Category Archives: Comments

Closing down Freelancing Science shop

It’s finally time to close down Freelancing Science shop. I will post in a different place, under more general domain name and on self-hosted WordPress installation. Visit my new site over at

I’m moving because existing form and scope of this blog has been more and more frustrating. I’m going to continue experiments with different approaches to scientific career, but this is not going to be the main topic of the new site. Additionally, I don’t want to suddenly spam people who subscribed to this blog when I was more interested in bioinformatics with non-scientific topics.

The new site will explore large number of different fields, such as systems science, photography, dynamic processes, biocomplexity, memetics, but also the topics covered here, such as science 2.0, bioinformatics, structural biology or data visualization. If you aren’t interested in any of new topics, you can subscribe only to selected notebooks (categories).

Within a month or so, commenting will be closed.


Posted by on April 8, 2010 in Comments


Transitions, transitions

Quite a few things happened while I was away. If you’re interested, here’s not so short summary of my internet hiatus:

Research area

I think I’m done with bioinformatics. My current research area seems to be located somewhere between systems biology, theoretical biology and information/complex systems theory. I hope to build on Dawkins work, deal with emergence in biology and study subtle effects in biological systems. While I’m not sure if I will have anything interesting to show ever, I don’t have energy to do yet another project which involves programming/web interfaces/dealing with data/annotations/modelling etc. I’m done with analytics, time for synthesis :).


Last year I wrote a post dreaming about small non-profit contract research organisation. This model of Research-as-a-Service has materialized in a virtual research institute which we have finally launched few days ago (materialized in something virtual, sign of times? 😉 ). The setup is quite simple – the institute gets a project (or applies for such) and then it searches for researchers/institutions/freelancers which are willing to subcontract parts of the project. We have outsourced not only research part, even money gathering (writing grants, etc.) is done by external company. The setup is quite flexible and pretty transparent – for example, we may represent somebody’s rights, but no intellectual property is owned by the institute. Why such institution? We become a single point of contact for a large and diverse group of scientists, which are willing to do some research for real money but don’t have time and energy to hunt for gigs by themselves. While I have an academic job, I’m in the middle of transition from being a freelancer, to being a jobs provider for freelance scientists. More on that in some other post.

Open science

I plan to spend way more time on advocating open science (all of its flavors), but… in Polish. This step is out of large frustration that even prominent figures in Polish science have no idea about changes in the science internet-aware researchers are watching and creating. Knowledge about even basic things like Open Access is dramatically low in Poland (a number of people here equals OA with low quality publications which have not been peer-reviewed). With few friends, we have a number of projects in the pipeline (for example, we hope to launch a nation-wide, created by professionals  promotional campaign – bilboards, TV commercials etc. – for open science). If any of these actually works, I will let you know if we have any measureable success 😉 .

Labels, labels

Robert Anton Wilson tells a nice story in his book Prometheus Rising:

William James, father of American psychology, tells of meeting an old lady who told him the Earth rested on the back of a huge

“But, my dear lady,” Professor James asked, as politely aspossible, “what holds up the turtle?”
“Ah,” she said, “that’s easy. He is standing on the back of another turtle.”
“Oh, I see,” said Professor James, still being polite. “But would you be so good as to tell me what holds up the second turtle?”
“It’s no use, Professor,” said the old lady, realizing he was trying to lead her into a logical trap. “It’s turtles-turtles-turtles, all the way!”

Another story is a comment from my advisor about putting my real research plans in some proposal (he supports these plans):

The most likely a reaction from reviewers will be something like this: “Nice start, some decent papers, PhD looks good. And then he got crazy.”

I feel like screaming “Labels, labels, labels, all the way!” when facing stiff schemas of what scientists “is” or what artists “is” etc. It’s a hard task by itself to integrate multiple passions and multiple interests into a coherent structure. I don’t need another set of issues because of labels people attach to seemingly creative professions. But limiting myself only to topics consistent with the image of an online scientist became even more frustrating. Therefore expect that this blog (or any other venue I choose to express myself) is going to become a lot more diverse in topics and form.

