Project acronym DISCOVERER
Project A novel chemical discovery platform enabled by machine learning
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Proof of Concept (PoC), ERC-2020-PoC
Summary Computational design and discovery of molecules and materials relies on the exploration of increasingly growing chemical spaces. The discovery and formulation of new drugs, antivirals, antibiotics, catalysts, battery materials, and in general chemicals with tailored properties, require a fundamental paradigm shift to search in unchartered swaths of the vast chemical space. This is in stark contrast to current approaches, which start from (commercially available) libraries of compounds from various suppliers. Within the ERC Consolidator grant BeStMo (grant agreement ID 725291) we aimed to substantially advance our ability to model and understand the behaviour of molecules in complex environments. As a result, we successfully developed a set of machine learning and physics-based methods for covalent and non-covalent interactions that now allow an accurate and efficient modelling of molecules of increasing size (from 10 to 1000 atoms). These methods now enable routine calculations of quantum-mechanical properties of molecules throughout chemical compound space, provided that enough reference data is produced as a starting point for training. Within DISCOVERER, we aim to promote a paradigm shift in chemical discovery by inverting the selection pyramid by starting with pre-defined parameters from which new chemical entities are designed through machine learning and AI-enabled algorithms. We can do so by integrating these modules into a commercial platform: “Chemical Space Machine”. DISCOVERER’s main goal is to finalize the development of a commercial alpha version of “Chemical Space Machine” and setting up its commercialisation strategy.
Summary
Computational design and discovery of molecules and materials relies on the exploration of increasingly growing chemical spaces. The discovery and formulation of new drugs, antivirals, antibiotics, catalysts, battery materials, and in general chemicals with tailored properties, require a fundamental paradigm shift to search in unchartered swaths of the vast chemical space. This is in stark contrast to current approaches, which start from (commercially available) libraries of compounds from various suppliers. Within the ERC Consolidator grant BeStMo (grant agreement ID 725291) we aimed to substantially advance our ability to model and understand the behaviour of molecules in complex environments. As a result, we successfully developed a set of machine learning and physics-based methods for covalent and non-covalent interactions that now allow an accurate and efficient modelling of molecules of increasing size (from 10 to 1000 atoms). These methods now enable routine calculations of quantum-mechanical properties of molecules throughout chemical compound space, provided that enough reference data is produced as a starting point for training. Within DISCOVERER, we aim to promote a paradigm shift in chemical discovery by inverting the selection pyramid by starting with pre-defined parameters from which new chemical entities are designed through machine learning and AI-enabled algorithms. We can do so by integrating these modules into a commercial platform: “Chemical Space Machine”. DISCOVERER’s main goal is to finalize the development of a commercial alpha version of “Chemical Space Machine” and setting up its commercialisation strategy.
Max ERC Funding
150 000 €
Duration
Start date: 2021-09-01, End date: 2023-02-28
Project acronym DREAM
Project Demonstration of a Radar Enabled weArable platforM
Researcher (PI) Bjoern Ottersten
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Proof of Concept (PoC), ERC-2020-PoC
Summary Sport research and procedures that aim to increase performance or assist recovery after an injury often require capture of athlete’s motion. However, implementing a motion capture system in routine practice takes significant effort. Capture volume, weather conditions, motion dynamics and athletes' timing (where timing defines coincide movements in relation to external factors) are the key parameters for outdoor sport activities (e.g. track and field or football), yet no available motion capture system is suitable for much needed high accuracy absolute position measurements of body segments in outdoor conditions with minimal setup effort for large capture volumes, which is capable of measuring the athletes' timing. Therefore, there is a significant unmet need for a portable motion capture system that can perform accurate infield measurements on a large volume, even in diverse weather conditions (e.g. sunlight, fog, rain) with the capability of the athletes' timing analysis, which is a combination of reaction time, decision -making and co-ordination in relation to external factors.
DREAM aims to generate a motion capture and mapping system (minimum viable product) that creates a complete orientation and absolute position measurement with no external position reference, provides reliable orientation of body segments even for high dynamic motions, and has a small form factor, which is minimally invasive for the athlete. Further, the offered solution is complementary to existing solutions and operates in real time. DREAM’s value proposition is a cost-effective, robust and accurate infield motion capture and mapping system with minimal setup effort, for large field coverage in any place and in any condition. The uniqueness of the product stems from the complementarity between radar and IMU sensors, enhanced athletes timing analysis, all enabled through an innovative
algorithm developed in the AGNOSTIC ERC Advanced grant (ID 742648).
