Friday, July 20, 2018

Dr. Faustman Publishes Follow On BCG Data From Phase-I Trial

Dr. Faustman published a paper [r2] and a poster [r1] that contained results from an extension to her Phase-I trial [r17].  These results have generated a lot of buzz, and the study was complex, so this is going to be a long post with four sections:  First, a quick summary.  Second, a more detailed discussion of her results.  Third, a discussion of the buzz surrounding those results.  And fourth, a discussion of where her research goes from here.  The [dN] marks mean that there is more discussion about this point at the end of the blog post, and the [rN] marks are references which are also at the end of the posting.

I've written a total of 18 blog entries on this line of research over the last 10+ years, and you can read them all here:

The short history is this: Dr. Faustman is trying to cure type-1 diabetes by using BCG, a widely used tuberculosis vaccine.  Dr. Faustman published phase-I clinical trial data in 2012, and is now publishing data from an extension to that trial. 

Quick Summary of Results and Importance

All of these points are discussed in a lot more detail below, especially including the data they are based on, and how I got from the data to these summary points:
  1. C-peptide is the FDA, researcher, and industry standard for evaluating cures for type-1 diabetes, and the C-peptide data reported here shows the BCG did not cause a rise in C-peptide levels.  These results mean that this extended phase-I trial has worse results/is farther away from a cure, than the initial phase-I study reported years ago.   The first phase-I showed tiny increases in C-peptide, but here, no clinically significant increases are seen.
  2. A1c data is generally used to evaluate treatments for type-1 (not cures).  The A1c data is the best data reported here (an improvement of about 0.8), and is similar to several other treatments already available or in later phases of clinical trials.  All the data presented here is based on a very small number of people who actually got BCG (3 people in some cases 12 in others).  Furthermore, it is inconsistent.  At some points in time the BCG group did worse than the control groups, while at other times they did better. 
  3. Dr. Faustman had a theory as to why BCG could cure type-1 diabetes.  The paper is clear that the A1c results seen here are not caused by this theory.  The paper presents a new theory to explain the cause of these results.  
  4. There is a phase-II trial underway (with results expected in 2023), so we will have more data then.
  5. And finally, the primary end point for the phase-I trial was autoreactive t-cells, and this extension to the phase-I trial did not include data on autoreactive t-cells, which means the clinical trial was unsuccessful.
Results and Discussion

As with all science, the important information is the results of the study, so let's take a look at the data presented (and the data that was not presented):

A1c Data
Graph is from Dr. Faustman's paper, and is presented
 for educational purposes only.

The best data in the paper was A1c data.  The graph at the right (taken from the paper) shows the A1c numbers for the people treated with BCG (in red) vs. two types of control groups (in black). [r2]

You can see that the people treated with BCG had worse A1c numbers for the first two years after the treatment.  They then improved noticeably for the next two years, and then gradually increased for the next four years.  Overall the patients had worse A1c numbers for the first two years, and better for the next six years.

Importance of the A1c Data

For me, this data does not support the idea that BCG is a cure for type-1 diabetes.  It doesn't even support the idea that BCG is a treatment for type-1 diabetes.

First and most importantly, A1c data is typically used to measure treatments not cures [d1].  This is for a very good reason: many things, unrelated to a cure, impact A1c numbers.  Being more aggressive about insulin dosing,  going on a low carb diet, using a CGM, or taking an SGLT or GLP-1 drug can all impact A1c numbers as seen here [d2], but none of them are a path to a cure.

On the other hand, the only thing that impacts C-peptide numbers is the body generating its own insulin [d3].  That is why researchers commonly use (and the FDA expects) C-peptide as the end point for clinical trials aimed at curing type-1 diabetes [d5].   Generating your own insulin and maintaining that production is what cures type-1 diabetes, and it is exactly what C-peptides measure.  This is an important point and discussed in detail in [r9] (the conclusions of the D-Cure workshop).

Second, the data above in inconsistent: worse for two years and better for six.  If you are going to argue that the good numbers (3-5 years out) are really caused by BCG, then you have to assume that the bad numbers (0-2 years out) are also caused by the BCG.  After all those numbers are closer to the BCG dose.  It seems much more reasonable to me to assume that neither the bad numbers nor the good numbers had much to do with the BCG dose.

Third, existing treatments have already shown better and more consistent improvements in A1c than are seen here.  These are described in more detail in [d2] and [r11-13].  If I wanted to get excited about new treatments for type-1 diabetes, BCG would get in line with the many treatments which have stronger evidence in larger clinical trials [d10].

Fourth, the eight year data is based on 3 people, and the five year data on 12 people, and there are two problems with these numbers.  The big, obvious problem is that they are tiny, especially the 8 year data [d6]. The second issue is that more people were added after the end of the phase-I trial.  This is unusual.  Normally an "extension" or a "follow on" trial simply follows the same group of people (or a subset) for a longer period of time.  It's quite unusual to see new patients added after the end of the trial as described by the clinical trial registry.   

The A1c results also have a serious problem with "results switching" described [d7] and [r16].

