Open access vs Paid access in scientific literature: Can there be a middle ground?

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Recently Prof. Michael Eisen, the founder of PLOS One and an open-access science-publishing evangelist, made a rather startling revelation in his blog post[1] as to why he, as a founder of such a model, is seeing the merit in reverting back to the paid-access model; and admiring the haloed halls of big names in scientific publishing like Nature, Science and Cell.  YES! He made an April Fool's prank and made me bite into it !#%$ :D. Jokes apart, the article did tend to bring about the whole issue of access to scientific literature and the business model (yes there is one!) surrounding it.

To aspiring scientists and researchers, getting access to published paper simplistically relied on the institution where they worked. Who cared who paid for it, right? Well! As we all know there is no free lunch. But then, it leads us into the whole thing behind the rising costs imposed by the publishing houses, their conventional stronghold and the whole movement that led to the current level of open-access publishing. It’s a long discussion and I would leave that to the discussion in the comments below. Yet I can try to summarize it.

Frankly, this is a very touchy issue. The ecosystem of access to published literature and scientific publishing is not the same as it was back in the day. Biol. Abstracts/Chem. Abstracts/Current contents anyone? Someone paid for it and it was a painstaking process to spend long hours in the library. Today, a personal computer in the lab and access to Pubmed and Internet has changed everything.

I got a chance to understand scientific publishing early on when I tried to start a concept journal at Georgetown University. In the process, I quickly gathered the rudiments of the world of scientific publishing, the major publishing houses and the way scientific world blissfully, yet precariously, hinged upon. I was seeing the growing wave of open access publishing and had my own points to grind. I realized a few important things

It cost to publish. Even in an online world somebody had to maintain the servers and 24/7 accessibility. This is besides the cost to maintain the editorial team to maintain a semblance of presentation and readability.

The peer-review system was paid nil. Yes! Nobody ever realizes that they form the bedrock behind the whole edifice of scientific publishing. Even being an editor was not so financially rewarding. Tell me how many of us have been paid by a journal for peer-reviewing (besides having an ego trip). Even being an Editor has not been such a financially rewarding one for many.

Yet, it also cost the institutions their arm and leg to have institutional access to haloed publishing names. Not every University or research institution could have access to major journals. So, if a post-doc from an under-funded institution could not access a paper, he had to suffice with the ‘abstract’ from Pubmed and make his argument. So much for integrity in scientific publishing.

Internet publishing was beginning to boom and driving down the costs of publishing. Suddenly every academic could dream of being a self-appointed ‘Editor’.

So this kind of laid the basis behind the open-access movement and its evangelists. With the boom of internet and cheap publishing online, every wannabe had to be an open-access. Just borrow some server space and quickly assemble an editorial board (easy right!). After all, many languishing academics are waiting there. Peer-review system got killed. They were always the unpaid yet overworked group while being the most crucial in the line of defense against biased work. Remember! Just instruments and data don't make up science paper. Evaluating the claim in the paper calls for a separate skill altogether. Speaking of which, the peer-review system has been virtually hijacked. Be it the publishing houses that keep their roster of ‘resident experts’ (who searches and maintains an unbiased panel do you think) or open-access houses which are yet to develop any standards in maintaining one. Any wonder why the general public is skeptical about any ‘scientific’ claims!

This is a ranting that can go on. But a solution has to be worked upon. Remember a couple of crucial yet counteracting points...

Funded work needs to be accessed by everyone (at least affordably). Also, if it is funded by the taxpayer, then everyone should have access to it.

Nothing comes without a cost. OK... that was a ‘duh!’ kind of philosophical thing to say and yet so very real! Remember it also costs to maintain a good peer-review system besides sucking up the publishing costs.

Technology changes and will hence greatly affect the access to scientific literature

So where does that leave us? It is armchair logic, yet so relevant, to say develop a business model that does not bleed the underfunded labs while sustaining the publishing houses and its haloed peer-review system.

But, it is not so hard after all. An open forum consisting of academia, publishing houses has to set open-industry standards that adapt to changing times. Whatever has happened in such a name has been closed doors and informal, and has not got us anywhere. Period. Let a discussion like this focus on these points (and ones I haven't yet brought up) rather than simplistically arguing open-access vs. paid-access. Science demands it! I am trying to keep the points crisp simply because a whole thought process gets underway.

