Posts Tagged ‘SARS-CoV-2’


SARS-CoV-2 Testing and Outcomes in the First 30 Days After the First Case of COVID-19 at an Australian Children’s Hospital

Reporter: Gail S. Thornton, M.A.


Objective: International studies describing COVID-19 in children have shown low proportions of paediatric cases and generally a mild clinical course. We aimed to present early data on children tested for SARS-CoV-2 at a large Australian tertiary children’s hospital according to the state health department guidelines, which varied over time.

Methods: We conducted a retrospective cohort study at The Royal Children’s Hospital, Melbourne, Australia. It included all paediatric patients (aged 0-18 years) who presented to the Emergency Department (ED) or the Respiratory Infection Clinic (RIC) and were tested for SARS-CoV-2. The 30-day study period commenced after the first confirmed positive case was detected at the hospital on 21st March 2020, until 19th April 2020. We recorded epidemiological and clinical data.

Results: There were 433 patients in whom SARS-CoV-2 testing was performed in ED (331 (76%)) or RIC (102 (24%)). There were 4 (0.9%) who had positive SARS-CoV-2 detected, none of whom were admitted to hospital or developed severe disease. Of these SARS-CoV-2 positive patients, 1/4 (25%) had a comorbidity, which was asthma. Of the SARS-CoV-2 negative patients, 196/429 (46%) had comorbidities. Risk factors for COVID-19 were identified in 4/4 SARS-CoV-2 positive patients and 47/429 (11%) SARS-CoV-2 negative patients.

Conclusions: Our study identified a very low rate of SARS-CoV-2 positive cases in children presenting to a tertiary ED or RIC, none of whom were admitted to hospital. A high proportion of patients who were SARS-CoV-2 negative had comorbidities.

Keywords: Australia; COVID-19; SARS-CoV-2; children; novel coronavirus.




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A Series of Recently Published Papers Report the Development of SARS-CoV2 Neutralizing Antibodies and Passive Immunity toward COVID19

Curator: Stephen J. Williams, Ph.D.


Passive Immunity and Treatment of Infectious Diseases

The ability of one person to pass on immunity to another person (passive immunity) is one of the chief methods we develop immunity to many antigens.  For instance, maternal antibodies are passed to the offspring in the neonatal setting as well as in a mother’s milk during breast feeding.  In the clinical setting this is achieved by transferring antibodies from one patient who has been exposed to an antigen (like a virus) to the another individual.   However, the process of purifying the most efficacious antibody as well as its mass production is limiting due to its complexity and cost and can be prohibitively long delay during a pandemic outbreak, when therapies are few and needed immediately.  Regardless, the benefits of developing neutralizing antibodies to confer passive immunity versus development of a vaccine are evident, as the former takes considerable less time than development of a safe and effective vaccine.  For a good review on the development and use of neutralizing antibodies and the use of passive immunity to treat infectious diseases please read the following review:

Margaret A. Keller1,* and E. Richard Stiehm. Passive Immunity in Prevention and Treatment of Infectious Diseases. Clin Microbiol Rev. 2000 Oct; 13(4): 602–614. doi: 10.1128/cmr.13.4.602-614.2000


Antibodies have been used for over a century in the prevention and treatment of infectious disease. They are used most commonly for the prevention of measles, hepatitis A, hepatitis B, tetanus, varicella, rabies, and vaccinia. Although their use in the treatment of bacterial infection has largely been supplanted by antibiotics, antibodies remain a critical component of the treatment of diptheria, tetanus, and botulism. High-dose intravenous immunoglobulin can be used to treat certain viral infections in immunocompromised patients (e.g., cytomegalovirus, parvovirus B19, and enterovirus infections). Antibodies may also be of value in toxic shock syndrome, Ebola virus, and refractory staphylococcal infections. Palivizumab, the first monoclonal antibody licensed (in 1998) for an infectious disease, can prevent respiratory syncytial virus infection in high-risk infants. The development and use of additional monoclonal antibodies to key epitopes of microbial pathogens may further define protective humoral responses and lead to new approaches for the prevention and treatment of infectious diseases.