Summary
Sport research and procedures that aim to increase performance or assist recovery after an injury often require capture of athlete’s motion. However, implementing a motion capture system in routine practice takes significant effort. Capture volume, weather conditions, motion dynamics and athletes' timing (where timing defines coincide movements in relation to external factors) are the key parameters for outdoor sport activities (e.g. track and field or football), yet no available motion capture system is suitable for much needed high accuracy absolute position measurements of body segments in outdoor conditions with minimal setup effort for large capture volumes, which is capable of measuring the athletes' timing. Therefore, there is a significant unmet need for a portable motion capture system that can perform accurate infield measurements on a large volume, even in diverse weather conditions (e.g. sunlight, fog, rain) with the capability of the athletes' timing analysis, which is a combination of reaction time, decision -making and co-ordination in relation to external factors.
DREAM aims to generate a motion capture and mapping system (minimum viable product) that creates a complete orientation and absolute position measurement with no external position reference, provides reliable orientation of body segments even for high dynamic motions, and has a small form factor, which is minimally invasive for the athlete. Further, the offered solution is complementary to existing solutions and operates in real time. DREAM’s value proposition is a cost-effective, robust and accurate infield motion capture and mapping system with minimal setup effort, for large field coverage in any place and in any condition. The uniqueness of the product stems from the complementarity between radar and IMU sensors, enhanced athletes timing analysis, all enabled through an innovative
algorithm developed in the AGNOSTIC ERC Advanced grant (ID 742648).
Max ERC Funding
150 000 €
Duration
Start date: 2020-10-01, End date: 2022-03-31
Project acronym VALIDATE
Project Verifying Authenticity with Liquid crystal-Derived Anti Theft Encoding
Researcher (PI) Jan LAGERWALL
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Proof of Concept (PoC), ERC-2019-PoC
Summary Product counterfeiting, sometimes related to the theft of the original, has emerged as a significant economic issue, with the market value of pirated products equalling or exceeding the gross domestic product of some European countries. A 2016 report from OECD in cooperation with the EU Intellectual Property Office (EUIPO) found that in 2013 counterfeit products sold were worth €375 billion, totalling 2.5% of global trade. Counterfeit products range from high-end consumer luxury goods, to business-to-business products such as machines, chemicals, raw materials or spare parts, and to common consumer products such as toys, pharmaceuticals, cosmetics and food. Some counterfeit products, in particular in the latter category but also, e.g., spare parts, are of low quality, thus creating additional health and safety threats. Valuable raw materials can be stolen at the site of production or in transit, sometimes being replaced by a copy that can be difficult to detect as such by the receiver, sometimes reappearing on the market with no means to detect them as stolen. VALIDATE aims to investigate the commercial feasibility of Cholesteric Spherical Reflectors (CSRs) coatings as high-security identification tags, within a work plan that aims to take our innovation from a Technology Readiness Level (TRL) of 4 to 6/7. This will serve as a key stepping stone towards full commercial exploitation of our CSRs as a game-changing material for authentication. The value proposition of VALIDATE is a physical identifier tag that is effectively unclonable as a result of the manufacturing process, naturally tamper-evident and hard to simulate due to the complexity of the generated patterns. VALIDATE’s end goal is to have a comprehensive description of the commercial feasibility of our technology and, if positive, what commercialization route has the best risk/benefit ratio.
Summary
Product counterfeiting, sometimes related to the theft of the original, has emerged as a significant economic issue, with the market value of pirated products equalling or exceeding the gross domestic product of some European countries. A 2016 report from OECD in cooperation with the EU Intellectual Property Office (EUIPO) found that in 2013 counterfeit products sold were worth €375 billion, totalling 2.5% of global trade. Counterfeit products range from high-end consumer luxury goods, to business-to-business products such as machines, chemicals, raw materials or spare parts, and to common consumer products such as toys, pharmaceuticals, cosmetics and food. Some counterfeit products, in particular in the latter category but also, e.g., spare parts, are of low quality, thus creating additional health and safety threats. Valuable raw materials can be stolen at the site of production or in transit, sometimes being replaced by a copy that can be difficult to detect as such by the receiver, sometimes reappearing on the market with no means to detect them as stolen. VALIDATE aims to investigate the commercial feasibility of Cholesteric Spherical Reflectors (CSRs) coatings as high-security identification tags, within a work plan that aims to take our innovation from a Technology Readiness Level (TRL) of 4 to 6/7. This will serve as a key stepping stone towards full commercial exploitation of our CSRs as a game-changing material for authentication. The value proposition of VALIDATE is a physical identifier tag that is effectively unclonable as a result of the manufacturing process, naturally tamper-evident and hard to simulate due to the complexity of the generated patterns. VALIDATE’s end goal is to have a comprehensive description of the commercial feasibility of our technology and, if positive, what commercialization route has the best risk/benefit ratio.
Max ERC Funding
150 000 €
Duration
Start date: 2019-09-01, End date: 2021-06-30
