Key Takeaways
- Alphabet’s Isomorphic Labs is advancing from AI research to human clinical trials, creating a significant, albeit highly speculative, biotechnology call option within the tech giant’s portfolio.
- A sum-of-the-parts valuation suggests the market currently assigns negligible value to this venture, which resides within the cash-burning ‘Other Bets’ segment. Success, however, could unlock value comparable to established mid-cap biotech firms.
- The path to commercialisation is perilous, with clinical trial failure rates historically exceeding 90% and an evolving, uncertain regulatory landscape for AI-developed therapeutics.
- Should Isomorphic Labs demonstrate early-stage clinical success, it could trigger a fundamental re-rating of large-cap tech companies with substantial, non-core R&D projects, forcing a portfolio allocation shift.
The recent disclosure that Alphabet’s DeepMind is preparing for human trials of its first AI-designed medicines has sparked considerable discussion, including a pertinent question from analyst StockSavvyShay regarding the division’s latent value. While the prospect of curing diseases with artificial intelligence is profound, for investors the more immediate challenge is dissecting the financial implications. Attaching a credible valuation to a nascent, cash-incinerating venture embedded within a near two-trillion-dollar titan is a formidable exercise in assessing deep-seated, asymmetric potential.
From Protein Folding to Pharmaceutical Pipelines
The foundation of this venture is Isomorphic Labs, a spin-off from DeepMind, which itself was acquired by Google in 2014. Isomorphic’s purpose is to leverage the groundbreaking work of AlphaFold, an AI model that solved the 50-year-old grand challenge of protein structure prediction. By accurately modelling the three-dimensional shapes of proteins, the system provides a map to understand disease mechanisms and design novel drug molecules to interact with specific biological targets. Demis Hassabis, the head of both DeepMind and Isomorphic Labs, confirmed that the company is “getting very close” to initiating its first human trials, marking a critical transition from computational theory to clinical reality. [1, 2]
This approach aims to radically compress the drug discovery and development timeline, a process that traditionally consumes over a decade and billions of dollars with an astonishingly high rate of failure. By using AI to identify promising candidates and predict their behaviour, Isomorphic Labs hopes to improve the odds and reduce the cost, effectively industrialising an activity that has long been a blend of science, serendipity, and brute force screening.
The Valuation Conundrum: A Sum-of-the-Parts Sketch
Alphabet does not report Isomorphic Labs’ financials separately. It is bundled within the ‘Other Bets’ segment, a collection of high-risk, long-term projects that collectively generated $4.96 billion in revenue in the last twelve months but posted an operating loss of $7.57 billion. [3] The market, quite rationally, assigns a negative or negligible value to this segment in most valuation models, focusing instead on the cash flows from Search, Cloud, and YouTube.
To gauge the potential hidden value, one can employ a speculative sum-of-the-parts (SOTP) analysis. Using recent financial data and applying conservative, industry-standard multiples, we can estimate the value of Alphabet’s core components and then consider what Isomorphic might be worth as a standalone entity.
| Alphabet Segment | LTM Revenue ($B) | Applied Multiple | Estimated Value ($B) |
|---|---|---|---|
| Google Search & Other | $242.1 | 5.0x Sales | $1,211 |
| Google Cloud | $41.5 | 9.0x Sales | $374 |
| YouTube Ads | $34.9 | 6.0x Sales | $209 |
| Other Bets (Isomorphic Labs) | $5.0 | Speculative Asset | $20 – $50+ |
Note: Last Twelve Months (LTM) revenue figures are based on Alphabet’s Q2 2024 earnings report. Multiples are illustrative and based on sector benchmarks. The speculative value for Isomorphic is a hypothetical range based on valuations of public, clinical-stage AI-biotech peers.
Even a conservative valuation of $20 billion to $50 billion would be significant, representing a heavily risk-discounted appraisal of a company with several pre-clinical assets. For context, publicly traded AI-driven drug discovery companies like Recursion Pharmaceuticals and Schrödinger command multi-billion dollar market capitalisations without having a drug approved for market. Isomorphic Labs, backed by Alphabet’s balance sheet and computational infrastructure, could arguably warrant a premium if it achieves early clinical validation.
