Successful Case Study of New Encapsulated Islet Cell Device

Research topics ebb and flow over time.  I remember when my daughter was first diagnosed 10 year ago (was it really that long ago?) that encapsulated beta cell research was all the rage.  Then it seemed to die off, just leaving Living Cell Technology (LCT) in the field.  Now it seems to be heating up again.

Successful Case Study of New Encapsulated Islet Cell Device

Background

Encapsulated  beta cells are one potential cure for type-1 diabetes.  Beta cells are wrapped in a protective coating and are put in a person.  The coating allows blood sugar in, and insulin out, but does not allow the body's immune system to attack the beta cells. It also allows nutrients in and waste products out. This allows the beta cells to naturally grow and to react to the body's sugar by generating insulin which goes into the body's blood system. Meanwhile, the body's autoimmune attack can not target these beta cells, and you don't need to take any immunosuppression drugs (as you would for a normal beta cell transplantation).

Encapsulation research started in people in the 1990s.  The current leaders in the field are LCT, in phase-II human trials, and University clinical Hospital Saint-Luc and The Sydney Project who have both done phase-I trials.  Plus there is Sernova, the Islet Sheet Project, Viacyte (and probably several more) in animal research.

This Study

These researchers (who I will call "the Dresden group") have published a case study.  A case study report on a single person, so it's not a clinical trial.   For this person, they implanted some human beta cells (from a cadaver) encapsulated using their own alginate technology [d1], and added an oxygen infuser (which had to be reloaded every day) [d2].  The researchers implanted 2k cells / kg, which is about 1/5 of what they expect to need to cure someone.  It is very common in phase-I trials to give a very small amount of whatever you are testing, in order to check for safety.  They monitored insulin usage, and measured C-peptide levels every three months.  After 10 months, they removed the capsule and ran some tests on it.

Results

C-peptides in Response to Carbs
One way to test the effectiveness of this device, is to give the patient some sugar, and see if they generate insulin (by measuring C-peptide levels) in response to that sugar.  These researchers tested the patient once every three months, and the data is shown in the graph below:

Notice that all three response lines are pretty much the same [d3].  That is very positive news, because it means that the implanted beta cells worked just as well after 9 months as after 3 months. Previous encapsulated beta cell treatments have degraded over time, and the results after 9 months would be noticeably worse than after 3 months.

Insulin Usage Before and After
Prior to implantation, this patient used about 52 units of insulin per day.  After the implantation he used 43 units.  That's a drop of 17%.  For the first human trial, with a dose much smaller than expected for a cure, that's a very promising result.  It is especially interesting that by transplanting about 1/5 as many cells as they expect to need, the patient required almost 1/5th less insulin.  That might be coincidence, or it might foreshadow more good news to come.

Fasting C-peptides
These measured about 0.04 nmol/L on average.  The MedScape normal range (ie. non-diabetics) is about 0.26-1.03 nmol/L, so these guys were well below normal.  But again, for a first case study, with a small dose of islets, this has promise.

Moving Forward

This research needs to move forward in three ways, and hopefully they can move forward in all at the same time.  First, they need to run an actual clinical trial (ie. get more people treated).  Case studies just don't attract the same attention as clinical trials, nor should they.  One important next step for this research program is to implant this in 6-20 people and see what happens.  The second step is to implant more beta cells, and the third is to find a better way to supply oxygen to the cells.

For this case study, they implanted about 2k/kg cells.  They believe that about 10k/kg cells will need to be implanted to cure type-1 diabetes.  If you look at the insulin requirements for the patient, they dropped just below 20% after implantation.  So the next big question is, if you give more beta cells, do they generate more insulin, in proportion?  If so, that is very important.

Discussion

These researchers are using human cadaver beta cells and a proprietary alginate encapsulation technology, but of which have been done before by others.  However, they are also doing something unique, which is oxygenating the cells.  They hope that providing extra oxygen will make the cells work better and survive longer.  The trade off is that the oxygen generation system requires daily maintenance.

The obvious research to compare this to is LCT's "Diabcell".  In LCT's most recent clinical trial (a Phase-II trial), they implanted  a total of 10k/kg cells in 4 patients and 20k/kg cells in 4 patients.  The higher dose group saw a 20% drop in insulin usage. LCT did not report on the durability of this result.  So we don't know if they continued to use 20% less for months, or if the effect went away relatively quickly.  So the most recent LCT results and the Dresden results are very similar, except that these researchers reported on durability and the LCT researchers have not, and the Dresden team used far fewer cells.

In addition to the possibility of being a cure by itself (especially if the oxygen supply issue can be solved), this research is also important for what it tells us about encapsulated beta cell longevity in general.  If bigger trials show the same durability (that the cells continue to work for a long period of time), that strongly suggests that the problem that causes encapsulated beta cells to die over time is a lack of oxygen.  So that means that everyone trying to create encapsulated beta cell cures will know to concentrate on the oxygen supply.  Although this might not be new news to researchers: I remember  David King (Islet Sheet developer) talking about the importance of oxygen supply years ago.

News articles: http://health.usnews.com/health-news/news/articles/2013/10/28/scientists-report-transplant-advance-for-type-1-diabetes
http://idw-online.de/pages/de/news558740
General link on encapsulation: http://en.wikipedia.org/wiki/Cell_encapsulation

Extra Discussion

[d1] Alginate is a general term that covers all (or almost all) of the recent encapsulation techniques.

