🧵The @US_FDA's materials on @Merck's #Molnupiravir and its potential to induce problematic #SARSCoV2 variants are HERE:

📄section 4.3.2.5 (pp. 30-36)
👉fda.gov/media/154418/d…

📺at 2h51m, 3h46m, 4h5m, 5h12m, 7h32m
👉

Observations to follow.
1/n
@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 Image
@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 Image
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 Image
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 Image
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 Image
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 Image
7️⃣Molnupiravir disproportionately induces TRANSITION mutations (C:G>U:A).

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 Image
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 Image
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 Image
🔟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 Image
🗞️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 Image
See Virological post with @sarperotto on this issue here 👇
Some conceptual figures illustrating our concerns are here👇

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Chase W. Nelson 倪誠志

Chase W. Nelson 倪誠志 Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @chasewnelson

21 Jun
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
Read 6 tweets
21 Jun
今天在 🇹🇼 #天下 @CWM_en 雜誌已刊出: "台灣抗疫成就 遠距工作、創新檢測成關鍵 "。 我與 @cptwei 寫了一篇有關建議 #Taiwan 對抗升 #COVID19 疫情的文章,主要是落實遠距工作、新的科學性篩檢方式。所有工作性質可以遠距辦公的員工,都必須改為遠距工作。重點如下 ⬇️ 1/6 opinion.cw.com.tw/blog/profile/5…
當前的台灣可說是提供了病毒滋養的溫床 — 尤其SARS-CoV-2 #Alpha (B.1.1.7)。依賴症狀的檢疫措施將會漏掉至少 50% 的病毒感染者。新型冠狀病毒會懸浮在空氣中並隨時間經過充斥整個房間。像辦公室這種通風不良的空調環境尤其危險。2/6
非必要地進公司辦公,會增加原可避免的傳染機會。特別是工作上的接觸通常是(應雇主要求)而非自願地,從四面八方聚集大量人群,並且持續相當長一段時間。應為社區人流居高不下。因此增加遠距辦公,我們確信 是控制這波爆發非常關鍵的政策。3/6
Read 6 tweets
20 Jun
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
Read 6 tweets
19 Jun
中文 version 6月19日 #Taiwan 🇹🇼 #COVID19 update.
今日(6/19)的疫情圖表,翻譯了中文版,共六張圖.
🙏 謝謝 @mitchlinmusic 翻譯! (如果中文有錯,請跟我們說!)
1️⃣ 高風險人流趨勢 - @cptwei analysis - WORKPLACE MOBILITY 辦公 remains HIGHER than other outbreak-halting countries ⬇️ 1/6 Image
2️⃣ 篩檢量能的趨勢,並與確診數做比較列出陽性率 2/6 Image
3️⃣ 確診數趨勢 (當日公布數版本) 3/6 Image
Read 6 tweets
19 Jun
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 Image
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 Image
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 Image
Read 6 tweets
18 Jun
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 Image
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 Image
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 Image
Read 6 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us on Twitter!

:(