Summary of the efficacy of antibody in the prevention and treatment of infectious diseases

Bacterial infections
 Respiratory infections (streptococcus, Streptococcus pneumoniaeNeisseria meningitisHaemophilus influenzae)
 Other clostridial infections
  C. botulinum
  C. difficile
 Staphylococcal infections
  Toxic shock syndrome
  Antibiotic resistance
  S. epidermidis in newborns
 Invasive streptococcal disease (toxic shock syndrome)
 High-risk newborns
 Shock, intensive care, and trauma
Pseudomonas infection
  Cystic Fibrosis
Viral diseases
 Hepatitis A
 Hepatitis B
 Hepatitis C
 HIV infection
 RSV infection
 Herpesvirus infections
 Parvovirus infection
 Enterovirus infection
  In newborns
 Tick-borne encephalitis

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A Great Explanation of Active versus Passive Immunity by Dr. John Campbell, one of the pioneers in the field of immunology:Antibodies have been used for over a century in the prevention and treatment of infectious disease. They are used most commonly for the prevention of measles, hepatitis A, hepatitis B, tetanus, varicella, rabies, and vaccinia. Although their use in the treatment of bacterial infection has largely been supplanted by antibiotics, antibodies remain a critical component of the treatment of diptheria, tetanus, and botulism. High-dose intravenous immunoglobulin can be used to treat certain viral infections in immunocompromised patients (e.g., cytomegalovirus, parvovirus B19, and enterovirus infections). Antibodies may also be of value in toxic shock syndrome, Ebola virus, and refractory staphylococcal infections. Palivizumab, the first monoclonal antibody licensed (in 1998) for an infectious disease, can prevent respiratory syncytial virus infection in high-risk infants. The development and use of additional monoclonal antibodies to key epitopes of microbial pathogens may further define protective humoral responses and lead to new approaches for the prevention and treatment of infectious diseases.


However, developing successful neutralizing antibodies can still be difficult but with the latest monoclonal antibody technology, as highlighted by the following papers, this process has made much more efficient.  In addition, it is not feasable to isolate antibodies from the plasma of covalescent patients in a scale that is needed for a worldwide outbreak.

A good explanation of the need can be found is Dr. Irina Robu’s post Race to develop antibody drugs for COVID-19 where:

When fighting off foreign invaders, our bodies make antibodies precisely produced for the task. The reason vaccines offer such long-lasting protection is they train the immune system to identify a pathogen, so immune cells remember and are ready to attack the virus when it appears. Monoclonal antibodies for coronavirus would take the place of the ones our bodies might produce to fight the disease. The manufactured antibodies would be infused into the body to either tamp down an existing infection, or to protect someone who has been exposed to the virus. However, these drugs are synthetic versions of the convalescent plasma treatments that rely on antibodies from people who have recovered from infection. But the engineered versions are easier to scale because they’re manufactured in rats, rather than from plasma donors.

The following papers represent the latest published work on development of therapeutic and prophylactic neutralizing antibodies to the coronavirus SARS-CoV2

1.  Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody.

Pinto, D., Park, Y., Beltramello, M. et al. Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody. Nature (2020).                                                                            https://doi.org/10.1038/s41586-020-2349-y


SARS-CoV-2 is a newly emerged coronavirus responsible for the current COVID-19 pandemic that has resulted in more than 3.7 million infections and 260,000 deaths as of 6 May 20201,2. Vaccine and therapeutic discovery efforts are paramount to curb the pandemic spread of this zoonotic virus. The SARS-CoV-2 spike (S) glycoprotein promotes entry into host cells and is the main target of neutralizing antibodies. Here we describe multiple monoclonal antibodies targeting SARS-CoV-2 S identified from memory B cells of an individual who was infected with SARS-CoV in 2003. One antibody, named S309, potently neutralizes SARS-CoV-2 and SARS-CoV pseudoviruses as well as authentic SARS-CoV-2 by engaging the S receptor-binding domain. Using cryo-electron microscopy and binding assays, we show that S309 recognizes a glycan-containing epitope that is conserved within the sarbecovirus subgenus, without competing with receptor attachment. Antibody cocktails including S309 along with other antibodies identified here further enhanced SARS-CoV-2 neutralization and may limit the emergence of neutralization-escape mutants. These results pave the way for using S309- and S309-containing antibody cocktails for prophylaxis in individuals at high risk of exposure or as a post-exposure therapy to limit or treat severe disease.


