Is Opower the model for getting us to wellness and health?

This is a post about nudges. And optimism.

There’s a story I read a long time ago by David Brin. It’s called “The Giving Plague,” and the protagonist is a virologist and epidemiologist who describes his life working on viruses and vectors. The Plague of the title is a virus that has evolved the ability to make infected people enjoy donating blood. Recipients keep giving blood, leading to an exponentially expanding network of people who find themselves giving blood regularly and even circumventing age and other restrictions to make sure they can give their pint every eight weeks.

The central twist of the story is that the protagonist’s mentor, who discovers this virus, realizes people who donate blood also perform other altruistic acts–that the act of giving blood changes their own self image. Makes them behave as better people. And so he suppresses the discovery, for the greater good of society. The protagonist, a rampant careerist, begins plotting murder to allow him to take credit. But before he can act, more diseases strike, the Giving Plague moves through the population, and the protagonist forgets about it in his efforts to cure newer diseases.

And if anyone thinks something like this is too outlandish, I encourage you to read this piece about Toxoplasma gondii and how it makes infected mice charge at cats, the better to be eaten so that T. gondii can spread. Yeah.

But what does this story have to do with the future of wellness and health?

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The potential for “Found Research” in fecal transplant treatments

All opinions are my own and do not necessarily reflect those of Novo Nordisk.

A few days ago the New York Times ran a nice article discussing a recent test of whether fecal transplants can be done using a pill format delivery system. The research, reported (and free, no less!) in the Journal of the American Medical Association, was peformed by physicians at Massachusetts General Hospital who had formulated human feces in an encapsulated pill format to see if that would be effective as a kind of fecal transplant. Fecal transplants  appear to overcome infections by Clostridium difficile in patients. However, the conventional method for providing a fecal transplant is to deliver a liquid slurry either nasopharyngeally or via an enema-like procedure, neither of which is easily scalable. Also, yuck.

The current work, in which 14 of 20 patients responded to initial treatments using the poop pills, and an additional 4 responded the second time around, provided a proof of concept that a frozen, pill format delivery system may be a workable alternative to the current standard.

But as I was reading this article, I was struck by another thought. Are we missing a great opportunity for research into the interplay between the microbiome and human physiology?

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Baseball analytics, arthritis, and the search for better health forecasts

All opinions are my own and do not necessarily reflect those of Novo Nordisk.

It’s Fourth of July weekend in Seattle as I write this. Which means it’s overcast. This was predictable, just as it’s predictable that for the two months after July 4th the Pacific Northwest will be beautiful, sunny and warm. Mostly.

Too bad forecasting so many other things–baseball, earthquakes, health outcomes–isn’t nearly as easy. But that doesn’t mean people have given up. There’s a lot to be gained from better forecasting, even if the improvement is just by a little bit.

And so I was eager to see the results from a recent research competition in health forecasting. The challenge, which was organized as a crowdsourcing competition, was to find a classifier for whether and how rheumatoid arthritis (RA) patients will respond to a specific drug treatment. The winning methods are able to predict drug response to a degree significantly better than chance, which is a nice advance over previous research.

And imagine my surprise when I saw that the winning entries also have an algorithmic relationship to tools that have been used for forecasting baseball performance for years.

The best predictor was a first cousin of PECOTA. Continue reading

Big Data and Public Health: An interview with Dr. Willem van Panhuis about Project Tycho, digitizing disease records, and new ways of doing research in public health

All opinions of the interviewer are my own and do not necessarily reflect those of Novo Nordisk.

One of the huge and perhaps still underappreciated aspects of the internet age is the digitization of information. While the invention of the printing press made the copying of information easy, quick and accurate, print still relied on books and other printed materials that were moved from place to place to spread information. Today digitization of information, cheap (almost free) storage, and the pervasiveness of the internet have vastly reduced barriers to use, transmission and analysis of information.

In an earlier post I described the project by researchers at the University of Pittsburgh that digitized US disease reports over the past 120+ years, creating a computable and freely available database of disease incidence in the US (Project Tycho, http://www.tycho.pitt.edu/) This incredible resource is there for anyone to download and use for research ranging from studies of vaccine efficacy to the building of epidemiological models to making regional public health analyses and comparisons.

Their work fascinates me both for what it said about vaccines and also for its connection to larger issues like Big Data in Public Health. I contacted the lead researcher on the project, Dr. Willem G. van Panhuis and he very kindly consented to an interview. What follows is our conversation about his work and the implications of this approach for Public Health research.

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Dr. Willem van Panhuis. Image credit: Brian Cohen, 2013

Kyle Serikawa: Making this effort to digitize the disease records over the past ~120 years sounds like a pretty colossal undertaking. What inspired you and your colleagues to undertake this work?

Dr. Willem van Panhuis: One of the main goals of our center is to make computational models of how diseases spread and are transmitted. We’re inspired by the idea that by making computational models we can help decision makers with their policy choices. For example, in pandemics, we believe computational models will help decision makers to test their assumptions, to see how making different decisions will have different impacts.

So this led us to the thinking behind the current work. We believe that having better and more complete data will lead to better models and better decisions. Therefore, we needed better data.

