Saturday, March 14, 2015

23andMe De-risks with Data, then Gets Into Drug Development

A while back, I wrote that even though 23andMe was hit with its problems with the FDA, the company would be able to run for quite a while with the data it already had in hand.  In 2013, 23andMe had over 400,000 (now, almost 900,000) sets of consumer data from which they could mine interesting bits of information and connect clinical trial sponsors with people (i.e. subjects), or possibly vice versa, and command a tidy stream of revenue from anyone willing to pay.

That was the model then.  I always figured that 23andMe would partner with pharma companies to extract value from their consumer genetic data, but I didn't expect that the company would wade into the drug development space itself. 

With hiring Genentech's Richard Scheller, 23andMe is poised to put together a stellar team with two huge competitive advantages over partnering with pharma that essentially de-risk as a pharma company from the start: 1) Having internal data to launch projects from and 2) having a community of people that seem really willing to help out in clinical trials.

Monday, February 9, 2015

A very cool animation of protein synthesis

Animation is under-appreciated as a communications medium in a lot of science.  Whether that's because the best animations use some artistic license - and aren't 100% accurate - or because creating them is a skill that a lot of science geeks don't have, I leave for another post.

For the moment, here's a really intriguing animation of a protein being synthesized from DNA.  Enjoy:



Video found via labroots.com

Monday, January 26, 2015

Real time data analytics pays off immediately in hospitals

This is a nice article at Harvard Business Review, outlining how hospitals implemented a better data analytics system and recouped the entire cost doing so in under a year:
In the case of the ThedaCare, the staff- and technology-related cost of implementing [Clinical Business Intelligence] was about $750,000. ThedaCare ... has seven hospitals and 25 clinics, [and] created an application that provides frontline clinical managers with up-to-date information about admissions and staffing in their units, allowing them to make real-time adjustments to staffing.

In the first year that managers had the app, ThedaCare saved $850,000 in overtime costs.
Link

Monday, December 8, 2014

Big Changes: Getting an MBA while Postdocing

It's been a long while since last posting here but there's a reason for it: I've been extremely preoccupied with what's become a huge change in my life: Pursuing an MBA while doing a postdoc.  I've already begun courses at the University of Toronto's Rotman School of Management, and have to say so far so good.

First of all, I'd like to say that most people have been extremely, unwaveringly, supportive in my decision to pursue this goal.  First and foremost there's obviously my spouse and family, but also my current PI, Lincoln Stein, as well as a number of individuals and colleagues at the OICR.  I don't think I'd have been able to consider making the time for it in most other academic research environments. 

It's difficult, but it's not madness, as suggested a few years ago at New Scientist in the context of a combined PhD/MBA.  Personally, I think it would have been easier to balance workloads in a combined PhD/MBA program, but then again, I don't think I would have had the appreciation for what business school offers without the work experience I gained as a postdoc.

As I go through this long experience (And it is long -- 32 months -- as I'm taking the Morning MBA program at Rotman), I'll probably write several posts that touch on some or all of the following key points.  If you're considering combining business school with research (at the post-PhD level), you might thinking about challenges that fall under any of the following points:

  1. Time management.  This, by far, is the biggest challenge for me.  After putting in on average 45-50 hours a week into postdoctoral research, allocating the ~10-20 extra hours (it varies) for MBA classes, assignments, reading, and team work is a challenge.  And on top of that there's family life to keep sane.  The first things that went were hobbies (reduced to watching videos on Fine Woodworking), recreation (reduced to reading), and hanging out with friends (sorry, guys).  All of those gave way to sleep, which is kind of important. 
  2. New, complementary, subjects to study.  From what I can see, the biggest benefit of an MBA for science types is that the topics are mostly new.  I'm not aware of any research programs that encourage students to take courses on accounting, economics, or negotiation, but these kinds of courses at Rotman were immensely interesting to me because they're complimentary to almost everything I had studied to date.  Studying something out of your element enhances the breadth of your skillset.
  3. The price.  Business school isn't cheap.  I don't think people go to business school unless they really want to build their career in that direction.  It's already expensive for most people, but it's especially pricey for people coming out of academic jobs, with MBA tuition running about 3-4 times the annual salary of a PhD student and about twice the salary of a postdoc.  
  4. Your classmates.  This is one of the most interesting points of my experience.  There are a handful of 'scientists' (with MScs and PhDs) at Rotman, but many of the people I study with are in financial services, engineering, marketing, and mining.  You learn a lot about how things are done outside of research from these people, and most of the time things are done differently.
Those are the four big areas that I've been thinking about, so if you're a science geek and are thinking of going the MBA route, by all means reach out to me and I'll try to put together a post to address your questions.

