Antiviral Therapeutics for Rapid Response Against Pandemic Infectious Diseases

Project Information

AVITHRAPID

Grant agreement ID: 101137192

DOI

10.3030/101137192

EC signature date 17 November 2023

Start date 1 January 2024

End date 30 June 2028

Funded under

• Health

Total cost

€ 7 459 253,75

EU contribution

€ 7 459 253,75

Coordinated by

FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV
Germany

Periodic Reporting for period 1 - AVITHRAPID (Antiviral Therapeutics for Rapid Response Against Pandemic Infectious Diseases)

Reporting period: 2024-01-01 to 2025-06-30

Summary of the context and overall objectives of the project

The European Consortium "Antiviral Therapeutics for Rapid Response Against Pandemic Infectious Diseases" (AVITHRAPID) aims to
support the search for novel broad-spectrum antiviral compounds by advancing multiple approaches.
Building on a pre-existing set of bioactive small molecules, which are at least at the validated hit level, AVITHRAPID strives for the
development of pre-clinical candidates targeting several viruses. This will be achieved by combining the relevant expertise
for pre-clinical drug discovery, including molecular modeling, biochemical and cell-based assays, X-ray crystallography, medicinal
chemistry, biophysical binding studies, ADMETox profiling, in vitro and in vivo PK, as well as animal disease models. In addition, the
consortium aims to conduct a Phase 2a clinical trial for a small molecule developed against Zika virus.
Moreover, the consortium aims to identify and validate further viral targets and thereby contribute to the search for novel antiviral
targets. As a consequence of the activities in AVITHRAPID, an early-stage drug discovery pipeline will be established that can be used
to rapidly identify and develop novel antiviral compounds against emerging diseases.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The consortium has achieved several successes. This includes the identification and validation of several new small molecules targeting viral diseases.

We have further validated and optimised several small molecules addressing viral targets that were in addition evaluated using different antiviral assays.
Several peptide-porphyrine conjugates demonstrated good efficacy in two animal models (mouse and neonatal mouse model)

Our work on formulatons led to the identification of an optimal liposomal formulation (Formulation C), capable of efficiently encapsulating antiviral compounds.

We have identified serotype-specific vulnerabilities and outbreak-linked mutations of Dengue virus through phylogenetics.

AVITHRAPID released two machine-learning based models for predicting small molecule solubility and hERG toxicity based on proprietary data from a pharmaceutical partner.

Various virtual screening campaigns resulted in several novel inhibitors of SARS-CoV-2 and Dengue virus as shown by preliminary experimental validation. These compounds may serve as starting point for the development of novel therapeutics.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

WP5 achieved promising results by developing synthetic fusogenic liposomes which will be fused with natural milk-derived extracellular vesicles (mEVs) to obtain a hybrid drug delivery platform. This innovative approach goes beyond the state of the art by integrating efficient drug encapsulation with the biological activity and biocompatibility of mEVs, potentially enhancing both the efficacy and safety of antiviral therapies. The hybrid vesicles represent a novel system capable of improving bioavailability, targeted delivery, and therapeutic modulation. Their dual function—carrier and bioactive agent—may offer advantages over traditional delivery systems.

Several virtual screening campaigns resulted in higher hit rates compared to literature data, suggesting superior quality of the chosen methodology.

The prediction accuracy of the solubility model is 82.3 % and superior to many commercially available tools.