Description du projet DEENESFRITPL Plateforme innovante d’apprentissage automatique pour la prédiction de candidats potentiels dans le processus de découverte de médicaments La phase initiale du processus de recherche de médicaments a un impact considérable sur le taux de réussite des nouveaux candidats médicaments. La conception de médicaments assistée par ordinateur (CADD) est l’outil le plus rentable de recherche de nouveaux médicaments. Elle permet de cribler de vastes bases de données de molécules et de simuler leur interaction in vivo. Cependant, la simplification des simulations dans le but d’obtenir un temps de calcul acceptable se solde souvent par un faible taux de réussite dans la recherche de molécules bioactives. La société Pharmacelera, basée en Espagne, a pour objectif d’introduire une nouvelle norme de calcul pour la CADD en utilisant une plateforme d’apprentissage automatique pour une prédiction précise des propriétés moléculaires des molécules candidates et des interactions moléculaires pertinentes. Le projet MolPredict, financé par l’UE, mènera une étude de marché et un examen technique pour évaluer la faisabilité de l’entreprise. Afficher les objectifs du projet Masquer les objectifs du projet Objectif The competitiveness of the R&D process in this industry has been steadily declining during the past two decades. Whereas in 2000 the average cost for developing a new drug was close to €1 billion, in 2015 the estimated cost was €2.58 billion, a 150% increase. Consequently, the different actors of the pharmaceutical R&D industry have an urgent need to improve their effectiveness to develop new drugs. In this sense, the early stage of the R&D process shows the greatest potential to increase the success rate of new drug candidates, as it is in this phase where candidate molecules are selected for further testing in humans. Computer Aided Drug Design (CADD) is the most cost-effective tool for drug discovery. These technologies allow researchers to screen large databases of molecules and simulate its interaction in vivo. However, they are extremely intensive in computational resources. As a result, existing solutions have to implement simplifications in the simulations in order to incur acceptable computational times. These simplifications come at the cost of accuracy, finding a low rate of bioactive molecules that, in addition, usually fail during clinical trials. Pharmacelera aims at creating a new computing standard for Computer-Aided Drug Design (CADD) through an open machine learning platform that enables accurate prediction of molecular properties of candidate molecules based on quantum-mechanics (QM) calculations during drug development. By providing early stage ADME-Tox analysis, thus dramatically reducing the failure rate of the drug design process. In addition, by combining HPC, new disruptive molecular modelling techniques (computational chemistry) and machine learning, PharmAgile will be 20x faster and 10x more precise than any existing solution. Consequently, PharmAgile will be able to reduce the overall costs of drug development by up to 19% and the drug development time up to 8%. This translates into $335 million and 2 years saved per new approved drug. Champ scientifique medical and health sciencesbasic medicinepharmacology and pharmacydrug discoverymedical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugsmedical and health sciencesbasic medicinemedicinal chemistrymedical and health sciencesclinical medicinenatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Thème(s) EIC-SMEInst-2018-2020 - SME instrument Appel à propositions H2020-EIC-SMEInst-2018-2020 Voir d’autres projets de cet appel Sous appel H2020-SMEInst-2018-2020-1 Régime de financement SME-1 - SME instrument phase 1 Coordinateur PHARMACELERA SL Contribution nette de l'UE € 50 000,00 Adresse CL ESTEVE PILA NUM, 11 P.1 PTA.1 08173 Saint Cugat Del Valles Barcelona Espagne Voir sur la carte PME L’entreprise s’est définie comme une PME (petite et moyenne entreprise) au moment de la signature de la convention de subvention. Oui Région Este Cataluña Barcelona Type d’activité Private for-profit entities (excluding Higher or Secondary Education Establishments) Liens Contacter l’organisation Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 71 429,00
