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>>> Examine the K-M curves for Satraplatin (a chemotherapy) in the pivotal SPARC trial and you’ll see that they separate late <<<
PFS is not "survival". It remains to be seen if PFS correlates with survival or any other clinical benefit with regards to satraplatin. Nevertheless , it will be approved on the basis of a surrogate primary endpoint producing soothing stats , notwithstanding that the trial was effectively an unblinded one , unless satraplatin is so devoid of any characteristic SEs or clinical signs as to be undetectable , in which case the tumor wouldn't notice it either. Remember , it's chemo , or at least it's supposed to be.
That's true too , of course. Everyone wants survival curves that diverge from event #1 forward , but I wouldn't want a drug review method that routinely discards immunotherapy drug candidates because they produce late-separating curves.
Late-separating curves with immunotherapies may be partly a consequence of trials involving late-stage patients. Use in earlier-stage patients may generate the survival curves that everyone is more familiar with. Of course , you need that approval in the late-stage patients first , and you can't get it with those funny curves.
Catcha-22 ! Catcha-22!
Thanks , Clark. I guess this is the fundamental problem that needs to be resolved between the immunologists and the chemo crowd. If immunotherapies are going to get a fair shake , the statistical reviews are going to have to deal with the different survival kinetics. The patients who are still alive at 3 yrs. wouldn't be too concerned if they knew that the survival curves they contributed to just separated a month ago. ;)
>>> How much of the shortfall in log rank p-value and HR is attributable to smaller size? <<<
"Very little. Trial size was only a small contributor."
Clark ,
Can you elaborate on this some ?
Say a large trial achieved the same 3-yr. survival figures as 02A , 32% vs 21%. That's a 52% relative improvement in 3-yr. survival. Surely that would yield high statistical significance at some reasonable trial size , at least by landmark-type tests , no ? If so , and log-rank K-M would fail to yield a similar outcome , then there would seem to be some problem in Statisticsland.
My tendency is to look at the last standing data as being most predictive , and that's the 3-yr. survival rates. 01 and 02B numbers seem to reflect a range that's within the variation expected in small trials , and the integrated figure is what I'd place my bet around for the outcome of a large trial ( 33% vs. 15% , or a 120% relative improvement ). The K-M curve has to get to that 3-yr. point in some manner that makes sense in a larger trial , i.e. , the zigs and zags in the curves will smooth out , and the associated stats will have to make sense as well.
TIA for your comments.
>> i'm not condoning it. I think it is really stupid and puts investors and researchers in a bad place. <<
I'm glad to hear that , and my apologies for a hasty assumption to the contrary.
Your point about the availability of the abstracts to certain groups illustrates why these types of injustice persist. The only people who really suffer from them are the ones with little or no power to effect any change in policy.
While on the topic , here's another source of investment info that we should all have free , immediate access to : FDA Advisory Commitee meetings. Sure , we can pay some online company $150 to view it , or pay even more to travel to D.C. to attend in person , but as taxpayers shouldn't we be getting a free online view , in real time ? I'm sure there's an official excuse , like that PDUFA fees pay for the AC mtgs. , not taxpayers , but whatever the excuse is , it stinks. The main reason they won't do it is because they want to minimize public scrutiny of the inner workings of the FDA , for fear of arousing multiple " Provenge eruptions " .
>> these are not really restricted IMO. It's jsut the individual retail investor who doesn't have access. Almost everyone in the industry or working for an investment firm has access. <<
Jeez , I'm flabbergasted by that one.
Think back about why Reg FD was created in the first place. Investment firms were being fed material nonpublic information that allowed them to profit on trades at the expense of individual investors and others "out of the loop".
It's disconcerting to me when we're surrounded by corruption of all kinds in every walk of life , and seemingly intelligent people pass it off with a wave. The implied solution is : " If you can't beat 'em , join 'em. "
Thanks , but no thanks.
Re : ASCO Data Leaky
If the ASCO policy is not a violation of Reg FD , it should be.
Companies aren't supposed to be able to disclose material information selectively , in a way not accessible to the public. How do they get away with this ?
The Golden Rule rules again , I guess.
>> Perhaps, Pl1 hadn’t yet had a strong enough coffee to pick up on it. <<
Possibly , but there is another possible explanation : As mouton says , this is a tough crowd. One survival mechanism in such an arena is " Keep 'em guessing ".
