Jeff Gilchrist Profile picture
Jan 10, 2024 32 tweets 6 min read Read on X
Broad-Spectrum #COVID-19 #Therapeutics and #Prophylactics

An interesting presentation by Yunlong Richard Cao @yunlong_cao talking about their development of broadly #neutralizing #antibodies based on prediction of #viral #evolution ( ). 🧵1/
Slide showing how the immune barrier induced by vaccines and natural infection have been repeatedly evaded by the new COVID-19 variants. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
Read on to find out how their research team developed a neutralizing antibody solution (injection & nose spray) that works with all current variants, including the older SARS1 virus from 2003 and the currently globally dominant BA.2.86 Pirola clan of variants. 2/
Slide showing SA55 available as an injection to act as a long-term prophylactic or therapeutic for immunocompromised people (80-90 day half-life). Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
Slide showing SA55 available as a nasal spray that is supposed to be low cost and provide short-term prophylactics (3 sprays per day) with 8-12h protection per spray providing high neutralization in the mucosa. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
An unrolled one-page web view for this long thread that may be easier to read or share can be found here ( ). 3/
The COVID-19 virus is evolving so quickly with such massive unmitigated transmission that clinical development of vaccines and antibody drug development is too slow and can't keep pace. 4/
Even if updated vaccines can be designed quickly, they still take 4+ months to deploy and by then the variant landscape has already changed. 5/
Back in 2020 Dr. Cao found 300 human neutralizing antibodies and their team picked the 2 most potent antibodies to develop therapeutics. 6/
They passed phase 2 clinical trials but before they were ready to be used, the Omicron variant could already escape the antibodies, wasting about $150M. 7/ Slide of personal example of how viral evolution ruins clinical development. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
What is really interesting, there are still several of those original 300 neutralizing antibodies that remain potent to all variants to date, so they chose the wrong antibodies to develop. 8/
Dr. Cao wanted to find out how you identify the most broad-spectrum antibodies instead of the most potent ones so they are more likely to remain effective even with viral evolution. 9/
If you can try to predict viral evolution you might be able to select or design the best antibodies that will work long-term. 10/
For the past few years, Dr. Cao has been working on predicting the evolution of the SARS-CoV-2 virus. While mutations in the virus happen randomly, only the fittest survive and become successful which usually means they need to follow two criteria:

11/
1) maintain high binding efficiency to the ACE2 receptor to ensure viral replication
2) escape human neutralizing antibodies to evade immunity

