Coverage From ID Week 2020

A new podcast episode featuring Mei Mei Hu of Covaxx, whose company has made great strides toward a preventive option in mere months.

What It's Like to Make a COVID-19 Vaccine

Biotech company OncoSec has secured an IND clearance from the US Food and Drug Administration (FDA) to begin a phase 1 trial to study their CORVax12 vaccine. This is the first DNA vaccine candidate for COVID-19 to deliver the spike protein from SARS-CoV-2 and the immune-activating cytokine interleukin 12 (IL-12).

The vaccine combines OncoSec’s immuno-stimulant IL-12 expression platform, TAVO (tavokinogene telseplasmid), with NIH’s DNA-encodable stabilized trimeric SARS-CoV-2 spike glycoprotein to treat COVID-19.

The CORVax vaccine is designed to drive a coordinated long-term anti-viral response, capable of activating both cellular and humoral immune responses. The company’s TAVO IL-12 expression platform stimulates immunity in immunocompromised cancer settings and could be particularly relevant for patients at highest risk from COVID-19.

The Providence Cancer Center in Oregon is collaborating with OncoSec, and the former will be a trial site. Bernard Fox, PhD, chief, Laboratory of Molecular and Tumor Immunology, Earle A. Chiles Research Institute at Providence Portland Medical Center is the principal investigator for the trial.

“I think one of the advantages we bring to the trial from a cancer perspective is we are used to doing sophisticated immunological monitoring, and we have standards in place that have been broadly accepted,” Fox stated. 

 recently about the vaccine’s platform, how adding IL-12 can potentially help augment responses in older patients, the trial’s parameters and insights on long-term immunity.

Videos

OncoSec recently received an FDA IND clearance to begin a phase 1 trial. 

Using a Cancer Therapy Platform as a Potential COVID-19 Vaccine

Convalescent plasma transfusions have long been touted as a potential treatment for patients with coronavirus disease 2019 (COVID-19) induced severe pneumonia. The treatment has been frequently administered to patients with COVID-19 based largely on observational data. However, there is a minimal amount of data from controlled, randomized studies to support the use of this therapy.

, found that there was no observed significant difference in the clinical status or overall mortality in patients administered a convalescent plasma transfusion when compared to a placebo. This research supports other recently published studies that have come to a similar conclusion.

News of the research has been making the rounds on social media. On Twitter, 

Editor-in-Chief Jason Gallagher, PharmD, tweeted, “swing and a miss in an RCT for convalescent plasma for severe Covid19. >90% received steroids Median days of symptoms were 8; 46% of those tested had no detectable antibodies at baseline. In the supplement, no trend towards efficacy for those ppl.”

The study was a double-blind- placebo-controlled, multicenter trial in 12 clinical sites throughout Argentina. The researchers were supported by the Hospital Italiano de Buenos Aires. Trial participants were assigned in a random 2:1 ratio, either receiving a placebo or the convalescent plasma transfusion in addition to standard treatment. The plasma was collected from donors with a total SARS-CoV-2 total antibody titer of 1:400.

The primary outcome of the study showed no significant difference between the plasma group and the placebo group after 30 days of treatment. Secondary outcomes included no significant difference in mortality rate or clinical status between the 2 groups. No noted differences were demonstrated in time to death or in the time to clinical improvement.

The discoveries from the study go against numerous findings from a series of nonrandomized studies that touted the power of convalescent plasma transfusion in treating patients with COVID-19. This apparent contrast demonstrates the importance of randomized, controlled trails, especially during a pandemic.

“In our trial, the use of convalescent plasma therapy in addition to standard treatment in patients with severe pneumonia due to Covid-19 did not reduce mortality or improve other clinical outcomes at day 30 as compared with placebo,” lead author Ventura A. Simonovich, MD, wrote. “We believe the use of convalescent plasma as a standard of care in such patients should be reevaluated.”

Articles

Important finding shows convalescent plasma provides no significant benefit in severe COVID-19 cases.

