Thursday, September 25, 2014

VC-01 by ViaCyte Starts a Phase-I Clinical Trial

Some people are horrified at the idea of curing diseases by using embryonic stem cells.  If you are one of those people, stop reading now!  This posting is all about curing type-1 diabetes using human embryonic stem cells.  In the future, you should skip over all my blog postings with the tag VC-01 or ViaCyte.

ViaCyte (previously known as Novocell) has started a phase-I clinical trial for their encapsulated beta cell product, which is called VC-01.  This device is designed to cure type-1 diabetes.  The encapsulation 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 immunosuppressive drugs (as you would for a normal beta cell transplantation).  The cells inside the coating are human beta cells, grown from human embryonic stem cells.   Here is the company's official diagram:

This Trial

This trial will enroll 40 adults who have had type-1 diabetes for over 3 years.  There is no control group, but some people will get two implants while others will get 4 or 6 implants.  C-peptide will be measured after 6 months, and safety issues will be tracked for 2 years.  They hope to finish in August 2017.

Patients are being recruited now in San Diego, California, USA, and they plan to add more locations in the future.

Clinical Trial Record:
ViaCyte Page:
Twitter Traffic:

Discussion and Opinions

Encapsulated beta cells seem like a straight forward cure for type-1 diabetes, but companies have been working on them since the 1990s, without creating a cure.  There appear to be several difficult problems to solve, especially getting oxygen to the new cells.   Bottom line is this: while encapsulated beta cells sound like a "just needs engineering" cure for type-1 diabetes, decades of work has not led to a cure yet, so it is obviously harder than it looks.

Finally, ViaCyte is very well funded.  In the last few months, they have gotten over $16 million from CIRM, $20 million from Johnson and Johnson, $5 million in venture capital, and half a million from JDRF.

Similar Work

LCT's Diabcell is similar to ViaCyte's VC-01, in that they are both encapsulated beta cell devices. They do use different encapsulation coatings, and Diabcell uses pig beta cells, while VC-01 uses beta cells grown from human embryonic stem cells.  LCT has been tested in people for over 6 years, and is currently in phase-II trials.  (At one time it had approval to be sold in Russia, but it never was sold there.) There is also a device being tested at the University Clinical Hospital Saint-Luc in Belgium, which uses human beta cells (from cadavers) and a different encapsulation coating. 

Several organizations are doing animal tests on various encapsulated beta cell devices.  These include Cerco Medical, Beta-O2, DRI, and several more.

Finally, several organizations are doing human tests on beta cell devices which are not (yet) encapsulated, but they hope to encapsulate in the future.  DRI is doing work like this, as is Serova.  If beta cells are not encapsulated, then you must take immunosuppressives for the rest of your life, so I don't consider those a cure, yet. However, if they then progress to the point where immunosuppressives are not needed, then they would be a cure.

Terminology Note

Some of the news coverage refers to VC-01 as an "artificial pancreas", however I only use that term for electro-mechanical devices.  I use the term "encapsulated beta cells" for devices like VC-01.  You might also hear people refer to it as a "bioartificial pancreas".

If you care about the stem cell production method, here is the company's diagram:

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 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.

Wednesday, September 17, 2014

JDRF Funding for a Cure 2014

In the US, we are in 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 of 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: 70% of the treatments currently in human trials have been funded by JDRF. (And the number is 71% 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, because there are so many of those that it would be hard to include them all. For a recent summary of some (not not all) AP research, please read this blog posting:

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.

This 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: currently there are no treatments aimed at curing type-1 diabetes which are in phase-III trials (under the definition of cure that I use).  This is the second year in a row there have been no phase-III trials underway, and it's not a good thing.  Even worse, I don't see a phase-III study starting even next year.  However, phase-III trials grow out of phase-II trials, and there was big growth in the number of phase-II trials this year.  I'm very hopeful that in a few years, these will naturally result in a number of phase-III trials.

