Summary
- Profile Type
- Technology offer
- POD Reference
- TOIT20231123022
- Term of Validity
- 5 December 2023 - 4 December 2025
- Company's Country
- Italy
- Type of partnership
- Research and development cooperation agreement
- Targeted Countries
- All countries
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General information
- Short Summary
- Italian ICT company carried out a feasibility study in the field of precision medicine focused on analysing and identifying different materials (carriers) suitable for the release of drugs into the body through machine learning. The proof of concept (PoC) is available as a web app and the company is now looking for partners (Universities, research centres or pharmaceutical companies) to further implement the tool under research cooperation agreement.
- Full Description
-
SME located in Piedmont region (North-West Italy), founded in 1995 as internet solution and web related services provider (such as website development, e-mail and hosting), progressively expanded its business to asset and facility management in sectors like utilities, pharma and automotive.
Investing around 10% of its turnover in research and development, the company actively participates in research and feasibility projects as a way to stay at the forefront of knowledge and keep transferring research results into new products and services.
In the framework of a collaborative research and innovation project funded by the European Regional Development Fund, the company, together with local industrial and academic partners, has carried out a feasibility study in the field of precision medicine, focused on analysing and identifying different materials (carriers) suitable for the release of drugs into the body.
Ongoing research studies concerning identification of carriers’ optimal characteristics to efficiently release active ingredients into the body are based on carriers’ behaviour simulations using quantum-mechanical methods, which could be very expensive in terms of both time and costs.
The proof of concept (PoC) realized by the company with machine learning algorithms could help pharmaceutical companies or research centres study and prepare suitable carriers without running all the simulations. The search field is therefore narrowed down to a smaller number of candidates where to focus more in-depth research at a later time, allowing both time and cost saving.
While carrying out the feasibility study, two machine learning prototype models were developed, able to make predictions on the structure-property relationships of metal-organic microporous materials (metal-organic frameworks). In fact, metal-organic frameworks are chemically very versatile because they are made up of structural units that can be modulated and assembled with different topologies. Furthermore, the three-dimensional porous lattices are characterized by cages and channels of different shapes and sizes which make them selective for the capture and release of molecules. The results obtained with metal-organic frameworks molecules have been verified and the distribution of electric charges has been accurately calculated, as well as the results obtained with the predictive model.
The PoC is currently available as a web app, with the potential of providing a professional service based on the models created, targeting research centers/pharmaceutical companies that need to select metal-organic frameworks molecules suitable for complete computational analysis with the aim of creating “carriers” of drugs for precision medicine.
The company is therefore looking for partners (Universities, research centres or pharmaceutical companies) interested in adopting and further implementing the tool under research cooperation agreement, with a view to bringing the technology to the market. - Advantages and Innovations
-
• Time/costs efficiency compared to quantum-mechanical methods;
• Help for pharmaceutical companies/research centres, avoiding running all simulations;
• Web App available for metal-organic frameworks structures. - Stage of Development
- Under development
- Sustainable Development Goals
- Goal 3: Good Health and Well-being
- IPR status
- Secret know-how
Partner Sought
- Expected Role of a Partner
- Ideal partners are Universities, research centres or pharmaceutical companies working in the precision medicine field, interested in adopting and further implementing the Artificial Intelligence tool for controlled drug release optimization, under research cooperation agreement.
- Type and Size of Partner
- University
- Big company
- SME 50 - 249
- SME 11-49
- R&D Institution
- Type of partnership
- Research and development cooperation agreement
Dissemination
- Technology keywords
- 03004006 - Organic Substances
- 06001015 - Pharmaceutical Products / Drugs
- Market keywords
- 05007002 - Pharmaceuticals/fine chemicals
- 05003005 - Drug delivery and other equipment
- Sector Groups Involved
- Digital
- Health
- Targeted countries
- All countries