2.  Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells

Yunlong Cao et al.  Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells. Cell (2020).



The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here we report the rapid identification of SARS-CoV-2 neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients. From 8,558 antigen-binding IgG1+ clonotypes, 14 potent neutralizing antibodies were identified with the most potent one, BD-368-2, exhibiting an IC50 of 1.2 ng/mL and 15 ng/mL against pseudotyped and authentic SARS-CoV-2, respectively. BD-368-2 also displayed strong therapeutic and prophylactic efficacy in SARS-CoV-2-infected hACE2-transgenic mice. Additionally, the 3.8Å Cryo-EM structure of a neutralizing antibody in complex with the spike-ectodomain trimer revealed the antibody’s epitope overlaps with the ACE2 binding site. Moreover, we demonstrated that SARS-CoV-2 neutralizing antibodies could be directly selected based on similarities of their predicted CDR3H structures to those of SARS-CoV neutralizing antibodies. Altogether, we showed that human neutralizing antibodies could be efficiently discovered by high-throughput single B-cell sequencing in response to pandemic infectious diseases.

3. A human monoclonal antibody blocking SARS-CoV-2 infection

Wang, C., Li, W., Drabek, D. et al. A human monoclonal antibody blocking SARS-CoV-2 infection. Nat Commun 11, 2251 (2020). https://doi.org/10.1038/s41467-020-16256-y


The emergence of the novel human coronavirus SARS-CoV-2 in Wuhan, China has caused a worldwide epidemic of respiratory disease (COVID-19). Vaccines and targeted therapeutics for treatment of this disease are currently lacking. Here we report a human monoclonal antibody that neutralizes SARS-CoV-2 (and SARS-CoV) in cell culture. This cross-neutralizing antibody targets a communal epitope on these viruses and may offer potential for prevention and treatment of COVID-19.

Extra References on Development of Neutralizing antibodies for COVID19 {Sars-CoV2} published this year (2020)  [1-4]

  1. Fan P, Chi X, Liu G, Zhang G, Chen Z, Liu Y, Fang T, Li J, Banadyga L, He S et al: Potent neutralizing monoclonal antibodies against Ebola virus isolated from vaccinated donors. mAbs 2020, 12(1):1742457.
  2. Dussupt V, Sankhala RS, Gromowski GD, Donofrio G, De La Barrera RA, Larocca RA, Zaky W, Mendez-Rivera L, Choe M, Davidson E et al: Potent Zika and dengue cross-neutralizing antibodies induced by Zika vaccination in a dengue-experienced donor. Nature medicine 2020, 26(2):228-235.
  3. Young CL, Lyons AC, Hsu WW, Vanlandingham DL, Park SL, Bilyeu AN, Ayers VB, Hettenbach SM, Zelenka AM, Cool KR et al: Protection of swine by potent neutralizing anti-Japanese encephalitis virus monoclonal antibodies derived from vaccination. Antiviral research 2020, 174:104675.
  4. Sautto GA, Kirchenbaum GA, Abreu RB, Ecker JW, Pierce SR, Kleanthous H, Ross TM: A Computationally Optimized Broadly Reactive Antigen Subtype-Specific Influenza Vaccine Strategy Elicits Unique Potent Broadly Neutralizing Antibodies against Hemagglutinin. J Immunol 2020, 204(2):375-385.