As a side note, even as a measure of treatment success, A1c is falling out of favor as compared to "time spent in range" and quality of life measures as proposed by the "Beyond A1c" movement:

C-Peptide Data

As stated previously, C-peptide numbers are the best measure of progress towards a cure [d4], so these are the numbers we should pay the most attention to.  Here are a few quotes from the paper: 
"The BCG-treated type 1 diabetic subjects at year 4 after glucagon challenge had a negligible to no return of clinically significant C-peptide. "
"The human pancreas after BCG even at four years after repeat vaccinations did not secrete significant insulin as clinically measured by C-peptide."
"Therefore we concluded that BCG vaccinations did not induce a clinically meaningful return of C-peptide levels in the pancreas by regeneration" [r2]
The paper reported that at 4 years (the point of highest A1c effect) the C-peptide numbers for the treated patients were "in the range of 2–3 pmol/L."  Table 1c in the paper included C-peptide numbers, but the numeric data was not included in the paper or the supplemental materials.  My eyeballing of the data is that the control group started off just below 2 pmol/L and the treated group started off just above 2 pmol/L.

Importance of the C-Peptide Data

In terms of measuring progress towards a cure, C-peptide data is the most important data.  When the FDA, EMA, or other researchers evaluate this study, it is the key data they will look at [d11].  It shows no progress towards a cure.  That is bad news for BCG-as-a-cure research.

Several Additional Metabolites

In addition to A1c and C-Peptide data, the paper also reported on a variety of metabolites.  These are various chemical markers of what is happening inside the body.  The purpose of these measurements is to try to figure out what was causing the changes to A1c seen in the study.  If you care about these details, then I urge you to read the paper [r2].

The statistically significant differences between people with type-1 who were given and not given BCG are summarized as follows:
In the purine pathway, adenine, N6-carbamoylthreonyladenosine, 7-methylguanine and N2,N2-dimethylguanosine all statistically showed significant increases in BCG-treated T1Ds compared to untreated T1Ds [r2]
Autoreactive T-Cell Data

This study reports on an extension to the phase-I trial, but it does not report on the primary outcome of that study (autoreactive t-cells) [r6].  In the world of clinical trials, this means this extension to the phase-I trial was unsuccessful.

A clinical trial is considered successful if there are good, statistically significant results for the primary outcome, using standard data analysis.  You can read a lot more about this definition here:
The key point is that not reporting on a primary end point, means the trial has failed.

The autoreactive t-cells results were involved in the "results switching" described [d7] and [r16].

The Change of Theory

Until this publication, Dr. Faustman believed that BCG worked by causing the body to generate more TNF, and this TNF caused the body to generate fewer autoreactive T-cells [r17].  Fewer of these bad T-cells resulted in a cure [d9].  She has published a few papers and edited a book on this theory [r10].

However, in this paper she makes it clear that this theory is not causing the A1c changes.  To quote her paper:
"The mechanism for lowered HbA1c values was not equivalent to the NOD [non-obese diabetic] mouse pancreas regeneration after BCG treatment" [r2]
And the paper describes a replacement theory:
"[BCG causes] a cellular switch from primarily oxidative phosphorylation, a low glucose utilization state, to augmented early aerobic glycolysis, a high glucose utilization state associated with high purine metabolism" [r2]
BCG lowers A1c by changing the way the body uses glucose, so that it burns more, which lowers blood glucose levels and therefore A1c numbers.  The new theory and the old theory are completely different.  Among other things, the old theory was based on immunology, while the new theory is based on glucose metabolism.  The new theory could replace the old theory, or both could be happening in parallel.

The Importance of The Change In Theory

Initially, I didn't think this change mattered much.  I'm much more focused on the question of effectiveness than mechanism.   (Put another way: I want a cure for my daughter, and I don't care exactly why it works, so long as it does work.)  But then I realized the implications of this change in theory.

BCG has finished a phase-I clinical trial.  At this point, most drugs would have two reasons to think they might be successful: the results of their phase-I trial and the results of the previous animal experiments.   That means that even if the phase-I trial was unsuccessful, the researcher could still rely on the animal trials for motivation, and try another human trial to capitalize on whatever good results were seen in the animal studies.   This is particularly important for BCG because the phase-I trial did not lead to successful C-peptide numbers.

However, Dr. Faustman is now saying that the TNF theory did cause the good results in mice, but is not causing the good results in people.  So therefore, it is hard to go back to her animal research to get support for her current human research.  And the human research itself is not yielding good results [r21].

Why The Hype?

A big part of the reason this study is important, is because of the buzz it has generated.  Therefore, understanding where that buzz comes from is important.  In my opinion, the results from the paper don't merit much excitement.  The hype comes from the news coverage of the press release, and I think it is always a mistake to react to hype in press releases when the underlying paper does not generate the same level of excitement.  This is a general problem in medical research and I'd recommend reading the articles listed here [r14].  Those articles cover the problem from several different points of view.

 The press release starts out with this sentence:
"Long-term follow-up of participants in clinical trials of a generic vaccine to reverse advanced type 1 diabetes finds significant clinical benefits, including restoration of near-normal blood sugar levels." [r3]
Consider the word "reversal", which is often interpreted to mean "cure".  (Compare "drug X reverses disease Y to "drug X cures disease Y".  Same meaning.)  Reversal is also in that first sentence to refer to results in people.   However, in the body of the paper, different forms of reversal are used 5 times (3 times for mice, 1 time to say the results did not include reversal, and 1 time for speculation about reversal).  Never in the paper was the word "reversal" used to describe the results in people, yet it was used in exactly that way in the first sentence of the press release.

