Currently, healthcare is reactive, which hinders the diagnosis of sickness and increases the risk of undetected illness. Furthermore, healthcare often generalises treatment – drugs are prescribed using statistical averages and work for half of those who take it (source: The Jackson Laboratory — What is personalised medicine?). Industry misses out on the opportunity to use individuals' genetic data for the prevention or highly-personalised treatment of a wide range of diseases. It requires technology-reinforced solutions that would analyse an individual’s genetic data and draw connections between such data and the person’s probability of being affected by certain diseases, as well as the most effective treatment methods. Such solutions will allow small and medium-sized enterprises (SMEs) to create novel products and services to boost the competitiveness of European industry.
What is the current situation/existing inefficient solution?
There is no established solution for efficient widespread collection, analysis and application of genetic data on the market – the area is mostly untapped. Only breast cancer is partially addressed by genetic profiling.
Stakeholders affected by this problem
Citizens, practitioners, service providers, corporates, regulators, clinical trial facilities.
How will the solution change the lives of the beneficiaries?
Genetic data can be leveraged for preventative healthcare in three general areas
- everyday disease prevention
- severe disease prevention
- drug consumption monitoring (including side effect analysis)
In each case the solution offers a technological boost beneficial to both patients and providers of medical goods and services: hospitals, practitioners, coaches, software and hardware developers.
For instance, genetic profiles may be used for healthcare programmes, lifestyle coaching, assessing health risks, as well as for the prevention and treatment of a variety of diseases – cardiovascular, diabetes, cancer, mental illnesses etc.
How will the solution impact European industry?
The challenge encompasses many areas of healthcare and the solution will boost the competitiveness of the whole healthcare industry by improving the efficiency of medical services, by providing SMEs and start-ups with technology they could use to develop innovative products and business models in the predictive healthcare domain, and by speeding up post-COVID recovery.
What are some of the potential actions that could be taken to solve this problem?
The solution could collect and analyse data, and present it in an interpretable and user-friendly way, derive recommendations or insights (e.g. for patients, practitioners, companies and policymakers), as well as integrate the insights in the ecosystem of related applications.
What are the technical methods that could be used to tackle the challenge?
Statistical modelling, machine learning, etc.
Technical and non-technical specific requirements for the solution?
The developed solution should align with the respective EU legislation.
Support for the teams tackling this challenge
Estonian Biobank will provide the data to create tools to extract insights. They will also share review papers, opinions about the current state of the art related to the data and provide the experience and know-how on how to use the data. Expert mentors will support the teams throughout the hackathon.
Datasets available during the hackathon
A mock dataset will be constructed based on the real Estonian Biobank repository with more than 200,000 consenting participants with existing genetic profiles and electronic health records of at least 15 years. Datasets will be provided based on the ideas of the teams selected to participate in the hackathon.
The winner will receive Estonian Biobank’s mentorship and support in the further development of the prototype along with continuous access to data and a chance to enter Estonian Biobank’s acceleration programme free of charge.
About the challenge partner
The Estonian Biobank (EBB) is a population-based biobank of the Estonian Genome Center at the University of Tartu (EGCUT). Its cohort size is currently close to 200,000 participants ('gene donors' aged 18 and older) and closely reflects Estonia's age, sex and geographical distribution. Estonians represent 83%, Russians 14%, and other nationalities 3% of all participants.
Genome-wide association study (GWAS) analyses have been performed on all gene donors, and RNA samples from 2,100 individuals are available for gene expression studies, along with 45 biomarkers from serum and plasma.
As Estonia systematically collects health histories of its citizens, genetic information from Estonian Biobank can be easily correlated with real-life healthcare records to find interrelations.