Convalescent Plasma Falls Flat in New Study

A recent Pennsylvania School of Nursing study has shown that survivors of coronavirus disease 2019 (COVID-19) significantly improve with the aid of home health care (HHC) workers. Data uncovered through the study indicates increasing home health care greatly improves the recovery time of patients who receive it.

, received data from more than 1,400 patients who were admitted to home health care after recovering from COVID-19 and being discharged from a hospital. The average age of the cohort was 67 years old, with common comorbid conditions like hypertension and diabetes. In most cases, the patients had an average of 6 functional deficits, mostly to do with activities of daily living (ADL).

One month following the discharge from HHC, a majority of the patients showed improvements in cognition, anxiety and dyspnea. It was also shown that with the assistance of home health care, such as physical therapy and skilled nursing, 94% of the patients achieved statistically significant improvements in both functional outcomes and symptom burden. The average functional deficit dropped from 6 to 1, showing a notable improvement in functional gains.

"Our findings suggest that acute care providers might carefully consider which COVID-19 survivors would benefit from home health care after hospitalization," Kathryn H. Bowles, PhD, RN, lead author on the study said. "A decision support tool to identify general hospitalized patients for home health care referral may be helpful."

The study recommends that to prepare for postacute care surges due to COVID-19, an expansion of HHC use should be made to provide skilled nursing and rehabilitative services in the home. This will help to prevent the transmission to other patients, which can occur in inpatient facilities.

“The positive outcomes profiled in this study suggest the value and importance of discharging vulnerable COVID-19 survivors to skilled HHC to support their recovery,” Bowles writes. “Increasing referrals to HHC has the potential to provide support and achieve improved recovery for perhaps many more patients.”

Recent study shows COVID-19 survivors health improves with support of Home Health Care.

COVID-19 Survivors Improve with Home Health Care

A recent study using an artificial intelligence (AI) tool has produced an algorithm that can predict the outcome of patients diagnosed with coronavirus disease 2019 (COVID-19). The algorithm will assist clinicians in providing a more effective intervention plan based on patient’s specific disease presentation and health history.

, was conducted by a team of engineers at the Rensselaer Polytechnic Institute. The method was developed by using chest computed tomography (CT) images in conjunction with data including demographics, the patient’s vitals and blood test results. The CT images were used to assess a patient’s lung infection severity, and the researchers combined that information with the non-image data. Plugging the data points into the algorithm, they were able to predict specific patient outcomes, like whether or not they would need ICU intervention.

"As a practitioner of AI, I do believe in its power," Pingkun Yan, PhD, leader on the study said. "It really enables us to analyze a large quantity of data and also extract the features that may not be that obvious to the human eye."

In total, 295 patients from three different hospitals in the United states, Italy and Iran had their data collected. The engineers were able to predict the type of treatment the patients would end up needing by using just the algorithm. The new algorithm will be integrated with a previous one Yan developed which helps to assess cardiovascular disease risk in patients.

"We know that a key factor in COVID mortality is whether a patient has underlying conditions and heart disease is a significant comorbidity," Yan said. "How much this contributes to their disease progress is, right now, fairly subjective. So, we have to have a quantification of their heart condition and then determine how we factor that into this prediction."

The team is working in close collaboration with doctors at Massachusetts General Hospital and are supported by a grant given to them by the National Institutes of Health. The grant was awarded to them to help provide potential solutions for the ongoing worldwide COVID-19 pandemic.

"This critical work, led by Professor Yan, offers an actionable solution for clinicians who are in the middle of a worldwide pandemic," Deepak Vashishth, the director of CBIS said. "This project highlights the capabilities of Rensselaer expertise in bioimaging combined with important partnerships with medical institutions."

An artificial intelligence (AI) algorithm predicts outcomes in patients diagnosed with COVID-19.


Algorithm Predicts COVID-19 Outcomes

A recent study has provided new and deep insights into the current coronavirus disease 2019 (COVID-19) pandemic. The research analyzed epidemiological data from early Superspreader events during the first wave of COVID-19 in Austria.

