Cohort stratification

Clinical trials often fail due to patient heterogeneity, where broad inclusion criteria overlook differences in biological responses.

This leads to two key problems: reduced trial efficacy, as non-responsive patients dilute the results, and inefficient use of resources, as time and money are spent on trials that may not benefit a significant portion of the population.

Stratify. Predict. Treat.

We use our PIMS platform to select patients whose samples show they are likely to respond well to specific targeted medicines, supporting the development of precision treatments tailored to those patients. To achieve this, we leverage our access to patients and their pathological tissues. Our prospective indication-agnostic tissue collection and biobanking capabilities allow us to work directly on patient material.

PIMS is a label-free platform which analyses patients’ cells or tissues to identify their biological responses to drug candidates, or already approved drugs, enabling:

  • Precise patient stratification: Beyond demographics, the platform identifies patients most likely to benefit from a drug, increasing trial success.
  • Biomarker discovery: The platform uncovers new biomarkers, which can predict treatment responses and aid in earlier diagnoses. These biomarkers also drive the development of therapies targeting specific disease pathways for more effective treatments.

Our strategy consists in three steps:

Patient stratification using PIMS platforms

Mode of Action Identification in responder vs non-responders using NPOT platform

Predictive biomarkers identification

Using PIMS and NPOT, we identify patient subgroups most likely to benefit from treatments by analyzing molecular interactions responsible for their responses. We then validate predictive biomarkers within the studied cohort and larger populations to ensure their reliability and applicability across diverse patient groups. This approach enhances precision in treatment development and ensures more effective patient targeting.

Target & MoA deconvolution

Target validation and engagement

Lead compound selection

Cohort stratification

Indication priorization

Biomarkers discovery

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