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Posted by on October 28, 2009 in Comments, Research, Science and Art


Open Science: a step towards Open Innovation

Open Innovation is a catchy phrase, but I don’t think we are that close to it, as many people claim. Innocentive, InnovationXchange or NineSigma operate in the very small market, and this market does not seem to grow as fast as we would wish. Innocentive posted some statistics as of 2nd of June, 2009, so given these numbers and amount of open challenges, it’s safe to assume that as of today, around total of 1000 challenges were posted and ca. half of them were awarded. If you compare that numbers with almost 200 0000 patents issued only by US Patent Office in 2006, it gives a clear picture of the size of the market open innovation crowdsourcing companies (edit: as Jean-Claude points out in the FriendFeed comment, Innocentive and the other two companies mentioned earlier are rather crowdsourcing, not “open innovation” companies) are operating in. There are plenty of reasons why OI did not yet become mainstream (too many to list) and for that to happen, there are two important steps that we need to make first.

Open Science must become mainstream

I’ve been advocating Open Science for some time and I’m following Open Science luminaries for much, much longer. At some point it hit me that Open Science in its fullest form is not an issue that scientists can truly solve by themselves. Open Science crosses domain of Science – it’s an issue for Science, Politics and Business. We should experiment with various ways the research is done, collaborate openly, attempt to invent new business models to fund science and spread “open” meme as much we can. However, the real deal will be made between people in power from these three domains. Why this is necessary to achieve that before we may fully innovate in the open? Because in this step we will sort out all the problems we have today with intellectual property and technology transfer (both being not efficient enough for today’s standards). I cannot envision that happening in other domain – we are paid to collaborate and test ideas. This community is able to hit every major obstacle to “open” in a very short time. And once we have these obstacles removed there’s a next step:

Working models of Open Science should be tested outside of Science

In other words I postulate that whatever solutions work in domain of Science, these should be tested outside of it, in other domains. Not vice versa. Principles of Open Source software did not prove to be useful in open drug development (see Joerg’s post on the topic). Crowdsourcing will not advance quantum physics. Not all aspects of collective intelligence are working in Science. We simply need to invent working solutions within the domain first, and then test them in other domains, such as art or engineering. This step will provide another set of protocols, changes and adjustments that will allow seekers and solvers (to use Innocentive’s nomenclature) to work efficiently together crossing every domain.

Open Innovation is not a single step

I may be proved wrong by some genius that will solve Open Innovation proovedissues in a single brilliant step, but so far I believe that we need more than one to achieve this goal. And it is important to recognize that Open Science is a great opportunity to come closer to it. The sooner we realize it, the better.

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Posted by on July 2, 2009 in Comments, open-science


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Visual analysis in not only about seeing

I’ve just sumbled across this short video on work of Turkish artist Esref Armagan, born blind, who nonetheless paints and draws. I will let you draw your own conclusions – mine are briefly expressed in the title of this post.

Hat tip Mayer Spivack.

Reblog this post [with Zemanta]Update: if you cannot see video embedded, here’s a link.
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Posted by on June 29, 2009 in Comments


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The Future of (Life) Scientists

This post is directly inspired by excellent essay by Michael Nielsen entitiled “The Future of Science“. While Michael writes about science itself (and how openness will be playing big role in scientific process) I wanted to write few words about how and where I see scientists in a near future (or rather how the research will be done – I’m not even touching the broad topic of alternative careers for scientists). While it sounds like a complementary essay to Michael’s work, I wouldn’t dare to call it so – think of it as a collection of loose notes gathered over months of learning from online science community. Also, please keep in mind that it’s written by a biologist and as such biased towards life sciences.

It’s no news that academic environment has changed so much that a joy of research spans only small fraction of day-to-day scientists’ life. “Publish or perish“, bureaucracy, money hunting, lack of tenure track positions, impact factor, ever-postdoc are only few of many issues within academic system. There’s quite a lot of interesting initiatives that aim at improving the system and some of them will certainly succeed by solving directly some of the issues above or more likely, by creating a niche within academia in which these issues will not apply. However, I think in the long run academia is not going to be the main environment where the research is being done and more importantly, there will be infinite gradation of research jobs, allowing people from many different fields with many different skills to contribute to scientific projects.

That said, I also believe that amount of data and knowledge produced will lead to enormous specialization of scientists. This does not contradict the previous statement: I don’t think that some teenager will design and develop in his spare time a new molecular dynamics algorithm, but finding new genetic associations or inventing another way to modify bacterial genome so it has better biodegradation features sounds to me like a reachable project for many people. Specialization will be one of many factors influencing creation of new types of scientists. And what are these types? Let me describe a few.