[d2] One important question is: how long is the oxygen generator used?  The paper makes it sound like it was used for the whole 10 months that the device was in use.  However, one of the researchers was quoted as follows:

For that reason, the current version of the device had an oxygen port on the outside of the body attached via tubing that had to be refilled daily by the patient for as long as a month or two, Block explained.

Source: http://health.usnews.com/health-news/news/articles/2013/10/28/scientists-report-transplant-advance-for-type-1-diabetes
and that implies the oxygen generated is only needed for a short time.  Since the generator needs to be refilled each day, and that is a hassle, this duration is important.  I did ask the researchers how long the oxygen generated was used for, but had not heard back at the time I finished this posting.

[d3] Different people view this data differently.  I tend to see them as all being about the same, but at least one person (Celsus, on islet.org) thinks that the 3 month is stronger, because it ends stronger.  However, when I look at the whole graph, I think they are all similar.  The official way to make the comparison is AUC "area under the curve", and I don't think the researchers did that math.

Joshua Levy -- http://cureresearch4type1diabetes.blogspot.com
publicjoshualevy at gmail dot com
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Tidepool 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.

Carnitine As Newborn Marker for Type-1 and Speculative Cure

Carnitine As Newborn Marker for Type-1 and Speculative Cure

A team in Italy has been storing blood samples taken the day a baby is born.  Another team performed the following experiment:  If a child was diagnosed with type-1 diabetes at age 6 or less, they tested the stored blood for Carnitine and a variety of closely related chemicals.  These chemicals occur naturally and are biologically active, in your body.  They are vaguely related to B vitamins, but are not technically vitamins themselves.  The team then compared the levels of these chemicals to the levels in the newborn blood taken from babies who had not been diagnosed with type-1 diabetes, but were born within one day of those that were.  (These children formed a control group.)

The results were striking: the children who would later get type-1 diabetes had statistically significantly lower levels of many of these Carnitine related chemicals.  Now, they did not find a clear line, where carnitine levels below X singled type-1 diabetes, and over Y was safe.  There was significant overlap.  What they found was that on average lower levels predicted higher type-1 rates. [d1]

This study could be the first step towards predicting type-1 diabetes.  Obviously, being able to predict type-1 diabetes at birth, even if not perfect, would still be very helpful, both in terms of extra vigilance for earlier diagnoses [d2], and for early intervention and prevention.

Speculation About A Cure

This brings up the issue of "cause vs. association".   Specifically, the study did not show that low levels of Carnitine cause type-1 diabetes, but only that low levels are associated with type-1.   From an early detection point of view, this doesn't matter.  As long as something can be measured early, it doesn't really matter if it is a cause or an association.  But for prevention the "cause vs. association" question is critical.

The researchers [d3] who ran this experiment, think that low levels of Carnitine (and/or related compounds) during the first day or two of life, causes type-1 diabetes later in life.  It's a unique theory.  I've never heard any other researcher who believes anything similar.  The theory is low Carnitine triggers a failure when the body is starting up it's immune system, that it never recovers from, and that manifests itself as type-1 diabetes later in life.  Their full paper is on-line (link below), so you can read their explanation yourself.

If low Carnitine during the first few days of life does cause type-1 diabetes, then perhaps it could be prevented by giving Carnitine supplements to pregnant women, or to newborns.  Neither of these interventions is impossible.  Today it is recommended that pregnant women (and even those trying to get pregnant) take folic acid, to prevent a specific type of birth defect.  And also, newborns are often given vitamin K (and a Hep B vaccine) within hours of birth.  So similar could be done for Carnitine, if it mattered.

Obviously, the next step would be an intervention study, where people are given Carnitine, and then tracked to see if it lowers the chance they will get type-1 diabetes.  Such studies require a lot of people, and a long time, so I would not expect a quick answer.  The study reported on here, is a retrospective, population based study, and so is much less persuasive than an intervention study. The good news is that L-carnitine is available now as a "dietary supplement" so setting up an intervention study should not be that complicated.

News article:
http://www.gazzettadelsud.it/news/66934/Possible-cause-of-juvenile-diabetes-found-in-Italy.html
Full paper:  http://www.nature.com/nutd/journal/v3/n10/full/nutd201333a.html

Extra Discussion

[d1] In more detail: what they found was that, for a whole group of Carnitine related chemicals, people who later got type-1 diabetes had -- on average -- lower levels, than those who would not get type-1.  None of these chemicals could be used alone to predict type-1 diabetes.    None of them had a line which separated type-1 diabetics from everyone else.  Instead, at higher levels very few people got type-1 diabetes, at the middle levels it gradually shifted from few type-1s to more and more of them.  And then at lower levels the number of type-1 diabetics were higher.  But you could never say "level X means type-1" or "level Y means you will not get type-1".

This brings up a critical question: even if none of the chemicals gave a yes/no answer to the question of future type-1 diabetes, maybe by combining data for all the chemicals we could give a yes/no answer.  There is no discussion in the paper of the authors' attempt to use mathematical analysis to see if a combination of different chemical levels could be used to predict type-1 diabetes.

[d2] For example, diabetic ketoacidosis at the time of diagnosis might become much more rare, than it is now, if people were on the lookout for type-1 from birth.  Obviously, there is a downside in terms of hypervigilance, and over protectiveness, etc.  But the only way we can get to prevention is through early intervention, and the only way to get to early intervention is to predict who is going to get the disease.

[d3] This group of researchers was led by Gian Franco Bottazzo, who is generally credited with discovering (in 1974) that type-1 diabetes was an autoimmune disease.  Obviously, this was a huge breakthrough in type-1 research.  He has won the Banting medal, and several other international honors.

