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PatientsLikeMe: openness hits medicine

24-Mar-08

There’s a great story by Thomas Goetz in yesterday’s NYTimes magazine about PatientsLikeMe, an online community for people with chronic diseases.

I’d read a little bit about patientslikeme before, but didn’t fully recognize the depth of their ambitions to collect and analyze patient data.

One of the most interesting things about PatientsLikeMe is the eagerness of patients to share their detailed data, and that the same cultural currents of openness that that have been driving social media seem to extend to traditonally private, personal clinical data. There is also a virtuous cycle of transparency - the more data people share, the more disease gets ‘demythicized’ and the taboos against discussion are broken.

It is easy to see the risks in patients trying to take off-label prescriptions into their own hands, and the opportunity for excessive optimism in interpreting uncontrolled trials and anecdotal advice. Transparency, however, is ultimately a good thing and the only way to ensure reliable data. The lack of transparency in traditional clinical trials is unfortunate, and results in missed research opportunities and too much potential for spin, truthiness, and quenching of undesirable results. Individual patients own their medical information, and ought to have the power and tools to publish, aggregate, and analyze data about themselves and each other.
Goetz also blogs at Epidemix, and has posted a related WNYC interview there.

Fed acts decisively to boost liquidity

17-Mar-08

The Fed, in its latest emergency move to increase liquidity, has authorized the printing of $236 million of new currency:

New $2 Bill

‘internet addiction disorder’ and respecting attention

03-Mar-08

There’s a timely piece in the Times about taking a ’secular Sabbath’ away from electronic distractions. Scoble and Roger Ehrenberg also recently lamented ‘attention thieves.’

I’m guilty too. There are precious few times in which I put away the blackberry: yoga class (@Karma) and dancing. And bed, I suppose. (usually).

Taking a break is obviously a good idea, but doesn’t address the core problem: what we really need are information tools that adequately respect and value our attention, and give us more control over our attention. I think there are three characteristics that many of these old and new applications need to adopt in order to let us focus better without cutting off cold-turkey: context, feedback, prioritization.

Context

Traditionally, we had different physical places, times, and things for different tasks. To work, you went to the office. To read, you went to the library. If you were reading for work, you read the business section. If you were slacking off, you’d read the entertainment section.

We’re now free of such physical limitations, which is wonderful, but the result is that all of the streams of our activities flow to us simultaneously, and are presented to us merged.

We need to be able to set our context, and then have our software be humane and intelligent enough to respect it. Our IM status, for example, has busy / do-not-disturb settings. Such settings ought to be able to be applied across the whole gamut of information inputs, not just IM.

Feedback and Monitoring

Our information tools ought to help us monitor where our attention is going. Tools for analyzing clickstream, such as the early work from AttentionTrust and perhaps Atten.tv might help us see where attention is going. RescueTime is another neat application that lets us see where time/attention is going (or being wasted). And news.ycombinator has a noprocrastination setting that cuts one off after checking too many times. Making the behavioural changes to focus attention and lock out the attention theives is made much easier if software can provide the right sorts of feedback and incentives.

Prioritization

Software needs to do a better job at figuring out what messages are important and justify disruptions, and which can wait. The blackberry does a nice job of letting one configure different behaviours for different types of messages, such as ‘Level 1′ alerts that match a list of senders. But these tools are crude, and make use of little of the data which they might.

Humans are fallible, and media is often designed and evolve to steal attention, because it is valuable. Our software needs to be designed to recognize our finite cognitive limitations, avoid abusing our attention, and help us to stay disciplined.

Now back to real work!

notes from the HBS Healthcare Conference

22-Jan-08

As all hell breaks loose in the markets, it’s probably healthy to step away from twitter for just a couple of minutes to take a longer-term perspective. I had the pleasure of attending the HBS Healthcare Club conference on Saturday, and thought I’d collect and post my notes on some of the big picture issues in healthcare and biotech that were discussed. I tended to stay at the product and technology focussed sessions, rather than those focussed on services and reimbursement, because, well, I’m a science guy at heart.

Sidney TaurelOutgoing Lilly CEO Sidney Taurel gave the keynote just after lunch, and he laid out the risks and changes facing the pharmaceutical industry (besides patent expirations!) and how Lilly is adapting to meet them.