Mind, brain, intelligence amplification – future Nobel Prize winners

This category emerged pretty recently, after reading Deepak’s post on uniqueness (or lack of it) of someone’s contribution to science. I always had this notion that no matter what I did, it would be done in a near future by someone else, but this time I could put it into words: science is like sports –  winner takes it all and there’s always a winner. Because prestige of an institution or fame of a scientist plays a big role in getting one’s research funded, competition for money will lead to development of procedures that will aim at producing Nobel Prize winners (or equivalents) analogous to sports training programs.

1933 Nobel Peace Prize awarded to Norman Angel...
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Techniques like neurolinguistic programming, biofeedback or binaural bits (just to name a few) are surrounded by such a hype, that it’s hard to believe they are worth something. However I think there’s a solid field emerging from these inventions that aims at dealing with issues we create in our lives. Have you heard that Google had opened School of Personal Growth as a part of the Google University, teaching things like mental development, emotional development, holistic health, well-being  and finally a Buddhist notion, “beyond the self”? I think it’s no mistake – it’s an attempt to help employees to consistently work at their optimal speed. And there’s story is published by Nature in April last year results of a poll of using brain-doping drugs among scientists. And there’s an inspiring talk by Juan Enriquez on arrival of Homo evolutis. I believe it’s just a matter of time big universities will launch (probably secretly) their own programs for training high profile scientists. And judging from the comments to the Nature’s poll I don’t think many people will object – science, unlike sports, doesn’t have to pretend it’s fair.

Getting research done – staff scientist

This type doesn’t require introduction. If one doesn’t have to waste time on advancing career and hunting for money, one becomes a very efficient scientist. Staff scientist positions are available in many countries and I wish it could be more of them in the future, especially in bioinformatics – where a single person can be trained to do everything from microarrays analysis to molecular dynamics in a relatively (!) short time (and become then a very important asset in the lab).

Experienced specialist – nomadic freelancer

Nissan_NV200 photographed in Tokyo Motor Show 2007
Image via Wikipedia

This is category I was aspiring to. Here you can read little details how I tried, and here when and why it failed. I still think it can be done, although not in every field and not all the time. My hope was that telecommuting is the future of freelance scientists, but Bora offered entirely different solution: co-researching spaces/science hostels:

A coworking space has three important components: the physical space, the technological infrastructure, and the people. A Science Hostel that accommodates people who need more than armchairs and wifi, would need to be topical – rooms designed as labs of a particular kind, common equipment that will be used by most people there, all the people being in roughly the same field who use roughly the same tools.

From what I’ve seen, people doing structural biology (especially NMR-related research) tend to enjoy similar to a freelancer status: they can do a crucial high tech task, which takes no more than several weeks to finish and often the task is needed so rarely that there’s no point in employing the specialist  full time (or to do in-house training).

The main disadvantage of this mode is something called “consultant’s dilemma” (hat tip Harold Jarche): when you’re working you’re not generating new ideas or business, and vice versa.

In a  failure of interdisciplinary approach – translator, integrator

I expect that lots of people will disagree with me on that, but I think on the long run interdisciplinary approaches are going to fail. The area where a reason for failure is most visible is genome sequencing. Deep knowledge about single simple organism such as bacteria is beyond capability of most (if not all) laboratories and teams and that’s why publishing a genome is just a starting point, not end to a process. It takes years of work of experts in their own small fields to extract all useful information from the single sequence.

Once this situation becomes more of an issue, scientific translators may emerge. Such person will track scientific literature in two (or three or four, such as language translators) small fields and will tell group of researchers from one field what important has been published in other field. Will similar service become part of libraries or such people will become independent consultants? I have no idea.

I don’t think that gaps in knowledge will be corrected by talking to colleagues or by review process. Here’s a perfect example (in used-to-be prestigious journal): neither authors nor reviewers have noticed that the structure containing so-called trimerization “octads” is a perfectly fine, quite regular, heptad-based coiled-coil (you guess it right, these “octads” were separated by six residues, giving together fourteen – two coiled-coil heptads). It was already visible in the sequence figure – but only if you knew that things like coiled-coils exist and were already studied by Francis Crick. After almost a year and a half correction wasn’t submitted which means the community does not care either.


As soon as we have our own Paul Graham and a clear, well-described path of how to make a startup in life sciences successful, we will have a bloom of bioentrepreneurs. Life science is a field comparable to high-tech, not software industry. It requires different skills and different approach, but no one has so far put it into words that we can follow. Also, we need more hardware providers in area of life sciences. If you want to build a mobile phone, it’s a matter of days to order its every single part. If you want to build your own sequencing machine, I wish you good luck, because it will take considerably longer (you need to wait until respective companies are built and offer their products).

