NorthWest Biotherapeutics Inc (NWBO)

[pgsd]

Linda Liau adds her comments re: [in addition to LP's comments, also below]

The is a Comment on the Food and Drug Administration (FDA) Other: Demonstrating Substantial Evidence of Effectiveness for Human Drug and Biological Products Guidance for Industry DRAFT GUIDANCE
For related information, Open Docket Folder

Comment
Chair of UCLA Department of Neurosurgery and inventor of personalized brain cancer vaccine DCVax-L, Dr. Linda Liau is one of the world's most forward-thinking brain surgeons. Having spent more than 25 years on GBM research, Dr. Liau developed the individualized treatment to work with a patient's unique immune system to detect and attack cancer cells that remain after tumor removal.

"One problem with finding GBM cure, according to Liau, the fact that the disease is so heterogeneous - that it presents differently from patient to patient - means that the standard clinical trial approach has so far been less than helpful when it comes to identifying a cure.

Liau thinks comparative analysis may be a good start, allowing physicians to treat patients individually, rather than by strict adherence to standard trial protocols.

I think people have to think about the patient when designing trials. Now, we design trials and end-points based on the way we design the mast studies. We have a treatment group and placebo group. At the end we see which group does better.

I don't think in patients you can do that. If I were a patient, I'd hop from one trial to another depending on what sounds promising or what's available at the time. A lot of patients do that, and then you really cannot necessarily control for that. Let's say someone took TOPA and then went on another trial. Was there any effect from the drug that they had before?

I think that's an issue in terms of when we design these trials, what should we have in mind? We have the patient more in mind. And I think, within the field of neurosurgery and neuroscience and not just brain cancer, a lot of people are advocating comparative analysis. Not necessary using randomized clinical trials as the gold standard but using real-world data.

How would you actually treat this patient? Not how would you treat this patient based on the protocol in the clinical trial. Because a lot of times, what we want to do is what's best for the patient. And sometimes, it's not necessarily congruent with the strict protocol procedures that you have to abide by to keep a patient on the clinical trial.

For instance, I must get a dozen or more emails or calls every week from random people about how they can get the dendritic cell vaccine, DCVax. And personally, I can'tone, I can't do that on a clinical trial. But even if it was FDA-approved, unless it's covered by insurance how do you pay for them?

So, how do we fix that problem? All of these trials fail because the treatments don't work, but I think a larger part is we're not designing the trials right. But part of it is that it's difficult to provide these trials if you truly want to do what's best for your patient.

"I must get a dozen or more emails or calls every week from random people about how they can get the dendritic cell vaccine, DCVax. And personally, I can'tone, I can't do that on a clinical trial. But even if it was FDA-approved, unless it's covered by insurance how do you pay for them? So, how do we fix that problem? All of these trials fail because the treatments don't work, but I think a larger part is we're not designing the trials right. But part of it is that it's difficult to provide these trials if you truly want to do what's best for your patient.

For instance, I'll just take what happened with the DCVax. You really want to get clean data. We've never allowed for patients to get the vaccine once they failed, because they will. You enrolled in the trial. You had a recurrence, and now you'll have to try something else.

I could tell you patients are fighting to get the vaccine. And even if you tell them, "Well, there's no proof that this works. This is the whole reason we have to do the trial. I can't tell you that there's any benefit." But I guess the counterargument that I hear quite often is, "well, the side-effects aren't bad." And they're not. So, it's like, "Well, if it's not going to hurt me why can't I have it? Why can't I try it?"

Because of that it's hard to prove something based on what the FDA requirements are without being a little cold-hearted and saying, "Well, no, you're not allowed to try that."

So, a part of it is having the FDA think a little bit differently about what constitutes approval. On the converse, like the Optune device, that Novocure device, is FDA-approved. But I must say a lot of patients are like, "Well, I don't really like it." And I think on the physician side, we just don't understand how it works and there are a lot of problems with the clinical trial design.

There was no true placebo arm, but they did design it in a way that met the FDA checkboxes. So, it was approved, but a lot of us don't really believe that it works. I think it's one of these things where if your ultimate goal is to cure GBM, it's hard to reconcile all these different factors; the regulatory factors, the financial factors, as well as the science and the biology of the tumor itself, which is very complex"

LP's comments:-

March 19, 2020

RE: Docket No. FDA-2019-D-4964: “Demonstrating Substantial Evidence of Effectiveness for Human Drug and Biological Products; Draft Guidance for Industry”

Filed electronically at http://www.regulations.gov


Dear Food and Drug Administration:

Northwest Biotherapeutics, Inc. (NW Bio) is submitting comments to the Food and Drug Administration (FDA or Agency) on the draft guidance entitled “Demonstrating Substantial Evidence of Effectiveness for Human Drug and Biological Products”.

