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Algen Biotechnologies

Algen Biotechnologies

San Diego, United States· Est.
algenbio.com
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Private Company

Total funding raised: $3.2M

Overview

Algen Biotechnologies is a private, pre-clinical stage biotech leveraging a powerful, integrated platform of next-generation CRISPR gene modulation and AI foundation models to revolutionize therapeutic discovery. Founded in 2018 with strong scientific roots in Jennifer Doudna's lab, the company aims to reverse-engineer disease trajectories at scale to identify high-confidence therapeutic targets. A significant $555 million partnership with AstraZeneca in 2025 validates its platform and provides substantial non-dilutive funding to advance its pipeline.

Genetics & GenomicsAI / Machine Learning

Technology Platform

Integrated platform combining AlgenCRISPR (proprietary next-generation CRISPR system for precise gene modulation) and AlgenBrain (AI foundation model trained on dynamic gene expression data to predict disease-driving RNA signaling networks).

Funding History

1
Total raised:$3.2M
Seed$3.2M

Opportunities

The major partnership with AstraZeneca validates the platform and provides substantial non-dilutive funding to advance technology and discovery programs.
The growing demand for AI/ML solutions to de-risk drug discovery presents a large market for platform licensing and further partnerships across multiple therapeutic areas.

Risk Factors

The platform is highly complex and unproven in delivering clinical-stage assets; failure to generate novel, actionable targets would undermine its value.
The company faces intense competition in the AI-driven drug discovery space and must navigate the complex and contested foundational CRISPR intellectual property landscape.

Competitive Landscape

Algen competes in the crowded 'tech-bio' sector with companies like Recursion, Exscientia, and Insitro that also apply AI/ML to drug discovery. Its specific differentiation is the deep integration of a proprietary, next-generation CRISPR system for data generation, aiming to create more causal, human-relevant training data for its AI models compared to competitors relying on public or observational data.

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