Company and Stock Identity

How GSK Connects to the Public Market

Company structure
Public company
Market access
Direct listing: NYSE: GSK. The ordinary shares also trade in London, and the New York listing is an ADR programme.
Stock name
GSK plc
Ticker and exchange
NYSE: GSK
Research focus
GSK buys AI tools, so read its announcements for the stage the work reached. Access to a model is not the same as a signed licence, and a licence is not the same as a medicine in a trial. Its own figures are worth separating too: 32.7 billion pounds of 2025 turnover and 66,800 staff come from its about page, while any claim about what an AI partner delivered usually comes from the partner's release, not from GSK's accounts.

GSK is publicly held and has no controlling owner. Its investor pages give the legal issuer as GSK plc, registered in England and Wales number 3888792, and its ADR programme page says the receipts trade on the New York Stock Exchange under the symbol GSK, with one ADR representing two ordinary shares and JP Morgan Chase Bank, N.A. as depositary. Its about page gives the head office as 79 New Oxford Street, London. Verified on the company's own investor and about pages on October 24, 2026.

Dated Market Snapshot

Oct 26, 2026

Last price
$51.10
Change
+0.69%
Previous close
$50.75
52-week high / low
$61.695/$42.845
Market cap
103,360,257,335

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

... Chai Discovery ... Company source

GSK takes Chai Discovery's designs into its own labs first, then signs a collaboration

Chai Discovery announced on 9 October 2026 that GSK will get access to its platform, including its protein folding and design models, to support discovery work across GSK's pipeline. The announcement says the deal followed a wet-lab evaluation in which Chai's models generated designs against GSK targets zero-shot, without training on those targets, and that GSK then tested the designs itself. Chai's wording is that GSK conducted internal wet-lab testing of the designs, finding binders to all tested targets. Christopher Austin, GSK's senior vice president of R&D technologies, is quoted saying GSK evaluated the models across a panel of diverse targets and saw designs with strong binding affinities. Joshua Meier, Chai's co-founder and chief executive, is quoted saying the evaluation let both teams assess the models against a range of therapeutic targets in the lab. No payments, milestones or number of programs were disclosed.

Why it matters: A binder is a long way from a medicine. It means a designed molecule stuck to the thing it was aimed at, which is the first hurdle of many, and nothing here says any of it will help a patient. What makes this one worth noting is who ran the test. The lab work was done inside GSK on GSK's own targets, so the result is not the AI company grading its own homework. Zero-shot matters for the same reason: the models had not been tuned on those particular targets, which is closer to how a new program actually starts. The open question is money. No payments or program counts were disclosed, so this could be a broad licence or a small pilot, and the announcement does not say which.

... Chai Discovery ... Company source

Novartis gets access to Chai Discovery's antibody design models

Chai Discovery announced on 13 July 2026 that Novartis will get access to its AI models, including Chai-3, to support therapeutic antibody discovery across multiple targets. Financial terms were not disclosed, and the announcement gives no number of programs or milestones. Fiona Marshall, Novartis's president of biomedical research, is quoted saying AI is already reshaping how the company discovers medicines and that applying advanced models to problems like antibody design lets it explore a broader range. Joshua Meier, Chai's co-founder and chief executive, is quoted calling it a significant step forward. The announcement also names Pfizer and Eli Lilly as earlier users of Chai's models.

Why it matters: This is an access agreement, which is the lightest kind of deal in this field. A large drug company can hand a model to a research group, try it on a few targets and walk away without ever announcing that it stopped. Nothing here is a result, and nothing here involves a patient. What it does tell a biologics team is that the design models cleared whatever internal review Novartis runs before outside software touches real programs, and that Chai now has three of the largest drug companies on that list. Treat the names as a signal about the software being taken seriously, not as evidence that it works.

See company developments across the healthcare AI market.

Careers and Qualifications

What to Know Before Applying

Work areas: GSK's careers pages group its openings into research and development, technology, engineering, global supply chain, business operations, and sales and marketing, plus graduate programmes and apprenticeships. The research and development side names medicine development and supply, chemical manufacturing and controls, and genomic sciences.

Qualification signal: For the AI-adjacent roles here, drug discovery context counts more than a general data science background. Someone who has worked beside a wet lab and understands why a design has to be made and tested will be more useful than someone who has only trained models on public data.

Check current roles at GSK. 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
Research and development leaders, clinical development teams, business development staff, and investors tracking where AI partnerships lead
Primary use case
Sponsor, license, or partner on AI research, molecule design, and trial measurement in drug development
Typical deployment
Drug developer. AI arrives through a research collaboration, a licence, or a tool used inside a clinical trial.

Evidence questions

  • What stage did the agreement reach, and were any payments or milestones disclosed?
  • Which programs or molecules does the AI work actually touch?
  • Has anything from the collaboration reached a clinical endpoint rather than a press release?

Regulatory and workflow questions

  • If AI produced a measurement used in a trial, has a regulator accepted that measurement?
  • Which regulatory submissions, if any, depend on the AI work?
  • Who is responsible for the quality of an AI-generated result inside a trial record?

Data and contract questions

  • Whose data trained the model, and what did the drug company contribute?
  • Who owns a molecule or design the collaboration produces?
  • What happens to the shared data if the collaboration ends?

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