Imagine if doctors could know exactly which medication will work for a patient without spending months on trial-and-error. This project looks at blood markers and genetic data to spot people who won't respond to standard psychiatric drugs early on. It's like having a GPS for mental health treatment instead of guessing which road to take.
Up to one third of psychiatric patients fail standard drug therapy, leading to a costly and dangerous trial-and-error treatment process. There is currently no reliable way to identify these 'treatment-resistant' patients early in their care.
The project developed a large-scale genetic database for treatment resistance and multimodal machine learning models to predict patient response based on blood markers.
If you are a drug development firm dealing with high failure rates in psychiatric clinical trials — this project developed genetic and biological markers that identify non-responders. This allows for better patient stratification in trials for schizophrenia, bipolar disorder, and depression.
If you are a diagnostic kit manufacturer dealing with a lack of objective biomarkers for mental health — this project identified blood-based markers using the Olink Explore HT panel. You can use these findings to develop a commercial test for treatment resistance.
If you are a CDSS provider dealing with outdated 'step-wise' treatment guidelines — this project developed multimodal machine learning models to predict risk. This enables the creation of a tool that suggests intensive treatment paths based on a patient's biological profile.
Based on available project data, no specific pricing or commercial cost for the resulting tools has been disclosed.
The project uses large international datasets and pan-European clinical trials, suggesting the underlying data models are designed for large-scale application across different populations.
Based on available project data, specific licensing terms are not mentioned, though the consortium includes 4 industry partners who typically manage commercialization paths.
The project is currently navigating regulatory approval for Randomised Controlled Trials (RCTs) in accordance with international laws for clinical trials.
The project is prototyping the integration of personalized treatment decision support and patient-oriented decision-making boards into clinical practice.
The consortium is heavily research-driven with 15 universities and 6 research institutes, but it maintains a critical commercial link with 4 industry partners (including 2 SMEs). Spanning 14 countries, this structure ensures that the biological findings are validated across diverse European populations, reducing the risk of regional bias in the predictive models.
Contact Universitaet Muenster regarding the Psych-STRATA pharmacogenomics program.
Contact us to identify the specific industry partners in the consortium for licensing opportunities.