Cures in Phase-II Human Trials
Summary: there are 21 trials in phsae-II, and 15 of them have been funded by JDRF, while 6 have not. Here are the treatments that have been funded by JDRF:
  • AAT (Alpha-1 Antitrypsin) by Grifols Therapeutics and also Kamada 
  • Abatacept by Orban at Joslin Diabetes Center
  • Abatacept by Skyler at University of Miami (Prevention)
  • 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
  • Gleevec by Gitelman at UCSF
  • Oral Insulin (Preventative)  
  • Rituximab by Pescovitz at Indiana
  • Stem Cell Educator by Zhao (Established)
  • Teplizumab (AbATE study team)
  • Teplizumab by Herold/Skyler/Rafkin (Preventative)
  • Umbilical Cord Blood Infusion by Haller at University of Florida
  • Ustekinumab by University of British Columbia
  • 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
  • BCG by Faustman at MGH  (Established)
  • Brod at University of Texas-Health Science Center
  • Secukinumab by Novartis Pharmaceuticals
  • Vitamin D by Stephens at Nationwide Children's Hospital  (Prevention)
Cures in Phase-I Human Trials
Summary: there are 19 trials in phase-I, and 13 of them are funded by JDRF, while 6 are not. Here is the list funded by JDRF:
  • Alefacept by TrialNet
  • ATG and GCSF by Haller at University of Florida  (Established)
  • ßAir bio-artificial pancreas by Beta-O2's at Uppsala University Hospital in Sweden (Established)
  • TOL-3021 by Bayhill Theraputics   (Established)
  • CGSF by Haller at University of Florida
  • Trucco at Children’s Hospital of Pitt / Dendritic Cells (DV-0100) by DiaVacs   (Established)
  • IBC-VS01 by Orban at Joslin Diabetes Center
  • Leptin by Garg at University of Texas
  • Lisofylline by DiaKine
  • Nasal insulin by Harrison at Melbourne Health  (Prevention)
  • Polyclonal Tregs by both Trzonkowski and Gitelman 
  • Pro insulin peptide by Dayan at Cardiff University
  • VC-01 by Viacyte (Established)
Not funded by JDRF:
  • 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
  • Monolayer Cellular Device  (Established)
  • Rilonacept by White at University of Texas
  • The Sydney Project, Encapsulated Stem Cells  (Established) 
Summary of all Trials
40 in total
28 funded by JDRF
So 70% 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
13 of these treatments (33%) are being tested on established type-1 diabetics.
Of these, 8 are funded by JDRF
So 62% of the trials recruiting established type-1 diabetics are funded by JDRF.

Compared to Last Year
In 2013 there were 37 treatments in clinical trials, in 2014 there are 40 (growth of 8%)
In 2013 there were no treatments in Phase-III trials, in 2014 there are none (no change).
In 2013 there were 15 treatments in Phase-II trials, in 2014 there are 21 (growth of 40%).
In 2013 there were 22 treatments in Phase-I trials, in 2014 there are 19 (drop of 14%).

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.
  • If there are different clinical trials aimed at proving effectiveness as a cure and as a preventative, or effectiveness in honeymooners and established diabetics, then those are counted separately.
  • 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.
Some Specific Notes:
  • The FDA's clinical trials web site lists two studies being done on Cyclosporine and Lansoprazole ("Prevacid") as a combination treatment.  These trials were listed over 18 months ago but not started recruiting patients.  I have not included them in my list of clinical trials. 
  • LX4211: This drug is a SLGT2, and I don't think it is likely to be a cure.  It might turn into a treatment that can be paired with insulin for better results, but not a cure.
  • Serova's Cell Pouch and DRI's BioHub: These two clinical trials are both testing one piece of infrastructure which might be used later in a cure.  They are testing a part of a potential cure.  However, in both cases, the clinical trials being run now require immunosuppression for the rest of the patient's life, so I'm not counting them as testing a cure.
  • INGAP: This treatment was in human trials twice, but long in the past.  The current testing is being done by a high school student, and I'm not counting it as cure research until I see better results than were seen before (and which previously led nowhere).
  • GABA
This is an update and extension to blog postings that I've made for the previous five years:

Finally, please remember that my blog (and therefore this posting) covers research aimed at 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
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.

