Health News

Pfizer's coronavirus shot shows promise by triggering immune response

Experimental coronavirus vaccine from Pfizer triggered levels of antibodies up to THREE TIMES greater than those seen in recovered patients, early data shows

  • Researchers randomly gave 45 healthy volunteers either a low dose, a medium dose or a high dose of a coronavirus vaccine, or a placebo
  • Those who received the vaccine were given two shots, except the high dose group after half developed fever
  • The vaccine generated levels of neutralizing antibodies between 1.8 and 2.8 times greater than those seen in recovered patients 
  • No life-threatening side effects were seen and Pfizer hopes to start a large-scale human trial later this summer 

An experimental coronavirus vaccine being tested by Pfizer Inc and its German partner BioNTech showed encouraging early results, the companies announced on Wednesday.

The trial recruited 45 people, who received either a low, medium or high dose of the vaccine in two shots or a placebo.    

Volunteers given either the low or medium dose had immune responses in the range expected to be protective, when compared to COVID-19 survivors, according to the preliminary findings.

The results, which were published on pre-print site, have been submitted for publication in a scientific journal, but have not yet been peer-reviewed.    

Researchers randomly gave 45 healthy volunteers either a low dose, a medium dose or a high dose of a coronavirus vaccine, or a placebo. Pictured: The first patient enrolled in Pfizer’s COVID-19 vaccine clinical trial at the University of Maryland School of Medicine in Baltimore receives an injection, May 4

Those who received either two shots of the low or medium dose of the vaccine generated levels of neutralizing antibodies between 1.8 and 2.8 times greater than those seen in recovered patients (above)

‘We still have a ways to go and we’re testing other candidates as well,’ Philip Dormitzer, chief scientific officer for viral vaccines at Pfizer’s research laboratories, told STAT News. 

‘However, what we can say at this point is there is a viable candidate based on immunogenicity and early tolerability safety data.’ 

The vaccine candidate from Pfizer and Biotech uses part of the pathogen’s genetic code to get the body to recognize the coronavirus and attack it if a person becomes infected. 

For the study, three groups of 12 received either a 10-microgram dose, a 30-microgram dose or a 100-microgram dose. Nine were given a placebo.

The highest dose shot caused fevers in about half of the group, so a second shot wasn’t given.

Three weeks later, participants were given a second dose. Following that, 8.3 percent of the 10-microgram group and 75 percent of the 30-microgram reported fevers.  

However, these side effects did not result in hospitalization, nor were considered life-threatening, and resolved after about one day.  

The immunization generated not just antibodies against the virus but specifically neutralizing antibodies, meaning they stop the virus from infecting human cells.

Results showed the levels of neutralizing antibodies were between 1.8 and 2.8 times greater than those seen in recovered patients. 

Volunteers who received one 100-microgram dose had lower levels of antibodies than those who were given two shots of the low or medium dose. 

Following news of the preliminary results, shares of Pfizer rose by four percent on Wednesday.

The US pharmaceutical giant hopes to begin a large-scale trial this summer, but did not specify which jab it would be testing. 

Around 200 vaccines are being developed around  the world with more than 15 currently in later-stage human trials such as AztraZeneca in partnership with Oxford University, Inovio and Moderna.

A number of pharmaceutical companies are expected to begin human trials later this summer including Johnson & Johnson, Merck and Sanofi.  

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Designing anew: Radical COVID-19 drug development approach shows promise

Nearly every drug that is, or has ever been, used was derived from nature—harnessing compounds created by organisms over eons to fight diseases. But decades ago, biochemists postulated that it might be possible to design a new drug from scratch by linking up amino acids in precise ways.

The tricky part, as it turned out, was predicting in advance how the amino acids in a protein would fold. The folded form determines the three-dimensional shape of the protein, as well as its electrostatic potential, and hydrophobicity (the degree to which a molecule is repelled from a mass of water)—factors that are critical when it comes to designing an effective drug.

David Baker, professor of Biochemistry at the University of Washington and head of the Institute for Protein Design there, pioneered methods for using computers to predict how proteins fold. Based on that knowledge, he and his team have designed new, never-before-seen proteins for use as drugs, sensors, or even biological logic gates.

This approach is known as de novo protein design. There are currently only a few drugs in trial that have used this approach, but it holds incredible potential—and at no time has such an approach been more critical than now.

The platform that the Institute for Protein Design developed allows for the rapid design of protein binders to target proteins of interest. Computer (in silico) simulations generate a library of candidate protein sequences that are then tested at their in-house testing facility. Promising candidates are evolved both in silico and in the wet lab until a final binding protein is created.

