Anavex Life Sciences Corp (AVXL)

[Biostockclub]

Putting AAIC presentation into context
- from a very big picture, overview, perspective [SUPER LONG]

AAIC 2019
Anavex’s Gut Microbiota Biomarker based on the original “n” - Relevance to our strategy

Outline:
What is Precision Medicine - Overview
i. How small is too small for testing correlations (the signal is great, and it is obligatory to tap every possible hidden edge found. Remember the recent debate over whether it was the duty of Amgen to test Enbrel? Wasn’t, imo, but we have a duty if strong signal, imo.)
What this new information means - gut Microbiota
Combined with already established information/ genetic
When/how to use this new information
Further data to come/ clinical
How this will make it impossible to fail trials
Reality check: other companies which are integrating data to enrich via Precision Medicine
The mention of cross-research: sleep, seizures, microglia, disease modifying strategies elsewhere - them;
AB correlations and clearing in the gut - us
The publication to come: it cannot be simply what was presented. It was stated at ASM that it would be presented in a publication instead of a conference. Look for enriched data to come. It cannot be a redux of the presented data as that would not be novel.

WHAT IS PRECISION MEDICINE?

What is this elusive thing we refer to as “precision medicine” and why are we chasing it? Why are we invested in this strategy? It sounds interesting, new, and promising, but will it make a difference in the field of CNS Disease and is our company approaching this correctly? Also, how long does this approach take to yield results?
(Don’t forget that within the last several months we have purchased inventory, registered a name for our compound, set up sites to screen and enroll patients for 3 indications, and have provided for extensions for all 3 of these. Additionally, we have registered for a Shelf offering to raise $250M and it became effective as of 7/16.)

Why precision medicine, as opposed to accurate medicine? Precision medicine is the ability to reproduce a desired outcome in a variety of specific cases which all end up in a very tight range of each other. This equates to reliability, predictability, and necessitates the use of standardized measurements to gauge results very accurately. Accuracy is the ability to hit a single target over and over again. Precision is the ability to cluster a grouping of outcomes in a very small window.
In medicine, a branch of science, we notice that traditional blood tests, such as cholesterol, sugar, thyroid, etc, are considered normal if they fall into a range. It is agreed upon, universally, that each person can be “normal” with slightly different readings of cholesterol, sugar, and so forth, as long as they fall within a normal range. There is not one single specific value which correlates to “perfect” cholesterol, or PSA. We have slightly “elevated” out of normal range, which warrants further monitoring, and “red flag” out of range levels which require more immediate attention.
The undertaking of precision medicine requires that we understand we are trying to bring test scores of patients which are out of range back toward a more normal range with as much precision as we can in order to recognize that progress is being made to stop or reverse a specific condition. We can move in the direction of certain targets with precision and be advancing against a disease. This is no different from science, in general, and military struggles. Same with sports, only far less at stake. This accounts for the fact that so many analogies have been military or sports related. So, are we “winning the war” on CNS diseases? Are we advancing the “troops” or the “ball”?

This is where biomarkers come into play. We need a way to measure the “placement” of the ball, such as yard line markers, in bounds and out of bounds. We need a gridiron which never changes, regulation sized balls, and basket heights, and such, to correlate our performance standards against others as well as against a clock when timing running events or car races on a measured track distance.