I've been told that if you and your girlfriend find yourselves walking thru a bad neighborhood at night and notice a group of dangerous-looking thugs who appear to be swooping in for the kill , the best strategy is to immediately start screaming at your girlfriend , using the most vile language possible , while simultaneously pulling her hair and smacking her around. If you draw blood or knock out a tooth or two it's even better. The bad guys will see that you're a raving lunatic and go looking for easier targets. I've never tried this technique but I've had a couple girlfriends in the past when I wish I'd had the chance.
PL1 may just be shrewd enough to be using a variation of this method , IMO.
Re : Heavy multivitamin use, advanced prostate cancer linked
Linked as in associated , not as in causally.
This study is better than many that you see on diet and supplements in relation to disease , but it's not definitive by any means.
The problem that can confound a study like this is that patients may have better diagnostic tools than docs when it comes to detecting " something going on down there " in the period before a cancer would be detected using standard techniques. This group of patients would be the ones most likely to look for supplements that would address problems in that area. Zinc and selenium are two supplements suggested by the health food gurus as being beneficial for prostate health .
There was no association between the supplements and localized disease , so either the supplements facilitate development of more advanced disease , or the pre-diagnosis symptoms of more advanced disease prompts greater use of supplements.
The whole supplement and alternative medicine field is a jumble of conflicting ( and conflicted ) opinions , small and poorly-designed studies , and quality control issues with the supplements themselves.
About the only things I'm certain of are that pet food is bad and beer is good.
Either this makes no sense , ...
...or I'm having a stroke :
NEW YORK (Reuters Health) May 04 - Patients with gastroesophageal reflux disease (GERD) appear more likely to have Mycobacterium avian complex (MAC) lung disease than are those without MAC disease, according to an observational study by Australian investigators published in the April issue of Chest.
http://www.medscape.com/viewarticle/556091?src=mp
Actually , it makes sense , I just don't know if the observation merits publication or not.
>>> Improved Immune Function, Vision, Skin, Male Sexual Function, Well-Being & Energy are Strongest Claims <<<
It could have been worse. They could have said :
"Improved Immune Function, Vision, Skin, Male Sexual Function, Well-Being & Energy are Secondary Benefits"
The primary benefit being , of course , immortality.
Edit : BTW , where can I get some of that stuff ?
>> Were you the lone survey vote for Telaprevir? <<
No , I voted for Provenge. I don't recall all of the list , but I doubt if I would have ranked Telaprevir any higher than 4 or 5. Too much still in doubt there.
For me , Provenge has been the most fascinating biotech story in memory , though that may say more about my memory than anything else.
Provenge might not mean much from a " big picture " perspective , or it might be huge. If it turns out that Provenge is delayed for a few years but approved , and then subsequent fine-tuning and combos with other treatments result in dramatic advances in cancer therapy , this decision , in retrospect , will be earth-shaking , IMO. " FDA Roadblock Costs Lives ; Heads Roll ". If Provenge fails eventually , we'll wonder what all the fuss was about.
Even if Provenge is just one of many eventual therapeutic cancer vaccines , by being the first approved it would have represented a dramatic advance and would have given a big boost to the whole field. Since I believe biologics in general , and immune-based therapies in particular , are the only hopes for significant progress in tx. of advanced cancer , and since advances in this area will spill over into others , like autoimmune and infectious disease , any adverse effects of the FDA decision on funding in these areas could have profound consequences. Basically , I think Thornton had it exactly right. Time will tell , I suppose.
JMHO
>> What do you see as the pros and cons of the CTP approach relative to the PEGylation approach for producing next-generation versions of protein drugs? <<
I haven't really looked into it but maybe I will since it is an interesting question.
I know that some proteins don't seem to PEGylate well , for whatever reasons. If you assume that CTP proteins would be manufactured using some recombinant-based method , you have the advantage that you end up with a finished product , instead of one that needs to be PEGylated in a separate step.
The CTP approach might be useful for things like peptide- based protease inhibitors where half-life of the peptide is a limiting factor and where having a big PEG molecule flopping around might interfere with binding to the active site.
>> Modigene (MODG) and is focused on drugs using the Carboxyl Terminal Peptide, whatever that is. <<
It's kind of a funny name for the technology , since all proteins already have a carboxyl terminal peptide , so it makes you wonder why they need another.
The amino- and carboxyl- ends of peptides and proteins are analogous to the 3' and 5' ends of a DNA strand , for example-- just a notation that reflects the binary structure of the individual components of the strands that is maintained throughout the strand , so that there is always a defined " front end " and "back end ".
