Applying open source methodology to disease research could speed up the process of drug discovery, according to researchers at the University of Sydney.
Dr Matthew Todd, senior lecturer at the university's School of Chemistry, said that the current method of drug discovery is extremely competitive and mostly carried out behind closed doors to protect certain ideas and any commercial benefits down the track.
University of Sydney researchers are openly sharing their lab notes, primarily through a blog - The Synaptic Leap - as well as Twitter and Google+ and currently have around 15 contributors to a malaria project that is in pilot stages.
"Drug discovery is a complex process involving many different stages and the open source method has huge potential for improving the early phases before clinical trials have commenced," Todd said.
"It works to a certain model which involves research done behind closed doors where nothing is shared outside of an organisation, like a company or university," Todd said.
"Eventually, way down the line, the work is published and if there is something interesting in there, it's usually patented before it's published in order to recover costs otherwise others can just take your work and use it for themselves."
Todd labelled the open source movement as "transformative" and compared the way proprietary software development is carried out behind closed doors, in contrast to open source programmers that co-ordinate and share their code and ideas.
"What we're proposing is that while you're doing the work, you release everything onto the internet as you're doing it so everyone can see it and by doing that you allow people who are not part of your core team to input whatever they want, they can advise and they can get involved in the project.
"This is exactly the way the software works; it means anybody with a computer can help out and in the case of our project, anyone who is reading what we're doing and has access to a lab in particular can just start making molecules and get involved."
According to Todd, the whole incentive to applying the methodology to drug discovery is getting a result quicker, although no drug has been discovered using the open source method to date.
"If you've got a problem and you want to solve it you need a lot of people looking at it and basically our approach is exactly that, so if you want to solve a really difficult problem like finding a drug for malaria then you need more people looking at the problem and you can't do that if you work in a patent system where you're secretive."
There are numerous barriers to the adoption of the model, Todd said, all of which he argues are psychological.
"One is that in academia we are rewarded for our publications and the things we put in journals and we have to be in charge of our own publications and produce things from our own private lab because we're competing with each other and we need to be graded in competition with the people around us.
"In an open sharing model it's more difficult to work out who has done what and who is in charge of a certain project and so it goes against the model of academic publishing a because you end up with papers that lots of people have contributed to."
Another issue is the potential for the theft of ideas, he said, with the absence of patents enabling anybody to exploit the work academically or commercially.
"One of the misconceptions about doing work like this is that you can't publish in an academic journal but we've shown that's not the case," he said. "Also in academia in general, you don't publish negative results but we're publishing everything which we think is important and much better for the discipline I think."
Todd has previously applied the open source approach to a project which focused on making a drug for the parasitic disease, Bilharzia.
"We solved that problem much faster because we had everything open source and we had a bunch of advice and help from people, particularly companies," he said. "We discovered the way of making this molecule which is now being looked at by a company to scale up.
"We had about 100 contributions from people from outside of our core team at the University of Sydney and about 75% of these were from industry so the minority of comments were from academia which was surprising, I expected academics to get way behind the project but it's as though they were more secretive than industrialists."
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