Nevertheless, I’m sure it will happen. Streamlining life sciences is something that lots of people are talking about.

Clean data needed – biocurator

The more data the more errors. Recently, I’ve stumbled upon interesting functional annotation of a protein: will die slowly. Search on NCBI reveals few dozens of proteins with such annotation. This is a terse description of a phenotype, however I don’t think should be used as a protein name. Paul Davis suggested that this propagated from Drosophila, since fruit fly gene names have a long history of names blurb:

Early work refers to the gene as fruity, an apparent pun on both the common name of D. melanogaster, the fruit fly, as well as a slang word for homosexual. As social attitudes towards homosexuality changed, fruity came to be regarded as offensive, or at best, not politically correct. Thus, the gene was re-dubbed fruitless, alluding to the lack of offspring produced by flies with the mutation.

It’s nothing new that to reach holy grail of many fields (text mining, ontologies, automated discoveries, predictions), we need manual curation of biological data (even Wolfram Alpha is based on curated data). Similarly to staff scientists, biocurator jobs are already appearing in science job listing.

Science as creative hobby – “not even a scientist”

In the introduction I’ve mentioned a teenager inventing new genetic modification of an organism. While to some it may sound difficult, unquestionable success of iGEM competition shows that it doesn’t require 20 years of research experience to come up with such ideas. Lots of knowledge and lots of data create opportunity for people outside academia to jump in and make a valuable contribution. The necessary requirement in “openness” – as long as the data and publications are freely available, there’s a space for outsiders.

I expect (or I hope) amateur science to grow in the following years – especially in the less bureaucratic countries. If we don’t see many of such examples yet, it’s the education system to blame – kids don’t realize that remixing data and remixing video are very similar things that differ only by a target audience, but both can be cool :).

Knowing your position – “lighthouse” scientist

Lighthouse’s primary role is to assists in navigation – it helps you find your position on the map. Lighthouse is not a point of reference – as a point on the map is usually no more important than any other points. Lighthouse helps you understand where you are. Tech crowd has its own “lighthouse” people, for example Tim O’Reilly. Our small online science community has Bill Hooker. Neither of them seem to have outstanding resume (sorry to write that, I’ve seen better ones), but to understand where you are it’s worth to pay attention to what they say. They seem to understand particular part of our world much better than anybody else.

To put it in other words, a lighthouse scientist isn’t necessarily a person with the biggest achievements or a person who has a brilliant vision of the future – it’s a person who sees trends and movements, has a wider perspective and most importantly knows what’s important. In recent discussions on the blogosphere about bioinformatics as a field of science, Sean Eddy didn’t express his opinion – which I think is a very meaningful response.

Final thoughts

I’ve sketched this map to organize lots of thoughts and discussions around future directions of science. It is far from being complete and full of wishful thinking, but still helped me to wrap my mind around couple of issues in this area. Probably the most important thing I’ve realized is what was put into introduction: that the future may open lots of options for people willing to stay close to science. Those who realize this will benefit from them as first.

Update: there are interesting comments over at FriendFeed already.

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Posted by on March 26, 2009 in Comments, Community, Research


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What would you (do you) teach your kids?

Image via Wikipedia

This post is inspired by a question Iddo posted over at FriendFeed, in The Life Scientists room:

Teaching my 7 year old Logo (using kturtle). Any ideas for a good programming book for kids?

Other than programming, what would you (or do you) teach your kids? What kind of skills science geeks consider important, that aren’t really tought in schools (at least not at the level you’d want schools to teach them)?

My first thoughts were about remixing digital media, 3D modelling and printing (I believe 3D printers will become quite cheap in few years) and technical side of photography but I didn’t really spend much time on this topic (it’s obvious from this list). What’s your opinion?

UPDATE: Feel free to comment on this post’s FriendFeed thread.

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Posted by on March 8, 2009 in Comments


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(Do not) Beat ideas half to death

This is short post/note to self – to see if the way I think about science today will change in couple of years. Its enigmatic title comes from Stu Jenks, one of my favourite photographers. He wrote in the introduction to his works:

I’ve been doing a series of spirals. You know how it is with us artists. We take one idea, and then beat it half to death.

If we substitute “artists” with “scientists” it still sounds true. This is efficient (in modern terms of scientific productivity) way of doing research, but probably not always the best one. While I know that many breakthrough discoveries in science were results of years of hard work, not all of them required fifteen years to establish a procedure only. So, the question is if rapid switching between fields (every few years or so) is a good idea? It probably depends. Ask me in a few years how it works in my case.