MODG has just found a particular CTP that confers stability to proteins , so they'll produce CTP-modified proteins as an alternative to , say , PEGylated proteins.
Beeg Pfahrma ?
bIG pHARMA ?
>> five companies with more than $2B in annual revenues from generic drugs , investors need a name to describe the major players in this arena. Does anyone have a suggestion? <<
-Big Pharmasortacals ?
-Big Pharmalmost ?
>> On the science/biostatistics side, do you know of any company that has been able to do an interim look without any p-value penalty? If GNVC were able to get the FDA to change the protocol to OS survival rather than 12-month survival, then how do you see this affecting the enrollment numbers and the timelines? <<
I think the first interim look by GNVC was near penalty-free , since I suspect they only allocated a tiny p-value , knowing there was no chance for statsig so soon. For any look where you hope to get trial-stopping results , the allocation will be meaningful and will reduce remaining alpha , though maybe not in a strictly additive way , as Clark points out. There's really no avoiding this , otherwise everyone would take interim looks all the time.
I think the chances of getting P=0.05 at 12 months are probably similar by chi-square analysis of proportions surviving or by a log-rank OS analysis thru 12 months. If not , I doubt the FDA would allow the choice between methods. I think FDA prefers log-rank OS because it's more robust and less susceptible to chance variations that might result in a false-positive. That's why I suggested that maybe GNVC would have some bargaining power by agreeing to switch to OS. Then , as I see it anyway , the critical thing is whether the survival advantage of TNFerade continues growing at times past 12 months. If it does , they might get to statsig much faster by being able to include data out to 18 months or beyond. It then just becomes a matter of how many events are necessary , and what alpha they choose for the interim look. I have no idea what those figures might be , but I'd guess they'd enroll at least half of the original 300 , and let the last ones simmer for a year or so before the next look , using a P~0.01 to 0.02. I think they'd continue to enroll until they see the results of the second look , just to be safe.
Maybe some of the stat gurus can run a few thousand simulations for us and give us a better estimate. I'd ask , but I've been hard on the statisticians lately. :)
Re : GNVC / Thornton
Blade ,
IMO , GNVC is fully behind Thornton on this. If not , I'd expect him to be fired immediately for being such a loose cannon.
My guess is that GNVC sees this course of action as a calculated risk , but one worth taking. I think Thornton / GNVC smells a rat or two at FDA , and wants them exterminated before TNFerade gets too far along. His article would be suicidal for GNVC , given their desire to amend the SAP to allow another interim look and the fact that the FDA is the only thing standing between them and multiple drug approvals over coming years. OK , not the only thing. The FDA and 100 or so million$ are the only things. Anyway , some people at FDA are undoubtedly pissed at him right now. My suspicion is that a whole lot more are cheering him on. As a one-time insider at FDA , he knows as well as anyone when things are out of whack there. He strikes me as analogous to the fired US attorneys , and I hope his article helps to stimulate the same level of scrutiny of the FDA's workings as we're seeing now re: DOJ.
OT : Thanks , Fred , I'll check it out.
>> Over a hundred years ago, Dr. William Coley at Memorial Hospital in New York City experimented with bacterial agents that appeared to have properties in stimulating immune responses against sarcoma, <<
I believe his preps were called " Coley's Toxins ". If they had known of the chemotherapies that would come into common use against cancer , I think they would have chosen the name " Coley's Non-toxins " , instead.
>> Do you know if 9902B's protocol zero's out the confounding effects of crossover? <<
I'm not a stats expert , though there are some on this board. My specialty is heaping criticism on statisticians. ;)
I don't know of anything defined in the 02B SPA that deals with the crossover problem. The problem is somewhat reduced due to the inferior activity of frozen prep , as has been mentioned , and also because tx. is delayed in crossovers , but it still exists , IMO. Some sort of fudge-factor should be applied to the results to moderate the detrimental effects of crossover but I'm sure that would upset the statistical purists .
OT : PGS
So you live in a van , down by the river ?
Cool !!
http://messages.finance.yahoo.com/Stocks_%28A_to_Z%29/Stocks_G/threadview?m=tm&bn=7976&tof=1...
http://tinyurl.com/ytt9wo
)
Enough evidence to make you feel guilty about withholding it from trial participants but not enough to make you feel guilty about withholding it from the general public ? If there is a logic in that , it's twisted beyond recognition to me. People aren't forced into trials , they volunteer and give informed consent to the tx. they receive , or don't receive. The main point , however , is that the greatest good to society is done if efficacious drugs are recognized and brought to market quickly by use of non-crossover designs.
