Immunai

The models are the entire commercial offer. Pharmaceutical partners are not buying samples or sequencing, both of which they could procure anywhere, they are buying the interpretation, and the Immunodynamics Engine and the foundation models running over AMICA are that interpretation. The clearest demonstration is the October 2025 AstraZeneca agreement, in which the object of the transaction was a drug target the platform had identified. A company that sells what its model concluded, rather than a tool for reaching conclusions, sits at the top of this axis.

A human decision sits at the end by construction, because the output informs choices made by pharmaceutical development teams rather than acting on anyone directly. What raises the stakes above ordinary research tooling is the specific uses named: patient stratification and dose optimisation.

Both shape what happens to people enrolled in trials, deciding who is selected and how much drug they receive, so a wrong model output reaches a patient through a protocol rather than through a prescription. Nothing published describes how an insight is validated before it informs a trial design decision, what confidence is required, or where a sponsor is expected to seek independent confirmation.

Component disclosure is good and technical disclosure is thin. The architecture of the offering is named clearly in three layers, the AMICA database, the AMICA-OS operating system and the Immunodynamics Engine, and the input modalities are specified precisely as single cell RNA, surface protein, immune receptor repertoire and spatial gene expression rather than described as multi omics and left there.

Below that nothing is available: no model architecture, no training corpus size, no benchmark, no validation result and no peer reviewed methods publication was located, which is a notable gap for a company whose entire proposition is the quality of an inference.

The models are presented as proprietary and built in house over the company's own atlas, and the principal components are named, which is a partial disclosure of the kind this axis rewards. One external dependency is disclosed in a specific context: the Parker Institute collaboration names 10x Genomics Chromium technology as the single cell assay platform used to generate that dataset, which identifies part of the data production chain rather than the modelling stack.

No model framework, foundation model provider, compute partner or third party dataset incorporated into training is named anywhere, and for a company describing foundation models the absence of any statement about what they are built on is the gap.

The strongest commercial validation in this lane and no published scientific validation, which is an unusual combination worth stating plainly. Four large pharmaceutical relationships are documented with dates and values: three successive AstraZeneca expansions since late 2022, including one worth up to $85 million for exclusive rights to a target the platform found, plus Bristol Myers Squibb in January 2026 and Boehringer Ingelheim in June 2026.

Repeat purchase by the same sophisticated buyer across four years is a revealed preference that no case study can imitate. Set against that, no peer reviewed validation of the models, no published benchmark and no disclosed outcome from any partnered programme was located, so what is verifiable is that expert customers keep paying, not that the predictions have been shown correct.

The central stewardship question for this company is one its own business model creates, and it is unaddressed. AMICA is described as being enriched by the work performed, and the same atlas and models then serve other partners. That means data generated in one pharmaceutical company's clinical programme plausibly improves the models sold to its direct competitor, and patient samples contributed for one purpose contribute to commercial products serving others.

Nothing published describes segregation between partner derived data and the shared corpus, what a partner's data is permitted to train, or what happens to contributed data when a collaboration ends. Accumulation is the platform's stated advantage, which makes the absence of a boundary statement more significant rather than less. Data types and sources are disclosed clearly, which is what keeps this off the floor.

This axis applies here in substance, unlike elsewhere in this lane, and the applicable regime is not primarily the one the axis is named after. The platform is built on clinical samples and clinically annotated patient data arriving from sponsors and research institutions, so the governing framework is clinical research law, sponsor agreements, institutional review board approvals and the consent under which each sample was collected, rather than a business associate relationship with a covered entity.

Nothing published describes any of it: no statement on consent scope, de identification standard, or what patients whose samples enter the atlas were told about secondary use. The grade sits at the middle band because the company is transparent about what data it holds and silent about the terms on which it holds it.

Two passes located no certification, attestation, trust portal or security page. That absence carries more weight here than for the chemistry led companies in this lane, because this platform holds patient derived clinical data from multiple pharmaceutical sponsors simultaneously, which is both regulated personal data and highly sensitive commercial information belonging to competitors.

