Replies to post #192008 on Anavex Life Sciences Corp (AVXL)

[McMagyar]

Nice

[jtsmgoblue]

Wow. Way cool and great write-up!

[WolfofMia]

Upon approval, all those who frequent the MB are eligible for a free PC version of the program, in thanks for all the hard work, dedication, thoughts, and levity.

Thank you in advance Bio, I`m really interested to learn about this program.

I`m a EE, so you have stroke my curiosity cord very hard and I have few questions.

First I`m curious to know what kind of AI you are using self learning or trained.

Secondly, what data are you using to determine what is "success", drug approval,efficacy,revenue, all of the of them with different weights applied.

Third, you mentioned it is capable of analyse across a sector, each sector has different types of criteria (inputs that affect outputs). For example biotech are dependent on trials and approval, while tech companies are more dependent on growth and tech adaptability. So how are these different types of criteria fed to the program? Or is it based on pure fundamentals vs potential market?

Ugh so many more questions, can we just get a beta? I would love to give some free acceptance testing!

[XenaLives]

Your computer is just biased because it likes AI...

(not)

Anavex - medicine for the 21st century.

[sokol]

Bio, superb! As someone highly respected might say: “We got this.”Thank you.

[powerwalker]

Bio, once again, "Thank you!"

[tradeherpete]

Yeah Bio, amazing. Wow. OK, now how about throwing in 25000 positive posts from Ihub for avxl and get us to 90%?

[dadofmarcmax]

Proper preparation and planning is the key to success.

When I went to the investors meeting in 2016, I asked Missling about the screening process for any AD trial given my anecdotal experience in clinical Epileptology and general neurology in diagnosing other problems mimicking dementia or as a comorbid condition contributing to multifactorial effects on cognition beyond dementia. At the time, he went on to describe how they were focused on learning everything they could in the early stages in order to properly identify pure AD patients, in order to ensure the highest chance of success in getting a drug to market. This was prior to the shift to the “precision medicine” verbiage in the investor literature that occurred later on.

In 2016; I was impatient but realize now how important it is to go slow, lean and nimble nd learn all you can “on the cheap” before spending on more pivotal late stage expensive trials.

The preparation is mostly completed and the execution has begun, in earnest.

Thank you for the encouraging post at the end of a long day!

[nidan7500]

Bisotockclub, let me ask you this.

You would probably agree that the current Ph trials processes and methods have not changed a hell of a lot in 30 years or so.

I am thinking I would much rather have 400 patients monitored w/remote wireless sensing devices linked to AI controlled central processors with 24x7 continuous monitoring. Measuring key cognition parameters and health indictors w/detail to 6 decimal places as appropriate. EGG and all required links to detect and record elapsed time (ET), Sound responses, Light responses for time and amplitude. Ref all academic work done which shows response time links to cognitive processing ability and skills, capability. All data is in configuration controlled, FDA part 11 validated system monitored specifically to measure dose responses and life quality. You are now getting real time data from all patients 24x7, which you are able to track continuously using any kind of graphical displays you want. Each patient and all of them together being monitored.

OR

You have 200 patients being dosed the same w/standard scores being kept in traditional manner according to best practices. Use established paper, checklist systems and best available current technology to measure and record results. You will then compile the data in whatever systems available and review the results periodically as time allows. Patients will be in and out of clinics for typical evaluations of cognitive skills as are current protocols. You will continue to conduct this trail for 1 year.

Now at the end of this exercise you will have systems monitoring data real time for 400 people continuously producing trial information which is being seamlessly compiled and displayed for assessment. (400 patients x24x7 data). A gazillion data points of patient monitoring information.

Using todays trial system you would have 200 patients and data from whatever the trial interval allows for readout and analysis. Lets say every 2 weeks people get to be assessed for cog and QOL, and other as according to protocol.

Here's the question. which method provides the best patient safety and the most effective methods for trial information gathering robustness? Which presents the lowest ultimate risk to the regulatory body decision making process? (400 ptsx24/7x# of tests(n=20)) or old school (200 ptsx # tests x 24 data points for the years test) .

Now, which method-protocol presents the most trial data and consequently provides the most robust data set for lower risk decisions? Continuous real time AI monitoring or periodic manually assessed data?

That, IMO, Is what is on the table now and BTW the changes will allow full/better trials in a fraction of the time.

Is a system for trails capable of monitoring 400 patients continuously better from a decision risk standpoint than current trail methods?