Joshua Levy -- http://cureresearch4type1diabetes.blogspot.com
publicjoshualevy at gmail dot com 
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Tidepool 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.

Time to Diabetes By Number of Antibodies

This blog posting is not about research into a cure directly.  However, it answers an important question that I often see people asking:

My child (who does not have type-1) was tested for autoantibodies,

 and was found to have X of them. What does that mean?

Will he or she get type-1, and if so, when?

To put it bluntly, the best data I have ever seen on this question comes from TrialNet, and is wonderfully summarized on the slide below (which I did not create!):

I know this slide is a dense with information, so I discuss it below.
Survival Distribution Function is a (very poor) way of saying "% of people who don't have type-1".
Strata refers to the number of autoantibodies detected.

Basically, each line above represents a group of people with a different number of autoantibodies.  The top line represents people with zero autoantibodies when first tested, the second line from the top represents the group of people who had one autoantibody when first tested, and so on.  When first tested, none of the people in the group had been diagnosed with type-1 diabetes, so all the lines start at 1.0, meaning that zero percentage of the people in the group had type-1 diabetes.

However, as time progresses, some of the people in the group are diagnosed with type-1 diabetes, and so the lines drop as that happens.  So 0.8 on the left side means 20% of the group has type-1 diabetes.  As time passes, the lines move from left to right, so you can see on the bottom as one year goes by, two years etec.  Because of the small number of patients, and odd behaviors out at 8 years, I don't think I would use the 8 year data, but you can see how things change from 0 to 7 years.

So what does all this mean?

Let's assume that your child does not have type-1 diabetes, but tested positive for 1 autoantibody.  That is the solid purple line.  If your child is statistically average, then the chance that he or she will be diagnosed with type-1 diabetes after two years is very small.  Eyeballing the purple line at 2 years, it looks like it is maybe at 0.97; so the chance is 3%.   Even if you look out to 7 years, the line looks to me to be around 0.9, so that means a 10% chance after 7 years.

Unfortunately, the news is a little different if your child has four autoantibodies.  Those kids have a 50/50 chance of being diagnosed within the next two years, and by 6 years, the chance looks to be about 80%.  (Using the bottom most broken brown line of data.)

Discussion

First, no one can tell you if your child is going to get type-1 diabetes or not, and no one can tell you when it will happen.  This data is all about the percentage chance that someone will be diagnosed.

Second, in my opinion, this is the best data available, certainly for people who live in the USA. However, it is only one study, and it would be nice to compare it to data from other studies, and especially from other countries.  This slide reports on almost 25,000 people, and the study is constantly enrolling more people, and will report on them in future years.

Third, the numbers shown above are what happens naturally, without any attempt to prevent type-1 diabetes. So therefore, if researchers claim a treatment prevents type-1, they must provide data better than the data shown above. For example, if someone tells you, "My kid had all 4 autoantibodies, but I gave the drug X (or holistic, all natural, superfood Y), for a year, and that prevented their type-1 diabetes".   Then you can look on the table above, and see that only 30% of 4 autoantibody patients were diagnosed in the first year, just by chance.  So drug X or superfood Y should not be getting credit as a prevention.

Fourth, more generally, this data shows the importance of testing preventative treatments on large groups of people.  In one sense, not having type-1 diabetes is the normal situation, even people who have many autoantibodies.  If you follow them for a year or two, most will not get type-1 diabetes.  Statements like "Given drug Z, even people who had 3 and 4 autoantibodies did not come down with type-1 in the year they took it" are meaningless, because even without drug Z, most people would not be diagnosed in that time period.

I consider this a very important posting, because I know that some people are very scared and nervous after they find out how many autoantibodies their children have.  I want to encourage people to repost this blog entry, tweet it's URL, include it in newsletters, and generally to redistribute it (with credit, and in it's entirety) to anyone and in any way.  The question of "what do autoantibody counts actually mean", has been vexing us for years, and I think the slide above is the best answer I've ever seen.

I want to particularly thank the researcher who presented this slide, and also TrialNet, for collecting the data.
 
Joshua Levy -- http://cureresearch4type1diabetes.blogspot.com
publicjoshualevy at gmail dot com
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Tidepool 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.

The Value of a few Beta Cells

This blog post is about type-1 diabetes research, but not research aimed at a cure.

The Value of a few Beta Cells

A recently published study, which you can read about here:
http://diabetes.diabetesjournals.org/content/early/2013/09./23/db13-0881.abstract.html?papetoc
found that type-1 diabetics who were long out of the honeymoon phase and generated their own insulin had fewer long term side effects than those who did not.  This was true even if the amount of generated insulin was tiny.  I had always assumed this was true, so it is not a surprising finding.  However it is important, because in the past studies have shown that people over a certain level (0.2 nmol/l) benefited, but only about 10% of type-1 diabetics generated that much insulin.  What was found in this study, was that even people who generated 0.15 nmol/l were better off than people who generated 0.10 nmol/l, and so on.

Specifically, they found the effect was "linear" down to even the smallest amount of insulin they could measure.  This is very good.  It means that no matter how little insulin you generate, if you generate a little more, it is better for you.  The example in the abstract was that going from 0.10 to 0.15 nmol/l, resulted in an 8.2% drop in serious low blood sugar events, and a 25% drop in serious eye-sight issues.  Obviously, more type-1 diabetics have these lower insulin levels, so this study covers more real people.

Why Does This Matter?

