Antiverse

Company Information

Antiverse uses AI-driven antibody discovery to accelerate the development of therapeutics targeting challenging proteins, such as GPCRs and ion channels, for pharmaceutical and biotechnology companies.

We use the Business Model Canvas (BMC), which captures what the startups offers, how it reaches its customers and how profitable it could be.
Key Partnerships

What strategic collaborations do they have, and how do these enhance the company’s capabilities or reduce risk, etc.

  • Companies: GlobalBio, Inc.
  • Investors: Secures funding from i&i Biotech Fund I, Kadmos Capital.
  • Academic Institutions: Cardiff University
Key Activities

How are they creating value, improving relationships with customers, increasing operational efficiency, etc.

  • Value: Develops de novo antibodies for challenging targets.
  • Method: Enhances the AI-driven platform for improved predictive accuracy.
  • Relatinships: Collaborates with pharmaceutical and biotech companies.
Key Resources

What resources/assets do they need to deliver value.

  • Resources: Energy, combines machine learning with cell-free protein synthesis for antibody prediction.
  • Assets: Operates state-of-the-art labs in Cardiff, with additional facilities in Boston and Prague.
  • Team: Specialists in structural biology, machine learning, and medicine.
Value Proposition

What are they offering, how are they meeting customers needs, how are they differentiable from competition, etc.

  • Offer: Acceleration of antibody discovery, reduces discovery timelines to approximately six months.
  • Customer needs: Enhances predictive accuracy & precision of antibody-antigen binding predictions.
  • Differentiation: Focuses on antibodies for difficult targets like G-protein coupled receptors (GPCRs) and ion channels that is a niche in the field and relatively unmet.
Customer relationships

How will they build loyalty, maintain good relationships, what kind of relationships do we expect, etc.

  • Needs: Works closely/collaboratively with clients to tailor antibody discovery programs to specific needs.
  • Support: Offers ongoing assistance throughout the drug discovery process.
  • Opportunities: Engages in joint development projects to advance therapeutic candidates.
Channels

How will they reach their customers, how is their cost efficiency, customer acquisition, and retention, how will they distribute, etc.

  • Sales: Engages directly with pharmaceutical and biotech companies for partnerships and collaborations.
  • Online: Provides information and updates through the company website and digital platforms.
  • Events: Participates in conferences and seminars to showcase technology and network with potential clients.
Customer Segments

Who are they serving, what is the target market, market size, etc.

  • Targets: Pharmaceutical Companies that seek to accelerate drug discovery and development processes, biotechnology firms that need advanced antibody design for challenging targets, Contract Research Organisations (CROs) that offer services in antibody discovery and development.

Cost Structure

What are the major fixed and variable costs.

  • Variable: Materials for antibody production, consumables, energy consumption (AI-heavy), marketing.
  • Fixed: Salaries, lease of lab facilities, subscriptions.
Revenue Streams

how will they make money, what is the pricing structure, any additional/creative revenue streams, etc.

  • Service: Charges for antibody discovery and design services.
  • Recurring: Licensing Agreements, earns revenue from licensing proprietary antibodies or technology.
  • Payments: Receives payments upon achieving specific development milestones in partnerships.
We use Porter’s five forces to evaluate the company’s competitive position and dynamics of the market and any external pressures

1. Threat of New Entrants

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  • Antiverse’s AI platform requires specialised expertise in machine learning and structural biology.
  • Existing collaborations (GlobalBio) is positive for its reputation and may act as a barrier to entry.
  • IP and growing datasets reduce the risk of competitors developing similar solutions.

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  • Open-source AI frameworks and widely available computational resources make it easier for new startups to at least attempt entering.
  • Young company, Antiverse has e.g. limited brand recognition.

2. Threat of Substitutes

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  • Faster and more cost-effective antibody discovery than traditional methods.
  • Unique in that they are targeting challenging proteins that traditional approaches cannot.

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  • There is competition from other modalities of therapeutics (e.g. RNA-based therapies or small molecules).
  • There is always the chance that bigger AI companies (Anthropic, OpenAI etc) will produce an update that renders this obsolete.

3. Bargaining Power of Suppliers

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  • Has in-house expertise so probably will not need external technical resources.
  • Easily adaptable platform.

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  • Access to high-quality training data is paramount, and any limitation in availability or rising costs could be a problem.
  • It is becoming harder and harder to get AI and biotechnology experts as they are in high demand.
  • Slight dependence on specialised lab equipment.

4. Bargaining Power of Buyers

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  • Minimal competition at the moment.
  • Fast/accurate approach is preferable over conventional methods.

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  • Pharmaceutical companies have a lot of power in the sector.
  • Customer base is small and a niche.

5. Intensity of Current Competition

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  • The focus on difficult-to-target proteins makes competition less intense.
  • If they keep and increase current partnerships with investors and pharma companies they can create credibility before other competition enters.

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  • The overall antibody discovery market is crowded (e.g., AbCellera, Adimab)
  • Larger competition has the benefit of predatory pricing and can gate keep the market.

Resources