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Posted by on February 17, 2009 in Comments


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Timestamped FriendFeed activity – really public “profile”

Accidentaly, I have found a simple way for obtaining a time stamp for each entry and comment any person with publicly available lifestream makes on FriendFeed (except “Likes”, which do not seem to be timestamped at all). Activity of semi-randomly choosen person during the day (summarized over couple of weeks (!))  is shown below:

FriendFeed usage during 24 hours, summarized over couple of days.

FriendFeed usage during 24 hours, summarized over couple of days.

While relation between AM and PM periods is correct, time-zone is manually shifted, so it’s more difficult to guess who’s this activity is (but it’s not Robert Scoble if you want to ask). What does it tell? Basically, this person does not close FriendFeed window for the most of the day. Additionally, there’s a period of the day in which “catching-up” has place. Nothing interesting so far? Original data has much more details. It is possible for example to collect information when during the day particular person usually watches videos on YouTube. Guess – is that during working hours? 🙂

Ability to get that data for couple of weeks back without any trouble (I didn’t need to track this person’s activity for such period) was kind of disturbing. I knew it’s very simple to start tracking my habits, but I wasn’t aware of the fact that it’s also easy to see what I was doing over the last three weeks. Do you think it makes a difference?

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Posted by on January 29, 2009 in Comments, Visualization


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End of freelancing as scientist (for now)

The patchwork landscape of Masuria
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Almost a year ago I wrote a post about officially becoming “freelance scientist”. I didn’t really know what I was doing, but taking over the world from a small flat in the middle of nowhere in Poland sounded like a good idea. And it definitely was a good idea, however not in a way I thought it would be. Today I am hoping that all things will go fine and I’ll be employed since February in a calm academic environment.

What I aimed for?

My plan was to become freelance scientist – to be able to thrive financially and intelectually without relying on gaming grant systems. I had hoped to secure support from private sources, form a virtual institute and live happily in the middle of nowhere while still having an impact on the world’s science, possibly all under “open research” badge.

What didn’t work?

Side comment: if you read excellent piece by Hugh MacLeod entitled “How to be creative”, you shouldn’t find the issues below surprising :).

The main reason I started to look for a job already some weeks ago was that freelancing as a scientist turned out to be unsustainable financially. And don’t get me wrong – money wasn’t an issue, as long as I was willing to put all my time into other’s people projects. All. My. Time. Booking some time to work on my own ideas meant burning savings at a quick rate. But I had to work on my own ideas. I didn’t feel like I’m learning very much, because I worked on things I was already quite good at. Intellectual stretching was not that big.

Because of the issue above, I’ve put together far less work than I aimed to. I have lots of posts, manuscripts and presentations which I didn’t have time to finish. I was too busy doing freelance work, finishing the projects I had promised to do, inventing new projects and hiding under a bed worrying about where this is all going.

Working in the middle of nowhere was a plain mistake. It sounds nice, but f2f networking (“showing up”) is far more important than I’ve thought. Working in Poland is an issue on its own (no matter if you’re a freelancing or an academic scientist); working outside of any major city makes it even worse.

Partially connected to the former issue was the fact that I tried to do all things alone. Wrong. Very wrong. Things like virtual institute will not work, unless there’s a team. Period.

And finally, I didn’t give myself enough time to make the whole system work. It turned out that I had no idea about so many things influencing money-flow in the system, that it’s not surprising at all that it didn’t click in so short (12 months) time.

What worked?

One of two biggest advantages of this crazy 12 months was that it was a great learning experience. When I look at my older colleagues working in academic environment, I’m pretty sure they don’t experience “felling like an idiot” moments all that often. Such moments happen quite frequently in grad school, but seem to become rarer the further science career advances. On a contrary, I had such moments all the time in the last year. I was experimenting with blog posts, stupid ideas, unbalanced opinions and I was scared as hell each time. And I have learnt much more than I would do playing safe. Have you watched Ken Robinson’s talk at TED? He put a beatiful phrase – “prepared to be wrong”. Keep that in mind.

People were second most important factor here. I was amazed by a number of people that have helped me along the way. Lots of them have encouraged me, pointed to useful resources or invested significant amount of time into answering my silly questions. Many times I was blown away by the help I had not expected. Biogang/Life Scientists community rules.

Frequently quoted phrase from Bill Hooker’s essay, “I’ve never had an idea that couldn’t be improved by sharing it with as many people as possible — and I don’t think anyone else has, either.”, turned out to be absolutely true. Each time I presented my ideas, people were interacting with them, not judging them. I was given suggestions I would not come up with by myself, even if it was clear that we’re not going to do business together.

