Register for free to join our community of investors and share your ideas. You will also get access to streaming quotes, interactive charts, trades, portfolio, live options flow and more tools.
Register for free to join our community of investors and share your ideas. You will also get access to streaming quotes, interactive charts, trades, portfolio, live options flow and more tools.
What is of interest is the FACT THAT THEY ARENT PRESENTING.
Why would they present at every conference, and then all of a sudden, pull out of presenting in the fall, and not present at the SITC though they have presented every following year?
It means they are awaiting results of the trial paper. IMHO
NWBO @ SITC - Yes they are at the conference. They have 2 booths; 534 & 536 . As for presentations, it doesn't look like it. In my opinion this means that they are awaiting information from the data lock. If data lock has occurred, and the trial was being evaluated, and a paper being written, NWBO would NOT want to present anything mainly due to the fact that they wouldn't want to compromise the results of the trial, meaning they wouldn't want to provide any information that could be taken as a suggestion regarding the trial results. That could be a lawsuit just waiting to happen.
https://iplanprime.eventready.com/expomap/index.cfm?fuseaction=home.main&event_id=171
If NWBO has positive results, there maybe a strong case for accelerated approval, so 2 years to market seems overly conservative, particularly that they have Cognate's manufacturing capabilities in the US and several manufacturing capabilities in Europe. Moreover, stocks reflect future sentiment, and so with positive results, no matter if FDA approval has not happened, the price would skyrocket to the positive potential, and that would easily be over a $2 Billion market cap. I would suspect it would be ~$7 to $10 Billion if not more due to short volume. That gives a share price of $14 - $22 a share minimum (assuming 500 million shares outstanding, though its lower than this).
I disagree. It is less than 500 million, however, that would mean that all the warrants were executed, many of which are at $3 - $4 execution price which is more than $2. But let's just say its 500 million shares. Looking at KITE before it was no longer a stock, it jumped up to over $10 Billion market cap. And that was before P3 results. So if NWBO had positive P3 results, using $10 Billion market cap that jumps to $20 a share. However, with DCVax Direct's potential just from positive DCVax-L P3 results, could warrant a market cap of $50 Billion easily, pushing the price up to $100 a share or greater. So no, with positive P3 results, this stock will skyrocket!
Canis, are you illiterate? Can you not read what I wrote? I never once blamed BP for the mismanagement. All I stated was that with a lot of money, any stock can be manipulated, particularly one that has extremely "quiet" management. So no, I never stated BP was the result of mismanagement, or the decisions LP made. I do however, believe it is in BP's best interest that NWBO does not have positive P3 results. That I believe wholeheartedly, because if that is so, with Cognate's Manufacturing capabilities, NWBO could be a significant player in the immunotherapy industry, which is just starting its growth.
Not confusing if you read carefully. My point being:
If one billionaire can double the share price of a stock, from less than 0.50 a share, back above $1 a share, ON HIS OWN. What could a concerted effort achieve in influencing a small, risky, unknown and heavily criticized stock like NWBO that if P3 trial is positive, has the ability to become a major player in the immunotherapy industry. Simple as that.
These companies have the funding to:
Influence articles, blogs, pay shorts, influence investing firms to short the stock heavily, continued short pressure to devalue, and drop the stocks value.
No, because if DCVax-L works, then there will be too large a demand for the shares. My point was that if a billionaire alone can influence a stocks share price, then what could a concerted effort from some of the wealthiest companies in the world do to a possible threat.
WHY BIG PHARMA IS CONNECTED TO NWBO SHORTING (IMHO)
I wouldn't doubt it that there is a concerted effort with Big Pharma and connected, wealthy investors on the shorting of NWBO. Why would there still be shorts that come on these blogs/articles that are soooo fervently opposed to NWBO when it is 0.16 cents a share. There is not much to be made when shorting 0.16 cents, unless you are betting it all on failing. But then that is insanely risky.
It makes sense that Big Pharma or some wealthy investor/investment firm is utilizing large amounts to pressure NWBO to fail, and try and get them to either go bankrupt prior to P3 results.
Look at Pengrowth, PGH. This is a great example of how a company or wealthy investor can manipulate a stock. Schulich Seymour is one of the wealthiest Canadians (if not wealthiest), and he had taken a huge stake in PGH. SS bought in prior to it falling below $1. SS took a large stake in PGH. Well it recently cleaned up its books, and started looking much better financially, but it stayed around 0.50 cents a share. If it gets booted off the NYSE because it is less than $1 a share, well, that isn't good for SS.