Large pharmaceutical partners almost certainly imposed security requirements contractually before shipping trial samples, and the point is that none of it is visible publicly, so a prospective partner starts from zero rather than from a report they can request.

The company is a research partner rather than a device maker, and no clearance is claimed or apparently required. The boundary worth naming is that some of the stated uses sit close to a line. A model output used to select which patients enter a trial, or which patients should receive a therapy, is functionally a biomarker driven selection, and biomarkers that move from exploratory analysis into a registrational patient selection strategy attract regulatory attention as companion diagnostics. Nothing published describes where the company considers that line to sit, whether any partnered biomarker work is intended for a regulatory submission, or what validation standard applies when it is.

No governance framework, model documentation or fairness analysis was located, and the representativeness question here is concrete rather than abstract. A foundation model of the human immune system is only as general as the people whose immune systems trained it, and the training material comes substantially from clinical trial cohorts, which are long documented as unrepresentative of the populations that eventually receive the drugs.

The Parker Institute cohort is described by cancer type and patient count with no demographic composition given. If the atlas underrepresents a population, the biomarkers and stratification strategies built on it will work less well for that population, and that consequence lands in trial design and eventually in the label.

Responsibility is structurally shared and nowhere described. The sponsor makes and owns the development decision, and the clinical trial apparatus of regulatory review, ethics approval and consent governs what reaches a participant, which is real accountability sitting between a model output and a person.

What is absent is the company's own position: nothing states what a partner is entitled to rely on, what the platform's outputs are represented to be fit for, or where responsibility sits if a stratification strategy derived from the atlas turns out to be wrong and a trial enrols the wrong population. For an offering sold on the quality of its inferences, that silence is conspicuous.

Unlike the therapeutics developers in this lane, this company does integrate with customer systems, so the axis applies rather than being set aside. The relevant surfaces are sponsor side: laboratory information management systems, clinical data warehouses and downstream bioinformatics stacks, alongside the clinical annotation that has to be joined to sample level data for the atlas to mean anything.

Third party procurement analysis describes that integration as partnership specific and potentially requiring additional middleware, and nothing published by the company names a supported system, a standard or an interface. There is no provider electronic health record touchpoint, which is expected for this buyer.

This is a genuine cross border question rather than a formality. The company operates from New York with offices in Tel Aviv, Prague and Zurich, and the delivery model involves clinical specimens and their derived data moving to Immunai facilities for profiling rather than software being deployed to the customer.

Human derived samples and patient linked data therefore cross jurisdictions between the United States, Israel and the European Union, each with materially different rules on personal and health data transfer. No residency commitment, processing location statement or transfer mechanism was located, and for a European sponsor in particular that is a question to settle before any sample ships.

Considerably more disclosed than the norm here. Deal values are published rather than withheld, at up to $85 million for the inflammatory bowel disease agreement and up to $37.5 million across 2026 and 2027 for the oncology expansion, partners are named, cumulative funding of close to $270 million is stated, and headcount is given.

One qualification matters for anyone using those numbers: both are eligibility ceilings inclusive of milestones, not amounts received, and nothing discloses upfronts, milestone triggers or royalty terms, so the realised value could be a fraction of the headline. There is no published rate card because engagements are bespoke, which means a prospective partner cannot estimate cost without entering a negotiation.

Coverage is specified by indication rather than claimed generally. Oncology is the deepest area, and the Parker Institute cohort is explicitly pan cancer, naming non small cell lung, small cell lung, gastric, hepatocellular and melanoma among others. Inflammatory bowel disease is established through a dedicated AstraZeneca agreement, and the Boehringer Ingelheim collaboration extends to autoimmune disease through T cell target discovery.

Three therapeutic domains with named partners behind each is real breadth. It stays below the top grade because the platform is positioned as a model of the immune system generally while the demonstrated application is concentrated in immuno oncology.