Software development is never easy
November 30, 2007
Decisions on software design are hard. Jon Udell has a post about the “softness” of software that really resonates. One of the most difficult thing to do when writing product requirements has always been trying to figure out whom to target. Make it too flexible and the casual user finds things too complicated. Make things a little rigid and you lose your power users.
Fact remains, not everyone has the time to find every option and learn every trick. In the meantime, software developers are constantly trying to figure out how to try and make everyone happy, not always the best idea, since the results often end up at the “I Suck” part of the Featuritis curve. For a commercial company, such decisions are often the difference between success and going under.
Image by Kathy Sierra
Technorati Tags: Software Development, Usability
And you thought consumer genomics was a crowded space
November 28, 2007
Lets assume I am someone remotely important for a journalist to interview me and ask the following question.
“What life science story from 2007 has surprised you?”
This is an easier question to answer than one might think. Like many others, my gut feeling was that next-generation sequencing was the next big thing, but broader adoption, especially commercial adoption was going to happen slowly. Boy, was I wrong. The field moved at a dizzy pace. 454 got acquired by Roche Applied Science, Solexa got acquired by Illumina (for $600m), ABI commercialized Agencourt as SOLiD, Helicos went public, and those are just the big boys. The space has become increasingly crowded with a number of technologies, all competing to sequence the $1000 genome. VentureBeat points us to another company, Intelligent Bio-Systems, which claims technology that would make it possible to sequence a genome for $5000 in 24 hours.
I suspect that in the next few years, we will see further consolidation in this space, and cost reductions. As it is core facilities, service providers and pharma companies are beginning to acquire these systems at least 2 years ahead of the time I had predicted at the beginning of the year, despite high costs. Once costs fall into “reasonable” territory, I see an explosion in the number of next-gen systems out there. In other words, lots (and when I say lots I mean lots) of data, new technical challenges, bragging rights, and best of all the opportunity to do some really cool science. Perhaps before you know, consumer genomics companies will really be sequencing your genome for < $5000 or so (I am adding their margins into the price 
).
Technorati Tags: next-gen sequencing, genome sequencing, Intelligent Bio-Systems
The Blue Brain
November 27, 2007
IBM has always had a knack for killer research. Today’s exhibit: Blue Brain, the first comprehensive attempt to reverse-engineer the mammalian brain, in order to understand brain function and dysfunction through detailed simulations.
The project is as ambitious as it sounds. The goal is to mimic the behavior of the brain down to the individual neuron, and create a modeling tool that can be used by neuroscientists to run experiments, test hypotheses, and analyze the effects of drugs more efficiently than with real brain tissue. We use supercomputers to build climate and seismic models, so why not neurological models.
Technology Review has the details. Obviously there is a long way to go. The current point is only Phase I. In the future molecular and genetic level information will be added to the algorithms that generate the individual neurons and their connections. In other words, we could start simulating genetic neurological diseases. Sounds like science fiction, but it’s worth a shot and I do believe we will get there.
Technorati Tags: IBM, Neuroscience, Scientific Computing
Science continues to get more social
November 27, 2007
2collab, a service from Elsevier, which I received a demo of earlier this week, went live today, adding another player to the scientific social networking space. Richard Akerman has an excellent review over on his blog. As he notes, at this point of time 2collab can be compared to social bookmarking services like Connotea and CiteULike with Scintilla-like user ratings, but Elsevier seems to have larger plans for the service. While they don’t quite say which direction they will go, it is clear that their idea of “collaboration” goes beyond sharing bookmarks. Already the service has some fairly nifty features to set up public or private groups that could be developed around a specific collaboration, but given existing properties like ScienceDirect and Scopus, Elsevier is sitting on some excellent information resources which, combined with all the features for bibliography import embedded in 2collab, could form the basis for a collaboration space. In other words people could tee off collaborations based on a shared space in 2collab and continue to collaborate there. This could even be extended into a value-added paid service in the future if, e.g. you want to start storing information (images, etc) there. I am thinking Backpack-like functionality around a collaboration space of shared information resources like publications.