Wednesday, October 15, 2014

Going With Your Gut vs

Greg Satell, at Forbes, argues that a mix of computer driven predictions and human intuition will drive the future of marketing:
Yet as powerful as they have become, computers are not all powerful, they perform much better when guided by humans.  For example, in a freestyle chess tournament combining both humans and machines, the winner was not a chess master or a supercomputer, but two amateurs running three simple programs in parallel.
And that’s gives us a clue to where marketing is going.
With algorithm driven decision systems like IBM's Watson starting to guide medical decisions, I don't think it'll be long before research questions are computer guided as well.  People will still need to wade through potential ideas, but arguments that research and development are a purely human-driven enterprise don't seem likely to hang around much longer.

What's wrong with using technology to help you fulfill a job?

Thursday, September 18, 2014

Academic Conference Networking Tips

There's a nice article on networking at scientific conferences over at Cheeky Scientist. The best point of advice, which I unfortunately learned the hard way:
1. Skip the scientific talks.
You love science. I get it. Science is why we all went to graduate school. But you shouldn’t go to a conference to learn the science. Not if you want to get an industry job. ... Everything in the talk is either published or in an abstract in the conference booklet. Plus, you can always seek out the conference speakers (or their posters) later.
Point taken.  If you're watching presentations, you're not meeting anyone new.  Conferences are not about taking supercharged doses of PowerPoint slides over three days; Conferences are about conferring with people.

As I found out through experience, my best contacts were always made when I walked out of talks that didn't interest me or were just plain boring and tried to find people I wanted to talk to.  If you happen to run into someone walking out of the same talk, you at least have something common to start a conversation with.

Skipping conference talks brings me to a digression about how departments dole out travel funds for students.  Some places require students to return to headquarters and give a 'conference presentation', usually intended to inform people back home of interesting news from the conference.

If this applies to you, try to balance your news-gathering efforts with networking efforts.  You're not obligated to attend every single talk, and if you come back and bring people up to speed with 'what was hot' at the conference, you've probably done your job.

Back After A Long Hiatus

It's been a long while since I last posted, and there's a good reason why.  I'm currently putting together a post to describe the additional project that I've taken up, which required a lot of time away from blogging in order to tie up loose ends, prepare, not to mention take a decent vacation beforehand.

So in short, I expect to be contributing posts more regularly going forward.   The easiest ways to follow for new content are still @CheckmateSci and via RSS.

Cheers,
Paul


Tuesday, July 8, 2014

Five Tips on Doing Business in Silicon Valley. Actually, Five Tips on Doing Business Anywhere.

The folks at MaRS just released this little video highlighting five tips for doing business in Silicon Valley.  The advice is applicable anywhere.
1. To succeed, first understand the area’s history.
Whenever you're working with people outside of your area, be it geographical or outside of your area of expertise, you need to be able to relate to where they came from.  How do their values differ from yours?  What is important to them?  Is there something about that location or field that attracts certain type of people, or encourages a particular kind of behaviour (think entrepreneurship, research excellence, etc.)?
2. Spend your time there legally and intelligently.
Plan ahead to get the biggest return on your time investment. What
3. Be open to collaboration.
Share ideas with your potential partners.  Help them develop their ideas and they will help do the same for yours. 

