko
CEO and Co-Founder
HR
Hannu Rajaniemi
Co-Founder

Nikolai Eroshenko studied biomedical engineering at Virginia Commonwealth University (2005-2008) and earned his PhD in bioengineering from Harvard University (2008-2014), where he worked in George Church’s lab on novel DNA synthesis technologies and genome engineering tools beyond CRISPR.14 He co-founded HelixNano with Rajaniemi in 2013 and served as Chief Science Officer, leading the company’s mRNA technology development.6

Hannu Rajaniemi (born March 9, 1978, in Ylivieska, Finland) is a Finnish-American scientist, entrepreneur, and science fiction author.15 He holds a PhD in Mathematical Physics from the University of Edinburgh, a Certificate of Advanced Study in Mathematics from Cambridge, and a BSc in Mathematics from the University of Oulu. Before his PhD, he served as a research scientist for the Finnish Defence Forces.15

Rajaniemi is known in literary circles for the Jean le Flambeur trilogy, beginning with The Quantum Thief (2010), which was nominated for the 2011 Locus Award for Best First Novel.15 He founded ThinkTank Maths, a commercial research organization, and co-founded HelixNano in 2013.15 In 2023, he joined Plural VC as a partner focused on AI and biotech investments.16

His background spanning mathematical physics, science fiction, and biotechnology entrepreneurship gives him an unusual perspective on anticipating future biological threats — a skillset directly relevant to Red Queen Bio’s threat-mapping mission.

Red Queen Bio represents a distinctive approach within the biosecurity-AI safety nexus. While organizations like SecureBio focus on evaluating and restricting AI biological capabilities (the “Delay” framework), and IBBIS focuses on synthesis screening infrastructure, Red Queen Bio operates on the assumption that biological AI capabilities will continue to advance and that defensive infrastructure must scale commensurately.1

This “defensive co-scaling” thesis is philosophically aligned with arguments that AI safety should include building robust defenses rather than relying solely on capability restrictions. It also creates an interesting incentive structure: frontier AI labs fund the company because building defensive infrastructure may make it safer to continue advancing capabilities.2

The company is structured as a Public Benefit Corporation specifically to manage potential conflicts of interest arising from its partnerships with AI labs whose products create the very risks Red Queen Bio aims to counter.1

Key Questions (6)
  • Can defensive biological countermeasures actually be pre-built at sufficient speed and breadth to match the pace of AI-enabled threat development?
  • Does the 'defensive co-scaling' thesis create a moral hazard by making AI labs more comfortable advancing biological capabilities?
  • How does Red Queen Bio manage information hazards inherent in mapping AI-enabled biothreats with the same labs creating those capabilities?
  • Can a Public Benefit Corporation structure effectively prevent mission drift when primary funding comes from AI labs with competing interests?
  • Is $15M sufficient seed funding to build the integrated AI-wet lab pipeline needed for meaningful countermeasure development?
  • How will Red Queen Bio's approach complement or compete with government biodefense programs like BARDA?
OrganizationFocusApproachStructureAI Lab Relationship
Red Queen BioPre-built countermeasuresDefensive co-scaling; AI-driven designPublic Benefit CorpDirect funding from OpenAI
SecureBioCapability evaluation + surveillanceDelay/Detect/Defend framework501(c)(3) nonprofitEvaluation partnerships
IBBISSynthesis screening standardsOpen-source tools; international normsSwiss non-profit foundationIndirect (standards-based)
  1. Red Queen Bio Website - Mission, thesis, approach 2 3 4 5 6 7 8 9 10 11 12 13

  2. TechInformed - OpenAI leads $15M seed in Red Queen Bio - Funding announcement and context 2 3 4 5 6 7 8 9 10 11

  3. LongeVC - Red Queen Bio Raises $15M - Investor details 2 3

  4. PitchBook - Red Queen Bio Profile - Company details

  5. Red Queen hypothesis - Wikipedia - Name origin

  6. HelixNano Website - Company history 2

  7. Lean Startup - HelixNano founder interview - COVID pivot and mRNA technology

  8. Investing.com - OpenAI invests in Red Queen Bio - Business model details

  9. Jason Kwon on X - Defensive co-scaling endorsement

  10. Dagens - OpenAI funds biotech startup - Pipeline expansion plans

  11. PharmiWeb - AbTherx and Red Queen Bio Partnership - January 2026 partnership announcement 2 3

  12. Yahoo Finance - OpenAI backs startup - Investment governance details

  13. Goodwin - Red Queen Bio Seed Financing - Legal counsel announcement

  14. Nikolai Eroshenko - Crunchbase - Education and background

  15. Hannu Rajaniemi - Wikipedia - Biography 2 3 4

  16. TechCrunch - Plural VC recruits Rajaniemi - VC role