Also, the press release uses the term "near-normal blood sugar levels" repeatedly.  Many newspapers interpreted this to be near-cure, and wrote their headlines accordingly.  But let me ask you a simple question:  If someone has type-1 diabetes and uses a lot of technology and generally works hard at treating their type-1, and has an A1c in the mid or low 6s, would you describe that as "near-normal blood sugar levels"?  Maybe.  But that says nothing about if they are close to a cure for type-1 diabetes.  Saying "near-normal" generates a lot of hype, but a cure is based on not needing to constantly treat your type-1 diabetes.  And the study is clear:  No one treated their type-1 diabetes any less because of the BCG: not fewer blood checks, not less insulin.  Everyone continued their standard care: dosing for what they ate, counting carbs, and anything else that we would associate with type-1 diabetes [d8].

The subtitle of the press release is:
"Mass. General study finds novel mechanism underlying stable, durable blood sugar control" [r3]
Now take a look at the previous graph of A1c numbers.  Does that look stable to you?  Does it look durable?  Not to me.  Quite the opposite, the good results are completely dependent on when you look at the data.  Two years after treatment the numbers are bad.  Between four and six years they are good.  At the end of the study, they are heading back towards where they started.  This is neither stable or durable.

The press release gives specific A1c data for 3 years and 4 years, and the average for the four year period from 3-7 years.  The 4 year numbers are the best found in the study, the 3 year second best, and the 3-7 year time frame the "good years" of the study.  However, the 1st and 2nd years (when results are bad) are not mentioned, and the average presented in the press release specifically excludes those years. It's like calculating a child's GPA but excluding their worst grades.  Of course it looks good, but it doesn't represent their real level of accomplishment.

Where BCG Research Goes From Here

One answer to this question is simple: a phase-II study is already underway, so we just wait until 2023 for those results to be published.  For BCG to be successful as a cure, it needs a specific kind of good news from the phase-II study: C-peptide data which is both statistically significant and clinically significant, and which comes from a large group of people with a good control group.  As a treatment (something taken in addition to insulin) then A1c data is enough.  It would still need to be statistically significant and clinically significant, and come from a large group of people with a good control group.  But all of that is possible from the phase-II trial.

Another answer is this: At this point, both publications from the phase-I trial were unsuccessful.  While an unsuccessful phase-I trial usually ends the line of research, this is not always true.  My guess is that about 20% of the current current phase-II trials are occurring after an unsuccessful phase-I result.  So there is always some hope.

But the real question is, how optimistic should we be about this line of research?  In my opinion, not very optimistic.  Above, I've described why the C-peptide and A1c data in this specific paper don't give me much hope for success in the future.  However, when I look at the (roughly) 15 year history of BCG trials in people, and put this paper into the context of the previous BCG research, I see a couple of additional red flags:

First is the lack of forward progress, given 15+ years / 34 million dollars [r20].  Fifteen years is enough time to get from the start of a phase-I to end of phase-III trials, and $34 million is more money than most academic researchers can spend on one line of research.  But for all that, I don't see any forward progress.  In 2003, we had no data on BCG's curative effect on people.  Now, we still don't have any positive C-peptide data to answer that question.  The hope is that the phase-II trial will answer it in 2023 or so.

Second, is the changing target of the research.  Successful research tends to have one target ("primary end point"), and gathers more evidence and stronger evidence on that target over time.  That is the progress that researchers expect.  However this line of research has changed its target repeatedly.  When the phase-I study started, the primary end point was autoreactive t-cells [r6].  When the phase-I study ended, the headline data was C-peptides [r17], and now this extension headlines A1c data [r2].

Even worse, this paper conflicts with the previous paper, even though they are both based on data from the phase-I trial. The initial phase-I paper showed: small, good results for C-peptide, no good results for A1c data, and support for the TNF hypothesis.  This paper shows no good results for C-peptide, mild, good results for A1c data, and support for a sugar metabolism hypothesis, but not a TNF hypothesis.  Good science builds on itself: the first results might be small, but the next results are stronger.  But here, the next results are not bigger, they are different.  That is not the normal course of scientific progress.

Personal Note

Many people, with wildly different viewpoints, reviewed this blog posting.  I want to thank everyone who spent time on it.  It needed a lot of work, and benefited from every reviewer's feedback.   All mistakes are my own.

Extra Discussion [d-Numbered] Footnotes

[d1] Consider a simple example: injecting insulin.  If you inject more insulin your A1c will go down, but your C-peptide numbers will not change.  A researcher who is treating A1c as progress toward a cure will see injecting more insulin as progress towards a cure.  That is why researchers measure C-peptide to evaluate progress to a cure.

Or consider this: "in the 1990s, the FDA began to approve drugs for the treatment of diabetes based upon hemoglobin A1c (HbA1c) as the outcome. The prevailing belief was that risk reduction could be achieved by a clinical focus on reaching target values of HbA1c" [r18]

[d2]  For instance this slide [r20] presents data from four different groups treated with different type-2 diabetes medicines (two medicines at two doses).  All four of these groups dropped the same or more as is seen here.  And [r21] shows that simply using CGMs can lower A1c numbers in pregnant women about the same as seen here.  And [r22] shows that a new class of drugs (approved in type-2s and being tested in type-1s) called SGLTs lower A1cs about as much as seen here.  And the list goes on.