  • Global aging trend / ‘inversion of the age pyramid’
  • Emergence of “Health Technology Assessment” agencies
    • limiting access to new technologies
  • Patent issues in developing countries
  • Legislative risks: government interference with Medicaid in the US
    • US is the last bastion of free markets
  • Changing perceptions of risk vs. benefit
  • Perceptions of drug costs
    • ~ 10% of healthcare spend, but consumers are much more exposed to drug costs through copays than to other costs in the system

Changes that are going to help address these challenges:

  • Individual patient outcomes
    • Measuring outcomes instead of outputs; and focussing on individuals
    • pharmaceuticals will become partly an information product
    • Better (adaptive) clinical trials; Regulators are slow to adapt.
  • Openness of information
  • R&D moving towards a virtual organization
    • FIBNET rather than FIBCO
    • Outsourcing examples at Lilly:
      • med chem moving to China and India (ChemExplorer in Shanghai doing 20% of global chemistry)
      • Innocentive
      • Chorus
  • Big opportunities to use IT to track outcomes after drugs come on the market
  • Open source models for biomarkers
  • Systems Biology (As a computational biologist myself, I’m somehow skeptical that this is going to come through for the industry in time to save them from patent expirations :-)
  • Sales: fewer people; more competent people
  • Merging of pharma, biotech (Biologicals are already a huge part of Lilly)

Given what Mr. Taurel had said about the importance increasing openness and better post-approval outcome monitoring, I was very tempted to ask something about how the industry was increasing transparency and whether Lilly did everything it could in making data available about drugs like Zyprexa, but unfortunately we ran out of time for questions.

Trends in Medical Devices

The most interesting thing to me was the near consensus across the panel about the inevitable convergence of drugs, devices, and data.

spineDr. Stephen Oesterle (one of the most provocative speakers, and certainly the funniest) suggested a few specific companies to watch. In drug delivery, Tempo Pharmaceuticals is developing nanoparticle delivery systems for (small molecule?) drugs that allow for control over release rate and timing of drug combinations. (Tempo just did a Series B for $8.1M from Polaris, Bessemer, and Lux Capital.) In biologics, he suggested having a look at Alnylam, which has most of the IP on RNAi therapeutics locked up. The importance of RNAi is motivated by a simplifed model of disease: all disease is caused by too much or too little protein. For those rare diseases caused by too little protein, we can give it back, via protein therapeutics, cell therapy, or gene therapy. Too much protein however, and we need RNAi, antisense, or antibodies. Biologics are going require clever and new delivery systems, and delivery technologies for biologics are still a big long-term opportunity. Finally, Oesterle suggested having keeping an eye on the spine. Back pain is huge, and current therapies (spinal fusion) are lacking, yet the spine is relatively simple and very accessible surgically, and therefore low hanging fruit for new devices and approaches.

Georg Nebgen said trends to watch included: disposable devices; battery powered device; and greater automation, diagnostics moving to point-of-care and away from central labs, and that acquisitions are moving later.

Another interesting trend proposed is the vanity of an aging population - a market that is happily self-paid by patients.

Communication between devices is going to be big: we’re going to see networks of monitors, and start to close the loop between diagnostics, treatment and discovery.  Better monitoring is going to let us give drugs episodically, excactly when they are needed and effective, instead of all the time.  Implanted sensors are going to start to happen. All these sensors and diagnostics are going to generate data that will require security, storage, and analysis of the resulting signals. Big opportunities; totally unclear who is going to do it yet. (Doctors? Google/Microsoft? Payors? NewCos?)

On the more mundane side of things, we’re going to continue to see big investments in informatics for clinical trials. Still a huge source of pain, with way too much paper.
Langer

The closing keynote was by Dr. Robert Langer, who somehow I haven’t heard speak before. Langer offered up a nice checklist of scientific characteristics of successful biotech startups, and then backed them up with examples of successful companies he had started, with the caveat that business issues — like the right team — generally matter more.

  1. Platform technology - applicable to multiple products
  2. Ideally a product company
  3. Seminal paper (Science / Nature)
  4. Seminal and blocking patents
  5. In vivo proof of principle

Overall, the conference was fantastic - congrats to the organizers for putting together a great panel of speakers and running everything so smoothly.

MacBook Air Song: New Soul (Yael Naim)

16-Jan-08

Yael Naim 
I’ve been listening to a lot of pretty-girls-with-pretty-songs this weekend; it started with listening to Ingrid Michaelson on infinite repeat, and then I saw Juno, and I’m apparently a sucker for fiesty brunettes who can sing.  So it was a delightful surprise to hear the song chosen for the MacBook Air adNew Soul by Yael Naim, an Israeli-French singer (relatively) big in France. Check out the whole track, and the weirdly wholesome-yet-trippy video.  