Wednesday, September 10, 2014

DiaPep277 Development Canceled Due To Alleged Misconduct

This is the first paragraph from yesterday's press release from Hyperion:
Hyperion Therapeutics, Inc. (HPTX) today announced it is terminating development of DiaPep277 for newly diagnosed Type 1 diabetes. The company has uncovered evidence that certain employees of Andromeda Biotech, Ltd., which Hyperion acquired in June 2014, engaged in serious misconduct, including collusion with a third-party biostatistics firm in Israel to improperly receive un-blinded DIA-AID 1 trial data and to use such data in order to manipulate the analyses to obtain a favorable result. Additional evidence indicates that the biostatistics firm and certain Andromeda employees continued the improper practice of sharing and examining un-blinded data from the ongoing DIA-AID 2 trial. All of these acts were concealed from Hyperion and others. The Company has suspended the Andromeda employees known to be involved, is notifying relevant regulatory authorities, and continues to investigate in order to explore its legal options. Hyperion employees were not involved in any of the improper conduct.
A note on terminology:  Hyperion did not use the term "fraud" in describing what happened, although Globe News did, and another news service said "falsified data".  Instead, in their conference call and press release, Hyperion used terms like "serious misconduct and deceit", "collusion", "extensive measures to conceal their wrong doing", "actively and consistently lied", "dishonesty and deceit", "deception was extraordinarily serious", and so on.  Based on all that, I do think that "fraud" is the right term, but it is important to remember that I mean this word in the English dictionary meaning [d1], not the legal meaning.  No one has been convicted of any crime, not even charged, and I doubt anyone ever will be.

The sound track for this posting is here:!/s/Saturday+Night+s+Alright+for+Fighting/2UTbqy
(Note this is The Who's version, because I can hear the words better in it than in Elton John's.)

As usual [d] notes are at the bottom of the posting, and provide more details.

Background on DiaPep277

DiaPep277 is a peptide (a part of a protein).  It is a small part of a naturally occurring protein called "heat shock protein 60".  The hope was that it would cause the immune system to stop attacking beta cells.  Development was done by Andromeda (either as a separate company or a division within another company), and no other company is doing work in this area.  It is one of the potential cures for type-1 diabetes that I have followed from the very beginning of my research.  It had already finished phase-II trials when my daughter was diagnosed in 2003.  I have made more postings on DiaPep277 than any other potential cure, except for Diamyd.  You can read them here:

In 2008 I published a blog based on DiaPep277's earliest data from a phase-III trial and I felt the results were so small it was unlikely to be successful.  You can read that here:
However, in 2011 I published this slightly more upbeat blog:
I continued to follow it until 2013 when I "threw in the towel" stating that the results seen so far were so small that they could not lead to a cure (although I still held out hope they could lead to a new treatment).

What Happened?

As you read my description of what happened, it is important to remember that all my information comes from Hyperion (except for a tiny bit from Evotech), and none of it comes from Andromeda, or any of the specific employees who are alleged to have participated in the dishonesty.  If Andromeda or the people involved publicize their side of the story, I will likely need to update this, based on that new information.

It is normal practice to run two large clinical trials to get the data required by the FDA and the EMEA, and Andromeda had started two: DIA-AID-1 and DIA-AID-2.  They were designed to be twin studies and have 450 people each [d2].  Just last June, DiaPep277 was sold to Hyperion.  This sale included all rights to the new drug, and the transfer of some Andromeda employees who were working on it.  At that point DIA-AID-1 was complete and had been published, but DIA-AID-2 was not quite finished.  The completion date is early 2015.  So the Hyperion statistics team were evaluating the entire DIA-AID-1 data set, as a sort of practice run to get ready to analyse the DIA-AID-2 data, when it was ready.

You can read the DIA-AID-1 results in this paper:
Thanks very much to Diabetes Care, published by the ADA, for making the whole paper available on line.

When the Hyperion statisticians looked at the full data set for DIA-AID-1, they noticed something very odd.  If they analyzed the entire data set, then DiaPep277 did not have a statistically significant good effect in the primary outcome measurement.  The clinical trial had failed.  However, Andromeda had excluded 30+ patients from the analysis because they had violated the rules about who should be signed up [d3].  With those exclusions, the data showed a statistically significant good effect in the primary outcome [d4].  The study had succeeded. That's unusual, because the exclusions are supposed to be made "blind" (not knowing if the drug worked for those people, or even if they got the drug), and excluding people randomly from a trial, should not change the outcome.  These exclusions were done by an outside company which was involved in the clinical trial, and that company was not supposed to know who got the drug and who got the placebo.