The bottom line is that the average improvements seen in this study are similar to the average improvements seen in many other treatments, which are much closer to FDA approval (or already have EMA approval) for type-1 diabetes. 

When we look at A1c for people who got BCG over the life of the study, it averages about 6.6 which is about 0.8 below the 7.4 where it started.  (The result is a little worse (about 0.5) if we compare it to the control group, which started at about 7.1).

For comparison, all of these treatments have gotten results similar to the 0.8 improvement seen here in either type-1 diabetes, type-2 diabetes, or both:
    Semaglutide: A1c improvement of 1.5 [r20]
    Delaglutide: A1c improvement of 1.2 [r20]
    CGM use during pregnacy: A1c improvement of 0.6 [r21]
    SGLT2 inhibitors: A1c improvements of 0.5 to 0.8 [r22]

[d3] As an example, When was the last time your doctor said "If you do X, Y, or Z you will have better A1c numbers next time?  We get it all the time.  But when was the last time your doctor said "If you do X, Y, or Z your c-peptide number will be better"?  Never.  This shows both that A1c is a measure of treatment, and why it is not a good measure of a cure.

[d4]  For example the following quote is from the D-Cure workshop of international experts held in Barcelona in April 2007 [r9]:
"It is now an accepted approach to evaluate endogenous insulin secretion by measuring C-peptide levels (with highly sensitive and normalized measurement methods) in response to a physiologic stimulus (liquid mixed-meal) under standardized conditions."
This report goes on to specifically to consider and reject A1c as a measure of a cure:
"differences in HbA1c between treatment and placebo groups are minimal and thus cannot serve as robust measures of efficacy"
[d5] I reviewed all phase-III clinical trials aimed at curing type-1 diabetes in the last 15 years.  These are in the final stage of clinical trials, which lead (if successful) to FDA approval.  There have been 11 by my count, testing a total of 4 different treatments.   Of these, 6 used C-peptide as their sole primary outcome.  None used A1c alone as their sole primary outcome.  One used it as part of a dual primary outcome. Four used other measures as their primary outcome.

[d6]  It was not supposed to be that small.  The phase-I trial was supposed to have 12 treated people and 12 control [r6].  However, for reasons never published, the original trial only gave 3 people BCG.

[d7] Finally, these A1c results represent what is commonly called "results switching" in clinical trials, and this is very dangerous in reporting results.  Results switching is when the researcher says they are going to report one result (and designs the trial to do this), but then ends up reporting on a different result.  One of the reasons the FDA has a public clinical trial registry [r19] is specifically so that researchers need to publicly announce what their end points are ahead of time.  This prevents them from selecting end points to create success after the data is gathered.

Obviously, it is bad when secondary results are switched, and worse when a secondary result is used to replace an unsuccessful primary result.  However, in this study we see the worse form of "results switch" where an unsuccessful primary end point (autoreactive t-cells) is not reported, and replaced with a better, but still mediocre, result (A1c) which was previously not part of the study at all!

There are several articles on results swapping listed here [r16].

[d8] Compare Dr. Faustman's use of language in the press release with Dr. Bernstein's use of language.  Dr. Bernstein uses a low carb diet and aggressive insulin dosing to achieve A1c numbers lower than those reported in Dr. Faustman's research.  His target A1c is 4.5, much lower than Dr. Faustman achieved here.  However, Dr. Bernstein never refers to curing type-1 diabetes.  He is very clear that the low A1c numbers he aims for might be the same as someone without type-1 diabetes, but that is in no way a cure.

To put it bluntly: if you think Dr. Faustman's A1c numbers in the mid-6s represents a near cure, then you would have to agree that Dr. Bernstein's A1c numbers in the mid-4s would represent an actual cure, but no one does that.

[d9] The essence of Dr. Faustman's older theory on how to cure type-1 diabetes is:
  • BCG causes the body to generate TNF
  • TNF causes fewer autoreactive T-cells
  • Fewer autoreactive T-cells results in natural beta cell regrowth and more insulin generation
  • More insulin generation is the path to curing type-1
BCG (Bacillus Calmette–Guérin) is a biologic that has been given to over a billion people (in low dose) as a tuberculosis vaccine, and is also approved (in much higher doses) as a bladder cancer treatment. It is a generic drug with a very long record of safety.

TNF ("Tumor necrosis factor" or TNF-alpha) is a naturally occurring protein that can cause cells to die. It is involved in the natural regulation of immune cells.

"Autoreactive" refers to immune cells that mistakenly attack the body's own beta cells. The destruction of these beta cells leads to type-1 diabetes. This is sometimes referred to as an "autoimmune attack" because the body's own immune system attacks the body itself.

Many more details are available here [r10].

[d10] For A1c improvements, my standard (which I think is pretty common among both researchers and the FDA) is that changes below 0.5 are not of importance, changes above 1.0 are definitely important, and numbers between these are of mild importance.  So the BCG results (if supported by larger trials) would be in the mild interest area.

