Category Archives: Biotech/Pharma

Baseball, Bayes, Fisher and the problem of the well-trained mind

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One of the neat things about the people in the baseball research community is how willing many of them are to continually question the status quo. Maybe it’s because sabermetrics is itself a relatively new field, and so there’s a humility there. Assumptions always, always need to be questioned.

Case in point: a great post by Ken Arneson entitled “10 things I believe about baseball without evidence.” He uses the latest failure of the Oakland A’s in the recent MLB playoffs to highlight areas of baseball we still don’t understand, and for which we may not even be asking the right questions. Why, for example, haven’t the A’s advanced to the World Series for decades despite fielding good and often great teams? Yes there’s luck and randomness, but at some point the weight of the evidence encourages you to take a second look. Otherwise, you become as dogmatic as those who still point to RBIs as the measure of the quality of a baseball batter. Which they are not.

One of the thought-provoking things Arneson brings up is the question of whether the tools we use shape the way we study phenomena–really, the way we think–and therefore unconsciously limit the kinds of questions we choose to ask. His example is the use of SQL in creating queries and the inherent assumptions of that datatype that objects within a SQL database are individual events with no precedence or dependence upon others. And yet, as he points out, the act of hitting a baseball is an ongoing dialog between pitcher and batter. Prior events, we believe, have a strong influence on the outcome. Arneson draws an analogy to linguistic relativity, the hypothesis that the language a person speaks influences aspects of her cognition.

So let me examine this concept in the context of another area of inquiry–biological research–and ask whether something similar might be affecting (and limiting) the kinds of experiments we do and the questions we ask.

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Trying to figure the way through a 401(k) life

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Thomas Friedman’s thoughts on how we’re becoming a 401(k) nation have been kicking around the back of my mind for about a year. His Op-Ed piece described the shift in how retirement plans in the US have largely shifted from pensions to 401(k)s and used that transition to make a point about the changing nature of work.

In a pension plan, a defined input (so many year of work) leads to a defined output (a regular payment that starts upon retirement until the day you die) with the risk assumed by the employer. In a 401(k), there’s still a defined input (regular deposits into a managed investment account) but how much a person gets at the end carries no guarantees and the risk sits squarely with the employee.

Friedman’s insight was that work itself is following that same path. Where once the defined achievements of education and learned skills were enough to guarantee continued employment and a good, middle-class career (at least), that’s not really the case anymore.

The news a some months back that Amgen will be closing its Seattle site this year really drove that point home. It was a reminder that biopharma, like so many other industries, isn’t immune to the implications  of the 401(k) life.

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The potential for “Found Research” in fecal transplant treatments

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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

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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 →

The power law relationship in drug development

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

A few weeks ago a friend and I had the great opportunity to go see Nate Silver speak at the University of Washington. He’s a funny, engaging speaker, and for someone like me who makes his living generating and analyzing data, Silver’s work in sports, politics and other fields has been inspirational.  Much of his talk covered elements of his book, The Signal and the Noise, which I read over a year ago. It was good to get a refresher. One of the elements that particularly struck me this time around, to the point that I took a picture of his slide, was the concept of the power law and its empirical relationship to so many of the phenomena we deal with in life.

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Figure 1: Slide from Nate Silver’s talk demonstrating the power law relationship in business–how often the last 20% of accuracy (or quality or sales or…) comes from the last 80% of effort.

Because I spend way too much time thinking about the business of drug development, I started thinking of how this concept applies to our industry and specifically the problem the industry is facing with creating innovative medicines.

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