Except Hyperion's investigation found (according to Hyperion) that some of the Andromeda employees passed data to the outside company, and people at that company used that data to selectively remove patients from the study to bias the results.  Also, Andromeda employees changed the primary end point of the study [d5], so that it would be successful. In both cases, the decision was made "unblinded" (i.e. knowing who received DiaPep277, and who received placebo), when the decision should have been made "blind". This completely undercuts the results of the clinical trial.  Hyperion said that this did happen in the DIA-AID-1 trials results, and was also in process of happening in the DIA-AID-2 trial [d6]

Although Hyperion was careful not to name the company that did the statistical analysis for Andromeda (they always referred to it as an Israeli Biostatistics company), nor did they name any of the people involved.   However, on page 1399 of the DIA-AID-1 paper, there is discussion of what companies did statistical analysis as well as describing what each author did in running the study and writing the paper.  (In the future, I'll be checking to see if this company or these researchers are involved in any research I report on.)


Hyperion has said that there is no way to move forward with regulatory approval for DiaPep277, and they will not attempt it.  So DiaPep277 is dead.  That's the short term impact.  I suppose they could try to sell it to someone else, but who would want to buy it now?

The medium-term impact has three questions:

1. Will the paper describing the results from the DIA-AID-1 trial be retracted?  It was published in Diabetes Care (a journal of the American Diabetes Association), so it will be interesting if the authors retract it, or if the editors/publishers retract it [d7].

2. Will there be a civil lawsuit?  Will anyone face a criminal charge?  Remember that Hyperion paid tens of millions of dollars for DiaPep277 based largely on results which were invalid.  Andromeda and the nameless Biostatistics company are Israeli, while Hyperion is American, and I'm sure that will complicate both civil and criminal legal matters.

3. In addition to the results paper, Andromeda employees also published a research paper comparing the primary end points (new and old) of their study.  If Hyperion's can show that this data was manipulated, then this study should be retracted as well.

The abstract of the paper is here:
and says specifically that the findings were "unexpected", which Hyperion claims is untrue.

The long term impact is less predictable, but could be much wider.  How many other studies used the same biostatistics company?  Some of the researchers involved in this study are very big names, and have published many other papers, and worked with other companies, including some companies doing clinical trials.

Some Personal Notes

I gave up on DiaPep277 long ago, so in that sense, it was dead to me even before this came up.  But it is still deeply shocking.  (A statistician that looked at this situation described it as "staggering".)  At the end of the day, new drug safety and effectiveness are supposed to be shown via scientific testing. There is a lot of good statistics used to show that results are meaningful, and not due to chance, accident or mistake.  But all those statistics assume that the people running the study are not liars or cheats.  Detecting people who are willing to commit serious misconduct in their scientific studies is not easy.  Implementing the procedures necessary to detect active deceit in all scientific studies would be horribly expensive.  Currently, the FDA uses statistical methods, to find "honest" mistakes, rather than do the sort of investigations and surveillance required to find premeditated fraud.  That's part of the reason why I think it's important to the scientific process to see what consequences the people and corporations face in this case.   Because if other people and other corporations see that they don't face huge consequences, then they will be more willing to risk the same kind of misconduct that is alleged here.

In general, this blog does not report on financial transactions.   That is specifically because of Andromeda and DiaPep277.  Whenever a company buys a new drug, there are always very positive press releases, and early on I thought about reporting those in the blog.  But I noticed that DiaPep277, in particular, was getting passed around to a lot of different companies, and for no good reason that I could see.  I don't remember now all the moves (this was years ago), but I'm pretty sure that Andromeda sold it, got it back, sold it to someone else, and got it back again.  All the companies were Israeli, and as I remember it, some of them were partial owners of each other [d8].  I did not understand it.  That's a lot of moving around in a small market.  It convinced me not to report on company-to-company movement in my blog; that it didn't mean anything, or at least I didn't know the meaning.  But now, in retrospect, I wonder if it was a sign of trouble.  

Finally, I want to personally urge Hyperion to make public the researchers involved, and the evidence about each one's involvement in this alleged misconduct.  There are 21 named authors of the DIA-AID-1 study, and 6 named authors of the change-of-primary-endpoint paper (with much overlap).   Right now, all of these researchers are "under a cloud"  but it is likely that many of them did nothing wrong.  Maybe none of them did anything wrong, and the misconduct was done by others, or never happened at all.  But in any case, the whole type-1 world deserves to know who did what, and the supporting evidence.

Extra Discussion

[d1] For example (from "deceit, trickery, sharp practice, or breach of confidence, perpetrated for profit or to gain some unfair or dishonest advantage."