[d11]  Here are three supporting quotes:
Clinical studies aiming at preservation of beta cell function should be randomized, preferably double-blind and placebo-controlled and should include patients with a documented residual beta cell function. The primary outcome should preferably consist of co-primary endpoints including not only the change from baseline in C-peptide (e.g. C-peptide AUC) or, if appropriately justified, the percentage of patients with C-peptide increases above a clinically meaningful threshold following a physiological stimulus (e.g. liquid mixed meal) under standardized conditions but also HbA1c, frequency of hypoglycaemic episodes, particularly severe events, or the percentage of patients not requiring insulin therapy or with a relevant reduction in insulin requirements. Any of these endpoints not included as co-primary endpoint should be evaluated as important secondary endpoint. [r22]
FDA and EMA stand ready to approve disease modifying therapies for T1D. and have expressed reasonable expectations for demonstrating efficacy of therapies aimed at preserving insulin secretion in new onset patients. It is unclear what minimum treatment effect on preservation of C-peptide secretion, the regulatory primary efficacy endpoint, would be considered clinically meaningful for a new onset intervention. A small effect size (10-20% at two years) might be enough if the safety profile is very benign. [r23]
And finally, compare these two quotes from [r24]:
Efficacy endpoints. Stimulated C-peptide response is accepted as the regulatory primary endpoint because it is a direct measure of reducing the hormonal deficiency state of T1DM.
Secondary endpoints and their considerations. HbA1c is the gold standard measure of glycemic control, but it is an insensitive measure of improved beta cell function resulting from an intervention. 

Reference [r-Numbered] Footnotes

[r1] The Press Release:
and the Faustman lab FAQ is here:

[r2] The Paper:  and this includes supplementary data here:

[r3] Abstract of The Poster:
This tweet contains the poster and a little discussion:

[r4] Medical Press Coverage:

[r5] ADA/JDRF Response:
and coverage:

[r6] The FDA clinical trial record for the phase-I study:

[r7] The FDA clinical trial record for the phase-II study:

[r8] More than you ever wanted to know about how the FDA evaluates clinical trial end points:

[r9] This report summarizes the conclusions of the D-Cure workshop of international experts held in Barcelona in April 2007 and the current recommendations and updates in the field:

[r10] Dr. Faustman's most recent paper describing TNF as the mechanism of a cure was published in 2017:
And she had edited an entire book on the subject in 2014:
And she had several earlier publications on the same (now defunct) theory:



[r16] These are general references for results switching:
And this organization:
This abstract is an interesting read as well:

[r17] Initial results of the BCG phase-I clinical trial:

[r18] This paper argues that A1c is the right end point to measure treatments for type-2 diabetes:

[r19] This is a link to the US FDA's Clinical Trial Registry Site, plus an article about it:

[r20] Dr. Faustman's Lab has raised about $11 million for their phase-I trial and about $23 million for their phase-II trial:

[r21] The two key quotes from her paper are:
As previously published, the elevations in tumor necrosis factor (TNF) from the BCG vaccine stimulate cytotoxic T cell death and beneficial Treg expansion [in live mice and isolated human tissue]
and then:
The mechanism for lowered HbA1c values [in people] was not equivalent to the NOD diabetic mouse pancreas regeneration after BCG treatment



Joshua Levy 
publicjoshualevy at gmail dot com 
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Bigfoot Biomedical news, views, policies or opinions. In my day job, I work in software for Bigfoot Biomedical. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Friday, June 29, 2018

News from ADA 2018

The American Diabetes Association's Scientific Sessions for 2018 (called ADA2018 with hastag #2018ADA) just ended.  I was not there, but did monitor twitter and other social media to get a feel for what was going on.  As in previous years, it was about 90% type-2 and about 90% treatments (not cures), and of the remaining type-1/cure research, only a little was human trials of the type covered in this blog.

So anyway, here is a huge list of links (mostly links to tweets) which I found interesting for one reason or other.  I've tried to categorize them, and in a few cases, after the link, I've added a sentence or two about why I found them interesting.

Summary web sites:

Cure Related
Meta-Dopa, which I need to blog about:
Encapsulation for beta cells (animals, I think):

Smart Insulin:


Artificial Pancreas:
There were lots more, but these really called out to me.

General Interest:
Average A1c by age:
Vit D:
T2D delays T1D?
Mice vs. Humans:
Gut not important?
Patch Pump:
Half Units Matter:
Adjunct Therapy:
Bariatric Surgery T1D:
New Patch Pump:

Lots of comorbid conditions:

An attempt at a head-to-head comparison of islet transplants vs. Artificial Pancreas results.  Interesting!

The other form of bihormonal AP:
Most bihormonal AP research uses insulin and glucagon, but this one uses insulin and pramlintide.

Poster and Discussion:
ADA and JDCA joint letter (later supported by the Berrie Center):
These two guys (and many others) report dropping A1c, but no one calls them a cure:

Interesting to me:
Open Data Tools for Software Nerds:
I found the next tweet interesting because Cure was in title, but treatment in contents.  To me that shows a problem with "cure" research.  Much of it is not really aimed at a cure:

Low Carb:

Atkinson honored (nPOD and much more):

The "Most Obvious Research Conclusion Award"

Joshua Levy 
publicjoshualevy at gmail dot com 
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Bigfoot Biomedical news, views, policies or opinions. In my day job, I work in software for Bigfoot Biomedical. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Sunday, June 24, 2018

Alpha Difluoromethylornithine (DFMO) Starts A Phase-II? Trial in Honeymoon Type-1 Diabetics

This trial started recruiting in April 2015, but I missed it at that time, so I'm blogging about it now.