If a crossover design can be constructed with an accompanying SAP that will effectively "zero-out" the confounding effects of crossover , then I don't have a problem with it.
Re : GNVC
Wow ! Talk about biting the hand that might feed you one day. Mark Thornton in the WSJ today , speaking of the FDA Provenge and Junovan decisions , said :
"For now, however, one thing is clear: While our lawmakers obsess over FDA "safety reforms," no one is holding this government agency accountable for its complicity in stalling therapies for life-threatening diseases. "
http://www1.investorvillage.com/smbd.asp?mb=971&pt=msg&mn=112292
Bravo !!
EDIT
P.S. Thornton is a VP at GNVC , and is a former medical officer in the FDA Office of Oncology Products.
The crossover requirement for ethical concerns is a Catch-22 that only bureaucrats and Joseph Heller could love.
Any drug in a clinical trial to determine efficacy is , by definition , of unknown efficacy , therefore it's not unethical to withhold it from placebo arm patients. If you know it's efficacious , why are you running the trial ? If it's unethical to withhold from trial participants , how is it ethical to withhold it from everyone else ?
What IS unethical is to allow crossover designs to so confound results that a truly efficacious drug is never approved because of an inability to generate sufficiently soothing statistics. Not to mention that such trials must always be larger than they would be for a non-crossover design if they are to have any chance of succeeding , thus depleting the pool of needed trial enrollees for other potentially lifesaving drugs in development.
This from the same group of people who happily approve drugs based on surrogate endpoints ( soothing stats ! ) even when they have no freakin' idea whether the drug provides a true clinical benefit. They'll know whether it's truly beneficial only after running the post-approval P4 study , assuming the crossover design doesn't muck things up too much , of course.
Glycoproteins ?
Complex ones , that is. ;)
I assume it was because of a desire to maintain the blinded status of the trial as much as possible until all patients have reached 12 wks.
>> I believe you are omitting the fact that in the interim analysis the p value will be heavily influenced by the 180 or so patients who are much earlier in their course where the curve separation is much less. The time points of these alive patients would be censored but still contribute detrimentally I believe to the p value evaluation. <<
I did omit that from consideration because I assumed , probably incorrectly , that any such effect would be minimal after 180 deaths.
I agree that modeling can lead you astray when assumptions start to pile up. I would make the fewest and simplest assumptions -- that the population of 02B will look like 01/02A , that early vs. late enrollee relative health will not be a factor ( if it is , it would seem to be in favor of Provenge ) , and that the true HR is 1.5 , as by log-rank in the integrated set. I should have looked at the alternate Cox models , which I believe were in the AC docs , which could provide a sort of " average fudge-factor " that could be applied to the log-rank to arrive at an expected Cox result , though I don't recall if they looked at just 01 or both trials.
No worries , though. Clark will sort this all out for us soon. :)
Thanks to all for the input.
>> The p-values you cite for 9901 and 9902a are based on cherry-picked Cox analyses. <<
True. My intuitive analysis technique is not without flaws , I'll admit. Still , even just looking at the integrated log-rank P=.011 , obtained with fewer events , and assuming at least some plumping of the data by Cox analysis , it seems like a good bet.
Another consideration , I suppose , is whether one believes Provenge works. If Provenge works , then the extra events will be meaningful in increasing the odds of success at the interim look.
Re : GNVC
>> I think the PACT trial was looking for something like a 20-30% absolute improvement in survival, which is pretty much a doubling in pancreatic cancer. That type of hurdle is too optimistic, imo. <<
I don't think they ever explained in detail the powering assumptions they used , but they did mention at one point that they were using 30-40% 1-yr. survival as the assumption for SOC , which implies they powered assuming 50-60% survival in the tx. arm. Until this last call , I assumed that the primary endpoint was 1-yr. OS by K-M , so one thing is clear to me : Nothing about GNVC is clear to me.
I doubt that any significant alpha was spent on the first interim look. IMO , this was done mainly to provide data to flash around at meetings in the hopes of stimulating the interest of investors and enrollees. Now that they've seen the data , and combined with the slow enrollment so far , they're looking for a way to shorten the timeline to approval by a decade or so , if possible.
