@US_FDA@Merck First, @Merck and the @US_FDA panelists have done excellent work compiling and analyzing the available data. This was not an easy vote (13 YES/10 NO).
However, specifically on the potential for molnupiravir to induce new viral variants, the results only augment my concerns.
2/n
@US_FDA@Merck 1⃣MUTATION VS. SELECTION. The materials repeatedly confuse mutation and selection (e.g., "The Spike protein is already under evolutionary pressure with or without molnupiravir", 3hr).
Contrarily, the concern is this drug is a mutagen and provides RAW MATERIAL, not selection. 3/n
@US_FDA@Merck 2⃣PREVIOUS VARIANT OF CONCERN (VOC) MUTATIONS.
The results show molnupiravir does preferentially elevate C>U transitions, but also transversions.
Numerous VOC Spike mutations were identified in drug-treated patients—a potential problem if many take the drug (~2h50m). 4/n
3⃣HOW MUCH MUTATION?
Keeping in mind molnupiravir works by inducing too many mutations, the materials repeatedly employ two MUTUALLY CONTRADICTORY lines of reasoning: (1) the drug causes too MUCH mutation for the virus; (2) the drug causes too LITTLE mutation for a variant. 5/n
4⃣INDIVIDUAL VS. GLOBAL RISK.
The materials rightly note that the risk of a variant arising in ANY ONE PATIENT is low.
Of course. The issue is molnupiravir making more probable RARE EVENTS that go on to affect the GLOBE—the whole lesson of this pandemic and its variants! 6/n
5⃣EVOLUTIONARY PATTERN.
The materials repeatedly state that evolution with molnupiravir resembles that in nature—as if this were GOOD news!
One panelist even argues that more mutations are NOT a major problem b/c "With millions of individuals, #Omicron only popped up once"! 7/n
6️⃣The MUTATION RATE ELEVATION caused by #molnupiravir CANNOT be assessed without the raw sequence files. #bioinformatics
What some have interpreted as a ~2X rate elevation is actually POLYMORPHISM at frequency >5% in the within-host virus POPULATION, filtered by SELECTION. 8/n
But transition mutations are disproportionately likely to be SYNONYMOUS (no amino acid change), and are therefore less likely to influence viral fitness and contribute to LETHAL mutagenesis. 9/n
8️⃣ADHERENCE TO DRUG REGIMEN.
Even in the closely monitored trial, 5% of participants missed TWO OR MORE doses (3h59m)‼️
Incredibly, in the doc, it is suggested that early termination is an option if hospitalized—the WORST THING TO do for sublethal mutagenesis+transmission! 10/n
9⃣There was NO monitoring of FAMILY/CONTACTS, or of IMMUNOCOMPROMISED patients for viral REBOUND (~2h20m).
Moreover, assays for detecting viable virus LACKED SENSITIVITY.
Thus, we cannot assess the potential for onward spread of viable virus when taking #molnupiravir. 11/n
🔟ADAPTIVE LIMITS NOT REACHED. In a compelling presentation at 5h12m, @ismagilovlab notes that there is no evidence #SARSCoV2 has reached the limits of its (even relatively proximal) adaptive evolutionary potential.
Moreover, adaptation need not involve only Spike. 12/n
🗞️CONCLUSION: we don't have sufficient data to estimate the risk #molnupiravir will cause new variants when MILLIONS take it.
As noted by panelist @JamesEKHildreth, it was incumbent on Merck to estimate this risk and they didn't.
We can only hope our concerns are wrong.
13/13
See Virological post with @sarperotto on this issue here 👇
TODAY’S (6月21日) #COVID19 update for #Taiwan 🇹🇼
📉75 local + 0 imported cases 📉trend
📉20 deaths 📈trend
📈0.6% test positive rate
📈4.2% case fatality rate (CFR) since May 1
🧪13k tests ⤵️capacity
⚠️It's Monday. Numbers of tests and their positive rates are key metrics. ⬇️ 1/6
DAILY CASES REPORTED (pink bars) and their 7-DAY AVERAGE (pink line), where each day is the mean of itself and the previous six. DEATHS (crimson red bars) at the bottom. THRILLED to have room for the chart legend specifically in the top right quadrant! 2/6
AGE DISTRIBUTION OF CASES. Local cases from May 1-June 20 (age data for cases lag by a day), including those with missing locations. Only a single category is provided for ages >70, which constitute 14% of all cases. DATA ➡️ data.cdc.gov.tw/en/dataset/ags… 3/6
TODAY’S (6月20日) #COVID19 update for #Taiwan 🇹🇼
📉107 local + 2 imported cases 📉trend
📉11 deaths 📉trend
📈0.6% test positive rate
📈4.1% case fatality rate (CFR) since May 1
🧪20k tests ⤵️capacity
⚠️Fewer cases BUT many fewer tests, higher positivity, and higher CFR. ⬇️ 1/6
DAILY CASES REPORTED (pink bars) and their 7-DAY AVERAGE (pink line), where each day is the mean of itself and the previous six. DEATHS (crimson red bars) at the bottom.
AGE DISTRIBUTION OF DEATHS for May 1-June 20:
🔴64% are ≥70
🔴26% are 60-69
🔴10% are 30-59 years 2/6
AGE DISTRIBUTION OF CASES. Local cases from May 1-June 19 (age data for cases lag by a day), including those with missing locations. Only a single category is provided for ages >70, which constitute 14% of all cases. DATA ➡️ data.cdc.gov.tw/en/dataset/ags… 3/6
TODAY’S (6月19日) #COVID19 update for #Taiwan 🇹🇼
📉127 local + 1 imported cases 📉trend
📉20 deaths 📉trend
📉0.3% test positive rate
📈4.0% case fatality rate (CFR) since May 1
🧪36k tests ⤵️trend
⚠️WORKPLACE MOBILITY remains HIGHER than other outbreak-halting countries ⬇️ 1/6
DAILY TESTS REPORTED. Daily counts are subject to bias, with the fewest tests consistently reported on Mondays. This emphasizes the importance of 7-day averages, not daily values. The mean seems to be slowly rising, even though today's mean dipped. 2/6
DAILY CASES REPORTED (pink bars) and their 7-DAY AVERAGE (pink line), where each day is the mean of itself and the previous six. DEATHS (crimson red bars) are seen at the bottom.
DEATHS AGE DISTRIBUTION for May 1-June 19:
🔴64% are ≥70
🔴26% are 60-69
🔴10% are 30-59 years 3/6
TODAY’S (6月18日) #COVID19 update for #Taiwan 🇹🇼
📈187 local + 1 imported cases 📉trend
📈21 deaths 📉trend
📉0.4% test positive rate
📈3.9% case fatality rate (CFR) since May 1
🧪42k tests 📈capacity
💡Good to see a record high tests (42.2k) and record low positivity (0.4%). 1/6
DAILY CASES REPORTED (pink bars) and their 7-DAY AVERAGE (pink line), where each day is the mean of itself and the previous six. DEATHS (crimson red bars) are seen at the bottom.
DEATHS AGE DISTRIBUTION for May 1-June 18:
🔴64% are ≥70
🔴26% are 60-69
🔴10% are 30-59 years 2/6
AGE DISTRIBUTION OF CASES. Local cases from May 1-June 17 (age data for cases lag by a day), including those with missing locations. Only a single category is provided for ages >70, which constitute 14% of all cases.
DATA ➡️ data.cdc.gov.tw/en/dataset/ags… 3/6