Alpha Difluoromethylornithine (DFMO) is approved for two quite different issues.  The first is to remove/prevent facial hair in women, while the second is to treat sleeping sickness.  Neither of these are related to type-1 diabetes.   However, this drug was effective in lowering diabetes rates in NOD mice (which are predisposed to an autoimmune diabetes, similar to human type-1 diabetes), and that is what motivated this trial.

The Trial

This trial is recruiting people 12-40 years old, who have been diagnosed with type-1 diabetes in the last 2-8 months.  People will be divided up into 4 different groups, each getting a different dose.  Within each dose group, there will be 6 people who get the treatment and 3 people who get a placebo (and will be a control group).

Primary endpoints are safety related, while other endpoints (such as C-peptide) are targeted at seeing if it works.

The researchers hope to finish gathering data in Dec 2019, so publication should be some time in 2020.  (Although the primary outcome data will be collected in Dec 2018, so there is the possibility of partial results in 2019.)

This trial is being run in three locations:

Riley Hospital for Children: Indianapolis, Indiana, United States, 46202
Contact: Stephanie Woerner, FNP    317-944-2573 

Women and Children's Hospital of Buffalo: Buffalo, New York, United States, 14222
Contact: Michelle Ecker, RD, CDN, CDE    716-878-7609 
Children's Hospital of Wisconsin: Wauwatosa, Wisconsin, United States, 53226
Contact: Joanna Kramer, CCRC    414-955-8486 


Although listed as a Phase-I trial, in some ways it is more like a phase-II study, which is why I've listed it as a Phase-II? study.  The question mark signifies that this drug has never been tested on people with type-1 diabetes before.  I consider it Phase-II because it is the right size (42 people) and the right purpose (testing multiple different doses) to be a Phase-II study.

Clinical Trial Record:
Results in mice:

Personal Note

I am always surprised how much researching type-1 diabetes teaches me about other subjects.  One part of the story of DFMO is both fascinating and horrifying.  After being developed in the 1990s, it was used intravenously as a treatment for sleeping sickness.  However, in 1995 production was discontinued, because saving lives in Africa was not profitable. Various non-profits lobbied the producer (a big pharma firm) to restart production, but to no avail.  Meanwhile, researchers discovered that it "cured" facial hair in women.  The cream used to do this went into production in 2000, and has been on the market since then.   Under intense pressure from the World Health Organization and non profits, the big pharma company eventually agreed to provide the drug for free to non-profits for distribution to African sleeping sickness patients, starting in 2001.  My best guess is that the lack of drug between about 1995 and 2001 killed between 40,000 and 110,00 people (very roughly).

The key moment in making the drug available may well have been a "60 Minutes" episode.  This is an American weekly news show.  It showed patients dying of sleeping sickness, or enduring painful IV treatments, which was the best non-DFMO drug available, and then followed it up with DFMO's American TV add for removing facial hair.  The juxtaposition highlighted the money-at-the-cost-of-lives reality of the situation.

Joshua Levy
publicjoshualevy at gmail dot com
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Bigfoot Biomedical news, views, policies or opinions.  In my day job, I work in software for Bigfoot Biomedical.  My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Tuesday, June 12, 2018

GNbAC1 Starts A Phase-II? Trial

GNbAC1 is a monoclonal antibody which has completed phase-II testing for treating Multiple Sclerosis, which (like type-1) is an autoimmune disease.  GNbAC1 was developed by GeNeuro SA, a Swiss company, but is being tested in Australia.   They have partnered with Servier, a large French pharma company to do the phase-III trials required to bring it to the Multiple Sclerosis market.

A monoclonal antibody is an artificially created antibody which targets one very specific type of cell in the body.  Different monoclonal antibodies target different types of cells.  So if a disease is caused by a problem in one type of cell, then using a monoclonal antibody to target that type of cell is a promising treatment.  Because several monoclonal antibodies have been successful in treating other autoimmune diseases, they are an active area of research for curing type-1 diabetes.

Previously, GNbAC1 has been tested in four clinical trials as part of the Multiple Sclerosis development program, so its safety is well established (for an investigational drug).  However, since this is the first trial aimed at type-1 diabetes, I'm calling it a "Phase-II?" trial.  (The question mark meaning "no previous testing on people with type-1".)

This Study

This study has enrolled 60 people who were diagnosed with type-1 diabetes within the last 4 year.  The first part will be double blind, with 2/3s getting the treatment and 1/3 not.  After that will be a second, optional part which is not blinded (everyone will get the treatment).  Unfortunately, the primary end point for this trial is safety related.  But their press release does say that they will track various effectiveness outcomes as well (for example: C-peptide and insulin consumption).  The drug will be given as an IV drip once a month (six doses in each part of the study).  People in the study will be followed for about a year.

This study completed enrollment in January 2018, and GeNeuro plans to publish the results from the first part of the trial in September 2018, and the second part of the trial in the first half of 2019.  That is pretty quick!