[d2] This is a quirk of the American approval process.  It is law that there must be two studies to confirm the results.  Therefore, you can not run one 600 person study, you must run two 300 people studies, even if they are otherwise identical.

[d3] It is common for some patients enrolled in a clinical trial to be excluded from the results for a variety of reasons.  The most common is that someone drops out, and complete data for that person is not available.  However, people are sometimes enrolled by mistake in violation of the study's rules. For example, a trial might require first treatment within 100 days of diagnosis, but a review of paperwork, after the study completes might determine that the patient signed the paperwork within 100 days, but didn't actually get the drug until later.  Data for that patient would be (properly) dropped from the study results.

[d4] If you look at the patient flow diagram on page 1394 of the paper, you can see that a total of 34 patients were excluded from analysis.  It is the two boxes just below the "allocated" boxes, and these changes impacted both the "mITT" data and the "PP" data.  The claim Hyperion made was that these exclusions were made "unblinded" and were specifically tailored to bias the results.

[d5] The primary end point is the most important result of a clinical trial.  Usually, there is one primary end point, and several (less important) secondary end points.  If the primary end point shows a statistically significant good effect, then the trial is successful.  If this is not seen, then the trial is unsuccessful.  The FDA generally determines effectiveness of new drugs based on primary end points.  So therefore, changing the primary end point of a study, in the middle of the study is very unusual, and if it was done "unblinded" (ie. with knowledge that the current primary end point is failing, or the new one succeeding) that is scientific fraud (in my opinion).  Its the moral equivalent of moving the goal posts to the ball's location, rather than putting the ball through the (stationary) goal posts.

In the case of DIA-AID-1, both the original primary end point, and the new primary end point involved measuring C-peptide, but the two end points measured it in different ways.  The details are described in the comparison paper.  Abstract is here:

Remember that although Hyperion has said that this happened in the DIA-AID-1 study, I have not seen their supporting evidence, and so have no way of knowing if this is correct or not.

[d6] As part of this research the DIA-AID-2 data collected to date was unblinded, and Hyperion said that there is almost no chance that it would end up showing a good effect in the primary end point.  (Remember that most of the DIA-AID-2 data has already been collected, even as they are still waiting for the last few patients to get the last few data points.)

[d7] To be blunt, the paper contains the following two quotes (pages 1393 and 1394), which Hyperion now claims are untrue:  "Participants, investigator site staff, persons performing the assessments, and data analysts were blinded to patient allocation from the time of randomization until database lock" and "The study protocol was amended, and the statistical analysis plan was planned and finalized before the study was unblinded, with the GST clearly defined as the primary end point."

[d8] Even now, I don't have a complete list, but here is a partial list of companies involved in DiaPep277 development: Andromeda, Clal Biotechnologies, Teva, Peptor, DeveloGen, and Evotek.

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 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.

Thursday, September 4, 2014

ADA 2014: Other Topics, Pediatric Approval and Big Data

This blog posting covers two topics which I found interesting at ADA's Scientific Sessions 2014.  It contains much more of my personal opinions than a regular post.

Barriers to Pediatric Treatment Approval

This was an ADA session on getting drugs/treatments/devices approved for pediatric use.  It focused on one topic: why is it so hard to get pediatric approval for diabetes treatments (both in type-2 and type-1)?  The entire discussion panel took the position that getting pediatric approval for new treatments was too long/slow/difficult, and so there was no discussion of safety trade offs, or the that the extra work of pediatric approval led to commensurate increased safety.  Everyone just assumed that it didn't.

The answer to the question of why pediatric approvals were so hard was basically this: The FDA requires testing on adults before testing on children (part of the Helsinki protocol on medical testing).   So treatments get approved on adults.  But the FDA requires separate testing on children.  So approval for children comes years after approval for adults.  You don't want to start your pediatric testing before you know that the treatment is going to be approved for adults, so there will always be a gap of many years.  However, doctors can prescribe a treatment for anyone, once it is approved.  So if the treatment looks safe for kids, doctors will prescribe it, once it is approved for adults.  Many parents will encourage this, by clamoring for the newest treatments available.   Now the drug companies think to themselves, why bother testing on kids?  We're already getting profits from kid's prescriptions, and that's only going to increase.  So there is little motivation for them to do pediatric testing.  Of course insurance companies try to say "we won't pay for it for kids, because it hasn't been approved for kids", and sometimes they succeed and sometimes not.  At the end of the day, that just limits the treatment to more wealthy families, which creates another problem; newer pediatric treatments are limited to the wealthy, even for people who have insurance.