, was conducted by a research group at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences. The focus of the research was to gain a more thorough understanding of the SARS-CoV-2 virus and how its mutational dynamics and transmission properties allow it to spread so rapidly.

The project was called “Mutational dynamics of SARS-CoV-2 in Austria”, and made use of the country’s well-developed epidemiological surveillance system and its high-quality data. Austria’s healthcare system has conducted contact tracing on all of its 21,821 reported SARS-CoV-2 cases. This allowed the group of researchers to reconstruct many major infection clusters, analyzing their roles in the spread of the virus internationally. The data also allowed them to analyze genome sequencing from family clusters and transmission chains, determining genetic bottlenecks and the mutation dynamics of the COVID-19 virus.

Demonstrated through the study was how emerging low-frequency mutations of SARS-CoV-2 had become fixed in local clusters. These local clusters were followed by the virus spreading across countries, where viral mutational dynamics within individuals and across populations connected. This shows that the dynamics of superspreader events are driven by the amount of inter-individual exposures, as well as the quantity of transmitted viruses across time.

One cluster, which consisted of 76 confirmed cases, was reconstructed based on the epidemiological data provided and uncovered an obscure link between two clusters, illuminating a previously unknown relationship. "This example illustrates how contact tracing and virus mutation analysis together provide a strong pillar of modern pandemic control," Andreas Bergthaler, who lead the project said.

It was shown from the research that, on average, 1000 infectious virus particles are passed on from an infected person to a non-infected person, which is much higher in comparison to other infectious viruses like HIV. This finding raises important questions, including if reducing an infected person’s viral load through various measures like mask wearing and social distancing, could prevent the spread of the virus.

"Thanks to excellent epidemiological and our deep virus sequencing data, we could follow how the SARS-CoV-2 virus mutated in one individual and was then transmitted to others," Bergthaler said. The results of the study support other current research projects that are aiming to better understand the pandemic and how to control it.

New study provides deep insights into the COVID-19 pandemic.

Superspreader Events Provide New Insights into SARS-CoV-2

A recently created therapy for the influenza virus may help aid in the fight against COVID-19.

New Flu Therapy Potentially Effective Against COVID-19

This CDC panel discussed who should be vaccinated first and the flu-like effects from the vaccines.

ACIP Meets to Discuss Phased Allocation of COVID-19 Vaccines 

The guidelines were recently updated to reflect new information on COVID-19 treatment and management.

IDSA Releases New Guidelines For COVID-19 Treatment

The influenza therapy is expanded to include people who have been exposed to the flu. 

Baloxavir Indication is Expanded by FDA 

Accuracy of test may be influenced by size of population to be screened and prevalence of COVID-19 within that population.

Evaluation of “Rapid” Antibody Test in Britain Suggests High Number of False Positives

New details of SARS-CoV-2 have been obtained using 3D modeling, providing crucial insights into the disease.

Analyzing SARS-CoV-2 Replication Through 3D Modeling 

National Institute of Allergy and Infectious Disease (NIAID) has selected Metabolon to participate in a study on this subject.

Determining the Biomarkers of COVID-19 Outcome and Severity

Data shows their AZD1222 vaccine met its endpoint and they are preparing regulatory submission for conditional or early approval.

AstraZeneca Investigational COVID-19 Vaccine Shown to be 90% Efficacious

 A research team developed an algorithm review estimating not only hospital admissions, but also mortality outcomes in adults with COVID-19. 

Predicting COVID-19 Mortality

Children who were exposed to antibiotics before age 2 had a greater risk of childhood health conditions like asthma, celiac disease, obesity and ADHD, a new study in Mayo Clinic Proceedings found.

Top Medical News

Using a Cancer Therapy Platform as a Potential COVID-19 Vaccine

Convalescent Plasma Falls Flat in New Study

COVID-19 Survivors Improve with Home Health Care

Algorithm Predicts COVID-19 Outcomes

Superspreader Events Provide New Insights into SARS-CoV-2

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