12/ Slide showing survival of the fittest from random mutations of the virus. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
Following that hypothesis, Dr. Cao's team did high-throughput experiments to measure the impact of each mutation on the virus' infectivity and immune escape capability to predict the "optimal solution" for viral evolution. 13/
Using techniques developed over time they published a predictive model and highly immune evasive variant sequences in Sept. 2022. 14/
One month later in Oct. 2022 the BQ.1.1 and CH.1.1 variants that emerged XBB variant in Nov. 2022 sequentially gained the top 3 predicted mutations (346, 444, 460) and 490 for XBB. 15/ Slide showing the prediction model worked for new variants such as BQ1.1, CH.1.1 and XBB. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
Now it was time to try again to develop another solution but this time based on their virus evolution prediction model. 16/
They started with people who had been infected with SARS1 in 2003 who also had a COVID-19 vaccination in 2021 to screen 1400 antibodies and selected 1 for development. 17/
The neutralizing antibody they developed is called SA55 which can also neutralize SARS1 and many sarbecoviruses. 18/
You can see from the table that over time as new variants emerged, the other antibody therapeutics all stopped working since the virus evolved to escape those antibodies, while SA55 continues to neutralize even the latest BA.2.86 Pirola variants that are dominating globally. 19/ Slide showing variant escape of various therapeutics except for SA55 Sinovac solution based on virus evolution prediction. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
Previously, the most potent antibodies were selected which has already proven to be a bad strategy, instead you need to screen for the most broad ones. 20/
The reason they selected SA55 was by doing the mutation screening they found that SA55 can only be escaped by mutations on 503 and 504. 21/ Slide showing why SA55 was selected for clinical development, due to no immune pressure as the SA55 escaping sites. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
From their prediction model they know there is currently no immune pressure at locations 503 and 504 at all so choosing this antibody was a very safe choice. 22/
It is very difficult for a virus carrying mutations in location 503 and 504 to successfully transmit among a population which helps explain why after 2.5 years this antibody has not yet been evaded. 23/
SA55 has been made into multiple tools already. One is an injection for immunocompromised people to act as a long-term prophylactic with an 80-90 day half-life or therapeutic. It has already been used to treat 2,000 elderly patients in Beijing during the outbreak in December. 24/ Slide showing SA55 available as an injection to act as a long-term prophylactic or therapeutic for immunocompromised people (80-90 day half-life). Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
The second tool is a SA55 nasal spray that is supposed to be low cost and provide short-term prophylactics (3 sprays per day) with 8-12h protection per spray providing high neutralization in the mucosa. 25/ Slide showing SA55 available as a nasal spray that is supposed to be low cost and provide short-term prophylactics (3 sprays per day) with 8-12h protection per spray providing high neutralization in the mucosa. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
It has been used by over 200,000 people and provides about 80% protection against symptomatic infection. 26/
The real challenge is future vaccines. Choosing the XBB.1.5 variant for this fall's vaccine dose selection was not the optimal solution but a practical solution. 27/
From the time the XBB.1.5 variant was chosen in May to when the vaccine was deployed in the USA (September), there was already a 4x decrease in vaccine efficacy because variants had changed so much through natural evolution. 28/
Instead of always being behind, a new strategy is needed for COVID vaccine development and Dr. Cao suggests creating a broad-spectrum vaccine based on viral evolution prediction. 29/ Slide showing new strategy for vaccines to create broad-spectrum COVID vaccine based on viral evolution prediction. Image from: https://www.youtube.com/watch?v=OxpJM4gqwec
Instead of basing vaccines on already existing naturally occurring variants, design them based on mutation prediction from current variants to determine what the most likely mutations are going to be. 30/
Hopefully vaccine manufacturers will start using better strategies like this in the future than always chasing variants and being left behind. 31/
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More from @jeffgilchrist

May 10
*** Ontario Variant Update | May 10 ***

In Ontario, the NB.1.8.1.* "Nimbus" variant family shot to 74.7% of sequenced genomes from COVID tests while the XFG.* "Stratus" family dropped to 15.8% and the BA.3.2 "Cicada" family decreased below 10% again.🧵1/
#Ontario #COVID #Variant This multi-line chart tracks the lineage frequency of various COVID-19 variant families in Ontario over time, based on sequenced genome samples. The graph illustrates the changing prevalence of specific variant families, showing how different lineages compete and evolve as the dominant strains within the province.
Ontario released another month of sequencing data by age and we continue to see high ratios of Cicada in children with another 51 BA.3.2.2.* sequences out of 617 new sequences ( ). 2/publichealthontario.ca/-/media/docume…
With 126 Cicada sequences from 1,828 total, we see children still have the highest proportion which decreases after age 5-11 as age increases with significant drops from age 60+. 3/ This bar chart illustrates the percentage of the BA.3.2.* Cicada COVID-19 variant lineage among different age groups in Ontario over a designated time period. The graph visualizes the relative prevalence of the lineage across demographics, highlighting how the variant is distributed from young children to seniors aged 80 and older.
Read 11 tweets
Apr 28
*** Ontario Variant Update | Apr 28 ***

There was some competition for variant dominance during the month of March but the NB.1.8.1.* "Nimbus" family currently holds first place with 49.5% while the XFG.* "Stratus" family sits at 38.1% of sequenced genomes from COVID tests. 🧵1/ This multi-line chart tracks the lineage frequency of various COVID-19 variant families in Ontario over time, based on sequenced genome samples. The graph illustrates the changing prevalence of specific variant families, showing how different lineages compete and evolve as the dominant strains within the province.
The BA.3.2 "Cicada" family has been slowing climbing and now above 10%. 2/
Looking at specific variants, RC.5 Nimbus currently holds first place at 13.4%, SH.1 Nimbus is a close second at 13.3%, RC.6 Nimbus is making a comeback at 11.3%, XFG.1.1.2 Stratus is at 8.2%, RT.2 Cicada at 7.2%, PQ.2.1 Nimbus at 5.2%, and RE.1.2 Cicada at 2.1%. 3/ This multi-line chart tracks the lineage frequency of emerging COVID-19 subvariants in Ontario over time, based on genomic sequencing data. The graph visualizes the shifting percentage of total cases represented by each specific lineage, highlighting the growth and competition of various viral strains.
Read 10 tweets
Apr 13
*** Ontario Virus & Variant Update | Apr 13 ***