[1] ‘Why I, a founder of PLOS, am forsaking open access’ – Personal Blog of Prof. Michael Eisen, Univ. Berkeley – http://www.michaeleisen.org/blog/?p=1580

(c) Copyright - . All rights reserved. No part of this posted material may be used without direct consent from the author - Natarajan Ganesan

Bioinformatics and the race for the $1000 genome: How ready are the start-ups?

Section Contents

1. Watson had his genome sequenced – So what?
2. Commercializing Bioinformatics– Where is the market?
3. Business in an open-source era
4. Blueprint for market entry and further growth

Image source: Wikipedia - http://en.wikipedia.org/w/index.php?title=Image:Genetic_Variation.jpg&oldid=210884296


1) Watson had his genome sequenced – So what?

James. D. Watson recently had his full genome deciphered; he was the co-discoverer of DNA structure in the 50’s[1]. In other words, technology has rapidly moved beyond sequencing the ‘generic’ human genome to sequencing each and every individual’s entire genome on a routine basis. To scientists this means a gateway to an era of personalized genomic medicine and to the Pharma this means, marketing those individualized medicines.

What does this mean for Bioinformatics companies? What exactly are bioinformatics companies anyway (in this age of open-source information)? Are they different from Biotech companies? Do they have any markets? If so, how would their globalization plans look like? To understand this, let us fast forward to 10 years from now (probably even sooner!) – your health care practitioner prescribes a full length report of your genome sequence. Well, what does he do with it then – or for that matter the diagnostic lab he sends the report to?

This is where Bioinformatics companies and their products will step in. These software products/solutions will help process huge amounts of voluminous sequence data and run them against public and private databases to fish out medically relevant information. Simplified interfaces like Sequerome[2] will vastly aid research scientists and lab technicians scrutinize data in a seamless fashion. Thus, the Biotech and the Bioinformatics industry are different in that they involve different scopes. The products of the former help the growth of the latter.


2) Commercializing Bioinformatics! – Where is the market?

Well…already many Bioinformatics companies have started defining their niche and expanding their markets. The consumers span across institutions from all the countries. The products range from straightforward software suites (e.g. Redasoft[3],) to enhanced content providers (Ingenuity Systems[4]). By early 2000 itself, there were a reported number of 50 companies into the market and the estimate of this industry was in the tune of $1.4 billion in 2005[5]. They have been estimated to grow at an annual rate of 15.8%. Numbers apart, there has been a explosion in the growth of the Biotech industry over the past few years and consequently the requirement for commercial software for processing the data generated out of this technology. This has been further accentuated by the large scale projects in academic R&D in the last two decades.
Thus, when viewed in terms of market entry modes for a new Bioinformatics start-up there are enough proactive stimuli –

1. The products are unique – Each software tool does a specific function and has its own niche. Even if the market is saturated with all the tools, there will always be new concepts that handles data in many different ways.
2. There is exclusive information – Highly processed data is unique to each lab group, scientist and the project involved.
3. The market size is virtually untapped – Despite a healthy growing market, there is a vast unmet need among the scientific community. Consequently there is a great potential for profit advantage when the market is utilized strategically.
4. Economies of scale – The demands for creation and maintenance of software/enterprise solutions parallels with that of the software industry which is already an industry in its right. The question is that of the market and how it can be strategically tapped.
   

3) Business and markets in an open-source era

Initial estimates of the market in 2000 were more than $ 2 billion and the market was not even tapped. Yet, all the promises held by the industry have not seen its fruition in fullest in all these years and this has been in part due to the emergence of open-source projects. Practically all the major databases and crucial software is available for free to the researchers. Some of them are even fully open-source in that it is possible to download the source code and modify it to suit the needs. So, why would one want to purchase software when a public domain makes it an open access?
In short, the challenges faced are virtually identical to the software industry with the exception that the concept of open-source is more recognized and appreciated (for the sake of science, of course). This has left the industry scampering for new ways to generate revenue. Software solutions have started looking to enterprise solutions and funded projects. However, there exist R&D areas like drug discovery, modeling and simulation which continue to command their market. Dedicated bio-software companies like Accelrys[6] are the main players in this market. Pharma and Biotech have their own in house projects that are often proprietary. Another area is academic and institutional licensing. Some of the key drivers in this area are the cutting edge research carried out that rely crucially on Bioinformatics solutions, while proper funding remains one of the chief constraints.