I've written before about how operating in stealth mode stifles research projects and exposes scientists to several traps.  Collaboration takes effort, but can pay off in spades when you find good partners, especially in high risk, pre-commercial (i.e. basic) research.
4. Steer clear of the myths about Silicon Valley.
Not sure I fully agree with this one.

Myths exist about every place and every institution.  However, there are bad myths and good myths. 

Bad ones will usually serve to drive you to inaction.  They're the ones about cutthroat competition, backstabbing, politics, and favoritism.

Good myths, on the contrary, will encourage you to make connections and build on your ideas.  The good myths may turn out to be false, but at least they've led you to break that inertia of doing nothing.
5. Recognize that San Francisco is not Silicon Valley.
Aron Solomon's point is that they may be a 45 minute car ride away, but they are not the same kind of place.  The same is true about the many organizations that may exist in a technology cluster, even if they're within a 45 minute walk. 

Universities are different from research institutes, and independent research institutes are different from those associated with hospitals. 

A Big Cash Prize is a Great Motivator

A business plan competition for 'young' (under 36) scientists by Oxford Biotech Roundable and GSK figures out how to motivate scientists to come out to bat:
Our fundamental challenge was to generate enthusiasm for a biotech business plan competition and get people excited about entrepreneurship in a sector and region not known for its risk-taking culture. But we also knew that the caliber of researchers and students we sought to engage would need an attractive value proposition to incentivize them to invest their time and energy. In this respect, the grand prize (£100,000 or about $180,000) provided an attractive reason for entrants to engage with the competition rather than pursue more established career trajectories.
The rest of the article includes many other bits of useful knowledge, like the main obstacles young researchers face when considering entrepreneurship (think networks and poor mentors), but the importance of setting the value of prize, grant, or fellowship is clear: If you want quality applicants, the chance of getting a prize must be worthwhile.

Thursday, July 3, 2014

More Data Doesn't Mean More Interesting Data

David Beer, at Adaptive Computing, writes:
One of the keys to winning at Big Data will be ignoring the noise. As the amount of data increases exponentially, the amount of interesting data doesn’t.
He describes the problem of predicting what online video a user is going watch next, and how an analysis can quickly run the number of predictions up into thousands of possible 'next steps' to evaluate.
These are then compared with all of the other empirical data from all other customers to determine the likelihood that you might also want to watch the sequel, other work by the director, other work from the stars in the movie, things from the same genre, etc. As I perform these calculations, how much data should be ignored? How many people aren’t using the multiple user profiles and therefore don’t represent what one person’s interests might be? How many data points aren’t related to other data points and therefore shouldn’t be evaluated as a valid permutation the same as another point?
Thes points are probably the biggest value that an experienced scientist can provide to the scale of these data problems.  This kind of person has at least several years of work experience in a hypothesis driven research environment and is able to solve problems using incomplete data.  They probably have a PhD to go with that quantitative experience.

The first point, working in a hypothesis driven environment, demonstrates that that person should be able to devise a strategy to prove/disprove the hypothesis (I hypothesize that this customer will watch video Y after video X), and figure out how to do that efficiently without getting stuck in the weeds, or the irrelevant data Beer describes.  Unfortunately, it does take some skill to interview a person before you determine that they can actually do this, especially there are differences between yourself and the interviewee.

The second point, being able to use incomplete data, is something seems to come from experience.  Most people trained in research fields start off trying to collect the most data possible, and don't make a decision until 'more data is collected'.  It's easy to get stuck in a data collection rut, but eventually most people realize that it's actually OK to come to a conclusion before seeing the whole picture.

Collecting a lot of extra data costs time, resources, and puts a demand on your attention span until that elusive point of having 'enough data' is reached.  Sometimes that data is worth it, but many times it's not.  It just sits there because no one has time to do anything with it, so the data remains idle and risks becoming stale.  Unless it's actually your job to do so, be careful of making data for the sake of making data.
 