Starting in January, researchers in the Baker Lab began have been using their methodology to design a drug or vaccine to treat COVID-19. Their studies involve calculating the three-dimensional shape of millions of possible proteins, and then computationally testing how such proteins would fit into, and dock with, parts of the SARS-CoV-2 virus.

To assist in this effort, they are using the Stampede2 supercomputer at the Texas Advanced Computing Center (TACC)—one of the fastest in the world—as well as the network of volunteer computers known as [email protected] (Rosetta is the name of the software developed in the Baker Lab to predict protein folding and to design new proteins.)

“In just a two-month span, our team has been able to computationally design millions of protein therapeutics that target the seven major proteins related to COVID-19,” Baker reported in March.

To date, 733,000 proteins have been ordered, 323,000 of these protein therapeutics have been tested in the laboratory, and more than 2,000 have shown binding signals to their respective targets.

From Scaffolds to Protein Structures

The team began by testing its collection of 20,000 scaffold proteins that form the starting point for future drugs or vaccines. Each can be docked in over 1,000 orientations; and each dock is subsampled 1,000 times with slight perturbations—leading to 20 billion potential interactions to compute.

“In the scaffold phase, we’re looking for signs these are going to be atomically accurate,” said Brian Coventry, a Ph.D. student in the group working on the project. “If we’re off by 0.1 nanometers, there’s no way it will work. These things have to be perfect.”

The top 1 million of these docks then move forward to sequence design where each position on the scaffold backbone must be assigned an amino acid. With 20 amino acid choices at each position, and a variety of conformations for each, the computer must solve the combinatorial explosion to assign the best combination of amino acids to each scaffold.

From the 1 million designed proteins, they determine the most promising subset—roughly 100,000 proteins. The team sends a text file containing DNA sequences for these candidates to Agilent, a company that can create synthetic DNA molecules on demand. Agilent returns test tubes with physical DNA, which is then inserted into yeast genomes in such a way that the various synthetic proteins are made and displayed on tethers from the cell membrane of yeast, allowing them to be tested against the virus.

Based on the initial computational and experimental results, the team then engages in site saturation mutagenesis, where each individual amino acid on the chain is mutated at every location and re-tested to see how it behaves.

“We get data back and look at what made a given protein better or worse. And we ask the question: ‘Does this protein look like it’s working for the right reasons?'” Coventry said.

Based on the results and insights from the mutagenesis, they go one step further and develop a combo library that includes degenerate codons, where alternate nucleotides replace the typical ones in a given amino acid.

The best combination of mutations and replacements undergo further experimental testing including bacterial expression and thermodynamic analysis. Using this method, they derived 50 highly promising leads for the spike protein binder from an initial screening of 100,000 proteins.

“The spike protein binder is the most likely to result in a drug because of its mechanism of action,” Coventry said.

But the ability to create designer proteins is not the lab’s only innovation, nor is a single binder their final goal. They are also pioneering a new approach to drugs called mini-protein binders that combine the specificity of antibodies with the high stability and manufacturability of small molecule drugs.

Mini-protein binders have been shown to have much greater stability at elevated temperatures and better neutralization than comparable antibodies and natural protein derivatives. They are also approximately 1/30th of the molecular weight of typical proteins, and can be synthesized chemically, which enables the introduction of a wide variety of functionalities. Probably as a result of their small size and very high stability, they elicit little immune response.

“We aim to connect four to six of the most potent neutralizers in a single chain by flexible linkers to achieve highly avid binding with little potential for escape,” Baker said in a presentation to the Defense Advanced Research Projects Agency (DARPA), one of the funders of the research.

“We try to get many binders and connect them with linkers,” Coventry explained further. “The idea is that you get an avidity effect”—the accumulated strength of multiple affinities. “At least one of those proteins will be binding at any given time and the virus particle won’t be able to escape the chain. Since the binders block the viral binding epitope, the virus will not be able to enter our cells.”

Building on Collaborations

TACC is currently supporting more than 40 COVID-19 research projects. The one from the Baker Lab has been among the largest users of compute time on Stampede2 since it began in March.

“TACC has a lot of computing power and that has been really helpful for us,” Coventry said. “Everything we do is purely parallel. We’re able to rapidly test 20 million different designs and the calculations don’t need to talk to each other.” This type of approach, known as high-throughput screening, is a good fit for Stampede2’s architecture.

Baker and his team were able to ramp up quickly on TACC resources in part because of their involvement in an ongoing DARPA-funded program known as the Synergistic Discovery and Design (SD2), a multi-institution collaboration whose goal is to develop data-driven methods to accelerate scientific discovery.

Since 2017, the SD2 program has been developing pipelines to “design-test-learn” faster, using a combination of high-performance computing, advanced data management practices, automated laboratory testing, and machine learning. The collaboration between the Baker Lab and TACC is emblematic of that methodology and is helping to accelerate their research from idea to reality.

