PAR 1.64% 31.0¢ paradigm biopharmaceuticals limited..

research reports and media, page-4280

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    Sometimes I like to sit back and digest a pres like we had today and in fact we also had the updated slide deck from the Freemantle pressie just recently.

    I thought Paul spoke well today, it was concise, to the point, there was a little history of the trials and where we are coming from.

    I liked the mentioning of the stats. I suspected n would come down, I suspected the percentage chance of success once we actually start the blessed Phase 3 wouldn't be too bad. A 98% chance of success is what I, as a holder, want to hear, specially when there are a lot of facts about how many third phase candidates actually don't make it.

    Let me just elaborate on that one stat for a sec.

    In our 008, n was just 19. So p, even though n was so so low, approached or bettered 0.05 (sere below). Indicating Statistical Significance. Something that wasn't to be expected, the trial wasnt powered for this.


    https://hotcopper.com.au/data/attachments/6321/6321410-41aa69e28bf6e19082c87d7dbf2a1ae7.jpg



    My point of this elaboration was to state that it can be argued that Drug Effect size is a better indicator than p value.

    Why? Because Drug Effect Size is not affected by n.

    You can have just 19 patients in a study, you can have hundreds, you could have thousands.

    It is independent of sample size.

    Paul told us today that based on BOTH 005 and 008 averaged effect sizes, we will be a 98% chance of success.

    008 effect size was greater than 005.

    PAR have learnt from 005 and how to control placebo effect better and how to derive better effect size differences between active and placebo. We literally saw this moving upwards, lifting the average as the poster Torpy once alluded to the batches coming in from the SAS program and we saw the average increase! I'll include it as an appendix below for those that haven't read it, it's quite a read and not too long, you will get a sense of the improvements achieved over time. I know some of us think PAR are too slow, have their problems, can do things differently and dont UPOD....but you also have to acknowledge some of the positives too.


    Par is very confident of their P3. I must admit I was a little surprised that they told us about n coming down. It to me also shows their confidence. Maybe, just maybe, my glass is half full?


    The other slide I was happy to see was this one:

    https://hotcopper.com.au/data/attachments/6321/6321443-484ebbf0aa4ec3edab08a2e76981c895.jpg

    It documents how busy they have been with work very much hidden from the investor. This is the background work that they have been doing to feed data and info through to the authorities in prep for the clinical trials. They have had a number of interactions and meetings and have done a great body of ground work. It adds to the chances that we will get our P3 finally approved. Sure it's not over till we get it in writing.

    Again I wanted to also emphasis that I personally think it is good they are building in duration (404 day timepoint). It initially sounds bad, more time, more delay, more cost...but in actuality, this is one of the greatest things for us.

    It doesn't stop an interim top line read out at Day 56. It broadens our label potentially. It could very well not only mean increased uptake of our drug, better insurance reimbursement but that will equate to a better commercial deal for us.

    It's one thing to say we have Pain and Function and that we are pretty good at it...its next level to say that we have that AND this thing lasts. Oh does it last. On average no more drug required for at least 12 full months. To be able to rescind the disease in some cases and to do it safely with the durational aspect on the label...well the uptake and the convincing is done for the Docs.

    Yes we have heard about deals multiple times and it's been snuffed out harder than a firework in a downpour.
    But again, I think it's moving closer and certainly if...IF...these authorities decide to give us a go, the chances materially increase that we might just find ourselves with a commercial deal. In addition it could indeed be multiple regions over time.

    I've heard it a few times from different sources, these days it has to be closer to a P3 or a P3 candidate to have a higher chance of a deal and that's specially true in the OA space. The OA disease treatment sector is littered with failed drugs. Pharma and many larger investors want this de-risked before they will sign up. De risked means FDA certainty. It's really the last major hurdle for us.

    I also understand that we are at the show me the money juncture. Enough talk and promises, we need to really see the contract and the cash. Until that happens we are all going to have a degree of frustration, some a lot more than others. I get it.


    I liked Paul's presso today, concise, to the point and he seemed happy. Yes we need more than his happiness...we need commercial results, but we do still have to wait for the authorities.


    I'm waiting patiently.




    DYOR of course.











    APPENDIX



    Posted by @Torpy on 27/6/22 -----------------------------
    Ref: https://hotcopper.com.au/threads/back-to-the-future.6811324/page-5?post_id=62219313


    That SAS data is really interesting, and got me looking closer at it.
    When they report from each cohort seems they report the cumulative pain reduction.

    https://hotcopper.com.au/data/attachments/4459/4459851-1b39862c0a7328ed92f5504a829ec572.jpg

    If your whole population average increases with an additional cohort, the average of that cohort must be greater than the population average you end up with. Simple example.....If you have 10 samples averaging 5 and then when you get to 20 samples and it averages 6, it means the average of the second 10 is 7.

    So in our figures, cumulative averages ...
    n=34 - 44.9%
    n=76 - 47.3%
    n=89 - 49.6%

    ....means the three group averages were....
    n=34 - 44.9%
    n=42 - 49.2%
    n=13 - ....wait for it... 63.0%

    The final 13 subjects bumped up the entire population (89) average more than 2%, hence why the average of that cohort of 13 must be so much higher. I wonder what they did in that last cohort, and if it can be replicated in trials going forwards!




    REF: https://www.simplypsychology.org/effect-size.html#:~:text=Cohen%20suggested%20that%20d%20%3D%200.2,if%20it%20is%20statistically%20significant.
 
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