So what did SS do? He bought a ton more of the stock, and it shot up to $1 a share in a couple days. PGH management stated they didn't know why it did that, and stated there was no insider information, etc.... And then a couple days later, SS provided in the SEC declarations that he had purchased even more shares on the open market, which ultimately drove the stock back up over a $1.
If one investor can do this, what could investors and Big Pharma do to a stock like NWBO? Just to put this into perspective; The Pharmaceutical Industry itself, commanded $1.05 trillion dollars of revenue in 2016.
The US pharmaceutical industry alone spent $460 Billion a year. The top 10 US Big Pharma companies have a total market cap of nearly $2 Trillion dollars.
AND the Immunotherapy Industry is slated to grow to $201 Billion by 2020, with it already at $108 Billion in 2016.
http://www.marketsandmarkets.com/Market-Reports/immunotherapy-drug-market-137717755.html?gclid=EAIaIQobChMIzLnm2eKb1wIVCpJ-Ch2qXAA3EAAYASAAEgJ_bfD_BwE
With a successful P3 trial, and in-house manufacturing capabilities, NWBO would be positioned to be self sustaining, not require any of Big Pharma's support, and could potentially go after a sizeable portion of that $201 Billion (particularly if DCVax Direct worked).
So you see, there are companies at the top that would very much not want NWBO to succeed, and they have a lot of money, a lot of power, and a lot of contacts.
The lease is not bad news, it is good news. It is space that they wouldn't be able to utilize no matter if they received positive news yesterday.
Gord Downie was truly a Canadian hero, his stage presence was legendary, and he was a revered by many in the industry. Though not well known in the US markets, he was renown in the music industry. Eddie Vedder praised Gord at a Pearl Jam concert the same night as the Hip's final concert in Kingston, and played a tribute Hip song.
Gord will be truly missed!
Why in 2014? I am assuming that back then they were expecting the trial to be completed in 2015/16. Nevertheless, they obviously were trying to position themselves to have the ability to move on manufacturing at some capacity once P3 results came in. And it looks from the PRNewswire (and other posts) that they still have the an area for a manufacturing facility, but obviously wouldn't have been ramped up large enough in the next 3 - 5 years to require use of a warehouse.
We know that this area in Cabridge is a biotechnical hub, and just like silicon valley, you get knowledge clusters like this all over the world, particularly so that they can attract and hire qualified individuals. So having a facility in this area was a smart strategic move, and one that shows that NWBO isn't interested in selling off their IP technology to the highest Big Pharma bidder, but rather interested in becoming one of the Big Pharma companies. Another reason that a lot of money would target a huge sell off of the stock the last couple years. If P3 results are positive, or even extremely positive, NWBO is positioned for huge gains, and couple easily become a multi-billion dollar revenue generating monster within 5 years!
We don't know how long they have been advertising this property. These types of leases don't happen within Months of listing. They usually take a year or two on average. Also, it looks like they were looking for a specific type of deal, a 3 - 5 year lease. I am thinking most industrial leases have a minimum of 10 years in them. They wanted a shorter one, which means they expect to utilize that area in the near future.
Lease is GOOD NEWS! Even with overwhelming positive results from the P3 trial, ramping up manufacturing from nothing would take at least 2 - 3 years, in terms of the development, scale up, standardization, certification, etc.... If anything, NWBO would scale up and rely on their current manufacturing capabilities; i.e. Cognate, King's College, & Fraunhofer for the next 2 - 3 years, to begin receiving revenue, while investing in the ramp up and development of their own facility. They would now have ~$1M a year revenue from the warehouse that would have sat vacant for 3 - 5 years no matter if P3 results were overwhelming positive and they received AA tomorrow.
DCVax-L OS is not a longer tail compared to Stupp, it's a fatter tail. Meaning more patients are living longer. And this is backed up in that WE KNOW THAT ~ 100 or 1/3 of the overall population was living at least 22 to 25 months, and again, doesn't include the information of the other 2/3, meaning > 35% of the trial's population was > ~24 months. Looking at Stupp's trial results, < 30% lived 24 months or longer.
Fatter tail, NOT LONGER!!
I read below an 8K except stating that 9 patients were reimbursed through the HE program, however, no new patients have been enrolled in it due to the screening halt and wait to complete the P3 results.