Kudos to Apple (and their ad people) for picking the song - it works perfectly.     Aurgasm highlighted Yael Naim and New Soul last October, which was when I first heard it.   I wonder if an Apple ad can create a hit?

how to tie a bowtie…

13-Dec-07

Just in time for the black-tie-optional holiday party.

How To Tie A Bowtie

props to the Harvard Lampoon

checklists in medicine and investing

09-Dec-07

Atul Gawande wrote a fascinating article in this week’s New Yorker describing Peter Pronovost’s research on the impact of simple checklists on critical care:

Medicine today has entered its B-17 phase. Substantial parts of what hospitals do—most notably, intensive care—are now too complex for clinicians to carry them out reliably from memory alone. I.C.U. life support has become too much medicine for one person to fly.  Yet it’s far from obvious that something as simple as a checklist could be of much help in medical care […]  Pronovost and his colleagues monitored what happened for a year afterward. The results were so dramatic that they weren’t sure whether to believe them: the ten-day line-infection rate went from eleven per cent to zero. So they followed patients for fifteen more months. Only two line infections occurred during the entire period. They calculated that, in this one hospital, the checklist had prevented forty-three infections and eight deaths, and saved two million dollars in costs.             

Checklists do seem like a remarkably simple way to improve performance of a process as complicated as critical care. Checklists (or more complex algorithms) help to address both individual cognitive limits (attention, short-term memory) and problems in social organization (reluctance to challenge hierarchy).  If a checklist is good, I wonder whether a more complicated decision-support system is better - ie. one where the checklist items are dependent on the observed data.  Such a system might be harder to implement, and perhaps harder to convince people to use, which could outweigh a slight improvement in performance. Moreover, rather than guiding actions, the greatest bang-for-the-buck of a checklist is in preventing critical errors and oversights.  

This got me thinking about potential under-appreciated applications of checklists in other high-risk endeavours, such as investing and trading. Many people have processes for screening and selecting stocks with greater and lesser degrees of rigor.  Externalizing a process into a checklist makes it easier to execute in a disciplined manner   Indeed, there is already someone selling a software package called Checklist Investor, which comes with a set of checklists outlining investing workflows such as Graham’s Intelligent Investor.  One can take the algorithm-driven approach to its logical extreme and use pure quant strategies, but there’s clearly a place for art and instinct in investing, just as there is in the ICU.   I think that there is a potentially useful distinction between using algorithms for the constructive part of a process (such as stock selection), and using them as checks to avoid situations that could turn into major disasters — and avoiding those major disasters can have an enormous effect on performance.

the game is (still) just beginning

09-Dec-07

Remember, there are 6.5 billion people on this planet.  Miles to go before we sleep. Billion.  And growing. googleyahoofacebook

bubblicious

06-Dec-07

Funny stuff from RichterScales.com:

bug labs boston meetup

10-Oct-07

I stopped by middlesex last night to check out the Bug Labs boston meetup (thanks to AVC for the tip). A broad cross-section of the bug labs crew had come down (in an RV, apparently) from New York to chat, and all seemed incredibly passionate about the product and its prospects. (As an aside, it hit home how much journalism has changed when Dan Bricklin whipped out his microphone and started interviewing Peter Semmelhack, the Bug Labs CEO).

It seems that as much Bug is building a hardware platform, they are also out to create (or re-create) a culture and ecosystem of hacking hardware.

Most of the things one could do with the bug, one can already do with another open platform - the PC. The advantage of bug would seem to be as much in the software platform and community/ecosystem that they will enable as it is in the hardware. On the hardware side, because it is a portable, battery-powered device with sensors, there may well be all sorts of unanticipated applications out in the physical world. Of course, for hardcore hardware hacker, products like gumstix already let one build anything — but to go to the trouble of building something from scratch, you need to know what you want to build a priori. Bug may start off with some obvious uses, but then allow new configurations and applications to be discovered. The modular connectors, modular software, and platform for transmitting and applications will let applications evolve out in the hands of users.

This got me musing again about a much deeper, biological question that I’ve been interested in for a long time: What is relationship between modularity, hierarchy, and evolution? How does one determine the optimal level of abstraction at which evolution should occur? How does that vary with population (market) size and mutation rate (~cost)?