The key stages of the OASIS project

Timeline & Deliverables

Discover the main phases of the project and the expected results.

Project Phases

Launch

Establishment of clinical cohorts and start of patient recruitment

Collection

Intensive collection of biological samples and clinical data

Analytics

Molecular analyses, imaging and AI model development

Validation

Clinical validation of the OASIS score and companion tests

Deployment

Provision of tools for clinical practice

The major deliverables of the OASIS project

Expected Results

  • A predictive score for ADC response and toxicity (OASIS SCORE) based on clinical, molecular, and imaging data
  • The most suitable technologies to predict ADC response, to be developed as a companion diagnostic test
  • A structured European database combining biological and clinical data
  • A biobank of tumor-derived organoids
  • A next-generation ADC prototype developed from the results of the program

A turning point in precision medicine

Expected Impacts

For Patients

Predict treatment response and risk of toxicity. Improve survival and quality of life by avoiding ineffective therapies.

For Clinical Practice

Help doctors choose the right ADC for each patient, optimize the use of these therapies in treatment sequencing.

For Clinical Research

Enable more relevant selection of patients in clinical trials, reduce failure rates in the development of new ADCs.

For Health Authorities

Support the evaluation and approval of ADCs by regulatory agencies, enable “tumor-agnostic” authorization.

For Society

Control healthcare spending by reserving expensive treatments for patients who will truly benefit from them.

For the Pharmaceutical Industry

Guide the design of more targeted ADCs, reduce the risks of failure and anticipate drug demand.

Final Objective: Guide Therapeutic Decisions

All data collected will feed the development of the OASIS Score, a decision support tool based on artificial intelligence.

This score will estimate, based on the unique characteristics of each patient and each tumor:

  • The probability of response to a given ADC
  • The associated risk of toxicity

The goal is to guide treatment decisions as accurately as possible and determine which technology is most effective in predicting response to ADCs, with a view to developing it as a diagnostic companion test.