AI + Life Sciences: How Multi-Omics and Synthetic Biology Unlock the Next $100B Breakthroughs

AI life sciences is reshaping the way we understand biology, design drugs, and engineer living systems. AI + life sciences is no longer a futuristic concept; it is actively generating breakthroughs in drug discovery, multi-omics research, and synthetic biology. 

Startups leveraging these technologies are accelerating research timelines, reducing costs, and opening the door to potentially $100 billion opportunities across healthcare, agriculture, and industrial biology.

“What we’re looking for are founders who are using AI to tackle complex biology problems and building multi-agent systems to accelerate discovery,” said George Bandarian, Founder, General Partner & CEO, The Untapped Team.

Investors are noticing. According to statistics, global AI-driven healthcare startups raised over $25 billion in funding in 2024, reflecting the rapid adoption of AI technologies in life sciences. 

These startups are turning complex biology into scalable products, giving founders a massive opportunity to lead the next generation of life sciences innovation. 

The most important part is to find the best platform for all of this.

Untapped Ventures supports founders navigating this frontier, providing early-stage capital, domain expertise, and global networks to accelerate ventures from lab prototypes to industry-defining companies.

So, let’s read about AI, life science, and understand its role in today’s reality. We can begin with multi-omics.

What Is Multi-Omics And Why It Matters

Multi-omics integrates genomics, proteomics, transcriptomics, metabolomics, and epigenomics to create a comprehensive picture of biological systems. 

Traditional single-layer approaches miss critical interactions, slowing discovery and introducing inefficiencies. AI makes multi-omics actionable by analyzing complex datasets faster and more accurately than human teams alone.

Why multi-omics is a game-changer:

1. Comprehensive Insights: Understanding how genes, proteins, and metabolites interact uncovers new disease pathways.

2. Precision Medicine: Personalized treatments are possible by identifying molecular profiles unique to each patient.

3. Predictive Analytics: AI models anticipate patient responses, reducing costly trial-and-error in drug development.

4. Cross-Disease Applications: Insights from one condition often inform treatment strategies in others.

“We love when teams combine multi-omics data with machine learning to uncover insights no one could see before,” said George Bandarian, Founder, General Partner & CEO, The Untapped Team.

Famous examples:

• Tempus leverages multi-omics to accelerate oncology research.

• Grail focuses on early cancer detection using blood-based genomic and epigenomic analysis.

Integrating AI into multi-omics is no longer optional; it’s essential for startups aiming to create competitive, scalable life sciences solutions. You should keep up as well. 

Synthetic Biology: Engineering Life With AI

Synthetic biology allows scientists to redesign organisms, engineer proteins, or create entirely new biological pathways. 

AI enhances this field by modeling complex biological systems, predicting outcomes, and optimizing experiments, which accelerates innovation dramatically.

Key advantages of AI-driven synthetic biology:

1. Faster Iterations: AI predicts outcomes of gene edits before lab work begins.

2. Cost Efficiency: Computational models reduce expensive trial-and-error processes.

3. Scalable Innovation: AI can design molecules, enzymes, and biological circuits at an industrial scale.

4. Enhanced Safety: Simulations help identify potentially unsafe designs early, reducing risk.

It’s easier to understand through examples that have practically shown results, isn’t it?

Famous examples:

• Ginkgo Bioworks programs microbes for industrial uses, from flavors to materials.

• Moderna leveraged AI to accelerate mRNA vaccine development, demonstrating the power of computational biology in real-world applications.

Synthetic biology is transitioning from experimental labs to commercial viability. Founders entering this space can address industrial, healthcare, and environmental challenges with AI-powered precision.

What do you think, what other changes AI can do?

AI + Life Sciences: Transforming Drug Discovery

Drug discovery has historically been slow, expensive, and prone to failure, taking over a decade and billions of dollars per drug. AI + life sciences is revolutionizing this process, enabling faster, more accurate drug design and development.

