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Anavex had to collect the raw data for an odds ratio analysis. The problem is that Anavex may not be able to prove statistical significance using a traditional analysis. There is an argument by the company that titration complicated the analysis, but that is because of the trial criteria only. An analysis could be performed on the end dosage, however that would not align with the trial design for inclusion in each group. It is a paper vs reality thing. There is no way to separate the groups into maximum tolerated dosage with a placebo arm. Undoubtedly, a negative spic could be used on any further analysis, but it is all BS.
Since the trial was blinded a post-hoc analysis should be able to be performed with maximum tolerated dosage, pooled, to show benefit. The problem will be, if the 30mg group does not show statistical significance and the 50mg group does. Again, it would be BS, but you could not pre-specify who could tolerate the drug prior to dosing unless additional biomarkers are identified. This is BS, because the drug has shown to be safe and tolerable, regardless of the dosage. Take your chances and find out... the 'take at bedtime' caveat will probably also have naysayers because there is no evidence to support this case.
A real doctor would be able to understand a post-hoc analysis and not throw thier arms up on semantics.
If the trash was taken out at 6:05, and they said they would do it at 6:00, and the trash truck runs at 7:00, the result will be the same if you're only worried about getting rid of the trash.
I wonder if Cantor was short going into CTAD...
How long did it take for them to release results from that trial?
The truth is, we have the companies perspective on a third party analysis. Nothing more, nothing less. The company clearly stated they expect to release more data and information when they can complete analysis. I don't see that as incompetence.
The markets response is certainly underwhelming, but given all of the negative spin, I expect many investors are being cautious.
We aren't shooting for a high score, we are shooting for a significant correlation to dosing and meaningful departure from placebo. If the data is good enough for the "worse" result to demonstrate this significantly, then let's include all of the sample populations and skip the gold star for now. A confirmatory P4 would clarify optimal conditions.
Lane isn't spewing nonsense and accusations.
That's not being skeptic, that is called being pragmatic. Right now we have the companies interpretation of a 3rd party analysis. Let's see the peer reviewed analysis, including the data set.
Really, pulling out a Melissa Davis article...
The FDA should seriously consider the results of this trial and the millions of people that are suffering. If Lacanemab is hailed as a momentous breakthrough with brain swelling and potential deaths, what does that make Anavex 2-73? The safety profile is great and a double-blind, randomized, placebo-controlled trial showed significant results. What was the last alzheimers drug that was approved?
That happens alot with this stock.
It may not be that the "cabal" is seeking for Anavex to fail, but instead make money. There is nothing illegal about buying and selling shares and if that swings the stock price, then it swings the stock price. I don't believe that owning enough shares to influence large swings is illegal either.
Right now there are not enough layers of interest in this stock to prevent large swings. I wouldn't say big pharma doesn't have competing interests though. FDA has shown fault recently, and the SEC won't have an interest unless someone can provide proof or they discover something through audit.
Regardless if you believe in a cabal or not, the result is the same and in the end, if you make money you made an investment decision that returned a profit. Call it good, bad, or lucky.
Certainly there can be more than one investment strategy in a stock...
1 hour and 3 minutes later...
Or per the famous SpongeBob
ONE HOUR LATER...
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491757/#__ffn_sectitle
https://www.frontiersin.org/articles/10.3389/fphar.2020.00194/full
https://www.sciencedirect.com/topics/pharmacology-toxicology-and-pharmaceutical-science/muscarinic-acetylcholine-receptor-antagonist
https://www.biorxiv.org/content/10.1101/2020.10.12.324152v1.full
Interesting. Fairly tight sideways. Looks primed for a move.
What other indicators are being used at this early stage to conclude the patient has alzheimers? PET scans? Cerebrospinal fluid sampling? Genetic markers?
Is that a huge cup and handle forming?
What other metrics are they using to diagnose early alzheimers? MMSE of 28 is pretty high. Would you consider MMSE scores of 25-28 to be early dementia?
And they only have a $380 million market cap. Looks interesting.
It was not the tweet. I believe shorting was already underway. Feursteins tweet in combination with an already declining price just fueled the fire. This has happened repeatedly in this stock. I beleive if you wanted to find the correlation you would have to look at who is shorting the stock before the Feustein hit is released... what are commonalities with his other hit pieces. He used to be a little more sloppy in his social communication, I don't know if he still is. Feustein can play the odds though, and win, most of the time. Which stock does he commonly support? Like other analysts he can be wrong. Unlike most other analysts, he borders the line, if not crossing it, of slander and false representation based on unsupported evidence.