For More Articles on COVID-19 Please see Our Coronavirus Portal on this Open Access Scientific Journal at:


and the following Articles on  Immunity at

Race to develop antibody drugs for COVID-19
Bispecific and Trispecific Engagers: NK-T Cells and Cancer Therapy
Issues Need to be Resolved With ImmunoModulatory Therapies: NK cells, mAbs, and adoptive T cells
Antibody-bound Viral Antigens

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Crowdsourcing Difficult-to-Collect Epidemiological Data in Pandemics: Lessons from Ebola to the current COVID-19 Pandemic


Curator: Stephen J. Williams, Ph.D.


At the onset of the COVID-19 pandemic, epidemiological data from the origin of the Sars-Cov2 outbreak, notably from the Wuhan region in China, was sparse.  In fact, official individual patient data rarely become available early on in an outbreak, when that data is needed most. Epidemiological data was just emerging from China as countries like Italy, Spain, and the United States started to experience a rapid emergence of the outbreak in their respective countries.  China, made of 31 geographical provinces, is a vast and complex country, with both large urban and rural areas.




As a result of this geographical diversity and differences in healthcare coverage across the country, epidemiological data can be challenging.  For instance, cancer incidence data for regions and whole country is difficult to calculate as there are not many regional cancer data collection efforts, contrasted with the cancer statistics collected in the United States, which is meticulously collected by cancer registries in each region, state and municipality.  Therefore, countries like China must depend on hospital record data and autopsy reports in order to back-extrapolate cancer incidence data.  This is the case in some developed countries like Italy where cancer registry is administered by a local government and may not be as extensive (for example in the Napoli region of Italy).







Population density China by province. Source https://www.unicef.cn/en/figure-13-population-density-province-2017




Epidemiologists, in areas in which data collection may be challenging, are relying on alternate means of data collection such as using devices connected to the internet-of-things such as mobile devices, or in some cases, social media is becoming useful to obtain health related data.  Such as effort to acquire pharmacovigilance data, patient engagement, and oral chemotherapeutic adherence using the social media site Twitter has been discussed in earlier posts: (see below)

Twitter is Becoming a Powerful Tool in Science and Medicine at https://pharmaceuticalintelligence.com/2014/11/06/twitter-is-becoming-a-powerful-tool-in-science-and-medicine/






Now epidemiologists are finding crowd-sourced data from social media and social networks becoming useful in collecting COVID-19 related data in those countries where health data collection efforts may be sub-optimal.  In a recent paper in The Lancet Digital Health [1], authors Kaiyuan Sun, Jenny Chen, and Cecile Viboud present data from the COVID-19 outbreak in China using information collected over social network sites as well as public news outlets and find strong correlations with later-released government statistics, showing the usefulness in such social and crowd-sourcing strategies to collect pertinent time-sensitive data.  In particular, the authors aim was to investigate this strategy of data collection to reduce the time delays between infection and detection, isolation and reporting of cases.

The paper is summarized below:

Kaiyuan Sun, PhD Jenny Chen, BScn Cécile Viboud, PhD . (2020).  Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study.  The Lancet: Digital Health; Volume 2, Issue 4, E201-E208.



As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.


In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.


We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35–60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.


News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

A Few notes on Methodology:

  • The authors used crowd-sourced reports from DXY.cn, a social network for Chinese physicians, health-care professionals, pharmacies and health-care facilities. This online platform provides real time coverage of the COVID-19 outbreak in China
  • More data was curated from news media, television and includes time-stamped information on COVID-19 cases
  • These reports are publicly available, de-identified patient data
  • No patient consent was needed and no ethics approval was required
  • Data was collected between January 20, 2020 and January 31,2020
  • Sex, age, province of identification, travel history, dates of symptom development was collected
  • Additional data was collected for other international sites of the pandemic including Cambodia, Canada, France, Germany, Hong Kong, India, Italy, Japan, Malaysia, Nepal, Russia, Singapore, UK, and USA
  • All patients in database had laboratory confirmation of infection