What now?

The job I hope to land next year is going to address the things I’ve written about above. I hope to have some financial stability and necessary time to advance my plans. It will also provide a support for such events like “Startup weekend in science”, which I plan to invite you all later next year.

The main goal is still valid and I don’t give up on it. I’ve found (or rather the other way round) a real-life example, ProTech Institute from Lithuania, which means that it can be done – it’s just a little harder if you’re a (still,  but not for long) PhD student.

So it’s end of freelancing for now. Lessons learned. Back to real-life™ again :).

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Posted by on December 9, 2008 in Career, Comments


Thinking about RaaS: Research-as-a-Service

The research li...

Image by Getty Images via Daylife

Instead of disclaimer: this is a bunch of loose thoughts on an element of a possible future of research. I’m only touching some issues here and still I don’t have coherent vision of the commercial side of research. So, feel free to show me I’m very wrong – you’ll save me lots of time of coming to your conclusions :).

According to Wikipedia, Everything as a Service is a:

concept of being able to call up re-usable, fine-grained software components across a network.

While the most common example is SaaS – Software as a Service, this concept can be applied to other functions such as communication, infrastructure or data (the last one sounds very interesting). It recently occurred to me, that investments (or maybe I should call these partnerships) of biotech and pharma companies in academic research institutions are good examples of RaaS, Research as a Service. I think every situation where the research is done after the agreement (buying or licensing patented innovation doesn’t qualify) can be called RaaS.


To a company, there are obvious advantages of hiring scientists to get the research done, but I think there also would be plenty of good sides of such arrangement for us (of course I have no experience yet). Probably the biggest plus would be money and ability to get them in somehow predictable manner. I think it’s also important to be stretched intellectually from time to time (I assume that easy things aren’t worth outsourcing).

Many flavors of RaaS

Paying to an academic institution to come up with a new drug candidate is only one of many types of RaaS. There’s researching a given problem (something Innocentive or Nine Sigma are coordinating), coming up with an innovation (drug candidate example), providing expertise (consulting) or innovating and delivering (designing, building and implementing new machine, workflow or pipeline). We could find examples of all types happening everyday, but probably not in all scientific fields. Delivering something in biology is usually quite expensive and time consuming, while consulting gigs in quantum physics don’t appear all that often.

The point is that all these RaaS flavors can and are applied to academic institutions. In other words, many researchers provide commercial services using time and equipment paid from taxpayers money. And I think it’s not an issue – even more: it should be finally admitted and accepted (so we could get rid of the artificial division of researches into academic and all others; but that’s another story), and organized, so we could provide such services easier and more often.

Resources all over the place

The Health Commons project aims at building a framework that could help in sharing and organising research process aiming at developing new drugs. We seem to have lots of elements of such environment in place – we have many (or even too many 😉 ) scientists, some service providers, data centers and some work done on standards of operations and information exchange. If we forget about drug development, not much actually changes. We have workforce, some services aimed at researchers and lots of tools that help in communication in both directions.

Here’s example of research scenario: if I were to market a genetic test that identifies mutations resulting in oversensitivity or resistance to a drug (something which I believe will be the next hit after screening for disease markers), the whole research part wouldn’t require any significant involvement from my side. CRO (contract research organization) would take care of identifying patients with specific conditions, sequencing company would get me their genomes (currently $5000 each, but the price is dropping very fast) and as far as I know bioinformatics community, finding people to analyze the data wouldn’t be an issue at all. While such scenario is a bit too optimistic (I skipped lawyers in the process), we already have resources to make it happen.

Where is it going?

I imagine future RaaS provider as a small company (I’m not yet sure if a non-profit organization is a better fit for people interested in doing research; also, I don’t know how fast the issue of academic-commercial blur can be solved) made by a few scientists from different but closely related fields. The reason I see it small, is about mobility. And I don’t mean here physical mobility (which BTW may be required on some occasions) but mobility of focus – the main advantage of small organizations.

I imagine such company would be able to do consulting (and data analysis, maybe on the RedMonk model) and innovate at a software level. It would be able to do the work on site (small group again) and deliver the results quick (“bursty work”).

Pieces of this vision come from old Deepak’s posts and many FriendFeed discussions. I actually think about putting it into practice. What do you think I am missing here (other than marketing 😉 )?

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Posted by on November 3, 2008 in Comments, Research


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