The speed and the disruptive nature of the COVID-19 pandemic have taken both public health and biomedical research by surprise, demanding the rapid deployment of new interventions and the development and testing of an effective cure and vaccine. Considering the compressed timescales, the traditional methodologies relying on iterative development, experimental testing, clinical validation, and approval of new compounds are not feasible. A more realistic strategy relies on drug repurposing, required to identify clinically approved drugs, with known toxicities and side effects that may have a therapeutic effect in COVID-19 patients.
Technology Overview
In this invention, Northeastern University researchers have adapted the network-based toolset to COVID-19, recovering the primary pulmonary manifestations of the virus in the lung as well as observed comorbidities associated with cardiovascular diseases. The research results also predict that the virus can manifest itself in other tissues, such as the reproductive system and brain regions. Moreover, it could have neurological comorbidities. Northeastern University researchers build on these findings to deploy three network-based drug repurposing strategies such as relying on network proximity, diffusion, and AI-based metrics and ranking all approved drugs based on their likely efficacy for COVID-19 patients by aggregating all predictions the result arrived with 81 promising repurposing candidates. The drugs currently in clinical trials are used to validate the accuracy of these predictions, and an expression-based validation of selected candidates suggests that these drugs with known toxicities and side effects could be moved to clinical trials rapidly.
- This list of ranked drugs can have a therapeutic effect for treating COVID-19
- The combination of network methods is novel, which uses AI-network methods, graph theory proximity-based models, and diffusion methods
- Can find potential drugs and fast-forward towards clinical trials for COVID‑19 treatment
- License
- Partnering
- Research collaboration
Patent Information:
For Information, Contact:
Mark Saulich
Associate Director of Commercialization
Northeastern University
Deisy Morselli Gysi
Albert-Laszlo Barabasi
Italo do Valle
Onur Varol
Xiao Gan
Asher Ameli
Joseph Loscalzo
Marinka Zitnik