Over the last few years there have been several trials, which have raised the amount of insulin a person generates by similar amounts, which have been measured for months or years:

0.15 nmol/l    Zhao's Stem Cell Educator
0.16 nmol/l    Marek-Trzonkowska's Polyclonal Tregs
0.60 nmol/l    Herold's Teplizumab
(Numbers are measured under different circumstances, so should not be compared directly.  But you get the idea.  There are several different treatments which are all giving these kinds of results.)

This study shows the benefit of these treatments as they exist right now.  This can serve four important purposes:

First, it gives these clinical trials a benefit to the people participating, which makes it easier to recruit.  Right now, a researcher can say, we hope that your insulin dose might go down 2%.  And the patient (or their parents) say "who cares".  But if the researcher can say, "if successful you might have a 25% lower chance of blindness, or an 8% lower chance of serious low blood sugar, or something similar for kidney failure" (or all of these things).  That's a clear benefit.

Second, it gives insurance companies a reason to pay for these treatments (if/when the FDA approves them).  Insurance companies know how expensive blindness is, and the same for kidney failure, and trips to the hospital for low blood sugar.  They can do the math for every treatment, and this will encourage them to pay for the treatments.

Third, it gives a quicker, shorter path to a benefit.  Although a cure remains the same distance that it always was, this study suggests intermediate benefits might be seen much earlier in the process.

Fourth, it suggests that curing type-1 diabetes might be a little easier than our worst case worries. The worst case for curing type-1 is that we will need to stop the autoimmune attack and then regenerate all the beta cells that have been lost.  This research suggests that once the autoimmune attack is stopped, that maybe the body's own beta cells will regrow, or maybe they will only need a little prodding to regrow.  (This study does not provide any direct evidence that beta cells will regrow without help, but it does provide a little hope in that area.)

Related News

This study is not the only recent study showing that even long term type-1 diabetics generate some of their own insulin.  The link below is to a different study, which also found some natural production of insulin in established type-1s.  I think the link above is more interesting, because it went a step farther: it connected the small amounts of insulin to fewer long term complications, and fewer low blood sugar episodes.  But the one below also adds support to the idea that tiny amounts of insulin are produced in many type-1 diabetics:

http://www.sciencedaily.com/releases/2013/10/131009213816.htm?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+sciencedaily%2Ftop_news%2Ftop_health+%28ScienceDaily%3A+Top+News+--+Top+Health%29That is a

(If you are reading this on Brave Buddies, you notice this is the study that Lynn asked about a few days ago.)

A Quick History of Measuring Insulin Production

In order to measure insulin production, researchers actually measure C-peptide, because it is made when your body makes insulin, but is not part of injected insulin, so you can tell the difference between generated insulin and injected insulin, by measuring C-peptide.  In the past, about 10 years ago, the smallest amount of C-peptide that could be measured was 0.2 nmol/l.  Many studies found that about 10% of type-1s generated that much insulin, or slightly more, and 90% did not.  The tests reported no C-peptide, but everyone knew that it meant less than 0.2.

Meanwhile, pathologists looking at the pancreases of long term diabetics who had died, often found tiny, tiny numbers of beta-cells.  So they suggested that even long term diabetics generated a tiny, tiny amount of insulin.  But there was argument about this, and no way to know.  (Many researchers felt that the high BG numbers of a type-1 would prevent those beta cells from working, even if they did exist, for example.)

However several years ago, some researchers (in Europe, I think) created a lab test that could measure C-peptide amounts as low as 0.003 nmol/l.  As is the nature of these things, when it first came out, very few people knew about it, I suspect it was expensive, and no one was sure it actually worked.  (How do you test a test that is so much more sensitive than other common tests?) Anyway, over time the test became more widely known, I suspect it became cheaper, and researchers became more confident that it was actually as sensitive as claimed.

So now, we are starting to see papers that use this much more sensitive test to look at long term type-1 diabetics.  It is becoming pretty clear, by multiple studies, that if you look carefully enough, many more type-1 diabetics are generating a very little of their own insulin.

And now for something completely different.....My Involvement With Tidepool

Tidepool is a non-profit which is developing open source software to help use, manage, store, analyze, and communicate blood glucose data. This would be especially useful between different devices, over wireless networks, and on the web.  You can read more about it here:

http://tidepool.org/  

Howard Look is the prime mover behind it, and Dr. Adi (of UCSF) is also involved.  For those familiar with venture capital,  Bryan Roberts, who is a partner at Venrock is on the board of directors.

It is my hope that Tidepool will do two things:
1. Make it easier for companies (especially start ups and hobbyists) to create useful BG tools for type-1 diabetics.  I hope this will lead to more and different types of tools; things we can not even imagine now.
2. Make it easier for researchers to run experiments on new hardware and software.  Right now, in many cases, before you even start such an experiment, you need to duct tape cell phones to CGM devices, yourself, and write special purpose software, and so on.  I'm hoping the free software that Tidepool produces will help these researchers focus on their research, and not cobbling together software.

So in my professional capacity as a software engineer, I will be doing volunteer work for them.  It is certainly possible that in the future I will report on artificial pancreas clinical trails that use Tidepool software.  At least I hope that I do.

Joshua Levy -- http://cureresearch4type1diabetes.blogspot.com
publicjoshualevy at gmail dot com 
All the views expressed here are those of Joshua Levy, and nothing here is official JDRF, JDCA, or Tidepool 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.

JDRF Funding for a Cure 2013

In the US, we are starting the "Walking Season" when JDRF asks us to walk to raise money for a cure. So I'd like to do my part, by reminding you all how important JDRF is to the human trials of potential cures for type-1 diabetes, which I track.