  • 507 patient data was collected with 153 visited and 152 resident of Wuhan
  • Reported cases were skewed toward males however the overall population curve is skewed toward males in China
  • Most cases (26%) were from Beijing (urban area) while an equal amount were from rural areas combined (Shaanzi and Yunnan)
  • Age distribution of COVID cases were skewed toward older age groups with median age of 45 HOWEVER there were surprisingly a statistically high amount of cases less than 5 years of age
  • Outbreak progression based on the crowd-sourced patient line was consistent with the data published by the China Center for Disease Control
  • Median reporting delay in the authors crowd-sourcing data was 5 days
  • Crowd-sourced data was able to detect apparent rapid growth of newly reported cases during the collection period in several provinces outside of Hubei province, which is consistent with local government data

The following graphs show age distribution for China in 2017 and predicted for 2050.

projected age distribution China 2050. Source https://chinapower.csis.org/aging-problem/













The authors have previously used this curation of news methodology to analyze the Ebola outbreak[2].

A further use of the crowd-sourced database was availability of travel histories for patients returning from Wuhan and onset of symptoms, allowing for estimation of incubation periods.

The following published literature has also used these datasets:

Backer JA, Klinkenberg D, Wallinga J: Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin 2020, 25(5).

Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, Azman AS, Reich NG, Lessler J: The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of internal medicine 2020, 172(9):577-582.

Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KSM, Lau EHY, Wong JY et al: Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. The New England journal of medicine 2020, 382(13):1199-1207.

Dataset is available on the Laboratory for the Modeling of Biological and Socio-technical systems website of Northeastern University at https://www.mobs-lab.org/.


  1. Sun K, Chen J, Viboud C: Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study. The Lancet Digital health 2020, 2(4):e201-e208.
  2. Cleaton JM, Viboud C, Simonsen L, Hurtado AM, Chowell G: Characterizing Ebola Transmission Patterns Based on Internet News Reports. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2016, 62(1):24-31.

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Powerful AI Tools Being Developed for the COVID-19 Fight

Curator: Stephen J. Williams, Ph.D.


Source: https://www.ibm.com/blogs/research/2020/04/ai-powered-technologies-accelerate-discovery-covid-19/

IBM Releases Novel AI-Powered Technologies to Help Health and Research Community Accelerate the Discovery of Medical Insights and Treatments for COVID-19

April 3, 2020 | Written by: 

IBM Research has been actively developing new cloud and AI-powered technologies that can help researchers across a variety of scientific disciplines accelerate the process of discovery. As the COVID-19 pandemic unfolds, we continue to ask how these technologies and our scientific knowledge can help in the global battle against coronavirus.

Today, we are making available multiple novel, free resources from across IBM to help healthcare researchers, doctors and scientists around the world accelerate COVID-19 drug discovery: from gathering insights, to applying the latest virus genomic information and identifying potential targets for treatments, to creating new drug molecule candidates.

Though some of the resources are still in exploratory stages, IBM is making them available to qualifying researchers at no charge to aid the international scientific investigation of COVID-19.

Today’s announcement follows our recent leadership in launching the U.S. COVID-19 High Performance Computing Consortium, which is harnessing massive computing power in the effort to help confront the coronavirus.

Streamlining the Search for Information

Healthcare agencies and governments around the world have quickly amassed medical and other relevant data about the pandemic. And, there are already vast troves of medical research that could prove relevant to COVID-19. Yet, as with any large volume of disparate data sources, it is difficult to efficiently aggregate and analyze that data in ways that can yield scientific insights.

To help researchers access structured and unstructured data quickly, we are offering a cloud-based AI research resource that has been trained on a corpus of thousands of scientific papers contained in the COVID-19 Open Research Dataset (CORD-19), prepared by the White House and a coalition of research groups, and licensed databases from the DrugBankClinicaltrials.gov and GenBank. This tool uses our advanced AI and allows researchers to pose specific queries to the collections of papers and to extract critical COVID-19 knowledge quickly. Please note, access to this resource will be granted only to qualified researchers. To learn more and request access, please click here.

