Research-stage platform · Patent pending

Could the drug itself reveal who is more likely to respond—before trial enrollment?

Tartei has built a clinical-sample, FTIR and analytical foundation for investigating drug-induced response patterns. We expose patient-derived immune cells to a selected therapy and compare the resulting pattern with a matched control.

We are seeking pharmaceutical collaborators to design focused studies testing whether these patterns are associated with actual treatment outcomes and can help define potential responder groups.

Seeking pharmaceutical collaborators for tailored drug-response studies.

01

Patient-derived immune cells

02

Drug versus matched control

03

Outcome-linked AI study

01The challenge

A real treatment effect can be lost inside patient heterogeneity.

Patients with the same diagnosis can respond very differently to the same therapy. When responders and non-responders are analyzed together, a meaningful effect may be difficult to detect.

Drug developers need better ways to form responder hypotheses—and test them before committing to broader clinical development.

The molecule may not be the only question. The selected population may matter just as much.

02The Tartei approach

Don't start with one biomarker. Start with the drug-induced response.

Many biomarker programs begin with a marker selected in advance. Tartei starts with the biological perturbation itself.

Samples from the same patient are divided into drug and control conditions. FTIR measures the broad molecular change associated with exposure to the therapy. In the planned study, AI will examine how multiple spectral changes behave together and test whether the resulting patterns are associated with independently recorded clinical outcomes.

Layer

The drug becomes the probe

The selected therapy is applied directly to patient-derived immune cells outside the body. Comparing drug and control conditions from the same patient helps control for baseline differences between people.

Layer

FTIR provides a broad readout

FTIR measures a broad molecular response pattern in the cells and culture-derived material. This may capture coordinated changes that could be missed when an assay examines only one predefined marker.

Core of the platform

AI searches for responder patterns

In the planned outcome-linked study, our AI will analyze the complete drug-versus-control spectral difference. It will test whether shared response patterns are associated with better clinical outcomes.

03 — Workflow

From one blood sample to a testable responder hypothesis

Patient sample → Drug versus control → FTIR response → AI analysis → Potential responder group

  1. 01

    Patient sample

    Immune cells are isolated from the patient's blood.

    Peripheral blood mononuclear cells, or PBMCs, are immune cells isolated from blood.

  2. 02

    Drug versus control

    The sample is divided into matched conditions. One receives the selected therapy. The other serves as the control.

  3. 03

    FTIR response measurement

    FTIR measures the broad molecular response pattern produced under each condition.

  4. 04

    AI plus clinical outcomes

    In the planned study, our AI will analyze the drug-versus-control spectral difference and test whether it is associated with patients' independently recorded treatment outcomes.

    Actual clinical outcomes enter here as a separate, independent input.

  5. 05

    Responder hypothesis

    The analysis will look for shared patterns among patients who benefited, producing a potential responder group for further testing.

The output is a responder hypothesis to test—not a clinical treatment recommendation.

What is measured

The difference between the drug-treated and control parts of the same patient sample. Each patient acts as their own reference, helping isolate the drug-associated response from baseline differences between donors.

Intended output

A responder hypothesis: which response patterns occur in patients who benefited, and whether they could be tested in a future study.

04Current status

A strong foundation. The responder study is the next validation phase.

  1. 01

    More than 100 patient samples

    The team established research FTIR workflows and analyzed samples from more than 100 patients across rheumatoid arthritis and comparator groups, obtained through collaborating clinicians under the required ethics-committee approvals and informed consent.

  2. 02

    Multiple sample types

    The research has included plasma, whole blood and extracellular vesicles, or EVs, providing experience across different patient-derived materials.

  3. 03

    Algorithms and clinical relationships

    We developed algorithms to detect group-associated spectral differences and examine relationships with clinical and biological measures, including DAS28 and IL-6.

  4. 04

    Early drug-response feasibility

    Exploratory ex vivo drug-response experiments have been conducted using samples from a handful of patients. Drug-associated spectral changes were measurable, but the work is not yet sufficiently large to determine whether the patterns can identify responder groups.

The next validation study

We are seeking a pharmaceutical collaborator for a sufficiently sized, blinded and outcome-linked drug-response study.

The study will test whether drug-induced spectral patterns, analyzed together with independently recorded treatment outcomes, can support the identification of potential responder groups.

The therapy, patient population, experimental conditions, clinical endpoint and analytical plan can be tailored to the collaborator's development question.

What we have

Clinical samples, FTIR workflows, analytical algorithms and early drug-response feasibility.

What comes next

The study that tests the responder-selection hypothesis.

05Potential value

One platform. Several high-value development questions.

If supported by blinded, outcome-linked studies, the approach could add patient-derived response evidence to pharmaceutical development decisions.

Trial enrichment

Test whether the response pattern can help identify a patient group more likely to benefit in a future trial.

Patient-group selection

Compare drug-induced patterns across disease subtypes and clinically different patient populations.

Earlier development evidence

Add functional, patient-derived evidence when evaluating a therapy or development program.

Biomarker research

Generate responder hypotheses that can be tested in larger, independent studies.

06Clinical setting

Built inside the clinical environment—not separated from it.

Our research is conducted in a hospital-based laboratory setting, in close contact with collaborating clinicians.

Subject to the required ethics-committee approvals and informed consent, this environment allows us to obtain well-characterized samples from real patients, including people with complex clinical profiles and multiple conditions.

Comparison samples are also obtained from people attending routine workplace health screenings.

The close connection between the laboratory and clinical teams supports efficient study design and protocol development.

Daily interaction with treating clinicians

Samples from clinically complex patients

Screened comparison groups

On-site research and ethics infrastructure

This environment allows us to design studies around real patients and practical pharmaceutical-development questions.

07 — Partner with us

Bring one therapy. Let's investigate one important question.

We collaborate with pharmaceutical teams to design focused studies around a selected therapy, patient population and clinical-development question.

Each study can be tailored to the program's relevant sample types, drug-exposure conditions, controls, clinical endpoints and analytical requirements.

This is a practical first collaboration—not a request for a broad platform commitment.

One selected therapy

One defined disease or patient group

Patient-derived blood samples

Matched drug and control conditions

One relevant clinical outcome

Blinded analysis and written assessment

In a 30-minute meeting, we can discuss your therapy, patient population and development question—and explore how a focused Tartei study could be designed around your program.

Discuss a focused study

08Contact

Discuss a focused drug-response study

Do you have a therapy, patient population or development question that could fit this approach? Send us a short message.

We welcome both specific study proposals and early exploratory discussions.

Tell us briefly about your therapy, disease area or development question.

Please do not submit confidential information or patient-identifiable data.