COVID-19 or coronavirus is an infectious disease caused by a strain of a new virus, which is ravaging the world at present. So far, this new disease has claimed over 16,500 lives and infected more than 3,50,000 people across the globe. Brett Averso and Andrew Satz are two graduates from the department of Data Science Institute (DSI), Columbia University are making use of computer-based design to develop treatments for coronavirus as soon as possible.
Andrew Satz is the CEO and Brett Averso is the CTO of a startup, EVQLV. This startup is making algorithms that can computationally generate, screen, and optimize countless therapeutic antibodies. Making use of their technology, EVQLV is trying to come up with treatments that are very likely to assist in the treatment of COVID-19 infected patients. The machine learning algorithm quickly screens for therapeutic antibodies that have higher chances of attaining success in the treatment of COVID-19 patients.
Algorithms to Reduce both Time and Cost of Discovery of COVID-19 Treatment
Conducting discovery of antibody in a lab usually takes some years; however, with this algorithm, it takes only a week or so to spot antibodies capable of fighting against this infectious strain of the virus. As such, it is vital to speed up the development of COVID-19 treatment that could assist in the recovery of the infected people.
Andrew Satz opines that their algorithm can spot promising antibodies candidates capable of putting up an effective fight against the virus. He further adds that on an average, studies usually take around five long years along with almost half a billion dollar to figure out and optimize antibodies in a laboratory. Their algorithms would diminish the cost and time significantly, adds Satz.
Antibody discovery comprises the first phase of the entire process. Speeding up this process plays an important role in accelerating the pace of discovery of COVID-19 treatment. After EVQLV does the computer-based calculations to discover antibody and its subsequent optimization, the gene sequences of promising antibody is sent to its lab partners. The engineers and technicians in the laboratory then examine the antibodies, which takes some months in this case instead of many years. Successful antibodies are then implemented on studies on animal and then eventually on humans.
Satz states that it is possible to come up with a treatment for coronavirus ready by 2020-end, thanks to the international urgency to come up with a treatment for the same.