One thing that might be on Elsevier’s mind is competition with Nature, which has done an absolutely wonderful job of leveraging web 2.0 paradigms into science via properties like Scintilla and Nature Network. I don’t quite think Elsevier has the web 2.0 ethos down quite like the Nature folk do, but they do understand scientific research, which is why I hope they stay away from social networking and the information connectivities that Nature enables and focus on more formal collaborative relationships.
I have long been critical of Elsevier for throwing up pay walls around it’s publications. 2collab is free and open. It comes with an API, both excellent moves. Just imagine if the company would lower some more walls; the power of services like 2collab would only be amplified. In a closed environment, social bookmarking and collaborative research only go so far, and then you start banging into walls. Public/Private groups and collaborative spaces around open information are the way to go IMO. Let’s see how this falls out.
In a nutshell, 2collab is a good, well thought out and designed service in a field that’s getting a little crowded for a relatively small userbase (no Digg like traffic numbers here). I consider Elsevier to be competing with Nature, but I believe they should have a different focus to be successful (I don’t plan to leave Nature Network anytime soon). However, without opening up more of their properties, they are limiting the long term success of a very good product. I’ll be following the evolution of 2collab closely.
Technorati Tags: Elsevier, Social Bookmarking, 2collab
OSINT and pharma intelligence
November 26, 2007
In a recent Bio-IT World article, Jim Golden (CTO at SAIC) has written a very interesting piece entitled OSINT and the Pharmaceutical Enterprise. I suspect people outside the US are not aware of OSINT, but it stands for Open Source Intelligence, and has rather grim origins. In the aftermath of 9/11, it was recommended than an open source intelligence agency be created. This agency would focus on collecting actionable intelligence from publicly available information, leaving the CIA and others to focus on the cloak and dagger stuff.
Alright, so far so good. What does this have to do with pharma? Jim makes the argument that much of the information we need for sophisticated intelligence in the biopharma industry (for R&D, regulatory, sales, marketing, etc) is available in the public domain. This is the point where you go “what does this have to do with open source and intelligence?”. I agree wholeheartedly. This is no different from searching the frontiers of science, but with a fancier, more spy movie compliant name. That said, the rest of the article is interesting enough (just ignore the OSINT references).
IT systems to help create meaningful pharmaceutical OSINT in a meaningful way have not kept pace with more process-driven information systems
I think we all know that to be a fact
Every pharma company has invested in tools and techniques for enterprise-wide search, document discovery and management, knowledge management and business intelligence, and possibly even semantic-web type tools such as ontology creation and text mining. Such tools can play an important part in creating a pharmaceutical OSINT system to better inform company decision makers.
Very true as well. Sometimes it is surprising how much cool stuff is being done at various pharma companies, albeit often a little haphazardly.
Jim is completely right about one thing though. Technology is a means to an end. He argues that the central issues knowing what questions to ask and accurately determining what the right answer might be. I agree, but only to a point. If you have been following my Jeff Jonas-watching, you will know that the data finds the data. In other words, very often we don’t know what questions to ask.
In the article, Jim goes on to focus on two concepts, deep web mining and web 2.0, both subjects of much interest in these parts. I’ve referred to deep search in the past, and I completely agree that deep search has to be part of the biopharma intelligence effort, both internally and externally. That said, I think there is a lot of information that can be captured by mining the second part of the two concepts, what Jim calls web 2.0, and what I like calling the World Wide Web, and what will one day become known as the Giant Global Graph. Snarky comments notwithstanding, any pharma company not mining the world’s blogs, social bookmarking sites, etc is doing itself a disservice. Services like Lijit are part of my toolkit as a strategist for a reason. Combined with various mashup tools, one doesn’t have to invest in too much enterprise IT to get tons of information. Of course, if we can combing mining the edges of the web with powerful, smart querying, entity extraction and analytics, then we can be that much smarter about the information we get and the knowledge we derive.
While I think terms like OSINT are a little bit of an overkill for what to me is simply good business intelligence and data mining, I will be looking forward to the rest of Jim’s series. He is one of the more knowledgeable people when it comes to BioIT.
Further reading
Scientific intelligence is business intelligence
Technorati Tags: Search, Deep Search, Business Intelligence