Reading between the lines , my sense is they're hoping to make a trade with the FDA. They'll switch the primary endpoint over to a log-rank OS analysis -- which the FDA presumably would prefer to the current chi-square analysis -- if the FDA agrees to allow another interim look using an alpha and number of events that GNVC has calculated will have a high probability of success.
Re : interim look odds , etc.
I'm interested in any and all comments on a couple of topics :
-- I'm curious about what seem to be conservative estimates that have been posted regarding probablility of success at the interim look. Just intuitively , and based on 01 and 02A Cox results , it looks to me like the odds would be pretty good. Since 01 gave a P=.002 with only about 90 events , 02A got p=.023 with about 70 events , and the integrated dataset yielded a P=.0006 with ~160 events , it seems like an interim look at ~180 events would have much better than 50% odds of hitting a P of .015. If interim alpha is even higher , the odds are just that much better.
-- Does anyone think pending PDUFA-related legislation may be influencing current FDA actions ? The bill that passed the Senate 93-1 showed a level of consensus and bipartisanship virtually unheard of during The Bush Error . I expect a similar bill will move pretty quickly thru the House , and we might have a new law signed by this fall. The new law will likely authorize the FDA to require rather than just request post-marketing studies and will also probably give them greater authority to rescind approvals , restrict usage , etc. Might this law be seen by regulators as a kind of security blanket , giving them the courage to venture into the realm of "conditional approvals" for oncology drugs like Provenge , like the brave ( and much , much smarter ) folks over at USDA did recently with the canine melanoma therapeutic vaccine ?
-- What are the chances that the talk of an additional trial being necessary are true , based on a desire by the FDA to see data relating to either (or both) of the following two issues ?
1) Provenge plus tax vs. tax , since tax is now part of SOC.
2) A trial that does not involve any frozen prep , since the frozen prep is neither the treatment under study nor is it a placebo. The confounding nature of crossover trials is bad enough without adding to the mess.
TIA.
re: GNVC
>> Can you (or anyone) explain to me what the "chi-square" stuff is all about? <<
"Or anyone" is a much better source , believe me. :)
I don't think you need to worry so much about the details of the statistical tests in this example , except to understand that the K-M analysis is likely to be "richer" in the information it provides and , if TNFerade truly is effective , would demonstrate statsig efficacy earlier in the trial than the 1-yr. " % survival " analysis. The current endpoint analysis would look at the proportion of patients in the tx. arm surviving at 1 yr. in comparison to control arm and do a statistical test to determine if significance achieves the specified p-value. A K-M analysis uses every event as a separate data point , each occurring at a distinct time , so it provides much more information as to survival benefit at different times after treatment , rather than only at a single time point. In this case , if the K-M analysis also included data collected after 1 yr , it could greatly benefit GNVC , since some of the patients enrolled to date have been in the trial beyond 18 months. In a slow-enrolling trial like this I think you can see why the K-M analysis of OS would likely yield a statsig result earlier.
I think your interpretation of the 75% CI figure was correct , and I also think it was pretty good but it's not the kind of number I'd bet the farm on. The 75 % CI equates to a p=0.25 for the interim K-M analysis of 51 pts. , of which I gather maybe ~ 20 or so had been in the trial for > 1 yr.
>> If present enrollment trends continue, the pancreatic trial will take another two years or more to fully enroll. <<
I'd be willing to bet that enrollment accelerates significantly over the next 6-9 months , because of the recently added EUS sites and also the boost that should follow the oral presentation at ASCO , as more oncologists --and patients-- become aware of the interim results.
Truthfully , though , I'm as frustrated by the timeline as much as you are. I always thought that GNVC was wise to keep TNFerade all to themselves , rather than partnering. Now I'm not so sure. The system seems to be heavily stacked in favor of those drugs with a Big Pharma logo. A UBS logo probably doesn't hurt , either. ;)
Re : GNVC
Bladerunner ,
After listening to the CC , I think it's clear that GNVC would like to have a 'do-over' on the trial. The glacially slow enrollment is the killer , so the primary endpoint they chose is working against them. The primary endpoint is survival at 1 yr. with analysis by chi-square , a "landmark" type of survival endpoint that I gather is relatively uncommon in oncology trials. A secondary endpoint is OS by K-M analysis. It's not clear to me if the K-M data is collected only up to 1 yr. , or whether data beyond 1 yr. is included.