How AI accelerates drug discovery:

1. Target Identification: AI analyzes multi-omics datasets to pinpoint disease-relevant targets.

2. Compound Screening: Machine learning predicts which molecules are likely to succeed.

3. Clinical Trial Optimization: Predictive analytics design more efficient trials, reducing failures.

4. Repurposing Existing Drugs: AI identifies new applications for known compounds, speeding deployment.

“The combination of predictive models and high-throughput biology is what lets startups compress years of R&D into months,” said George Bandarian, Founder, General Partner & CEO, The Untapped Team.

Famous examples:

• Insitro applies machine learning to biological data, shortening timelines for novel therapies.

• Exscientia uses AI to design and prioritize drug candidates, leading to faster clinical trial initiation.

The global drug discovery market is projected to exceed $20 billion by 2030, making this space extremely lucrative for AI-first founders. Overall, the market and the internet have shown rises in AI implementation. 

Market Opportunity And Funding Trends

AI + life sciences is a rapidly expanding sector. As of 2025, over 70,000 AI startups operate globally, with AI driving more than 70% of venture capital activity in healthcare and life sciences, according to HubSpot. This illustrates a strong investor appetite for AI-native solutions in multi-omics, drug discovery, and synthetic biology.

Market signals for founders:

1. Massive Addressable Market: Multi-omics and synthetic biology applications could unlock over $100 billion in value within the next decade.

2. Early-Mover Advantage: Founders integrating AI early capture data, refine workflows, and define industry standards.

3. Growing Investor Confidence: Top venture funds prioritize AI-native life sciences startups.

Investors are not just betting on technology; they are betting on teams capable of combining biology, AI, and commercial insight. For founders, this is a rare chance to define a new frontier in life sciences.

Challenges And Responsible AI Adoption

Despite huge potential, responsible adoption is essential. AI models rely on large datasets, which raises privacy, ethical, and regulatory concerns. Founders must design systems that are safe, equitable, and transparent.

Key considerations:

1. Data Privacy: Biological and patient data must be securely handled with clear consent.

2. Ethical Use: Genome editing and synthetic biology involve societal and moral questions.

3. Regulatory Compliance: FDA, EMA, and other regulatory agencies require transparent, validated AI-driven methods.

4. Bias and Fairness: AI reflects the data it’s trained on, so auditing for bias is critical.

Responsible adoption not only ensures compliance but also builds credibility and trust with investors, patients, and collaborators.

How AI + Life Sciences Startups Win

Successful startups integrate AI at every stage of the workflow. Lessons from leaders:

1. Recursion Pharmaceuticals: Uses AI for image-based drug screening, testing thousands of compounds rapidly.

2. Zymergen: Leverages AI-driven automation to engineer microbes for industrial and consumer products.

3. Tempus: Combines multi-omics and clinical data to guide oncology treatment.

4. Grail: Detects cancer early by analyzing blood samples with AI-powered genomic tools.

Key strategies for founders:

• Integrate multi-omics early to build a strong foundation.

• Apply synthetic biology for scalable commercial applications.

• Use AI to accelerate experiments and minimize trial-and-error.

These approaches allow startups to move faster, reduce risk, and attract both investors and collaborators.

Your startup isn’t an exception, so do not miss your chance!

Real-World Examples And Case Studies

The impact of AI life sciences is best illustrated by companies already reshaping healthcare and biology. These pioneers show how algorithms, data, and biology can come together to unlock breakthroughs once thought impossible.

1. Moderna

Moderna became a household name during the COVID-19 pandemic, and AI played a decisive role in its speed. Traditionally, developing an mRNA vaccine could take years of trial and error, but Moderna’s AI-driven platform modeled countless variations and predicted the most promising designs. This reduced the design-to-trial process from years to just months, changing how the world thinks about vaccine readiness.

2. Ginkgo Bioworks

Ginkgo Bioworks has built what it calls the “organism company,” using AI to design microbes for industrial and medical applications. From bio-based fragrances to enzymes that reduce food waste, Ginkgo’s approach scales biology as if it were software. The company’s AI-guided platform can test millions of genetic edits, rapidly identifying strains with the best commercial potential.

