Noetik

The models are the product. What Noetik sells is access to its foundation models. GSK licenses OCTO-VC virtual cell models by subscription, and Noetik has deployed them to GSK for running and fine tuning. Agenus works with Noetik on TARIO-2 predictions of patient response.

The spatial dataset Noetik generates exists to train those models. No laboratory service, data product or drug candidate is offered alongside them.

Ask which model versions a license covers, and whether fine tuned models built on a licensee's data stay with the licensee.

Noetik publishes no oversight structure. Drug company scientists use the models for target discovery, virtual experiments and grouping patients, so people decide what to do with the outputs. But Noetik publishes nothing on how predictions are reviewed, when a simulated result should not be relied on, or how a prediction used to select patients for a trial is checked.

TARIO-2 is presented as predicting individual patient response, which raises the stakes of that gap.

Ask how prediction confidence is reported, what human review comes before a patient selection decision informed by TARIO-2, and how model errors are reported to licensees.

Noetik names its models and describes their data, without versions or update practice. It names OCTO, OCTO-VC and TARIO-2. The models learn by predicting missing biological information from the surrounding tissue, without hand labeled data.

The training data is described in detail: tumor samples from more than 4,500 patients, 196,000 tissue cores, 450 million cells and 2.9 petabytes. H&E images, a custom spatial protein panel, whole spatial transcriptomes and DNA sequencing are lined up across the same tissue. Technical reports describe OCTO and the virtual cell models.

No parameter counts, version history or notice of model changes for licensees is published.

Ask which model version a license delivers, how updates are released to licensees, and whether results change between versions.

Noetik builds its own models. It generates its own spatial dataset and trains its own foundation models, and no outside model provider is named or implied.

Everything around the models is unpublished: the sources of the tumor samples, any laboratory or data partners, the cloud provider, and the parties that handle licensee data during fine tuning.

Ask for the sample sources and data partners, the hosting provider, and the processors that touch licensee data.

Noetik names partners and lists research, without setting out results. GSK is a named licensee. Noetik reports that OCTO-VC met GSK's testing criteria in non small cell lung cancer and colorectal cancer before the models were deployed, without publishing the criteria or results.

Its research page lists technical reports on OCTO and on virtual cells, a white paper on predicting response to newer checkpoint inhibitors, and presentations at SITC 2024 and 2025, AACR 2025 and ASCO 2026. The ASCO 2026 work, with Agenus, predicted response to botensilimab with balstilimab. None of these is peer reviewed, and no figures, patient groups or comparisons are set out on Noetik's pages.

Ask for the testing criteria GSK applied and the results, and for the ASCO 2026 response prediction figures with the patient group and comparison.

Noetik publishes nothing on how patient data moves through its systems. It describes the size and types of its tumor dataset, but not where the samples came from, what consent covers, how the data was de identified, or how long it is kept. It also does not say whether a licensee's data used for fine tuning goes back into Noetik's training sets. No safety engineering for the models is published.

Ask for the sources and consent basis of the tumor samples, the de identification method, and written terms on whether licensee data can train Noetik's models.

Noetik states no HIPAA position and publishes no privacy document that covers the product. It builds its models from tumor samples, imaging, sequencing and spatial data from more than 4,500 patients, and deploys fine tuning to licensees who may bring their own patient data.

Its site publishes terms of use that cover the website only and disclaim responsibility for the privacy of information sent over the internet. No privacy policy, business associate position or data processing agreement is published.

Ask how patient level data reaching Noetik from partners is governed, whether Noetik processes licensees' data, and for the data processing terms.

Noetik publishes no security certification, attestation, trust center or penetration testing statement. Its website terms disclaim responsibility for the privacy of information sent over the internet. The company holds a large dataset drawn from patient tumors and deploys models into licensees' research.

Ask for any security attestation, its scope and date, and how the tumor dataset and licensee data are protected.

Noetik makes no device claim, and the models are sold for research and development. Licensed OCTO-VC models support discovery and patient grouping research inside drug companies, and nothing presents any model as a diagnostic. The FDA's databases list no Noetik device.

Predicting which patients respond to a therapy becomes a companion diagnostic use if it moves into selecting patients for trials. Noetik publishes no regulatory position for TARIO-2.

Ask whether TARIO-2 is meant for selecting patients prospectively and, if so, the planned regulatory pathway and partner.

Noetik describes testing in outline, with no results by group and no governance process. It reports that its models met a licensee's testing criteria, and lists technical reports and conference presentations. No results compared across cancer types, tissue sources, laboratories or patient groups are set out. Nothing describes how model behavior is evaluated before release or monitored afterward.

The dataset's patient sources and demographics are not described. That leaves open whether predictions hold for groups under represented in it.

Ask for results by cancer type, data source and patient demographics, and how a new model version is evaluated before it reaches licensees.

Noetik publishes nothing on what happens when a model is wrong. Its only published terms cover its website, which is provided as is. No error rate, warranty, remedy or correction route for model outputs is published, and the GSK license terms are not public beyond its commercial structure.

Ask what a license commits Noetik to when a model's predictions prove wrong, and for error rates on the tasks you would use the models for.

No clinical record integration exists, and delivery into a licensee's systems is reported without detail. Noetik reports deploying OCTO-VC to GSK for running and fine tuning, which shows the models reach a buyer's research environment.

No platform, cloud environment, data format or interface is named. Nothing describes how a licensee's own data is brought to the models.

Ask how models are delivered (hosted service, licensee cloud or on premises), which data formats fine tuning accepts, and what integration GSK runs in production.

Noetik publishes nothing about where the models run or where data rests. It reports deploying the models to GSK for running and fine tuning, without saying whether that happens in GSK's environment or on infrastructure Noetik hosts. Nothing describes where the tumor dataset is stored, which cloud provider is used, or whether data crosses borders.

Ask where licensed models run, where fine tuning data is processed and stored, and which cloud and region host Noetik's dataset.

No price is published, but one contract's shape is public. GSK's license is non exclusive, runs for five years and is a subscription, with annual fees after 50 million dollars upfront, covering models in two cancer types. That shows how Noetik sells: subscriptions to model access for named cancer types.

A contract value is not a price another buyer can apply, and no rate or tier is published.

Ask how the subscription is priced (per cancer type, per model or per seat), what fine tuning on your own data costs, and whether partnered programs such as the Agenus work carry different terms.

Noetik names where its models apply, with a partner's acceptance behind part of it. The licensed OCTO-VC models cover non small cell lung cancer and colorectal cancer, which GSK accepted against its testing criteria. TARIO-2 is applied to response to checkpoint inhibitor combinations with Agenus. The underlying data comes from tumor samples of more than 4,500 patients, without the cancer types listed on Noetik's pages.

Buyers are oncology research and development teams. The response prediction work with Agenus is why Noetik is also listed under clinical trials. No published figures show how the models perform in either licensed cancer type.

Ask which cancer types the dataset covers and in what numbers, and for results in the cancer types you would license.