If the survival curves continue to diverge beyond 1 yr. , then lots of post-1yr. data that could contribute towards a statsig determination of efficacy is being ignored using the current endpoint and analysis. Since they've already had one interim look , however , I have doubts that the FDA will allow wholesale changes to the SAP. My guess is that they'll get an extra interim look , with the associated alpha spend , and the second look won't be anytime soon. They've enrolled 85 pts. out of 330 planned to date and my guess is they would not take a second interim look ( based on the current endpoints/SAP ) before the halfway point , so it looks like we'll be watching the grass grow for a while.
Personally , I find it kind of relaxing.
;)
>> Why did the FDA not specify the efficacy data required ?<>
**If i recall correctly, some on the panel asked for a log rank analysis of 02B. Perhaps that is something that they will introduce to DNDN at the next meeting?**
That's one possibility , I suppose. Another is that they will retain the Cox analysis protocol for 02B , and also consider the data from 02A analysed using the same Cox covariates. In effect , this would be like adding alpha to 02B. If Cox is retained , and alpha is added ( and possibly redistributed between interim and final looks ) , probability of success at the interim look is high , IMO.
Re : DNDN
Nothing earth-shattering revealed on the DNDN call , but some tantalizing tidbits:
* The CMC concerns are not deal-breakers , nor will addressing them be rate limiting as to Provenge launch.
* Additional required efficacy data is the reason for delay . The CR letter was not specific about the nature of the data required , which I gather is somewhat unusual. DNDN will have formal mtgs. with FDA to get clarification. Informal talks have occurred , and it was hinted that the possibility exists for changes to the 02B interim look alpha-spend component ( so as to increase probability of success at the interim look , though at the expense of increased risk if the final look is required ).
* Both looks are event(death )-driven , and the interim look will have equal or greater numbers of events for analysis than did the final , integated analysis of 01/02A which had 160 events , thus the interim look of 02B has decent power , particularly if the alpha is boosted.
* 02B patient demographics and expected survivals is comparable to that of 01/02A integrated , based on a recent blinded analysis.
* Enough cash on hand to make it to the interim look , but not enough to proceed to launch if the interim look is good.
Question : Why did the FDA not specify the efficacy data required ? Might they be willing to allow lower standards than specified in the SPA because of the additional data provided by 02A ? Gold said 9901 data was in-hand when the SPA for 02B was formalized. Was 02A data also in hand ?
I don't think you throw 02A overboard just because it had a p=.33. It adds something to the pile of data. After all , a trial with a great p-value is nothing more than a disguised agglomeration of many smaller trials with lousy p-values.
Re : DNDN
IMO , we haven't seen the last of the DNDN fireworks.
>>> it's my opinion that Provenge would have been approved if 9902a had achieved a log-rank p-value of 0.10 and maybe even if it had achieved 0.15. <<<
Assuming , as you suggest , that the FDA only needed 02A to be supportive in order to grant Provenge full approval , and using the p-value of 0.1 as the requirement , doesn't this imply that 02B only needs to hit a p-value of 0.3 to bring the supportive data up to snuff ? ( .33 X .3 = 0.099 )
Using 0.15 as the cutoff for support , 02B would only need to hit p = .45 . ( .45 x .33 = .15 )
That was my understanding also , i.e. mutual non-exclusivity.
BTW , no criticism of your CC transcripts was intended , and I appreciate your efforts. My interpretation is strictly based on memory , and I couldn't even come close to quoting him exactly. It was just that when I looked at your transcript , I wondered how I came up with my interpretation. I had to fill in a lot of blank space , I guess. ;)
Re : DNDN
I just wish the FDA would provide some quantitative summary of the DNDN efficacy data package , as a basis for comparison to other BLAs and NDAs. Shouldn't they be able to look at any submission and come up with an all-encompassing , single numerical estimate of the probability of Type 1 error for efficacy ? If they can , what is that number for Provenge , so far , and what does it have to be post-02B analysis ?
I'm not sure that was the exact quote , but my interpretation of that discussion was that JP was saying that for polymerase / PI combo therapies , any approved polymerase inhib. will be combined with any approved PI , with not much chance that one particular combo would be dominant. Thus IDIX can do a combo study with the first PI that comes along , and the companies with PIs should look to IDIX first since they're furthest along with their polymerase (NM283).
JMO of what I think he meant. With JP , you get very little elaboration on most topics , and what little you get is sometimes indecipherable.