Let me give you the punch line up front: 65% of the treatments currently in human trials have been funded by JDRF. (And the number is 73% for the later phase trials) This is a strong impact; one that any non-profit should be proud of.  This summary does not include Artificial Pancreas research or stem cell growth trials.

Below is a list of all the potential cures, grouped by phase of trial that they are currently in, and separated into potential cures that JDRF has funded, and potential cures that JDRF has never funded.

The list is a list of treatments, and many of these are being tested in more than one clinical trial.  For example, the "ATG and autotransplant" treatment is actually running three trials, but since they are all testing the same treatment, it is only one item in the list.  The list below uses the following marks to show the nature of the treatments:
    (Established) One or more trials are open to people who have had type-1 diabetes for over a year.
    (Prevention) This treatment is aimed at preventing type-1 diabetes, not curing it.

Also remember that I give an organization credit for funding a treatment if they funded it at any point in development; I don't limit it to the current trial.  For example, JDRF is not funding the current trials for AAT, but they did fund earlier research into it, which helped it grow into human trials.  I include indirect funding of various kinds.  For example, the JDRF funds nPOD and helps to fund ITN and several other organizations, so I include research done by these other groups as well, as being indirectly JDRF funded.

Cures in Phase-III Human Trials
Summary: there are no treatments aimed at curing type-1 diabetes which are in phase-III trials   (under the definition of cure that I use).

In the past, I have listed DiaPep277 here, but their most recent results make it pretty clear that they are seeing a treatment result, not a cure result.  So I removed it from the list this year.  Also there are two studies being done on Cyclosporine and Lansoprazole ("Prevacid") as a combination treatment.  Those trials are filed with the FDA, but have not started recruiting patients, so they are not listed here, either.  Maybe next year.

Cures in Phase-II Human Trials
Summary: there are a total of 15: 11 of them have been funded by JDRF, and 4 have not. Here are the treatments that have been funded by JDRF:

• Abatacept by Orban at Joslin Diabetes Center
• Aldesleukin (Proleukin) at Addenbrooke’s Hospital, Cambridge, UK
• Diabecell by Living Cell Technologies  (Established)
• Diamyd, Ibuprofen ("Advil") and Vitamin D by Ludvigsson at Linköping University
• Oral Insulin (Preventative)  
• Rituximab by Pescovitz at Indiana
• Sitagliptin and Lansoprazole at Sanford Health
• Stem Cell Educator by Zhao (Established)
• Teplizumab (AbATE study team)
• Umbilical Cord Blood Infusion by Haller at University of Florida
• Xoma 52 by Xoma Corp  (Established)

Not funded by JDRF:

• ATG and autotransplant by Burt, and also Snarski, and also Li
• Atorvastatin (Lipitor) by Willi at Children's Hospital of Philadelphia
• Brod at University of Texas-Health Science Center
• Vitamin D by Stephens at Nationwide Children's Hospital  (Prevention)

Cures in Phase-I Human Trials
Summary: there are a total of 22: 13 of them are funded by JDRF and 9 are not. Here is the list funded by JDRF:

• Alefacept by TrialNet
• AAT (Alpha-1 Antitrypsin) by OmniBio and also Kamada 
• ATG and GCSF by Haller at University of Florida  (Established)
• TOL-3021 by Bayhill Theraputics   (Established)
• CGSF by Haller at University of Florida
• Trucco at Children’s Hospital of Pittsburgh   (Established)
• IBC-VS01 by Orban at Joslin Diabetes Center
• Leptin by Garg at University of Texas
• Nasal insulin by Harrison at Melbourne Health
• Polyclonal Tregs by both Trzonkowski and Gitelman 
• Pro insulin peptide by Dayan at Cardiff University
• Proleukin and Rapamune by Greenbaum at Benaroya Research Institute   (Established)
• Lisofylline by DiaKine

Not funded by JDRF:

• BCG by Faustman at MGH  (Established)
• CGSF and autotransplant by Esmatjes at Hospital Clinic of Barcelona  (Established)
• Encapsulated Islets at University clinical Hospital Saint-Luc   (Established)
• Etanercept (ENBREL) by Quattrin at University at Buffalo School of Medicine
• GABA by Lunsford at the University of Alabama at Birmingham.
• Monolayer Cellular Device  (Established)
• Rilonacept by White at University of Texas
• The Sydney Project, Encapsulated Stem Cells  (Established) 
• Pioglitazone by Wilson at Stony Brook 

Summary of all Trials
37 in total
24 funded by JDRF
So 65% of the human trials currently underway are funded (either directly or indirectly) by JDRF. Everyone who donates to JDRF should be proud of this huge impact; and everyone who works for JDRF or volunteers for it, should be doubly proud.

Just Looking at Trials on Established Type-1 Diabetics
11 of these treatments (29%) are being tested on established type-1 diabetics.
Of these, 6 are funded by JDRF
So 55% of the trials recruiting established type-1 diabetics are funded by JDRF.

Compared to Last Year
In 2012 there were 38 treatments in clinical trials, in 2013 there are 37 (drop of 3%)
In 2012 there was 1 treatment in Phase-III trials, in 2013 there are none (drop of 100%).
In 2012 there were 14 treatments in Phase-II trials, in 2013 there are 15  (growth of 7%).
In 2012 there were 23 treatments in Phase-I trials, in 2013 there are 22 (drop of 4%).