All of this leads to the worst possible outcome, from a patient's point of view: drug companies don't test in children, and doctors routinely prescribe for children.  We have use without testing.   Officially, the FDA can wag it's finger at both industry (for not testing) and doctors (for prescribing), but the bottom line is that it's the FDA's policies that promote this sad state of affairs.  (And the FDA can blame the Helsinki protocols for the problem, when the problem might really be their simple minded implementation of those protocols.)

In Europe, they have shifted towards requiring a plan for pediatric testing as part of the adult approval process, and the FDA is considering a similar change.  The idea, is that since some doctors will prescribe a treatment for children once it is approved for adults, the regulator agency should require some testing (or at least planning for testing) on children even as part of adult approval.

Another idea, promoted by researchers and industry, is to share control groups.  Right now, if you want to test a treatment, you need a treated group and a control group.  That often means you must recruit twice as many people than actually get the drug.  For example 150 people get the drug, and another 150 go through the study, but never get the drug.  To test a second drug you need to recruit another 300 people, and so on.  The idea here is to test several drugs at once, all sharing the same control group, so maybe recruiting 600 people to test 3 new drugs, instead of the 900 people it would take now.

Discussion (My Opinions)

I don't have a easy solution to this problem, but I think there are a few obvious things to consider:
  1. Although children are not identical to adults, we are all the same species (well, maybe not teenagers, but everyone else :-) and the current FDA policies that require testing on adults and then testing on children need to be relaxed to take into account both the similarities between adults and children, and the differences.
  2. Many devices are likely to work very similarly in children as in adults, and such devices should have extremely simplified child testing requirements.  In some cases having combined phase-III trials and approval.  (How can anyone claim that a BG meter is going to be different for children than for adults.  Even for a pump or CGM, the differences are likely to be tiny or nothing because the physiology that they are based on in the same.)
  3. On the other hand, drugs which impact growth or hormones are likely to have a different effect on children, and at the very least should follow the same adults first policy we have now.
  4. In between, there are lots of drugs which are likely to work very similarly for adults and children, and these could undergo overlapping (but not completely combined) testing, where some testing was done on adults first, but abbreviated testing can be done on children.
  5. In general, I think the EU's solution (more work up front) is not a good one, because it slows down approval by creating more hoops to jump through.  Also, if there was child-only problem with the drug, it might still block adult approval, and I don't think that is a good thing.
  6. Also, I think allowing doctors to prescribe "off label", but having many insurance companies not pay for "off label" use creates some bad effects as well.  But the question of insurance is much too big a "can of worms" to discuss here.
Two side-discussions on childhood type-2 diabetes:
1. In general, ADA 2014 sessions labeled "pediatric" were about half type-1 diabetes, and about half type-2 diabetes.  In itself, this shows how fast childhood type-2 diabetes is growing, since even 15 years ago, pediatric diabetes was almost a synonym for type-1 diabetes.
2.  I was really shocked by how bad the outcomes were for people diagnosed with type-2 diabetes in childhood.  In type-1 we are used to serious side effects that happen decades down the line, and can be minimized with good control during all that time.   But that's not the reality of type-2 diabetes in childhood.   Very serious side effects can happen during childhood.  They are hit with bad complications much earlier and much more commonly than people with type-1 diabetes.

Big Data

The term "big data" refers to using huge amounts of data to answer questions that were not even considered when the data was collected.  A "classic" data base task might be to record all the books a person buys, so that you can see what authors they like.  A "big data" task might be to record every book a person views while shopping, and every book they discuss on-line, and how quickly they read each page of each book they own, in order to answer questions about what they like, why they like it, and what they do based on their likes, etc.

There was an entire session on "Big Data" at ADA 2014. Although I don't work in Big Data specifically, I am a software engineer, and I do understand the topic.  It was interesting to hear how medical researchers view big data, and also interesting that none of the papers in this session would be considered "big data" by software engineers.

Monitoring Data from Doctor Office Visits

Two of the talks focused on what I would call "more data" (but no where near "big data").  These guys were talking about integrating more medical data from more sources.  But the amounts of data they were talking about was so small that they would not qualify as "big data" for anyone in the industry. (Indeed, the data was so small, it would easily fit "in memory" for a mid-sized virtual machine at my work site.)

