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 baseball efficiency: the traveling salesman had nothing on a baseball scout

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

The MLB draft is coming up and with any luck I’ll get this posted by Thursday and take advantage of web traffic. I can hope! Anyway, Tuesday in Fangraphs I read a fascinating portrayal of the draft process, laying out the nuts and bolts of how organizations scout for the draft. The piece, written by Tony Blengino (whose essays are rapidly becoming one of my favorite parts of this overall terrific baseball site), describes all the behind the scenes work that happens to prepare a major league organization for the Rule 4 draft. Blengino described the dedication scouts show in following up on all kinds of prospects at the college and high school levels, what they do, how much they need to travel, and especially how much ground they often need to cover to try and lay eyes on every kid in their area.

One neat insight for me was Blengino’s one-word description of most scouts as entrepreneurs. You could think of them almost as founders of a startup, with the kids they scout as the product the scouts are trying to sell to upper layers of management in the organization. As such, everything they can do to get a better handle on a kid’s potential can feed into the pitch to the scouting director.

I respect and envy scouts’ drive to keep looking for the next big thing, the next Jason Heyward or Mike Trout. As Blengino puts it, scouts play “one of the most vital, underrated, and underpaid roles in the game.” While one might make the argument that in MLB, unlike the NFL or NBA, draft picks typically are years away from making a contribution and therefore how important can draft picks be?, numerous studies have shown that the draft presents an incredible opportunity for teams in building and sustaining success. In fact, given that so much of an organization’s success hinges on figuring out which raw kids will be able to translate tools and potential into talent, one could (and others have)  made the argument that scouting is a huge potential market inefficiency for teams to exploit. Although I’ll have a caveat later. But in any case, for a minor league system every team wants to optimize their incoming quality because, like we say in genomic data analysis, “garbage in, garbage out.”

As I was reading this piece, I started thinking about ways to try and create more efficiencies. And I started thinking about Big Data.  Continue reading

The innovators dilemma in biopharma part 3. What would disruption look like?

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

Part 1 is here.

Part 2 is here.

In the previous parts to this series I’ve covered both why the biopharma industry is ripe for disruption, and what the markets might be that could support a nascent, potentially disruptive technology until it matures enough to allow it to supplant the current dominant industry players.  In this final part I’d like to ask what disruption would look like and provide some examples of directions and companies that exemplify what are, to my mind, these sorts of disruptive technologies and approaches. With, I might add, the complete and utter knowledge that I’m wrong about who and what specifically will be disruptive! But in any case, before we can identify disruption, it’s worthwhile to ask what are the key elements of biopharma drug development that serve as real bottlenecks to affecting  human health, since these are the elements most likely to provide an avenue for disruption. Continue reading

What do labrador retrievers and NFL wide receivers have in common?

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

A.  They’re both being studied via mobile tech to create their ethograms.

What’s an ethogram?  I had no idea until I saw this PLOSone paper on using inertial sensors such as accelerometers and gyroscopes to measure the movements and behaviors of dogs, so as to create an ethogram, or collection of behaviors and actions, characteristic of labrador retrievers and Belgian Malinois.  For scientists studying the behavior and action patterns of different species, building an ethogram is essential to studies of animal behavior.  Without a standardized, objective catalog of behaviors, it can be easy for the perspectives of the observer to get in the way.  And it can make comparisons of data among different researchers (or coaches, as we’ll discuss in a bit) difficult.

And just as I was mulling over how that study shows the power of technology for behavioral research, the latest issue of Sports Illustrated came in the mail and I read a short, fascinating article by Tim Newcomb about how eight NFL teams have signed up with the company Catapult to integrate small GPS sensors into practice and game uniforms. This data allows a more accurate, granular and comprehensive view of how different receivers, for example, play the game.  Basically, building the receiver ethogram (using the term rather loosely). Sadly, this article is currently only in the print issue and not online that I can find.  But it’s at newsstands now.  You can go pick one up.  I’ll wait.

So let me delve into each of these articles a little more.

Continue reading

Mobile tech and the challenge and opportunity for design

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

Lots of things bother me when I’m driving my car.  But recently I’ve found that the number one thing making me bang my head on the steering wheel is when I’m behind a car at a stoplight, the light changes…and nothing happens. Many times I can see the back of the driver’s head, which is almost always tilted down, and I’m going to go out on a limb and suggest that this is because the person in front of me is texting or surfing the web.

A recent report from the Seattle Times that one in twelve active drivers in Washington State was observed using a cellphone while driving confirms how widespread this problem is. The thing is, the problem is, the opportunity is, this is only one small symptom of how our world is changing and becoming full of distraction. I may be irritated when the person in front of me isn’t paying attention but at the same time I’m continually impressed by the immediacy and mobility of technology.  In some ways, much as I might rant about people who are texting while driving, I also understand why. They do it because it’s easy, simple, and feeds our hardwired desire for rapid positive feedback.

So what can be done? Continue reading