NW Bio is a clinical-stage biotechnology company focused on developing personalized immune therapy treatments for cancer. We have developed a platform technology, DCVax®, which uses activated dendritic cells to mobilize a patient's own immune system to attack their cancer.

Our lead Phase III clinical trial is for newly-diagnosed Glioblastoma multiforme (GBM) brain cancer. We have also treated more than 20 diverse types of cancers, many of them orphan diseases, in our clinical trials and compassionate use cases.

We greatly applaud the Agency taking a more flexible and pragmatic approach to the requirements for demonstration of efficacy in clinical trials. This is essential both for patients and for the healthcare system. Many novel treatments fail to reach patients – not because of safety problems, but because they fail to satisfy rigid requirements for proof of efficacy. And the novel therapies that do make it through the gauntlet to meet these requirements end up being so expensive that the healthcare system cannot afford them for many patients.

The single biggest reason for skyrocketing drug prices is the skyrocketing development costs to being a drug through clinical trials…. and the single biggest driver of the development costs are rigid and restrictive rules on proof of efficacy.

Allowing efficacy to be assessed using external controls will be far more ethical and also far more feasible and affordable. Especially in diseases such as Glioblastoma, in which patient survival has not improved by more than a few months in the last 30 years, and in which the course of disease is strikingly consistent, it is really unethical to require a new cohort of patients to be assigned to placebos in every trial.

Allowing efficacy to be assessed using external controls will also alleviate major bottlenecks in the development of new medicines. Especially in areas of significant new drug development activity, such as immune therapies for cancer, it is very difficult for sponsors to enroll and retain patients in trials with placebo control arms.


There are two areas in which we believe the flexibility suggested in the Draft Guidance does not go far enough: areas relating to sub-groups and relating to p values.

In regard to sub-groups… when a trial fails to meet its endpoints with statistical significance in the overall ITT population, but does show meaningful benefits in a definable sub-group, we strongly urge that that drug be approved for that sub-group based on that trial, and that the sponsor not be required to start over and conduct another whole trial in just that sub-group population. Such approval should be allowed regardless of whether that sub-group was pre-specified or not.

We recognize that allowing such sub-group approval may not be considered ideal from a statistical perspective, but in the real world the patients who comprise that subgroup should not have to wait years while another trial is conducted (and potentially die in the meantime) – and the healthcare system simply cannot afford such an idealistic approach.

Instead of requiring another trial before approval of a new treatment in a sub-group, the Agency should require a post-marketing trial or registry to collect and submit additional data on efficacy. This post-marketing solution is especially appropriate when the trial endpoint was an important clinical benefit such as extended survival.

Sending a sponsor back to conduct another trial in just the sub-group population will add tens or hundreds of millions more in development costs, which will translate directly into a higher price for the drug after that additional trial, and the patent life will be running down during that additional trial, leaving a shorter time period within which the sponsor must recoup its costs and make its returns – a double whammy of increased development costs and shorter patent life which will result directly in skyrocketing drug prices.

Accordingly, we urge that the Agency add to the Draft Guidance express flexibility for product approvals for sub-groups in which there are meaningful clinical benefits, regardless of whether the sub-group was exactly pre-specified or not.

In regard to p value… professional statisticians and other professionals involved in data modeling and evaluation have been calling for years for the drug approval process to stop using a rigid cutoff
of p ≤ 0.05 for determination of statistical significance. A group of 800 such statisticians and professions published a paper making compelling case as to why such a rigid cutoff is inappropriate and fails to give an accurate picture of the real efficacy (or lack of efficacy) of a new
medicine. See, e.g., https://www.nature.com/articles/d41586-019-00857-
Other

It is not fair to patients for a potentially helpful new medicine to be blocked from approval by the rigid application of p value measures that even professional statisticians oppose. In addition – as with the rejection of sub-groups – the rigid application of p values to refuse product approvals is something that the healthcare system simply cannot afford. Each time a new medicine is rejected on this basis, it adds enormous development costs. It also prevents new competition by the new medicine. All of these factors are leading to the skyrocketing drug prices.


Accordingly, we urge that the Agency add to the Draft Guidance express flexibility in regard to p values, along the lines proposed by such a large number of professional statisticians.

Thank you for this opportunity to comment. Again, we greatly applaud the Agency’s Draft Guidance document and believe that the expanded flexibility it contemplates for use of external controls for demonstration of efficacy is very appropriate and much needed. We also believe the two additions we have urged above – relating to sub-groups and p values – are very appropriate and much needed as well.


Sincerely



Linda F. Powers
CEO, Northwest Biotherapeutics