On top of this, each model needs to be disease specific because each disease acts differently in how it spreads and what effects it has. In contrast, however, the basic data collection process that goes into creating the model for each disease is actually pretty similar across diseases. There is contacting those with the records of disease prevalence and its spread over time, collecting the data and then making the data ready for analysis. There’s considerable effort in that last part, especially as Health Departments often do not have the capacity to spend a lot of time and effort on responding to data requests by scientists.

The challenges are similar–we go through the same process every time we want to model a disease–so when we learned that a great source of much of the disease data in the public domain is in the form of these weekly surveillance reports published in MMWR and precursor journals, we had the idea: if we digitize the data once for all the diseases that would provide a useful resource for everybody.

We can make models for ourselves, but we can also allow others to do the same without duplication of effort. Continue reading

Big Data provide yet more Big Proof of the power of vaccines

All opinions are my own and do not necessarily reflect those of Novo Nordisk.

Time for another screed about the anti-vaccination movement.

Well, not about them per se, but rather about another study that demonstrates how much of a positive difference vaccines have made in the US. The article, from researchers at the University of Pittsburgh and Johns Hopkins University, describes what I can only imagine to be a Herculean effort to digitize disease reporting records from 1888 to 2011 (article behind a paywall, unfortunately).  Turns out there are publications that have been collecting weekly reports of disease incidence across US cities for over a century.  I have not been able to access the methods, but I can’t shake the image of hordes of undergraduates hunched over yellowed clippings and blurry photocopies of 19th century tables, laboriously entering numbers one by one into a really extensive excel spreadsheet.

All told, 87,950,807 individual cases were entered into their database, including location, time, and diseases.  Not fun, however it was done. Continue reading

Genetic counseling at Illumina

All opinions of the interviewer are my own and do not necessarily reflect those of Novo Nordisk.

Illumina is the industry leader in high-throughput sequencing platforms and over the past decade has employed a fascinating mix of innovation, creativity in approach, community engagement and aggressive exploration into different business areas. I recently had the opportunity to interview Erica Ramos, who works as a clinical genomics specialist and certified genetic counselor in the professional services group within Illumina’s CLIA lab, about Illumina and genetic counseling.

Kyle Serikawa:  Can you describe what Illumina is doing in the field of genetic counseling? That is, are you creating a genetic counseling service, or advocating an increase in training of genetic counselors, or creating materials to facilitate counseling?

Erica Ramos: So Illumina has four full time genetic counselors as part of their services group. We don’t provide direct services to patients; Illumina’s model is to provide support to the providers, the physicians. We support what’s being done in the genetics core at Illumina. As for training, we offer opportunities for that. Every year we welcome a second year student in genetic counseling for a 10 week, part time rotation. We’ve done about 5 of those so far. It’s an opportunity for those students to see how genetic counseling skills can be applied to a non-clinical setting. We see the internships as a way to engage these people who will go on to become genetic counselors. Illumina is also a very active in the genetics community, including membership in the American College of Medical Genetics and other organizations.

KS: Given the current landscape of, for example, exome and whole-genome sequencing, it seems like genetic literacy will become an increasingly important skill—both for understanding how genetic variants can be interpreted and also how genetic information will be communicated. How is Illumina thinking about educational needs in genetics?

ER: The genetics community as a whole is concerned about the need for wider understanding of genetics to help inform medical practice. From Illumina’s standpoint, one of the things we can do is to support the internships I’ve described as a way to provide exposure to non-clinical roles for genetic counselors, which broadens the potential market. Also, we’re providing a training option that maybe not all academic programs can support. At the same time, the universities themselves can see the developing need, and through supply and demand we hope to see an increase in the number of genetic counselors being trained.

There is also need for the education and updating of other professions. Physicians, nurse practitioners and others. Illumina has put on the “Understand Your Genome” symposia to work with providers who don’t currently have as deep an understanding as they would like.

KS: How do you see genetic counseling as synergizing with Illumina’s business interests? Continue reading

The Innovator’s Dilemma in biopharma part 2. Where are the markets for disruptive tech?

All opinions are my own and do not necessarily reflect those of Novo Nordisk.

h/t to @Frank_S_David, @scientre, and the LinkedIn Group Big Ideas in Pharma Innovation and R&D Productivity for links and ideas

Biopharma may be ripe for disruptive innovation to come in and overturn their markets but that doesn’t mean it will happen. There are constraints beyond those of pure business, including the simple fact that treating diseases is really difficult and we don’t know as much as we would like about how biology really works. I see today’s biopharma market as a victim of its own success. The 80s and 90s saw the creation of truly life-changing, effective drugs like statins, and that has set the bar high enough that I think we’ve passed the inflection point at which approaches like high-throughput screening are becoming less likely to yield a substantial improvement in effectiveness. I’ve used the analogy before of drug development occurring on an adaptive landscape (Figure 2), with every improvement moving up a hill towards the theoretical perfect medicine at the apex. The higher up the hill one gets, the harder it is to move uphill and most efforts move sideways or down, simply because there’s more territory in those directions. This is a constraint that a disruptive innovation would have to overcome in some way.

Figure 2

Figure 2: The adaptive landscape for drug development.  Yes I drew this myself.  I would plug the drawing program, except I think they’d probably prefer not to be associated with this image. Continue reading