According to Dr. Matthew Vaughn, Director of Life Sciences Computing at TACC, the protein design project appears poised to yield powerful new therapeutic molecules for the fight against COVID-19 due in part to the remarkable synergy between computational simulation and experimentation.

“The rapid pace at which the Baker lab has been able to onboard and become productive on a leadership-class resource like Stampede 2 reinforces just how critical our national investments in advanced computing capability and methodology have been and will continue to be in the future,” Vaughn said.

The team’s next milestone will be to develop multiple inhibitors that can reduce the response by half and that can be linked those together into a big molecule, or construct, that is well behaved.

Further testing to establish whether the mini-binder provokes an immune response would follow, and then the construct would be tested for efficacy in a petri dish, then in animals and humans.

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‘Pooled testing’ for COVID-19 holds promise, pitfalls

The nation’s top health officials are banking on a new approach to dramatically boost U.S. screening for the coronavirus: combining test samples in batches instead of running them one by one.

The potential benefits include stretching laboratory supplies, reducing costs and expanding testing to millions more Americans who may unknowingly be spreading the virus. Health officials think infected people who aren’t showing symptoms are largely responsible for the rising number of cases across more than half of states.

“Pooling would give us the capacity to go from a half-a-million tests per day to potentially 5 million individuals tested per day,” Dr. Deborah Birx, the White House’s coronavirus response coordinator, told a recent meeting of laboratory experts.

For now, federal health regulators have not cleared any labs or test maker to use the technique. The Food and Drug Administration issued guidelines for test makers in mid-June and wants each to first show that mixing samples doesn’t hurt accuracy, one of the potential downsides.

So it’s not clear when pooled testing may be available for mass screenings at schools and businesses.

The principle is simple: Instead of running each person’s test individually, laboratories would combine parts of nasal swab samples from several people and test them together. A negative result would clear everyone in the batch. A positive result would require each sample to be individually retested. Pooling works best with lab-run tests, which take hours—not the much quicker individual tests used in clinics or doctor’s offices.

The idea for pooling dates from World War II, when it was considered for quickly screening blood samples from U.S. draftees for syphilis. Since then it has been adopted to screen blood samples for HIV and hepatitis. And developing countries have used pooled samples to stretch testing supplies.

China reported using the approach as part of a recent campaign to test all 11 million residents of Wuhan, the city where the virus first emerged late last year.

“Americans think this is some new concept because ordinarily we don’t have this challenge of having to stretch testing capacity,” said Darius Lakdawalla, a health economist at the University of Southern California.

Lakdawalla and colleagues estimate that pooled testing could save schools and businesses between 50% and 70% on costs. Under their model, a group of 100 employees could be divided into 20 batches of five people. Assuming 5% of people carry the virus, only five pools would test positive, requiring individual testing. Ultimately, 45 tests would be needed for the pooled approach, versus 100 individual tests.

But pooling won’t always be the best option. Importantly, it won’t save time or resources when used in COVID-19 hot spots, such as an outbreak at a nursing home. That’s because the logistical and financial benefits of pooling only add up when a small number of pools test positive.

Experts recommend the technique when fewer than 10% of people are expected to test positive. About 7% of U.S. tests have been positive for the virus in the past week, according to an AP analysis, though rates vary widely from place to place. For example, pooling would not be cost-effective in Arizona, where a surge has pushed positive test results to over 22%. But the approach could make sense in New Jersey, with a positivity rate under 2%.

Nebraska’s state health laboratory used batch testing with special permission from the governor and the FDA in March. The lab’s director said they had to stop several weeks ago when their positive rate jumped to 17% with outbreaks at meat packing plants.

“We knew that pooling wasn’t working anymore when those rates started going up,” said Dr. Peter Iwen.

Reserving pooled testing for large groups with low rates of infection dovetails with the government’s increasing focus on people without symptoms spreading the virus, especially younger people.

“It’s a really good tool. It can be used in any of a number of circumstances, including at the community level or even in schools,” Dr. Anthony Fauci, the nation’s top infectious-disease expert, told a Senate hearing Tuesday.

Still, health officials may still have to convince some key players to adopt the method. LabCorp, one of the nation’s biggest testing chains, said in an email that it is familiar with pooled testing but currently believes “individual patient testing is the most effective and efficient way” to test for COVID-19.

Dr. Colleen Kraft of Emory University worries that batched testing—with its multiple rounds of screening for some patients—could slow test results, a key factor for getting those infected into quarantine.

“If you are trying to do something rapid, this actually prolongs the turnaround time,” Kraft said.

She and others also have concerns about accuracy, since test performance tends to drop when screening in larger groups of people where the targeted disease is less common.

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