One talk focused on scraping information from medical records and aggregating it.  Basically, they installed a server at a 100 or so doctors' offices ("medical practices") that used electronic medical records.  Every night, the server software would look at the newly updated records, and pull useful information and send it to a central server for analysis.  No identifying information was sent, so all data was anonymous and there were no privacy issues.

This data could be used to get an early warning of a flu outbreak or a rare side effect in an approved drug or an unusual drug interaction.  I very much hope that this can be used as a "safety blanket" to encourage more streamlined drug approvals, followed by more rigorous real use surveillance.  I think this combination can lead to the win-win of faster approvals and safer drugs.

In a real world (although small) application on this idea, the researchers looked at all problems reported by type-2 diabetics.  They noticed that many people who took two specific drugs at the same time had complaints about high BG numbers.  Now each of these drugs were supposed to lower BG numbers. Both had been extensively tested and found safe and effective in lowering BG numbers.  But by looking through 1000s of medical records, they found over 100 people who happened to take both, and they often had complaints (also in the their medical records) of high BG numbers.  The two drugs had never been systematically tested together.  The researchers gave both drugs to mice, and saw the mice BG numbers go up.   So the statistical discovery was confirmed in animals.  (Since it was a bad side effect, confirmation in animals was enough, you don't need to test something like that in people.)

A factoid from another talk at ADA 2014: In the US, 76% of people over 60 are taking more than one prescription drug.  And I'm sure the number is much higher for people diagnosed with a chronic disease like diabetes.  Yet drugs are often not tested together; indeed, people taking other drugs (especially for the same disease) are often specifically excluded from clinical trials to avoid uncertainty as to which drug is having what effect.

Recruiting and Running Clinical Trials on a Social Network

Another talk focused on using members of type-1 diabetes on-line groups as recruitment pools for studies, and making study participation much more like social networking.  I would view this as "crowd sourcing" clinical trials.  Therefore, it would be more natural to people who grew up updating Facebook status and sharing pictures.  Presumably such people are comfortable sharing their A1c, which drugs they take, and complications they experience.  These researchers have published some studies based on data from members of the TuDiabetes on-line community.

The researchers were generally worried about such things as "informed consent" to participate in a research study (and ethics in general), and also the quality of the data (especially self selection of the participants).   They did notice that early adopters tended to have better A1c numbers than expected, which suggested to me that they were "skimming" the people with good control, rather than a representative sample.

Discussion  (My Opinions)

Personally, for the "trials via social networks" idea, I'm more worried about deliberate manipulation, and I asked the speaker about this issue.  Not in type-1 diabetes, but in some other diseases, there are organized patient groups that have very strong points of view about their disease, and have actively tried to manipulate scientific research to agree with their views. (See discussion below.)  The researcher I questioned hoped that by using reputable groups (in this case TuDiabetes) they could minimize manipulation, and that statistical analytics might detect or prevent it.

I think that is wishful thinking because people can organize on one forum and then move to another to implement their manipulation, and also because the kinds of statistics usually used are not designed to detect or prevent deliberate, organized manipulation.  At the very least, we would need new kinds of statistics and new kinds of surveillance to protect these studies.

Details about Manipulation

For example, already in vaccine, abortion, and chronic fatigue syndrome (CFS) research, I have seen organized attempts to bias research by selectively submitting reports of side effects, boycotting research that might show something they don't believe, influencing participants in the research, etc.

Currently, the most common form of manipulation is creating spurious VAERS reports.  VAERS is a reporting system for vaccine side effects.  However, any medical professional can submit anything they want into the system.  So anti-vaccine groups run organized campaigns to ask doctors and nurses they work with to submit "side effects" that they claim are caused by vaccines.  Anti-abortion groups do the same for those vaccines which were developed using cell lines from aborted tissue.  Conservative religious groups do it for vaccines targeting sexually transmitted diseases.

More advanced forms of manipulation are also already in use.  Some chronic fatigue syndrome patients have started campaigns to actively discourage fellow patients from signing up for studies that might disprove their pet theories, boycott all studies by researchers who have previously published results they don't like, and even sabotage studies by getting patients to drop out of studies they have already started if those studies might come to a conclusion they don't agree with.  Both CFS groups and anti-abortion groups have organized mass ethics complaints against researchers whose work they disapprove of.

Research done via social networks would be even more open to similar organized attacks.

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 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.