How I Count Trials for This Comparison

• I give an organization credit for funding a cure if it funded that cure at any point in it's development cycle.
• I mark the start of a research trial when the researchers start recruiting patients (and if there is any uncertainty, when the first patient is dosed).  Some researchers talk about starting a trial when they submit the paper work, which is usually months earlier.
• For trials which use combinations of two or more different treatments, I give funding credit, if the organization in the past funded any component of a combination treatment, or if they are funding the current combined treatment. Also, I list experiments separately if they use at least one different drug.
• The ITN (Immune Tolerance Network) has JDRF as a major funder, so I count ITN as indirect JDRF funding.
• I have made no attempt to find out how much funding different organizations gave to different research. This would be next to impossible for long research programs, anyway.
• Funding of research is not my primary interest, so I don't spend a lot of time tracking down details in this area. I might be wrong on details.
• I use the term "US Gov" for all the different branches and organizations within the United States of America's federal government (so includes NIDDK, NIAID, NICHD, etc.)
• I don't work for the US Gov, JDRF, or any of the other organizations discussed here.  I have a more complete non-conflict of interest statement on my web site.

This is an update and extension to blog postings that I've made for the previous five years:
http://cureresearch4type1diabetes.blogspot.com/2012/09/jdrf-funding-for-cure-2012.html
http://cureresearch4type1diabetes.blogspot.com/2011/10/jdrf-funding-research-for-cure-2011.html
http://cureresearch4type1diabetes.blogspot.com/2010/09/jdrf-funding-research-for-cure-2010.html
http://cureresearch4type1diabetes.blogspot.com/2009/09/jdrf-funding-research-for-cure.html
http://cureresearch4type1diabetes.blogspot.com/2008/10/jdrf-funding-of-cure-research-phases-ii.html

Finally, please remember that my blog (and therefore this posting) covers research aimed a curing or preventing type-1 diabetes that is currently being tested in humans.  There is a lot more research going on, not covered here.

Please think of this posting as being my personal  "thank you" note to all the JDRF staff, volunteers, and everyone who donates money to research a cure for type-1 diabetes:

Thank You!

Finally, if you see any mistakes or oversights in this posting, please tell me!  There is a lot of information packed into this small posting, and I've made mistakes in the past.

Joshua Levy -- http://cureresearch4type1diabetes.blogspot.com
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.

Possible Cures for Type-1 in the News (Sept)

This blog posting is a collection of little news items, rather than a single large one.

Two Year Delay for LCT

In a very brief announcement, LCT said that it would delay general commercial availability of it's encapsulated pancreatic product (DIABCELL) from 2016 to 2018.  It sounds to me like they hit a problem in their phase-II study (an open label clinical trial in Argentina), and they need to fix that problem before continuing with their testing for approval.

LCT is developing an encapsulated islet cure for type-1 diabetes. Pig beta cells are wrapped in a coating and implanted into people.  The beta cells generate insulin in response to glucose, while the coating prevents the body's immune system from rejecting or attacking the new beta cells.  Several groups are developing technology like this, but LCT is the farthest along, as they are the only company with results from multiple human trials.

News: http://www.irasia.com/listco/au/lct/press/p130829.htm
Press release: http://www.lctglobal.com/html/blob.php/ASX_130829.pdf?attach=0&documentCode=5126&elementId=20084

ATG (Thymoglobulin) is Unsuccessful in a Phase-II Clinical Trial

ATG (non-human sourced, human T cell antibody infusion) is approved in the US for transplant rejection issues (not type-1 diabetes).  This was a phase-II clinical trial involving 58 people to test it's use for type-1 diabetes.  After one year, the C-peptide production in the treated group and the placebo group was about the same.  Here are two summaries of the results:

Our findings suggest that a brief course of ATG does not result in preservation of β-cell function 12 months later in patients with new-onset type 1 diabetes.

We recorded no between-group difference in the primary endpoint: participants in the ATG group had a mean change in C-peptide area under the curve ...

Press Release: http://www.sciencedaily.com/releases/2013/08/130827203920.htm
Summary: http://www.thelancet.com/journals/landia/article/PIIS2213-8587(13)70065-2/fulltext
Wikipedia information: http://en.wikipedia.org/wiki/Thymoglobulin

Phase-I Results of Dapagliflozin as a Treatment

Dapagliflozin is a pill used for treating type-2 diabetes.  It has been approved for use in the European Union, Japan, and elsewhere, but was rejected by the US FDA.  It has been resubmitted for approval in the US, and that second approval is still under consideration.  It is in a family of drugs called SGLT-2 inhibitors.  

Because the drug has already gone through phase-I, phase-II, and phase-III testing for type-2 diabetics, this early trial in type-1 diabetics was a phase-II study.  62 patients from 5 different locations were included.  Half got the drug, half got a placebo.  All had A1c numbers of 8.5% or higher and were treated for 3 months. 

The results were good, for a treatment.  A1c numbers dropped 0.7 to 1.0 for treated patients, and BG numbers were 30-40 points lower. 

Canagliflozin (Invokana) is a similar SGLT-2 inhibitor which is approved in the US, but I don't think it's been tested on type-1 diabetics as yet.

I don't plan to cover Dapagliflozin in the future, because it is a treatment not a cure, but I did think it was an interesting drug for type-1 diabetics who have trouble controlling their BG and have higher than desired A1c numbers.

