As stated in the consortium agreement with European Commission, the results obtained from Exscalate4CoV are protected by Intellectual Property to promote universal access. All scientific data produced by the consortium will be released in open domain.
18 June 2020 - Exscalate4CoV, the private-public consortium supported by the EU’s Horizon 2020 programme for research and innovation, led by Dompé farmaceutici and currently representing 33 partners, has requested access to clinical trials for the use of Raloxifene in Covid 19 patients.
Raloxifene, already used against Mers and Sars, has been indicated as effective against Sars-Cov2 by the “in-silico” research conducted by the consortium which has shown efficacy in countering the replication of the virus in cells. The IP for its use against Sars-Cov2 has already been protected to facilitate the largest possible access. Raloxifene would be used in mildly symptomatic Covid19 patients to halt the spread of infection.
Raloxifene is currently on the market for the treatment of a non-viral disease (osteoporosis) and is well-tolerated with a known safety profile. The compound is a marketed drug and has been approved by the EMA for clinical use.
This result emerged from the first virtual (in silico) screening conducted on the Consortium’s supercomputers of more than 400.000 molecules (safe-in-man drugs and natural products) made available by Dompé farmaceutici and the partner Fraunhofer (IME)to the Consortium. The molecules were prioritized if in clinical stage or already on the market. 7.000 molecules with certain promising characteristics were tested.
At the core of the project is Exscalate (EXaSCale smArt pLatform Against paThogEns), at present the most powerful (and cost-efficient) intelligent supercomputing platform in the world. Exscalate leverages a "chemical library" of 500 billion molecules, thanks to a processing capacity of more than 3 million molecules per second. Exscalate4Cov’s drug screening process matches massive supercomputing resources of more than 122 Petaflops from four major EU machines (Cineca’s Marconi - 50 Petaflops; ENI’s HPC5 - 51,7 Petaflops, and Barcelona Supercomputing Center’s MareNostrum4 -13.7 Petaflops, Julich’s Juwels - 7 Petaflops) with some of the continent’s best computational and life-science research labs to counter international pandemics faster and more efficiently. This enormous effort will receive experimental validation by the capabilities of consortium partners, both in direction of structural complexes elucidation and in the direction of mechanistic elucidation at biochemical and cellular levels.
For the second phase of testing, Exscalate4CoV consortium’s work continues to use high-performance computing (HPC) platform and aims to find highly specific novel molecules for the development of post-emergency solutions for SARS-CoV-2. As stated in the consortium agreement with the European Commission, the results obtained from Exscalate4Cov are protected by Intellectual Property. The Commission supported this Consortium with a grant of € 3 million of emergency EU funding for advanced computing against coronavirus. The aim of E4C is twofold: to identify molecules capable of targeting the new coronavirus (SARS-CoV-2) and to develop a tool effective for countering future pandemics. More specifically, E4C aims to:
- Establish a sustainable example for a rapid scientific answer to any future pandemic scenario. The model leverages a rapid and effective High Performance Computing platform for the generation and analysis of 3D models and experimental 3D X-ray resolved structures of protein targets from pandemic pathogens
- Drive a fast virtual identification of known drugs (repurposing) or proprietary/commercial candidate molecules to be further experimentally characterized;
- Define a workflow scheme for biochemical and cellular screening test to validate the candidate molecules in previous points and assure, through phenotypic and genomic assays;
- Prepare, together with EMA, a development plan for successful candidates for direct “first-in-human” studies or for further testing in animals for bridging studies;
- Identify SARS-CoV-2 genomic regions involved in host adaptation, pathogenicity and mutations.