| Title: | International consortium for integrative genomics prediction (INTERVENE) |
| Lead Institution: | University of Tartu |
| Principal investigator: | Dr Reedik Magi |
Application 78537
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About
Data science based methods (including artificial intelligence) are expected to have a transformative impact on our ability to understand disease development and trajectories and provide input for tailored treatment options based on individual's genetic make-up and other characteristics. Nonetheless, several challenges remain related to the advance of data science into everyday clinical practice. The emergence of genomic sequencing and other molecular profiling methods together with the digitalization of healthcare data collections have created unprecedented opportunities for better treatment options. INTERVENE is an international consortium that seeks to leverage these vast, but underused data resources to generate clinically actionable knowledge for improved understanding of diseases and treatment options tailored to individuals. It seeks to advance AI-facilitated analyses of complex medical data to develop genetic risk scores, which estimate the genetic predisposition for individuals to develop a particular disease. A central aim is to meet the urgent need for clinically validated risk scores with predictive value for complex and rare diseases, applicability for disease screening, and understandable by clinicians and citizens. INTERVENE will demonstrate the potential and benefits of powerful AI technologies on the next generation of integrative genetic scores (IGS). The clinical and economic benefits of IGS will be evaluated in disease areas with major public health burden. The newly developed IGS will be taken into the clinical environment and their real-world benefits will be evaluated together with clinical experts, European patients advocate groups and medical societies and considering regulatory and ethical implications. Thus, a framework for legally and ethically responsible translation into wider clinical practice will be developed.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 11869 | A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk | Bradley Jermy (+29) | 2024 | Nature Communications |
| 11819 | Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning | Remo Monti (+23) | 2024 | American Journal of Human Genetics |
Enabling scientific discoveries that improve human health