Scipher Medicine and its partners have identified a new approach that could cut the Covid-19 drug discovery timeline from years to months.
In partnership with Northeastern University, Brigham and Women’s Hospital, Harvard Medical School and Boston University’s National Emerging Infectious Diseases Laboratories (NEIDL) in the US, Scipher detected new drug opportunities for Covid-19.
This new method can be leveraged to quickly discover drugs for new and developing viruses.
The partners integrated network biology and artificial intelligence (AI) platform with clinico-genomic patient data and were able to reduce the duration of research to detect Covid-19 treatments from three years to just two months.
The latest approach is considered crucial progress in creating and testing efficient therapies against diseases, compared to standard methodologies that fail to meet the needs to rapidly develop cures for emergent diseases.
During the studies, the researchers detected repurposing opportunities that target the human proteome with a success rate of 62%.
Furthermore, 70% of the high-ranking candidates targeting the virus demonstrated the ability to attach viral proteins.
The researchers said that the study results predicted disease manifestations in body parts in line with clinical observations. But the appearance in various reproductive system tissues and spleen was not expected, possibly linked to disruptions in the immune system regulation.
Currently, Scipher is using its network biology and AI platform, Spectra, along with clinico-genomic data from the molecular diagnostic testing business, to develop new precision treatments for autoimmune diseases.
Scipher Medicine CEO Alif Saleh said: “Spectra’s proven ability to discover drug targets from patient data is unique in the industry.
“Our next objective is to leverage Spectra’s capabilities in pharma collaborations to transform drug discovery in autoimmune diseases and make the development process faster, more cost-effective and predictable.”
The company noted that Spectra is not a model but a disease representation.
Spectra can aid in detecting the individual disease signature of patients, forecast response to approved drugs and find new drug targets in people who do not respond to present treatments.