Navigating the Biotech Gauntlet
The enthusiasm must be tempered with a dose of clinical and regulatory realism. The path from a Phase I trial to an approved, marketable drug is an unforgiving one. According to analysis from the Biotechnology Innovation Organization (BIO), the overall likelihood of approval for a drug entering Phase I clinical trials is just 7.9%. [4] Failure can occur at any stage due to lack of efficacy, unforeseen toxicity, or strategic reprioritisation.
Furthermore, Isomorphic Labs is not operating in a vacuum. The field of AI-powered drug discovery is increasingly crowded, with agile competitors such as Exscientia, Insitro, and AbCellera all pursuing similar goals. While Alphabet possesses unparalleled resources, the biotech sector has historically rewarded focused execution over sheer scale. Regulatory bodies like the U.S. Food and Drug Administration (FDA) are also still formulating clear guidance for AI and machine learning in drug development, introducing an element of procedural uncertainty. [5]
An Embedded Call Option on the Future of Medicine
For investors in Alphabet, Isomorphic Labs is best viewed as an out-of-the-money call option with a very long expiry date. Its current contribution to the stock price is likely zero or even slightly negative due to the drag from ‘Other Bets’ operating losses. The position requires no direct capital allocation from shareholders, yet provides exposure to the immense upside of a potential breakthrough in one of the world’s largest industries.
The critical catalyst to watch will not be revenue, but data. A positive readout from a Phase I or Phase II trial would serve as a powerful proof-of-concept, validating the entire AI-driven discovery platform. My hypothesis is this: should Isomorphic Labs successfully advance even a single drug candidate into Phase II trials with positive efficacy data within the next three to five years, it will force a complete re-evaluation of Alphabet’s ‘Other Bets’. Such an event would not just add tens of billions to Alphabet’s market capitalisation, but would likely ignite a wave of M&A and strategic partnerships, fundamentally reshaping the competitive boundary between big tech and big pharma.
References
- Helms, C. (2024, July 6). Google DeepMind has grand ambitions to cure all diseases with AI. Now it’s gearing up for its first human trials. Fortune. Retrieved from https://fortune.com/2024/07/06/deepmind-isomorphic-labs-cure-all-diseases-ai-now-first-human-trials/
- Times of India. (2024, July 9). Google DeepMind is ready to start human trials of AI-designed drugs, company exec says ‘we’re getting very close’. The Times of India. Retrieved from https://timesofindia.indiatimes.com/technology/tech-news/google-deepmind-is-ready-to-start-human-trials-of-ai-designed-drugs-company-exec-says-were-getting-very-close/articleshow/111582344.cms
- Alphabet Inc. (2024, July 23). Alphabet Announces Second Quarter 2024 Results. Retrieved from https://abc.xyz/investor/static/pdf/20240723_alphabet_q22024_earnings_release.pdf
- Biotechnology Innovation Organization (BIO), Informa Pharma Intelligence, & QLS. (2021). Clinical Development Success Rates and Contributing Factors 2011–2020. Retrieved from https://www.bio.org/sites/default/files/2021-02/Clinical%20Development%20Success%20Rates%202011-2020.pdf
- U.S. Food and Drug Administration (FDA). (2023, May 10). Artificial Intelligence and Machine Learning (AI/ML) in the Development of Medical Devices and Drug and Biological Products. Retrieved from https://www.fda.gov/science-research/science-and-research-special-topics/artificial-intelligence-and-machine-learning-aiml-development-medical-devices-and-drug-and
- @StockSavvyShay. (2024, August 2). [$GOOGL DEEPMIND WANTS TO CURE ALL DISEASES WITH AI — HUMAN TRIALS ARE ABOUT TO BEGIN If OpenAI’s worth $500B, what’s DeepMind really worth?]. Retrieved from https://x.com/StockSavvyShay/status/1921198138037334312