Press release: http://www.clinicalendocrinologynews.com/news/top-news/single-article/dapagliflozin-explored-in-type-1-diabetes/5b2de5a29aa324691649e6a01768441b.html
Wiki: http://en.wikipedia.org/wiki/Dapagliflozin

Good Sources of News

I know that it is hard to find good news sources these days.  Two sources that I think are worth reading are:

DiaTribe newsletter: http://www.diatribe.org/ 
This is one of my favorite sources of information.  These guys understand type-1 diabetes and all of it's complexities.  They are not just cutting and pasting other people's press releases into their news articles, but actually applying their own knowledge and expertise to their reporting and analysis.

Ellen Ullman's Scoop.it page: http://www.scoop.it/t/diabetes-and-more   
This is a collection of media news stories, but it is a very good collection of media news stories. Unfortunately, the media does not do a good job of reporting on type-1 cures or treatments.  The reasons for this are too complex to discuss here.  But Ellen's page is my favorite way of reading about diabetes in the media.

Note that both of these sources cover both type-1 and type-2 diabetes, so be ready to mentally filter out the type-2 stories, if you only care about type-1.

Donating to Non-Animal Research

I was asked the following question: "I like to donate every year to help find a cure [for type-1 diabetes]. However, I don't want to support testing on animals. Have you come across any research groups that you think are effective but don't test on animals?"

I don't know of any research aimed at curing type-1 diabetes that has never used animal trials. Indeed, it is hard to see how such research could exist, given our current technology, and the technology we expect to have for the foreseeable future.  Curing type-1 diabetes is expected to require both changing the immune system and regrowing beta cells.  Both of these are complex interactions that occur only within actual animals.  There is no way to test either one of these effects in single cell organisms (which don't have separate immune systems or beta cells), or tissue samples, or in computer simulations.  So researchers either need to test on animals, or guess wildly, and then test in humans.  The second path is blocked by the FDA (because it's unsafe), but even if not, it's almost impossible that such guess work could lead to a cure.  

Now, if you want to only donate to research which is not currently using animals (which has already transitioned into human trials) then there are several research projects to choose from.  Any research in human trials would be a good target.  You can see a list from last September here:
http://cureresearch4type1diabetes.blogspot.com/2012/09/jdrf-funding-for-cure-2012.html
and I expect to post an updated list for this year in a few weeks.

But to put it bluntly: right now, if you are not willing to fund animal research, you are not going to fund a cure for type-1 diabetes.  For type-1 diabetes, cell cultures, tissue samples, and computer simulations are not good enough for research use.

Joshua Levy -- http://cureresearch4type1diabetes.blogspot.com
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.

Results from a Phase-II Trial of Teplizumab in Honeymooners

This blog posting covers the results from a phase-II clinical trial of a drug called Teplizumab.  This trial ran from 2005-2011 and was published on line in July 2013:
Abstract: http://www.ncbi.nlm.nih.gov/pubmed/23835333
(The full paper is not available for free on line, but one of the authors sent me a PDF, so I do have the published details: Thanks very much!)

I have written several blogs about this drug in the past, which you can read here:
http://cureresearch4type1diabetes.blogspot.com/search/label/Teplizumab

The sound track for this blog posting is "Wait" by Wang Chung from the "To Live and Die in LA" soundtrack:   http://grooveshark.com/#!/s/Wait/3IYAu1?src=5

Results

The key results are summarized in this graph, which I will explain below:

This graph shows a person's ability to generate their own insulin (as measured by C-peptide production [d1]).  Higher points on the left hand scale show more insulin production, so are good.  The bottom scale is the number of months from treatment, and treatment started about a month after diagnosis.

• In this study, about 55% of the people who were treated, had almost no effect.  This is the green line above, which is right next to the blue line (untreated people).
• However, about 45% of the treated people had a good response to the treatment, and this data is the red line.
• If you look at the responders (the red line), you can see that their insulin generation ability actually went up in the 6 months after their first dose.  And even about 20 months later, they were still generating as much of their own insulin as they were when first treated.   This is in stark contrast to the placebo group, and the non-responsive group, which steadily dropped for that whole time.

Comparing results from different studies is never straight forward, but here is my attempt to compare the recent TOL-3021 results to Teplizumab.  For this comparison, TOL-3021 results are for established type-1 diabetics and include everyone who got the best dosing regimen, while the Teplizumab results are for honeymoon type-1 diabetics, and only include "responders" (about 45% of total):

• Both treatments resulted in a maximum improvement of +20% in the body's ability to produce it's own insulin, as compared to their production at the start of the study.
• The duration of effect (until insulin production dropped back down to baseline) was about 6 months for TOL-3021 and about 20 months for Teplizumab.
• The absolute change was higher for Teplizumab than for TOL-3021.  The Teplizumab patients started out generating higher levels of insulin since they were in their honeymoon phase, so their maximum was 20% of a larger number.

Background

How Teplizumab Works

Teplizumab is a humanized monoclonal antibody [d2] which targets CD3 cells in the immune system in order to lower (or stop) the body's autoimmune response. This drug tries to prevent type-1, or lessen it's severity, by "turning down" [d3] the immune system's attack on the body's own pancreas cells. This basic approach has resulted in treatments (but not cures) for other autoimmune diseases. It does carry the possible risk that the body's immune system will not properly attack a real threat in the future.

The History of Teplizumab Clinical Trials

Teplizumab has a long history of clinical trials, and not all of it successful.  There are 9 clinical trials of Teplizumab either completed or ongoing at this time.  The quick summary is this:  A company called MacroGenics (partnering with Eli Lilly) put Teplizumab through a full round of testing, culminating in two large phase-III clinical trials.  It looked good in the phase-II study, but failed in the first phase-III study.  The second phase-III study was canceled.  In addition to the MacroGenics studies, there were other studies done by universities' researchers that were not directly related to FDA approval.  This study is the most recent of those.

