New Wisdom Yuan Guide: New Coronary Pneumonia globally diagnosed more than 340,000, death of more than 14,000. Yann LeCun tweeted: ‘Infecting COVID-19 doubles your chances of dying within a year. At a critical time, WHO is conducting large-scale global trials of four of the most promising new coronavirus treatments, and alumni of the Gobigbig Scoita Institute of Science are using machine learning to quickly discover new coronavirus treatments.
Original title: New coronavirus or personal mortality doubled during the year! Columbia alumni use machine learning to sift through antibodies
Editor/Zhang Jia, Wu Lin
Source: Xin Zhiyuan
On Friday, the World Health Organization announced a large-scale global trial called SOLIDARITY to find drugs that could be used to treat new coronary pneumonia. The study, which could include thousands of patients in dozens of countries, is as simple as possible so that even hospitals that have flooded into the large number of COVID-19 patients can get involved.
Scientists have recommended dozens of existing compounds for testing, but WHO is focusing on four treatments it considers most promising: an experimental antiviral compound called redsievir; the malaria drugs chloroquine and hydroxychloroquine; a combination of two HIV drugs, lopinavir and litonavir; and lopinavir and litonavir, plus interferon beta.
Data on the use of these drugs in PATIENTs with COVID-19 have shown that HIV combination therapy has failed in a small study in China, but WHO believes large-scale trials of more patients are needed.
In addition to testing existing potential drugs, it is also necessary to find new treatments.
DSI alumni use machine learning to quickly discover new coronavirus treatments
Two graduates of Columbia University’s Data Science Institute (DSI) are using computational designs to quickly discover treatments for coronaviruses.
Andrew Satz and Brett Averso are CEO and Chief Technology Officer of EVQLV, respectively. EVQLV is a start-up that creates machine learning algorithms that identify and screen hundreds of millions of potential antibody treatments in just a few days, far beyond any laboratory. It takes an average of five and a half years to find and optimize antibodies in the lab, and the algorithm can identify viral antibodies in just one week.
Finding antibodies is the first step in the discovery of new coronavirus therapies. “What our algorithm is doing is reducing the likelihood that drug discovery in the lab will fail. Satz added: “We try and error as much as possible in computer simulations to reduce the likelihood of errors in downstream labs.” This saves a lot of time from tedious and time-consuming work. “
Brett Averso says some antibodies designed by EVQLV are designed to prevent coronaviruses from attaching to the body. “The right-shaped antibody binds to proteins located on the surface of human cells and coronaviruses, just as the relationship between locks and keys. This combination prevents the virus from spreading through out of the body, potentially limiting the disease. “
EVQLV works with immunoprecise Antibodies (IPA), a company focused on the discovery of therapeutic antibodies. EVQLV sends promising antibody gene sequences to its laboratory partners after discovering and optimizing antibodies. IPA will then engineer, manufacture, and test the most promising candidate antibodies, a process that will no longer take years and take only a few months. Successful antibodies will be used in animal research, and finally human studies.
Given the urgency of the international fight against coronavirus, Satz said it is possible to prepare treatment options for patients by the end of 2020.
Satz and Averso, who met during their time at DSI, are committed to “data to good.” The two have worked together for many years in the cross-cutting areas of data science and healthcare, and in December 2019 established EVQLV, which aims to use AI technology to accelerate the detection, development and cure of health problems. The company has grown to 12 team members with technologies in the areas of machine learning and molecular biology, software engineering and antibody design, cloud computing, and clinical development. The duo typically work 100 hours a week because they are passionate about data science and are committed to “helping heal those in need.”
Yann LeCun retweet: Infected WITH COVID-19 doubles your chances of dying within a year
Recently, DeepLearning boss Yann LeCun tweeted a tweet from statistician David Speigelhalter and commented that if you are infected with COVID-19, the probability of death is about equal to the probability of death for any other cause in a year. Surprisingly, this is true regardless of age. Infection with COVID-19 doubles your chances of dying within a year.
In Speigelhalter’s blog post, he uses life tables provided by the Office for National Statistics. Due to congenital diseases and birth trauma, there is a peak in death after birth, and 9 or 10 years is a trough, followed by steady linear growth. Regardless of age, the proportion of people who die each year is growing at a rate of about 9 per cent. So the average risk of death doubles in eight years.
Annual risk of death in England and Wales 2016-2018 by the Office for National Statistics
A new report by researchers at Imperial College London provides estimates of the risk of death from a specific age after the new coronavirus infection, as shown in the table below.
Mortality rate after COVID-19 infection in different age groups
If the mortality rate after COVID-19 is superimposed on the “life table” above (drawing the 7th year of every 10 years), the results are shown below to show that the risk of death after COVID-19 infection is consistent with the normal risk of death.
Then, the COVID-19 risk was compared with the risk of death in the life table to arrive at a relative risk, ranging from 0.5 to 2.
It can be seen that the risk of death from COVID-19 is equivalent to the risk of death for any other cause within one year. In the blogger’s words, “infecting COVID-19 is like packing up the risk of a year to a week or two.”
But the bloggers also point out that there will be a lot of overlap between the two groups – many people who die of COVID-19 will die anytime soon – so these risks cannot be simply added together or doubled the risk of infection. Crucially, the NHS cannot be overwhelmed, but if COVID deaths can be controlled at around 20,000, as now suggested, the impact on overall mortality in 2020 may be minimal (although due to the stress of health services and the side effects of isolation), The underlying mortality rate is likely to increase). But, as we can see, the costs are enormous.
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DSI Alumni Use Machine Learning to Discover Coronavirus Treatments