Aiding the Hunt for Treatments

The traditional drug discovery pipeline relies on a library of compounds that are screened, improved, and tested to determine safety and efficacy. In dealing with new pathogens such as SARS-CoV-2, there is the potential to enhance the compound libraries with additional novel compounds. To help address this need, IBM Research has recently created a new, AI-generative framework which can rapidly identify novel peptides, proteins, drug candidates and materials.

We have applied this AI technology against three COVID-19 targets to identify 3,000 new small molecules as potential COVID-19 therapeutic candidates. IBM is releasing these molecules under an open license, and researchers can study them via a new interactive molecular explorer tool to understand their characteristics and relationship to COVID-19 and identify candidates that might have desirable properties to be further pursued in drug development.

To streamline efforts to identify new treatments for COVID-19, we are also making the IBM Functional Genomics Platform available for free for the duration of the pandemic. Built to discover the molecular features in viral and bacterial genomes, this cloud-based repository and research tool includes genes, proteins and other molecular targets from sequenced viral and bacterial organisms in one place with connections pre-computed to help accelerate discovery of molecular targets required for drug design, test development and treatment.

Select IBM collaborators from government agencies, academic institutions and other organizations already use this platform for bacterial genomic study. And now, those working on COVID-19 can request the IBM Functional Genomics Platform interface to explore the genomic features of the virus. Access to the IBM Functional Genomics Platform will be prioritized for those conducting COVID-19 research. To learn more and request access, please click here.

Drug and Disease Information

Clinicians and healthcare professionals on the frontlines of care will also have free access to hundreds of pieces of evidence-based, curated COVID-19 and infectious disease content from IBM Micromedex and EBSCO DynaMed. Using these two rich decision support solutions, users will have access to drug and disease information in a single and comprehensive search. Clinicians can also provide patients with consumer-friendly patient education handouts with relevant, actionable medical information. IBM Micromedex is one of the largest online reference databases for medication information and is used by more than 4,500 hospitals and health systems worldwide. EBSCO DynaMed provides peer-reviewed clinical content, including systematic literature reviews in 28 specialties for comprehensive disease topics, health conditions and abnormal findings, to highly focused topics on evaluation, differential diagnosis and management.

The scientific community is working hard to make important new discoveries relevant to the treatment of COVID-19, and we’re hopeful that releasing these novel tools will help accelerate this global effort. This work also outlines our long-term vision for the future of accelerated discovery, where multi-disciplinary scientists and clinicians work together to rapidly and effectively create next generation therapeutics, aided by novel AI-powered technologies.

Learn more about IBM’s response to COVID-19: IBM.com/COVID19.

Source: https://www.ibm.com/blogs/research/2020/04/ai-powered-technologies-accelerate-discovery-covid-19/

DiA Imaging Analysis Receives Grant to Accelerate Global Access to its AI Ultrasound Solutions in the Fight Against COVID-19

Source: https://www.grantnews.com/news-articles/?rkey=20200512UN05506&filter=12337

Grant will allow company to accelerate access to its AI solutions and use of ultrasound in COVID-19 emergency settings

TEL AVIV, IsraelMay 12, 2020 /PRNewswire-PRWeb/ — DiA Imaging Analysis, a leading provider of AI based ultrasound analysis solutions, today announced that it has received a government grant from the Israel Innovation Authority (IIA) to develop solutions for ultrasound imaging analysis of COVID-19 patients using Artificial Intelligence (AI).Using ultrasound in point of care emergency settings has gained momentum since the outbreak of COVID-19 pandemic. In these settings, which include makeshift hospital COVID-19 departments and triage “tents,” portable ultrasound offers clinicians diagnostic decision support, with the added advantage of being easier to disinfect and eliminating the need to transport patients from one room to another.However, analyzing ultrasound images is a process that it is still mostly done visually, leading to a growing market need for automated solutions and decision support.As the leading provider of AI solutions for ultrasound analysis and backed by Connecticut Innovations, DiA makes ultrasound analysis smarter and accessible to both new and expert ultrasound users with various levels of experience. The company’s flagship LVivo Cardio Toolbox for AI-based cardiac ultrasound analysis enables clinicians to automatically generate objective clinical analysis, with increased accuracy and efficiency to support decisions about patient treatment and care.