The reason we are looking at our original participants so very thoroughly, is that a number of them responded so favorably to our drug that we are obligated to learn why and include every possible reason. Had we not seen any response to our drug, we would not be where we are today. We might be looking at results for A3-71. Had we seen a single person, of the original 32, respond, we may or may not have followed up, depending upon the strength of the response. What we noticed from the original human clinical trial was that 6 persons out of 32 had significant strong response. Others had less significant response but still responded. Based upon this response profile, we had a genuine desire to learn why these responses occurred. From a purely scientific standpoint, one would want to know what accounted for any such data whether in the field of physics, botany, or other discipline. This is definitely post hoc, or after the fact. But, that is the proper design for learning who and what our drug targets precisely. Example: you troubleshoot your car AFTER the check engine light goes on. Routine maintenance is great for prevention of problems, but what happens when a sensor goes bad or wears out and CEL comes on?
The process is not “bad” or “wrong” just because you go to a mechanic after the light comes on. The process is broken when a mechanic decides that he or she will specialize only in changing sensors and when you bring your car into the shop, he or she changes the sensors before troubleshooting the car. Big, costly trials in medicine often form an hypothesis ahead of time and develop a drug which treats the disease based upon this. Then, they discover afterward if the drug worked or failed. That’s not far from a mechanic who stocks only sensors and if your muffler is shot you get a sensor. (That was Amyloid clearing drugs, fyi).
That doesn’t solve your problem, so you take it to another mechanic, who, changes your sensors. And, so does every mechanic you visit. You will spend a lot of time off the road and your problem will never be fixed.
Instead of stocking only sensors, Anavex is listening to the sounds the car makes when it idles, when it is in gear, when it shifts between gears, while going up and down hills, and so on. The company then compares the performance and noises to cars which run smoothly. Anavex checks to determine whether the car stalls when going up a hill or if it fails to slow when going downhill, and perhaps along the way we notice that the car does not stall while going up a hill if the radio and A/C are off. That’s a troubleshooting clue which needs to be discovered at some point along the way. I don’t know how much value people put into troubleshooting to determine the exact problem before fixing it, but I can suggest it is the best way to discover the cause of the problem and to solve it and get you back on the road. I would like folks who find no merit in our company’s process to live their lives according to the criticisms they have of our process. When they take their car in for a mechanical problem, they should insist that no data be gathered from the current state of the car, they must go in with a stated goal of exactly what they are going to replace and leave after securing that one stated objective only. That would be lunacy. In the Anavex model, it is also not only ok to look under the hood, but, as we learned yesterday, it’s ok to examine the tailpipe environment and test the exhaust for emissions. Also, we took the “used” dirty oil and tested it for different types of debris. Let’s you know the condition of some of the roads you have been traveling and the amount of dust/dirt/debris they tend to inflict on your system. (These are lifestyle issues, such as diet, exercise, air quality, etc)
In studying the original response pool, we have a limited resource, but very rich correlations can be derived from these. Meaningful ones. We are going about this process quite appropriately, from a scientific standpoint. This is a discovery phase, not a proof phase. I think that is where the logic falls apart, in asseverating that we lack significant evidence and they are only correlations. Please proceed to step two of the process, where the correlations are proved - after being uncovered (the uncovering is the monumental first step).
Seems we all agree that trial results will bring us success in the end, nothing less. If we can all see that and agree, what’s to miss in determining how exactly we will ensure those positive trial results? We need these building blocks as our foundation - don’t dismiss them, please. They won’t be the rocket blast, but they are the science, technology, engineering, launchpad, mission control, which will supply the needed components to make that rocket launch and land safely. This is the process. A giant sign was never going to fall from the sky saying, “Anavex has just cured CNS disease spectrum”.
Missling: Hold my beer...
*Giant sign drops from sky, on cue*
Me: Okayy, where was I?

But, really, I hope you see my point that as our process unfolds, each step is a giant leap. (Moon Mission reference. 50 years ago now, underway!! Spoiler: special commemorative portion at end...if you make it. Added incentive!)

Recently, Amgen was chided in the Press for choosing not to pursue its rheumatoid arthritis drug Enbrel as a possible treatment for AD. The company stated that the drug showed the possibility of preclinical promise - which is a whiff of a hint of a chance that it could treat a disease. They decided not to pursue because they said the data were not significant enough. People said it was their DUTY to pursue this avenue even if it would be expensive and fail(!), for the sake of advancing science. I strongly disagree that they had an obligation to run a high cost/low probability trial. However, an even stronger argument can be made for Anavex A2-73. That is why we are doing what we are doing. The signal in human beings was so strong that we truly DO have an OBLIGATION to account for this. The small “n” is what makes this an absolute must and the ongoing data we collect from these folks is of so very much value that it is impossible to value it, in the market at present, however, we can explain why it has such a high worth. By the way, in the case of the mechanic analogy, your car is an “n” of one. Mechanics have historical experience of many other cars with similar problems to compare yours to, but every car is unique even though they are factory assembled. (This is why the existence of “lemons”, which would not occur if the assembly line process were flawless. Granted, the use of robotics today reduces lemons, but still not perfect.)