Press Release:
Clinical Trial Registry:
General Background News Article:

MS research:

Background and Rational

This clinical trial has a very different rational, as compared to previous attempts to cure type-1 with monoclonal antibodies.  In the past, these antibodies have been used to target one of the defective cell types within the immune system.  The idea is to find an immune cell which is involved in the attack on the beta cells, and kill off those immune cells.  That idea has led to some progress, some suggestive results, but nothing like a cure.

These researchers have a different idea.  They note that part of the human genome contains HERVs, which are the remains of retroviral DNA which merged into our DNA millions of years ago.  The researchers believe that while this DNA does nothing most of the time, infection can sometimes cause one of these HERVs (called "pHERV-W") to activate and generate a protein (called "pHERV-W env") used by the retrovirus the DNA came from originally.  Even after the infection, the HERV DNA stays activated.  The pHERV-W env, in turn, causes autoimmune diseases.  If true, this would explain how viral infections can "trigger" type-1 diabetes.

These researchers believe that by using a monoclonal antibody to target pHERV-W, they can stop this process.   So while previous attempts to use monoclonal antibodies targeted malfunctioning immune cells, this attempt is targeting HERV DNA which (according to this theory) is the root cause of the autoimmunity.

Background reading:

Joshua Levy 
publicjoshualevy at gmail dot com
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Sunday, May 20, 2018

Results from a Phase-II ATG and GCSF Combination Trial

I'm embarrassed about this blog posting, because it is very late.  It reports on news announced about 18 months ago.  I was digging through some old emails, and found it.

ATG is Anti-Thymocyte Globulin, a biological agent used to lower immune reactions.
GCSF is Granulocyte Colony-Stimulating Factor, a biological agent which causes bone marrow to generate more stem cells and more immune cells, and put them into the blood stream.

So the two of them together could make an effective combination therapy against type-1 diabetes. ATG would lower the autoimmune attack, and GCSF would help the body regrow beta cells. At least, that is the hope. I wrote about the start of this trial here, and it contains a lot of background material:

In brief: this study took 25 people, 2/3s got the treatment, and 1/3 got a placebo.  The treatment was spread out over 12 weeks.  The primary result was C-peptide results after 1 year, but this paper reported on extended results after 2 years.

Results from a Phase-II ATG and GCSF Combination Trial

The following graph is from the paper, and you can see that for the first year the treated group did noticeably better.  (Meaning they generated the same C-peptide at the end as at the beginning, while the placebo group dropped over time.)  The 3 to 6 month time period was particularly strong, with the treatment group generating more C-peptide while the control group generated less.  The first year change was statistically significant.  However, during the second year, C-peptide numbers continued to drop for both the treated and placebo groups, and the separation between the two of them shrunk, so that the difference was not statistically significant.

Research Paper:

Clinical Trial Registration:


This is one of several studies which preserved beta cell function for a year during the honeymoon.  Early on, these studies gave me a lot of hope that they could be improved on, and eventually even lead to a cure.  However, so far I haven't seen any movement in that direction.  Treatments that preserved beta cells for one year, have (so far) not been extended to last longer.

Earlier results from this trial were strong enough so that this team started a follow on trial for honeymoon type-1s (people in their first 4 months after diagnosis):
Recruiting Site:
Clinical Trial Record:

There are two obvious questions in this research:
1. If this treatment were started prior to diagnosis (in people who had several autoantibodies, for example, but were not showing any symptoms of type-1 diabetes), would it prevent the onset of symptoms?
2. If this treatment were repeated on a yearly, or every two year basis, could it prevent type-1 diabetes completely?  And would the hassle and side effects of the retreating on a regular basis be worth it?

Unfortunately, the new study (in honeymooners) will not answer these questions.  But it is three times as large, so it will confirm that this study was not a fluke, and the results should be available very soon.  Recruiting was completed before July 2016, so primary data should have been collected by July 2017, and publication should be imminent.

Since this study started, there is now a new hope for this level of result ("preserving beta cells for one year").  Those results could be applied to presymptomatics: people who had two or more autoantibodies, but no symptoms of type-1.  Preserving beta cells for these people would have the effect of delaying the diagnosis of type-1 diabetes.  That would be great.  However, identifying presymptomatics to test this on has just happened in the last few years, and few studies have looked into this.  But I will be looking forward to seeing the results of these studies (as prevention).

Joshua Levy 
publicjoshualevy at gmail dot com 
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Saturday, April 21, 2018

250 Postings And Changes At Work

Last week's blog posting was my 250th blog posting on Current Research into Cures for Type-1 Diabetes!  Also, this year marks the 10th year of publishing the blog, as the first posting was in June 2008  (although I had created a precursor web page in 2006).

Changes At Work

In March I was laid off from my job as a software developer, so I took advantage of the impending job search to think about what I really wanted to do.  And I decided that what I really wanted was to use my software engineering skills to help the day-to-day lives of people with type-1 diabetes.

I limited my job search to companies that were working directly to make the lives of people with type-1 diabetes easier or better in some way.  I'm lucky to live and work in Silicon Valley, so there are several such companies (and non-profits) in the area.  I'm happy to say that starting in late April, I'll be starting as a "Staff Software Developer in Test" for Bigfoot Biomedical.

