How Machine Learning is used to find the COVID-19 Vaccine

How Machine Learning is used to find the COVID-19 Vaccine

Coronavirus is a newly declared virus that has caused the outbreak of respiratory illness that is given the name of COVID-19 which was first initiated and diagnosed in China. As per the statistics given by worldmeters, there are 145,384+ infected cases around the world with 5,416 deaths and 70,936 recovered cases of COVID-19. More than 35 countries over the globe have been affected by evacuations taking place to protect foreign nationals from the virus. Major countries like China, Japan, HongKong, Philippines, USA, etc. have been reported deaths each respectively. Stats are still fluctuating!

As per the information provided by various resources COVID-19 may be passed from person to person. Community spread has been seen which means people have been infected with the virus in a particular area including people who are unsure how and where they have been affected. People throughout China have been affected including over 100 countries. On January 30, 2020, the WHO declared the COVID-19

outbreak a public health emergency. The primary symptoms includecough, fever, and shortness of breath.

How does Machine Learning use to find any virus vaccine?

Those who are taking remedial measures in order to stay away from the COVID-19 are required to need a CT scan and AI is helping to speed up the diagnosis reducing the time from 5-minutes to 20 seconds.

Machine Learning can be valued in the healthcare industry with the ability to process huge datasets above the scope of the capability of humans and the algorithms are converted into insights that aid physicians in planning and providing care to get satisfactory treatment.

Computer-Aided Drug Design (CADD) has been come out as a method for developing candidate drugs for the treatment of many types of diseases. The discovery of drugs and developing a new drug is a very long-term process and very costly, that is why the CADD approach is used in pharmaceutical companies to resolve this issue to some extent.

It is a computational approach to discover developed, enhances and analyzes drug and biologically related active compounds. This approach is used for virtual screening, virtual library design, lead optimization and used for quick evaluation of large compounds to guide and speed up the development of the new active biological compound.

As the virus has raced around the world, more than 350 genome sequences have been detected, as shared by GISAID, an online platform.

The 3D design of Genome protein has been released. Various Biotech companies of China have been gearing up to repurpose existing drugs as treatment for the coronavirus outbreak in Wuhan.

The Ethics of using Machine Learning in Healthcare Let us understand the concept by taking an example of the deadliest pandemic of coronavirus. Machine Learning algorithms may help in detecting the severity of coronavirus in patients having the doubt of this deadly disease.

Google's DeepMind division utilized its most recent AI calculations and its registering capacity to comprehend the proteins that may make up the infection, and distributed the discoveries to help other people create medications. BenevolentAI utilizes AI frameworks to assemble drugs that can battle the world's hardest maladies and is currently helping help the endeavors to treat coronavirus, the first run through the organization concentrated its item on irresistible sicknesses. Inside

long stretches of the flare-up, it utilized its prescient abilities to propose existing medications that may be helpful.

How Machine Learning is used to find the COVID19 vaccine?

All Community is trying to find the solution, one of them is Matt O'Connor, he is data science and strategy coach also founder of Reboot.ai.

His approach was train the model from scratch so he can get robust and realistic molecules, He combined data sets from two sources: i) Moses data set and ii) ChEMBL data set. Together these two data sets represented about 4 million smiles and it took 4 days just to train the initial network.

After traning the model result score was <-16.075 and weight <900 daltons, he found one of the existing inhibitors Remdesivir (it was

designed for Ebola virus) has good score, he also found other novel inhibitors.

Chinese researchers have screened 30 different compounds (a mix of anti-HIV drugs, an immunosuppressant, an anti-schizophrenia drug, and also natural products and Chinese traditional medicines), for their efficacity on 2019-nCoV. According to the Chinese Academy of Sciences (CAS), three of these molecules have fairly good inhibitory effects: Remdesivir - initially designed to combat the Ebola virus, developed by Gilead Sciences. Works as an RNA polymerase inhibitor.

Chloroquine - an antimalaria drug initially discovered by Bayer, later repurposed as an anti-HIV in clinical trials. The anti-viral mechanism of action is still unclear to me.

Ritonavir - an anti-HIV drug developed by Abbott (now Abbvie). Works as a protease inhibitor.

The Chinese researchers are now trying to get approval for a clinical trial to validate their efficacy on 2019-nCoV in patients.

Computer-based intelligence or simply Artificial Intelligence can spot designs in information and make expectations, and the expectation is these instruments could recognize sedate possibilities to test on people inside months. WHO and governments across the globe are working

round the clock by using technology to fight the outbreak. Though the virus is spreading but taking precautions will help you stay safe from the pandemic of Coronavirus.

If you are planing to create something new with ML and need help contact us, At Valiant Technosof we have a team of developers which is an expert in Machine Leaning and AI. Stay healthy, Stay Safe

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