Antiviral Therapeutics for Rapid Response Against Pandemic Infectious Diseases

Informazioni relative al progetto

AVITHRAPID

ID dell’accordo di sovvenzione: 101137192

DOI

10.3030/101137192

Data della firma CE 17 Novembre 2023

Data di avvio 1 Gennaio 2024

Data di completamento 30 Giugno 2028

Finanziato da

• Health

Costo totale

€ 7 459 253,75

Contributo UE

€ 7 459 253,75

Coordinato da

FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV
Germany

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

Periodo di rendicontazione: 2024-01-01 al 2025-06-30

Sintesi del contesto e degli obiettivi generali del progetto

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.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

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.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

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.