In order to account for the response to our drug, the company, at some point, derived gut biome data from strong and weak responders, high and low dose concentrations. How does this help us in our quest to “tackle this disease”?
If the strong responders have similar gut bacteria which can be measured and found to fall within a tight range, this range can become significant in the same way that the lines on a football field are. We can say with certainty how much of certain types of bacteria are needed to create an imbalance strong enough to correlate with the symptoms of the disease state called Alzheimer’s, in this case, but also, Parkinson’s, Rett Syndrome. We can also know that our drug, much like a football kicker, is effective at certain levels (is accurate from the 47 and “iffy” beyond that). We know this because after learning of the correlation, we tested it on our patients and improved their response. That’s very good to know. We now know exactly that.

What else have we learned from our sample? We already discovered the genetic correlation between the wildtype SIGMAR1 gene and COMT gene and response to our drug; genes which appear in 80% of the general population.

If someone wishes to know why the drug responded strongly on only 6 trial participants out of 32 candidates, we now have 2 possible answers: perhaps the trial population was not reflective of the 80/20 general population. Perhaps, the trial had only 6/32 with the proper genetic make up. Or, it is possible that the genetic make up was in attendance but lacked the proper gut bacteria to enable the drug to reach higher concentrations in some participants.

Now, everyone can see the application of Aesop’s fable/moral about the Bundle of Sticks and why we are using this process. It is evident that the argument which states that the genetic data is meaningless because it is so small, and the argument that the gut analysis is just more of the same, can be easily dismissed when examined separately. I can break either of those over one knee just like a one inch stick. Very low hanging fruit - some posters dismissed the results throughout the day and into the evening and night following the AAIC presentation. But, when we have a bundle of those sticks bound together, it is very hard to break that over a knee. Guaranteed, this is what we are doing: adding sticks to a bundle like thin straws to a camel’s back. Eventually, camel will break; and eventually the bundle will not. The process is all about building a strong case out of smaller pieces, which, when stood alone, can not carry the significance required of this evidence, but, which, when taken together, are overwhelming.

When we combine the known genetic make up which responds to our drug with the gut make up which corresponds to the drug, we can use this in ph2b trials and extensions now and verify results. When we enroll ph3, we will need fewer patients because every one, EVERY SINGLE ONE, except placebo recipients, will respond and meet endpoints with flying colors. We could achieve a near 100% response rate. That is a fact. And it has been suggested or written or stated, that we fully intend to stack the ph3 trial. (I think I recall Investor posting the reference, if incorrect, I apologize.)

In order to increase the precision of an exercise, one can either use a larger sample size, or DECREASE the variability. Input determines output. If we input only those who will respond, the output will be complete response of the drug. We can do this without a huge lengthy trial. That is the beauty of precision medicine and it evolves from the scientific method and mathematics (solving for 4 unknowns is easy if you can develop 4 relationships and substitute them).

What else did the presentation tell us?
Slide 17 bottom
“Precision Medicine Using AI Improves Chance of Clinical Success – KEM platform to integrate clinical and microbiota data and identify potential biomarkers of response for ANAVEX ®2-73 in addition to testing for genomic biomarkers with improved clinical response to ANAVEX®2-73 in Alzheimer’s patients carrying wild-type (WT) SIGMAR1 and COMT genes”

Notice the three categories of biomarkers they are testing for (have tested for - this is all finished and findings only being released now after verifying within the extension group):
CLINICAL
GUT MICROBIOTA
GENETIC

They have presented the genetic biomarkers, and, now, the gut biomarkers, so the clinical biomarkers will be next. That means sleep - first and foremost, along with possibly exercise, mood, agitation. But sleep, as we know, is already part of the ph2b. There can be no doubt that our company has meaningful data (sticks which are being bundled to add strength) which it will use to make our ph3 trials impossible to fail. If anyone tells you anything different (...lots of drugs show early promise and fail in ph 3...) please remember that, “We are different”.