As this is a reimbursement program, it would make sense that since cash is already an issue for NWBO, even finding the cash for additional patients and then waiting for reimbursement (which may not even be the full reimbursement, we don't know), would be reason enough to wait for additional addition patients into that program.
Commercially available is much different than not approved.
Quiet periods include attending and presenting at conferences.....
That is interesting that NWBO didn't attend. Usually they attend these events even if there is no new information to provide. If anything, since this is a first, them all of a sudden pulling out and not attending, which tells me something could be on the horizon. Fingers crossed. Either good or bad news, let the wait be over!
Survivor1 - I would agree that looks plausible, however, I do think that this is assuming extremely high survival rates, so I feel like the 62 itself is a high number.
Sure I'll look at the updates on. I reposted as I wrote 2013 instead of 2014 for the example I was using.
Abeta - Your Calc is wrong - And I will explain why (repost).
Take for example 4th Quarter 2014. You state 20 patients enrolled during this quarter, and 6 or 30% are alive today and included in the 98.
However, that is 45 - 48 months from todays date. So what you are saying is that 30% of those treated in ~ Oct 2013 to Dec 2014 are all alive today.
Because the enrollments are staggered monthly, you must taken into account continual deaths.
Here is a good test; Like you identified from the Optune SOC results, ~ 5% of the cohort; 180 survived 30 months, or 900 days. SO 900 days from ~July 2017 would have been early 2015. Lets then tale (which isn't the case, but for simplicity) all patients enrolled and treated prior to last quarter of 2014. That is ~200 patients, and though it would be less (according to Optune's SOC data), lets say all 200 patients were treated in late 2014, that would mean that less than 5% would be alive for the summer of 2017. That is 10 patients, include the 6 from 2008/09 that we know are still alive, and that's 16 patients from 42014 4th quarter and before, however you are counting 65 alive in your chart.
Okay so lets look at the remaining 131 treated in 2015, using Optune's SOC % and splitting it into quarters as you did, we get:
1st Quarter 30 patients ~8% Alive 28 - 32 months = ~3(actually 2.4)
2nd Quarter 30 patients ~9% Alive 26 - 30 months = ~3 patients
3rd Quarter 32 patients ~15% Alive 22 - 26 months = ~5 patients
4th Quarter 19 patients ~19% Alive 18 - 20 months = ~4 patients
Which gives ~ 15 patients then add that to the 10 and you get 25 patients rather than over 100 patients.
Just a second comment, the Optune SOC numbers look really bleak, and most shorts have been argueing that DCVax-L' trial is showing HIGH SOC results and as such there isn't efficacy, however, if the SOC is actually like that of Optune's trial, then the efficacy will be huge.
Report TOS
Moderate
Abeta - Your Calc is wrong - And I will explain why.
Take for example 4th Quarter 2013. You state 20 patients enrolled during this quarter, and 6 or 30% are alive today and included in the 98.
However, that is 45 - 48 months from todays date. So what you are saying is that 30% of those treated in ~ Oct 2013 to Dec 2013 are all alive today.
Because the enrollments are staggered monthly, you must taken into account continual deaths.
Here is a good test; Like you identified from the Optune SOC results, ~ 5% of the cohort; 180 survived 30 months, or 900 days. SO 900 days from ~July 2017 would have been early 2015. Lets then tale (which isn't the case, but for simplicity) all patients enrolled and treated prior to last quarter of 2014. That is ~200 patients, and though it would be less (according to Optune's SOC data), lets say all 200 patients were treated in late 2014, that would mean that less than 5% would be alive for the summer of 2017. That is 10 patients, include the 6 from 2008/09 that we know are still alive, and that's 16 patients from 42014 4th quarter and before, however you are counting 65 alive in your chart.
Okay so lets look at the remaining 131 treated in 2015, using Optune's SOC % and splitting it into quarters as you did, we get:
1st Quarter 30 patients ~8% Alive 28 - 32 months = ~3(actually 2.4)
2nd Quarter 30 patients ~9% Alive 26 - 30 months = ~3 patients
3rd Quarter 32 patients ~15% Alive 22 - 26 months = ~5 patients
4th Quarter 19 patients ~19% Alive 18 - 20 months = ~4 patients
Which gives ~ 15 patients then add that to the 10 and you get 25 patients rather than over 100 patients.