Havana Syndrome?
Thanks froll, for the clarification.
This is interesting, to say the least. It is different if the company is mandating vaccination, or the research facility, or the local government. It sounds like from your comments that the girls still have a choice, except if they join the trial. That is BS. How does the clinical investigator know if effects are from Anavex drug or from vaccine. The trial population does not match the target population and could skew results, particularly toward failure.
https://www.rettsyndrome.org/covid-update-rett-syndrome-and-the-covid-vaccine/
https://doi.org/10.1212/WNL.0000000000012578
Is that by trial design or by the research facility?
Looks like the FDA may disagree: https://www.nytimes.com/2022/02/10/health/fda-cancer-drug-china.html
Those subgroups only drew a correlation among observations discovered in those subgroups. Saying those small sub groups in any way represent the target population is a reach. You could design a trial that sets exclusion criteria to that observation, and the compare to the target population for statistical significance, but to claim an observation discovered in 2 out of 21 is statistically significant and represents anything other that the sample population is ridiculous. Additionally, while another trial may be successful in demonstrating statistical significance with the specified exclusion criteria, Anavex cannot claim that it is effective for the whole diseased population.
It is beneficial in considering exclusion criteria for trial design when there are no other correlations to draw from.
Absolutely, the trial design must take that into account if you are attempting to look for findings in subgroups of the sample.
I think we may be saying the same thing. A statistical analysis should be performed to determine required sample size. Regardless of the amount of data, a statistical analysis will determine the likelihood a sample size will produce a desired result given an acceptable amount of variance. The desired result is whether the drug works is an adequate sample of the target population to account for variables in the target population. The target population may only be a subset of the entire population. If the trial design can account for the variables, a smaller sample size would be warranted. Taking a pot shot at sample size is a huge risk with investors money.
The FDA or any other regulator authority is not going to just be interested in whether statistical significance was achieved in a sample population, they are going to also want to know what the target population is and how the trial represents that population.
Example... I am making a drug that grows hair in balding males. We take a sample of 100,000 males 18-21 and they happen to all have brown hair. 90% of the sample regrew a full head of hair. What does this tell us about blondes or red heads, and anyone over 21? What is the confidence this drug would work in those people as well? Should the company be able to advertise that thier product can regrow hair in men?
Still a statistical problem. The precision medicine approach accounts for effect size in earlier and smaller trials. In effect, they have narrowed the sample size to a smaller target with increased likelihood for success. The trial population still needs to account for other variables that would be experienced in the targeted population.
No problem, just wondering if there was some new claim about the trial design. Trial size calculations are just a statistics problem.
Texas?
I should have known better, thanks Boi. Just because the trial size is different between companies does not mean it is less meaningful. Trials are powered to look for effect in different things, the drugs are not the same, thus the trials are not the same. As long as there is a significant corellation to the target population, an effect can be seen. Often trials are designed to be larger when the company has less confidence in reaching endpoints. This allows them to look for other effects in subsets of the trial population. A dirty precision medicine approach, ie. we don't know what else we may see, so cast a large net and look for any relationships. This happened in one of the AD trials from another company, can't remember off the top of my head. They ran the trial and after failure realized that a small subset of the population saw a larger decrease in AB plaque, so they re-ran the trial powered for the chacteristics of that subset. Larger poorly designed trials can lead to failure if you don't have bottomless pockets. There is nothing wrong with Anavex trial size, unless they change at the end of the trial, or attempt a very small trial population.
What trial size is smaller? Smaller does not equal precision, and can decrease the significance of findings if too small.
Ah, yes, brainpower. There was a set of LED lights on Amazon that were listed at 1,200 watts, 12 v, and included 16 ga wire for connection. Yeah, so I get the "brainpower" measure and will roll my eyes as I post this message.
Not the same, even if approved. This is cool-aid talk.
Really? So it was Misslings vision and innovation that created this company and got it where it is today? All while opening the minds of others and challenging the realm of MANY possibilities? I'm not much of a Musk fan, but his leadership has influenced the future of many around the globe.
Missling has the opportunity to take the ball and run. How he gets to the end zone is his contribution to the game. His contribution can have an impact on many, but to say he is another Musk is absurd.
THIS! I wonder if it would extend IP protection later on. It likely has to do with grants and funding, not to mention a successful AD drug would more than cover those expenses. Missling is good at the financial game.
Do you reeeeaally beleive that?
It is a clever approach. If it works in the end, it will reward investors.