4) Blueprint for market entry and further growth


It is well known that globalization has become one of the most strategic issues for marketing managers, and nothing could be truer than the case of a bioinformatics start-up. The industry is such that cost-input simply involves covering the programming and maintenance, while profits are there to be reaped from every corner of the world. However, if it were indeed so, why is it that the industry has not grown the way it could have OR why don’t we have any major players (besides the offshoots from R&D of big companies)? Could it be possible to overcome the open-source environment and look at a good model to capture the world market? Or is it simply that industry is so nascent that the time is not yet ripe to aim global? At best, there are players like Accelrys who have to crucially depend upon heavily funded groups with big projects. In other words, no other players have come up to pick all the low hanging fruits. The following matrix depicts the competitive strategies for new start-ups in Bioinformatics products.



The strikeouts represent the cases not applicable to any Bioinformatics company at present (given the nature of the business) and the arrow represents the direction in which startups and midsize companies should aim to move. The market is such that pressure/incentive to globalize is high, given the inherently international userbase of the industry. Hence the natural evolution of a small company or a startup should be to switch very quickly from Dodger to the Contender status.




[1] “DNA pioneer Watson gets own genome map”; - by Nicholas Wade, Int. Herald Tribune, June 1st 2007 http://www.iht.com/articles/2007/06/01/america/dna.php
[2] “A web-based interface facilitating sequence to structure analysis of BLAST alignment reports”; Biotechniques (2005), Vol 39(2), pp186-188
[3] Redasoft - http://www.redasoft.com/
[4] Ingenuity Systems - http://www.ingenuity.com/
[5] “Global Bioinformatics market …$3 billion by 2010” – Medical informatics news - http://www.medinfonews.com/ar/1h.htm
[6] Accelrys Inc - http://www.accelrys.com/

(c) Copyright 2008- . All rights reserved. No part of this posted material may be used without direct consent from the author - Natarajan Ganesan

Cone of Probable Path - Reconciling fate, probability and butterfly-effect

Hello Readers,

Help me with the following thought process as I try to reconcile the most probable future event from a given current event.

As you read on, you may tempted to take your own examples; I prefer to stay with a simple one - A Running Race frozen in time and the fate of a runner from there onwards. You may want to take other tangible examples like that of share price of a company in a stock market or fate of economy of a country from one point (if you are that ambitious).

The "Cone of Probable Paths" (as I like to put it) is more a set of postulates. It tries to reconcile fate, probability and possibly butterfly effect... I have pasted them below. Just read them for entertaintment - If possible try to respond helping me with the thought process. I moderate the discussion just so that we try to stay on course of the discussion.

1. Every occurence of an event sets in motion a Cone-of-probable-path (COPP) that, in turn, defines the next course of probable events.


2. The center of the cone represents high probablity and hence least effort to travel between two event points.


3. Consequently, the periphery of the cone represents path of lesser probability and hence greater effort to traverse the events.


4. Whether delineated or not, there exists a definite cone-of-probable path between any two event-cones. e.g. arriving at one event point from another always involves a cone of probable path.


5. The cone of probable path changes continuously as events occur in an event-chain. The COPP is also influenced by apparently unrelated parallel events occuring elsewhere.


6. While it is most often easy and possible to define the central part of the cone of COPP, it is often difficult to quantify the peripheral parts of such a cone.


7. A miracle may be regarded as the least probable path between two event-cones lacking valid documentation to define the cone-path.


8. In other words the event chain is like a sublimation process in physics.


9. Simply put, a miracle doesnt exist.

In short, I regard the future of any current event as a seed for probable future events (some more probable than the others). As a result, I envision a Cone of Probable Path (or Cone of probable space times) originating from every event, with the central part of the cone representing most highly probable paths.
(c) Copyright 2008- . All rights reserved. No part of this posted material may be used without direct consent from the author - Natarajan Ganesan