The IIA grant provides a budget of millions NIS to increase access to DiA’s solutions for users in Israel and globally, and accelerate R&D with a focus on new AI solutions for COVID-19 patient management. DiA solutions are vendor-neutral and platform agnostic, as well as powered to run in low processing, mobile environments like handheld ultrasound.Recent data highlights the importance of looking at the heart during the progression of COVID-19, with one study citing 20% of patients hospitalized with COVID-19 showing signs of heart damage and increased mortality rates in those patients. DiA’s LVivo cardiac analysis solutions automatically generate objective, quantified cardiac ultrasound results to enable point-of-care clinicians to assess cardiac function on the spot, near patients’ bedside.

According to Dr. Ami Applebaum, the Chairman of the Board of the IIA, “The purpose of IIA’s call was to bring solutions to global markets for fighting COVID-19, with an emphasis on relevancy, fast time to market and collaborations promising continuity of the Israeli economy. DiA meets these requirements with AI innovation for ultrasound.”DiA has received several FDA/CE clearances and established distribution partnerships with industry leading companies including GE Healthcare, IBM Watson and Konica Minolta, currently serving thousands of end users worldwide.”We see growing use of ultrasound in point of care settings, and an urgent need for automated, objective solutions that provide decision support in real time,” said Hila Goldman-Aslan, CEO and Co-founder of DiA Imaging Analysis, “Our AI solutions meet this need by immediately helping clinicians on the frontlines to quickly and easily assess COVID-19 patients’ hearts to help guide care delivery.”

About DiA Imaging Analysis:
DiA Imaging Analysis provides advanced AI-based ultrasound analysis technology that makes ultrasound accessible to all. DiA’s automated tools deliver fast and accurate clinical indications to support the decision-making process and offer better patient care. DiA’s AI-based technology uses advanced pattern recognition and machine-learning algorithms to automatically imitate the way the human eye detects image borders and identifies motion. Using DiA’s tools provides automated and objective AI tools, helps reduce variability among users, and increases efficiency. It allows clinicians with various levels of experience to quickly and easily analyze ultrasound images.

For additional information, please visit http://www.dia-analysis.com.

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via Special COVID-19 Christopher Magazine

Special COVID-19 Christopher Magazine

Christopher-coverAntonio Giordano, MD, PhD. explains what COVID is and how to contain the infection, pointing also to what will require attention next.

Please see this special release at http://online.fliphtml5.com/qlnw/zgau/#p=1


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via Dr. Giordano Featured in Forbes Article on COVID-19 Antibody Tests in Italy and USA

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Reporter: Stephen J. Williams, PhD

NCI Activities: COVID-19 and Cancer Research

Dinah S. Singer. NCI-DCB, Bethesda, MD @theNCI

  • at the NCI they are pivoting some of their clinical trials to address COVID related issues like trials on tocilizumab and producing longitudinal cohorts of cancer patients and COVID for further analysis and studies
  • vaccine and antibody efforts at NCI and they are asking all their cancer centers (Cancer COVID Consortium) collecting data
  • Moonshot is collecting metadata but now COVID data from cellular therapy patients
  • they are about to publish new grants related to COVID and adding option to investigators to use current funds to do COVID related options
  • she says if at home take the time to think, write manuscripts, analyze data BE A REVIEWER FOR JOURNALS,
  • SSMMART project from Moonshot is still active
  • so far NCI and NIH grant process is ongoing although the peer review process is slower
  • they have extended deadlines with NO justification required (extend 90 days)
  • also allowing flexibility on use of grant money and allowing more early investigator rules and lax on those rules
  • non competitive renewals (type 5) will allow restructuring of project; contact program administrator
  • she and NCI heard rumors of institutions shutting down cancer research she is stressing to them not to do that
  • non refundable travel costs may be charged to the grant
  • NCI contemplating on extending the early investigator time
  • for more information go to NIH and NCI COVID-19 pages which have more guidances updated regularly

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