3. Insitro

Founded by Daphne Koller, co-founder of Coursera, Insitro is at the intersection of biology and machine learning. The company uses massive cellular datasets and AI to uncover disease mechanisms and match patients to the most effective treatments. By combining biological insights with predictive models, Insitro shortens the long and costly drug discovery cycle.

4. Exscientia

Exscientia is one of the first companies to advance an AI-designed drug into human clinical trials. Its AI-first drug discovery process identifies candidates faster by filtering out less promising compounds early in development. In some cases, Exscientia reduced the preclinical candidate selection process from four years to under one, offering patients faster access to potentially life-saving medicines.

Together, these companies prove that AI in life sciences is not a distant vision but

a present-day revolution. Each breakthrough demonstrates how combining computational power with biology accelerates discovery, reduces costs, and makes treatments more personalized.

Actionable Steps For Founders

Succeeding in AI life sciences requires more than great code — it demands vision, scientific depth, and strategic execution. Founders can raise their odds of success by focusing on these core steps:

1. Combine AI with life sciences expertise

   • Build teams that blend data science with biology, clinical, and regulatory know-how.

   • Purely tech-driven approaches often miss critical nuances of drug development and healthcare adoption.

2. Integrate multi-omics data

   • Go beyond single data layers (like genomics alone).

   • Leverage genomics, proteomics, transcriptomics, and metabolomics together to reveal patterns that drive disease understanding and treatment design.

   • This integration is key to unlocking true precision medicine.

3. Leverage synthetic biology for scale

   • Use AI to design proteins, enzymes, and microbes at speed and scale.

   • Synthetic biology makes it possible to move from lab experiments to real-world applications like therapeutics, sustainable materials, and biofuels.

4. Secure partnerships early

   • Collaborate with pharma companies, research labs, and academic institutions to accelerate validation.

   • Engage with specialized investors, like Untapped Ventures, who offer capital plus mentorship, networks, and company-building expertise.

5. Validate and execute relentlessly

   • Prioritize proof-of-concept studies and intellectual property from day one.

   • Demonstrate credibility through peer-reviewed results, advisors, and early customer traction.

   • Execution speed, paired with rigorous validation, sets leaders apart from competitors.

Taking these steps helps founders transform bold ideas into real breakthroughs. The next Moderna or Ginkgo Bioworks could emerge from teams that act decisively today, building companies at the edge of biology and technology.

Conclusion: The AI + Life Sciences Breakthrough Era

AI life sciences is happening now. Multi-omics, synthetic biology, and AI-driven drug discovery are creating opportunities worth over $100 billion.

Founders who embrace these technologies early, think boldly, and integrate AI responsibly will define the next decade of transformative companies. That is why you need to find an investment platform that matches your goals today. 

Untapped Ventures evaluates AI + life sciences startups using three pillars:

1. Founder Vision: Teams that think beyond incremental change.

2. Technical Depth: Expertise in AI-native methods and domain knowledge.

3. Market Potential: A clear path to scale with defensible IP and data advantages.

By focusing on AI-first teams in multi-omics and synthetic biology, Untapped Ventures provides capital, mentorship, and operational support to help founders move from prototype to venture-scale impact.

Untapped Ventures partners with visionary founders to turn breakthroughs into venture-scale businesses. With capital, strategic guidance, and a global expert network, Untapped Ventures accelerates AI-first life sciences startups. If you have a bold idea, now is the time to act. The technology is ready, the market is ready, and Untapped Ventures is ready to help you succeed.

Are you ready to take your business to the next level? 

Then pitch us your idea and let’s work together!

FAQs

What Is AI Life Sciences?

It refers to applying AI to understand biological systems, accelerate research, and create innovative therapies.

How Does Multi-Omics Work With AI?

AI analyzes complex datasets across genomics, proteomics, transcriptomics, and metabolomics to uncover hidden insights.

Which Industries Benefit Most From AI Life Sciences?

Healthcare, biotech, pharma, agriculture, and environmental sciences see the largest impact.

Why Partner With Untapped Ventures?

Untapped Ventures provides early-stage capital, operational support, and access to a global network to accelerate AI + life sciences startups.