ASIDE: One of the neatest things I find about the customer analytics field (as compared with genomics or computational biology) is that data is basically being generated by the study population itself, for what is essentially free.

Tuesday, July 1, 2014

Snowflakes Visualize Wind Turbine Effects on Airflow

Oh yeah, by the way, 'Here we use snowflakes from a winter snowstorm as flow tracers to obtain velocity fields downwind of a 2.5-MW wind turbine'
say the authors of a really neat article at Nature Communications.

Checkmate Scientist is Closing Comments

Regular readers (there are about 200) may be sad to find out that I'll be closing comments going forward.

I've become much more busy over the last six months (as you may have noticed by the decrease in posts) and I've unfortunately been moderating an increasing amount of comments that are clearly from spammers.  I'd rather spend time reading and writing than deleting spam, and I think you'll agree.

As always, you can send in comments to comments@checkmatescientist.net or via Twitter to @pmkrzyzanowski and I'll do my best to respond.

Thursday, June 26, 2014

Ties in Science

First to market.

First to the finish line.

First to know.

First to file.

First to climb Mount Everest.

First country to land someone on the moon.

Human achievement is defined by one group out-competing another.  When the release of multiple research papers is coordinated, it may look like a tie but in reality one of two things has happened: Journal editors synchronized the release of papers to create a bigger impact, or two research groups shared enough information to synchronize their submissions.

If it's driven by editors, one of the groups is still first to submit.  In comparison, if it's driven by the groups, they've acted as one larger collective that's first to publish over all their competitors.

A long time ago, Andrew Carnegie quipped that "The first man gets the oyster, the second man gets the shell". 

There are no ties.

Wednesday, June 25, 2014

Hey TTC, we need Tax Credits, not Low-Income Transit Fares

Tess Kalinowski, at The Toronto Star, writes that the Toronto Transit Commission is considering implementing special fares for low-income riders:
The issue of income-based fares has been raised at the TTC and other city departments individually. Now, however,a report before Toronto’s executive committee July 2 recommends that staff from social development, the TTC, public health, planning and others develop joint guidelines for affordable fares. The policy would come back to council in early 2015.
The article later points out that six dollars per day on transit fares is a lot of money for lower income people, like the unemployed, but should include students as well.

Instead of rolling out a special Low-Income Metropass (I'm not holding my breath for the rollout of Presto just yet) and creating yet another class of fares, the TTC should work with the Ontario government to provide refundable tax credits on a single class of transit passes.

That's right, get rid of Post-Secondary and Senior Metropasses.  One class of TTC Metropass would probably simplify the TTC's operations to a small extent.

The best feature of this scheme is that since most post-secondary students are low income, and arguably some seniors are also low income, everyone the existing policies are intended to cover is still covered.  It would basically work like the Federal Transit Credit, except that if you earn less than $20k per year, you get 50% of your transit costs refunded, as an example.

As an aside, note that I said 'some seniors' as it's not really fair for me to be subsidizing people with pensions that exceed my income.  The same with the rare students getting by on dividends from inherited stock market investments.  Hey, it's not just me saying so: “It’s not necessarily fair to ask other customers to pay more [to subsidize low income fares],” says TTC chief customer officer Chris Upfold.

Running this scheme through the income tax system keeps everyone's income information more or less private.  It's hard enough for people to live on a low-income, and giving them a special card to identify them as such isn't really the hand up that they need.

Thursday, June 5, 2014

Learning to Start Businesses, in the Ivory Tower?

Over at Entrepreneur, Isaiah Hankel wrote what's, overall, just another article criticizing academic culture, but if you read it with an open mind you'll find a paragraph that's probably the most optimistic description I've ever read of what a research community can pull off, especially since Hankel's describing the academic community:
The ivory tower shouldn’t be perceived as a safe haven or a place for professionals to bide their time when the economy goes south. Rather it should be considered the best place to learn how to start and run a business [emphasis mine]. Academia’s sole purpose should be developing people not to just be professors, doctors and lawyers but ones who innovate and invent products and services.
Agreed, 100%.