Just a second comment, the Optune SOC numbers look really bleak, and most shorts have been argueing that DCVax-L' trial is showing HIGH SOC results and as such there isn't efficacy, however, if the SOC is actually like that of Optune's trial, then the efficacy will be huge.
Why PFS didn't fail;
Forget all the calculations, and statistical explanations. We know the enrollment schedule, we know when the last patient was enrolled (only 3 that month).
Statistics is all about probability. If you used the enrollment schedule, and used the percentages of patients that should be PFS free by Jan/Feb 2017, You would come up with significantly < 30 patients. The fact that there is 3 times that in itself shows efficacy.
Yes, the way it is worded is specifically correct, and as such, much more difficult for a non-statistician to understand. My explanation attempts were to state it in more layman terms so one can visualize how the data is effected when the trial is extended, and when data lock happens.
I assume that NWBO was leaning towards the fact that they are seeing the long fat tail with their longest survivors, therefore it was a smart move because the difference they have to prove is 2 month less, and as much as it is more difficult to show a lower p value, when you drop the median difference, there is only two values that are important. Median of control and median of vaccinated group. If they are at least 6 months difference it doesn't matter how long you wait, the endpoint fail, but if the median difference is met, because it's only 4 month, then at least you can wait longer and rely on the fat tail to push the p value down.
EXWANNABE - The larger and longer the at-risk group, the larger the variance, and if this is different from the control group, it effects the p-value.
You are arguing semantics, terminology. Sometimes one must explain in layman terms so others understand. It doesn't mean it is wrong.
exwannabe states " I understand what you are asserting quite well, and it is still wrong.
The calculations depend on % of events out of at-risk in the intervals. The censors count by being in the at-risk pool.
The censors are not "removed" (as LS thinks) nor are they assigned an event date (as you assert). They never event, but effect the event rate by being part of the "at risk". "
You state censors are not assigned an event date, however, A VALUE IS ASSIGNED TO THE RIGHT CENSORED PATIENTS WHEN CALCULATING THE STANDARD DEVIATION!!!
SO YOU ARE WRONG!
This is my last post argueing this. At data lock, the right censored patients will need some "event value" that will be used to determine the variance of each group (control & vaccinated).
So come datalock (and hence why they call it data lock; because the value of right censored patients are locked in at a specific value), an event value will/must be associated with the patients still alive, or those that have not seen tumor progression.
NOW, THE LONGER YOU WAIT< THE LONGER THESE RIGHT CENSORED EVENTS MAY GET, THE LARGER AND POSSIBLE GREATER THE STANDARD DEVIATION OF THE VACINATED GROUP.
Okay, I am done trying to explain this to you.
My opinion of this is NOT that the trial is continuing beyond 233 events, but rather LS stating that NWBO elected to let it continue from 249 PFS events to 233 OS events.
What I want to know is what did Marnix mean regarding the Publication being worked on over the summer. The slide from last week showed:
"Publication drafted over summer with input from investigators now being finalized."
YES BUT TRIALS DO NOT GET THEIR STATISTICAL SIGNIFICANCE FROM KM CURVES!! KM curves are used as a visual for the trial results.
AGAIN, the P-VALUE IS CALCULATED USING STANDARD DEVIATION OF BOTH GROUPS! And the longer the tail in the vaccinated group, the more it affects the standard deviation, the more it affects the confidence, and the p-value.
Argh! I feel like I am banging my head on cement trying to explain this to you!!
I am not sure where people or LS is getting that the trial has been continued on past the 233 events. Unless someone has a link to that. Also, not sure how one would know that the second 50% of the patients were less healthy.
The reason for keeping the trial as long as possible is that it provides longer results for the right censored patients, no matter if they are in the first or second 50%.
But there has to be a point where you need to do data lock and just crunch the numbers.
Sorry, 4 month difference for PFS, and 2 months difference for OS. Yes, and the reason that they were able to drop the difference from 6 month to 4 month was that they tightened the confidence by lowering the p-value to 0.02 instead of 0.05.
This was actually a smart move, because if the PFS difference came in at 5.4 months (< 6 months), and still had a low p value, the primary endpoint would have failed, BUT, the fact that it showed a 5 month increase on PFS would have still been huge. So instead, the lowered the difference to only 4 months, and made it require more confidence. That is also why they probably extended the data lock to 233 events, because the longer the vaccinated tail, the more likely the p-value will be lower.
I crunched similar data on an article of Seeking Alpha called Statistically Satisfying. I even used ICT107 data as well.