Several things attracted me to Bigfoot.  First, they are developing an Artificial Pancreas ("automated insulin dosing and delivery solution"), and I'm absolutely convinced that is the quickest path to better treatment, fewer complications, and an easier life for people who need insulin.  Second, their larger goal is to lower the overall burden of type-1 diabetes.   (Not just create a device that is technically better than the competition's, but to create a whole infrastructure of treatment, supplies, and support that is smooth and easy to use.)  Third, their internal software development infrastructure is cool.  It is what I'd expect from a Silicon Valley start up.

So what does this mean for the blog?

I'm not expecting any changes in the blog.  I stopped blogging on artificial pancreas research years ago, so there is no direct conflict of interest.  I won't be blogging on Bigfoot products or the products of competitors.  On the other hand, I will continue to blog about "current research aimed at curing type-1 diabetes" just as I always have.  For me, Artificial Pancreas type devices are treatments and I blog on cures, so there isn't any overlap.

I've already discussed the blog with the Bigfoot team (many are avid readers), and they are very supportive.  Bigfoot wants it's employees active in the type-1 world, and so being supportive of my blog fits into their general philosophy.

How You Can Help This Blog

There are three ways you can help this blog:
  • Tell someone about it.  I have zero budget for anything, and that includes publicity, so if you like this blog, the best way to help is to tell other people affected by type-1 about the blog.  If every reader, even just once a year, would tell one person affected by type-1 diabetes about this blog, it would reach 1000s of new readers.  And it doesn't matter if you verbally tell one person, tweet/facebook once, post to a forum or group, or send one email to one person.  It all helps.
  • If you read about research aimed at curing type-1 diabetes, which has not been discussed in the blog, then please tell me about it.  My email is below.
  • If you have questions about any blog posting or any research aimed at curing type-1 diabetes, please email your questions, or post them as comments to the blog.  These questions tell me what you care about, and they also tell me where I need to spend more time, so they are very helpful to making the blog better in the long term.
Thanks very much for all your support over all these years of blogging.

Joshua Levy 
publicjoshualevy at gmail dot com
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Bigfoot Biomedical news, views, policies or opinions.  In my day job, I work in software for Bigfoot Biomedical.  My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Saturday, April 14, 2018

Stem Cell Educator Starts Two Phase-II Trials

The Stem Cell Educator (SCE) is an attempt to cure established type-1 diabetes by exposing a patient's immune cells to umbilical stem cells, and then returning the cells back to the patient.  Each person had a blood draw, and then a particular kind of immune cell was separated from the blood and specially processed.  The processing phase uses umbilical cord stem cells previously donated by a third party.  The patient's own "educated" immune cells were then returned to the patient.  The stem cells did not go into the person; they were only used for the external processing.

In the last six months, two new studies have started, which I blog on below.  The first is in New Jersey and the second Beijing.

The New Jersey Clinical Trial (NCT02624804)

This study will enroll 10 people.  Everyone will be treated (no control group, no blinding).
The end points are mostly safety related, but there will be some efficiency related end points as well.  There is no mention of collecting efficiency data (such as C-peptide numbers, A1c data, blood glucose, insulin usage, etc.)

This study has started recruiting.  There was hope it would start in mid 2017, but the study needed some lab infrastructure which the medical center did not have at that time, hence the delay while the new labs were set up.

Recruiting at one site: Hackensack University Medical Center
    Hackensack, New Jersey, United States, 07601
    Contact: Mariefel Vendivil    551-996-5828 
    Contact: Andrea Ortega    551-996-3923 

Clinical Trial Records:
But note that this clinical trial record is out of date.  The study has not yet started recruiting, no efficiency end points are listed, and the completion dates are too short.

The Beijing Clinical Trial (NCT03390231)

This study will enroll 100 people.  Everyone will be treated (no control group, no blinding).
The primary end point will measure specific immune cells (which are involved in type-1 diabetes) one month after treatment.  Secondary end points will cover insulin sensitivity after a month, and A1c, blood glucose, and c-peptide measurements after three months.

They started in Nov-2017, and hope to finish in either July-2018 or Dec-2020 (see discussion below).

Recruiting at one site: Department of Endocrinology, Chinese PLA General Hospital
    Beijing, China, 100853
    Contact: Yu Cheng, MD,PhD    86 10 55499301 
    Contact: Yiming Mu, MD,PhD    86 10 55499301 

Clinical Trial Records:


Differing Results: This treatment has been previously tested twice before.  One of these clinical trials had strong results, but the other one had very weak results.  I've blogged on these in the past:

The researchers believe they understand why the two trials had different results, and are hoping to apply this knowledge to the current two trials, in order to get better results.

Date confusion: The FDA's clinical trial registration page requires researchers to list three dates for a clinical trial: start date, primary completion, and study completion.  (Once the trial starts, the first is known, while the second two are estimated.)  The primary completion date is when the last data for the primary outcome will be gathered.  The study completion date is when the last data for the study will be gathered.

For the Beijing study, the primary completion date is May-2018 and the study completion date is Dec-2020.  However, the primary end point is a month after treatment, while the secondary end points are either one or three months after treatment.  So that means the study completion date should be two months after the primary completion date, not 2 1/2 years!  My guess is that there are some two year end points as well, which are not listed in the clinical trial registry.   (The New Jersey trial also has two year end points which are not listed in the registry database.)

Joshua Levy
publicjoshualevy at gmail dot com
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.