There is no way that we can fail if we strengthen our signal with the right genetic matches, the right gut matches, and measurable sleep quality/duration improvement, regular exercise and whatever else the recipe calls for.

Our trials have been covertly developed to be impossible to fail. Now, with this public presentation, they became visibly more improbable to fail. Add sleep and other components until this becomes an endeavor that is impossible to fail. And, this, truly is, how you solve a problem, fix a car, cure a disease.


If you do not believe me, here’s a third party reality check (more prestigious than I, more experienced, and better compensated, also with more at stake):

When Eisai hired Dr. Hampel, they named another fellow to work directly on the same initiative as VP Clinical Research, Alzheimer’s, from within the company. Here is the PR: (please note the specialty, Epilepsy and Sleep/Wake Therapeutics)

May 2, 2019

“Dr. Irizarry, who joined Eisai in 2018 as Vice President, Clinical Research for the company's Epilepsy and Sleep/Wake therapeutic areas, will assume a new role with responsibility for the clinical development and overall strategy of the company's AD-related neurosciences portfolio.”

https://www.prnewswire.com/news-releases/eisai-inc-deepens-its-commitment-to-alzheimers-disease-with-key-executive-appointments-300843144.html

Then, add the cross reference to the PR posted by nidan yesterday, which states that Eisai is pursuing AB, Tau, and Microglia (this overlaps with A2-73’s mechanism. Additionally, we mention ABeta in our gut Microbiota presentation.)

If Eisai brings a gastroenterologist on board, that will be an obvious breadcrumb. Watch for things like this.

Btw, this was meant to be an overview of a systematic process taking place. As far as the significance of the particular correlations which Ariana’s KEM platform uncovered, as an AI/machine learning person, I can attest to the fact that these are the “real deal”. Ariana is not a fly by night company. They are professionals with the capability to mine data for edges and analyze those correlations appropriately. If anyone has any doubts, please show your work. This is a field of amazing revelations and noise. Professionals know the difference. Before questioning, show us your outlined “preferred method”. Anything else is a blustery waste of everyone’s time. Missling does not play games and he doesn’t do drama. (Other companies don’t analyze feces/bowel movements, they put out a PR every time they have one... just say’n)


In conclusion, (Lol)

“We choose to go to the Moon. We choose to go to the Moon in this decade and do the other things, not because they are easy, but because they are hard, because that goal will serve to organize and measure the best of our energies and skills, because that challenge is one that we are willing to accept, one we are unwilling to postpone, and one which we intend to win…”

— President John F. Kennedy, Sept. 12, 1962


The overview: Apollo 11 lifted off from Launch Pad 39A at Kennedy Space Center in Florida on July 16 and returned to Earth on July 24, splashing down in the Pacific Ocean after traveling a total of 953,054 miles in eight days, three hours and 18 minutes.

July 16 - 50 years ago, they lifted off!!


July 20, 1969 First man steps foot on moon surface. 50 years ago coming Saturday, 2 days...Nice!!!
Splashdown July 24, 1969 Mission complete and successful, Houston:)

Inspiring words to accomplish any and every goal: CHOOSE to set a goal, not because it is easy - because it is HARD. The process will:

Organize and measure the best of “our” collective energies and skills

Be Willing to accept the challenge and Unwilling to postpone it

Demonstrate that we intend to Win.


Salute to our brave pioneering astronauts and science engineers who changed the process and made history.

Salute to our medical researchers who are bravely pioneering ways to change the process and make history.

It is encouraging to know, by witnessing and remembering, what mankind is capable of. The faded, sunburnt flag is still planted there - a 50 year enduring tribute stands, to those who chose.

Past is prologue!
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