It matters in terms of calculating the statistical significance. The longer the PFS of the second 50%, the stronger the probability that there is an improvement or difference.
There is two things that need to be met, one, the median PFS difference has to be > 2 month. And the standard deviation of both groups need to be different enough to prove statistical significance which means the last 50% can effect the standard deviation. So yes, the second 50% can be very influential on the p value.
ExWannabe; first rule of statistics; THE PVALUE IS CALCULATED USING THE STANDARD DEVIATION WHICH REQUIRES EVENTS!!!!!!
I remember when everyone said Lululemon was a fad, and that no one should invest in the company, when it fell from $30 a share down to $4 a share. I was adamant that it would not falter, and that is the same I feel about the data we have seen so far with NWBO. With 25% and more showing PFS results greater than 15 months, there will be positive results!!!!!
exwannabe - "You do not understand statistics".
I left the quote above for you to reference your rebuttal. I am still confounded as to what you are trying to state. If you understand how the p-value is calculated, please do enlighten me, and tell me just how the two populations are compared without providing some type of event for those still alive.
Would love to hear how such a calculation takes place.
It states "Publication drafted over summer with input from investigators now being finalized". Not sure if they are crunching the data that I was doing on the overall blinded data to show overall results are high, or that the actual data lock has occurued and they are unblinding the data and crunching those numbers.
Not sure if you understood my comment. A right censored patient is one still living when data lock occurs. That means their "event" hasnt happened. So unless that patient is not included in the evaluation, some event value must be used or it can not be used in the calculation. If you use Logrank Wilcoxon rank, or whatever the method. And yes, I stated logrank is what is usually used. So no, I am not incorrect.
Explaining KM curves, p-value & stat analysis; Lets start with the KM curves.
KM Curves
The KM curve is significant to survival trials because it deals with censored patients. I think that many get "censored patients" mixed up as the ones lost to follow up, while it includes more than just those, specially (and most importantly) right censored patients. These are the patients that are still living after data lock, so there should be ~ 98 or so for this trial.
Here is a good explanation:
"Censoring means the total survival time for that subject cannot be accurately determined. This can happen when something negative for the study occurs, such as the subject drops out, is lost to follow-up, or required data is not available or, conversely, something good happens, such as the study ends before the subject had the event of interest occur, i.e., they survived at least until the end of the study, but there is no knowledge of what happened thereafter.
The KM curve provides ticks on the graph, and or does not finish the curve at the tail end for those still surviving. The KM curve is a graphical representation of the data, and not specifically part of the p-value calculation (statistical significance).
p-value
The p-value is calculated by doing a hypothesis analysis comparing the two populations. What you are essentially doing is taking each groups data/events, calculating the median, variance, and all the data points of each group and comparing them to see what the probability is that they are the same population. There are specific comparison techniques used for this in clinical studies, such as the Cox proportion hazard or logrank test (which is similar to the Wilcoxon Rank test I used on DCVax-L P2 data in my first article over 4 years ago).
From these tests a p-value is calculated, and gives the probability that these two groups are the same (no change), hence a low p-value is equated to success (p = 0.02 or 2% chance).
I believe that the right censored patients (those still living) are analyzed using their data lock date as their event, as one can not (and should not) extrapolate their "assumed" value.
Therefore, as I mentioned in my last post, but explained it in much more detail here, if there are numerous survivors (a fat, long tail), then (especially if the majority of them are from the vaccinated group), it actually benefits/strengthens the statistical significance (by lowering the p-value) the longer the trial goes, which means the longer the survival event time is defined for the right censored patients.
i.e. If data lock occurred at 248 events in Feb 2017, then there would have been ~> 100 right censored patients that were given OS events as if they died in Feb 2017. However, with the push for 233 OS events, and assuming datalock happened this month, 98 of those patients just added 6 months to their OS event when the p-value will be calculated.
So in reality that is huge, especially if more than 2/3 of those 98 were vaccinated, because that would add more weight to the two groups being different. That means that instead of those 98 having an OS range between ~16 - 36 months, those 98 patients will have an OS range between 22 - 42 months at minimum.
In actuality, as more patients move significantly to the right (eg. 4-5 years OS), the more that they influence the p-value (baring that the control group doesn't show similar long living OS surivors). So if these 6 months were added to patients already at 4 - 5 years, and boosts them to 5 - 6 years, then that will affect the p-value significantly more if the control group isn't showing that same length of OS.