Company and Stock Identity

How Isomorphic Labs Connects to the Public Market

Company structure
Alphabet company
Market access
Public parent: Alphabet, Nasdaq: GOOGL and GOOG.
Stock name
Alphabet Inc.
Ticker and exchange
Nasdaq: GOOGL / GOOG
Research focus
Do not treat Alphabet shares as pure exposure to Isomorphic Labs. Track drug-development partnerships, internal programs, outside financing, and milestones separately from Alphabet’s wider business.

Isomorphic Labs is not separately traded. It was launched within Alphabet and has also raised outside capital.

Dated Market Snapshot

Oct 26, 2026

Last price
$316.80
Change
-1.06%
Previous close
$320.21
52-week high / low
$408.61/$255.315
Market cap
3,874,464,000,000

Automated from Nasdaq. Check the exchange or investor-relations page for the current price.

Open the public company market data feed for the full directory, ownership relationships, stock identifiers, and dated snapshots.

First-Hand Company News

Latest Developments

... Isomorphic Labs ... Company source

Isomorphic Labs joins a Biohub effort to build biology data for AI models

Isomorphic Labs announced on October 7, 2026 that it has joined the Virtual Biology Initiative as a founding member to help generate AI-ready biological data. The initiative is convened by Biohub, and its stated purpose is to generate and make accessible the data enabling predictive AI models of biology. The announcement says participating organisations are collectively investing funding, data, computation and new measurement technology, and describes the effort as the largest coordinated commitment to generating AI-ready biological data to date, but it does not name the other participants or give funding figures. The stated result is an open resource for the research community. The announcement makes no clinical or regulatory claims.

Why it matters: This is a company admitting the bottleneck out loud. Protein structure prediction worked because decades of structures had already been measured and shared, and most of biology has no equivalent dataset, so models have little to learn from. Paying to generate that data and then giving it away is a bet that a bigger field beats a private advantage. Treat the largest commitment to date claim carefully, since the announcement names no partners and no figures, which makes it unverifiable from this page alone.

... Isomorphic Labs ... Company source

Isomorphic Labs raises 2.1 billion dollars to design drugs with AI

Isomorphic Labs announced on May 12, 2026 that it raised 2.1 billion dollars in Series B funding led by Thrive Capital. The round includes existing backers Alphabet and GV alongside new investors MGX, Temasek, CapitalG and the UK Sovereign AI Fund. The company says the money will power its AI drug design engine, scale the business globally and progress its drug candidate pipeline. The announcement discloses the round size but not a valuation or a cumulative total raised.

Why it matters: A round this size for a company with no approved medicine is a bet on the design step, not on a product. The useful thing to watch is not the funding but what it buys: AI drug design is judged by candidates that survive real trials, and the field has a long record of promising molecules that failed in people. Sovereign funds appearing on the list is its own signal, because governments now treat drug design capability as infrastructure rather than as a venture investment.

See company developments across the healthcare AI market.

Careers and Qualifications

What to Know Before Applying

Work areas: Machine learning, structural biology, chemistry, drug discovery, research engineering, and scientific product work.

Qualification signal: Research roles usually require deep scientific or machine-learning training. Published work, experimental fluency, and drug-discovery experience are stronger signals than a short certificate.

Check current roles at Isomorphic Labs. A careers page is the source of record for openings. This profile does not claim a role is open unless the company lists it now.

Related Healthcare AI Roles

Training to Compare

Buyer Snapshot

Best-fit buyer
Pharmaceutical R&D, biotechnology leadership, translational science, business development, and investors
Primary use case
Identify targets, design molecules, prioritize experiments, and connect biomedical data to research decisions
Typical deployment
Ranges from software and data partnerships to platform collaborations and internally owned drug pipelines

Evidence questions

  • Which results are prospective, reproduced, and tied to a clinical or experimental endpoint?
  • How many programs are AI-originated, AI-assisted, partnered, or internally owned?
  • What has advanced beyond target identification and preclinical reporting?

Regulatory and workflow questions

  • Which entity owns development, validation, and regulatory responsibility for each program?
  • How are model-generated hypotheses reviewed before experimental or clinical use?
  • What claims are about research productivity versus a regulated product?

Data and contract questions

  • Who owns generated molecules, targets, models, and derived data?
  • Which proprietary datasets create defensibility and which are licensed?
  • Can a partner reproduce outputs and export project data after the collaboration?

Evidence and Regulation

FDA Clearances on Record

No clearance is linked in this directory. That is not automatically a mark against the company. Some products support the people doing the work instead of reading a patient image or signal themselves.

First-Hand Sources