Hospitalizations due to COVID have gone down from 153 to 123 in the last update. Influenza hospitalizations decreased from 59 to 47 and RSV decreased from 110 to 85. 🧵1/

#Ontario #Virus #Variant #COVID #RSV #Influenza #Hospital Graph of New hospitalizations in Ontario due to COVID, Influenza or RSV.
Looking at age groups, those age 75+ had the highest rates of hospitalization due to COVID but decreased since last update. Second place is age 0-4 and their levels are currently increasing while age 65-74 has the third highest rate and also decreased since last update. 2/ Graph of New hospitalization rate in Ontario due to COVID by age group (100% Stacked).
The youngest age group 0-4 currently have a hospitalization rate due to COVID that are 17x higher than age 5-17, 17x higher than age 18-49, and 2.8x higher than adults 50-64. 3/
Read 25 tweets
Mar 22
*** Ontario COVID Hospitalization Rates by Age ***

Data is now available for hospital admissions due to COVID by age group going back to Oct 2021. This provides interesting insights into how much children have been impacted with serious infections compared to adults. 🧵1/ Graph of New hospitalization rate in Ontario due to COVID by age group (100% Stacked).
Chart of COVID hospital admissions per 100k population by age group from Oct. 2021 to Aug. 2025 in Ontario, Ottawa, and Toronto.
We have heard from many sources throughout the pandemic that COVID isn't serious in children or they are not impacted as much as adults with some people still claiming this today. 2/
What about today, with lower circulation happening more recently and not the huge waves seen in the past, is anyone even being hospitalized for COVID anymore? The most recent update (week of March 8, 2026) there were 188 people hospitalized in Ontario due to COVID. 3/
Read 20 tweets
Mar 14
*** Ontario Virus & Variant Update | Mar 14 ***

Hospitalizations due to COVID have gone down from 190 to 138 in the last update. Influenza hospitalizations remained stable around 49 and RSV decreased slightly from 194 to 184. 🧵1/

#Ontario #Virus #Variant #COVID #RSV #Influenza Graph of New hospitalizations in Ontario due to COVID, Influenza or RSV.
Looking at age groups, those age 75+ had the highest rates of hospitalization due to COVID but decreased since last update. Second place is age 65-74 and their levels are currently decreasing while age 0-4 has the third highest rate and also decreased since last update. 2/ Graph of New hospitalization rate in Ontario due to COVID by age group (100% Stacked).
The youngest age group 0-4 currently have a hospitalization rate due to COVID that are 11x higher than age 5-17, 5.5x higher than age 18-49, and 2x higher than adults 50-64. 3/
Read 16 tweets
Jan 11
*** Ontario Virus & Variant Update | Jan 11 ***

Hospitalizations due to COVID increased from 176 to 241 in the last update. Influenza hospitalizations have start dropping from the peak of 1,400 to 1,095 with RSV increasing from 121 to 156. 🧵1/ Graph of New hospitalizations in Ontario due to COVID, Influenza or RSV.
Looking back over the past few years, new hospitalizations for RSV have remained pretty stable the last two years around 2,500 and a decrease from 2023, while COVID has been significantly dropping each year, 26,571 in 2023 to 15,739 in 2024 to 6,788 in 2025. 2/ Graph of New hospitalizations in Ontario due to COVID, Influenza or RSV, grouped by calendar year.
Influenza has been doing the opposite, increasing significantly each year from 3,486, to 4,380 in 2024, to 12,818 in 2025. 3/
Read 13 tweets

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