Discussion

There are a lot of interesting issues here, but I'm gong to touch on some of the bigger ones:

Why did previous studies fail, while this study succeeded? This is a major question.  Remember that the study that failed had twice as many people as this one.  On one hand, it is reasonable to expect more accurate results from the larger study.  On the other hand, later trials can learn from the earlier trials, and the successful trial was later.  So should we side with the larger trial that was unsuccessful, or the later trial that was successful?  I think the answer is: we do more research, run more clinical trials.

The researchers in the study suggested that their better results were caused by treating generally younger people, and starting treatment closer to diagnosis [d4].  If these two factors did cause the difference, it is a mixed bag, because on the one hand it suggests that this really is a honeymoon-only treatment, but on the other hand, if approved as a regular treatment, then it is reasonable to assume that it will be given within a day or two of diagnosis, and even better results might be seen.

Could it continue forever? / Did the second dose help?  Another question which is critical to this research is this: Did the second dose help?  Because answering that question is critical to answering the question: can this treatment be extended for longer periods of time?  If the best this treatment can do is extend the honeymoon by 12 extra months, that has some advantages, but it's not an (obvious) path to a cure.  On the other hand if repeated dosing results in longer and longer honeymoons, that might someday lead to a cure.  And even more quickly: a preventative [d5].

Unfortunately, the news here doesn't look too good.  The second dose was given at about 12 months, so pretty close to the second row of dots in the graph above.  You'll notice that there is no improvement at that point.  The C-peptide measures don't change much (i.e. the slope of the line doesn't change at that point).  If the second dose had an obvious good effect, I would expect to see a bump up from about 12 to 18 months, much as there is a bump up between 0 and 6 months. Unfortunately, I don't see that.  An interesting trial would be to randomly give some people one dose, others two doses (as done here), and others three, four, or more doses [d6].  That would give very strong data telling us if extra doses resulted in longer effectiveness.

Is this a preventative, a honeymoon cure, or a cure for established type-1 diabetics?  In a sense, this study extended the honeymoon from one year to two years (approximately) in the 45% of the patients who responded to the treatment.  So right now the biggest question is: can this result be extended for longer periods of time?  If the answer is "yes", then it can be used as an important adjunct treatment.  It would lower insulin use, and presumably lower all sorts of long-term bad side effects of having type-1 diabetes.  Furthermore, if the results can be extended, then this might very well turn into a preventative.

Who is going to respond?  The difference between those who responded to the treatment as compared to those who did not respond, was large.  From a clinical point of view, it brings up a different question: can we tell ahead of time who is going to respond, so we don't even bother to treat people who will not benefit.  From a basic research point of view, this brings up a bunch of interesting questions which boil down to: why do some people respond and others don't?

The researchers did see differences in people who responded versus those who did not.  They do not have a single test that gives a simple yes/no answer, but by combining the results of several tests, they can say that some people are a lot more likely to be responders, and others much less likely. However, if the side effects are small enough, then it might be worthwhile to dose everyone.  We will need to know more about the rate adverse effects to be sure.

We know that many different genes are involved in type-1 diabetes, and several different autoantibodies, so studying Teplizumab may give insight into immunological differences between different populations of type-1 diabetics.

Discussion Footnotes

[d1] When your body makes insulin, it comes with a C-peptide attached, but if you inject insulin, there is no C-peptide.  So measuring C-peptide will measure just the insulin generated by the body.  Neat trick; very useful in all kinds of diabetes research.

[d2] Monoclonal antibodies is a method of creating therapies by finding one cell that attacks the cell you don't want, and cloning it.  You end up with a vast number of identical cells, all of which attack the cell you don't want.  By carefully chooing the starting cell, you can "target" the monoclonal antibody to attack a very specific type of immune cell.  Because of how they are produced, early monoclonal antibodies were targeted at mouse cells, rather than human cells, and this sometimes caused problems.  Later techniques were developed to make the cells more human like, but still not completely human.  These were called "humanised" or "chimeric" monoclonal antibodies.  Finally, techniques were developed to create fully human monoclonal antibodies, and these are called "human" or "fully humanized".

There are scores of monoclonal antibodies (of all three types) approved for use in the United States, for a wide variety of illnesses.  Different monoclonal antibodies have different safety profiles.  Most have names ending in "mab".

[d3] The medical term for this is "modulate".  Teplizumab is said to modulate the immune system.

[d4] The researchers also point out that this trial did not use a placebo and the previous trial did.

[d5] The treatment given here, was given just after diagnosis, and kept insulin production at or above current levels for 24 months or so.   So if we could predict that someone would come down with type-1 diabetes a few months before they actually did, then we could give them Teplizumab, and they would (theoretically, if all worked well) preserve their insulin production high enough to not be diagnosed, for 24 months.  Furthermore, if we could extend this treatment for longer periods of time, we could delay diagnosis for longer periods of time.  There is an ongoing clinical trial called "The Natural History of Type-1 Diabetes" which is specifically aimed at gathering data from one who gets type-1, when, and how to predict it.

[d6] Some patients in this study were given only one dose, while others got two, but it was not random.  The patients who had better initial results got the second dose.  This makes it hard to separate out the effect of one dose versus two doses, from the effect of "responder" versus "non-responder".

Joshua Levy  -- http://cureresearch4type1diabetes.blogspot.com
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.