The best way to explain is through an example, as you suggested.
The first one is the Structural Genomics Consortium, which started with one pharmaceutical company joining a high-throughput technology-driven arrangement led by a Canadian researcher and linking up with the Wellcome Trust Fund, a group in Oxford University. That produces 25% of all of the protein structures available in the world, and that goes directly into a shared database.
Since then, eight pharmaceutical companies have joined this consortium, and we're now just entering phase three of its life. The interest from the pharmaceutical companies is that they get access to hundreds and thousands of things, whereas if they were just one-on-one with a research group, they would be doing 10 or 20 things. It's the scaling of what the technology can do. At scale this is incredibly productive and, as I say, is one of the most productive precompetitive research consortia in the world.
The other one, believe it or not, is in the energy sector. Four or five of the big Canadian-based oil companies have joined together in a genomics-based project, the goal of which is the remediation of tailing ponds and looking at microbial communities that live in the bitumen in the oil sands, trying to liquefy that oil and make it more easily extracted.
You can see why oil companies would think of that. It's a high-risk field. Who knows whether it's going to work or not? They believe in putting a few million bucks in there to see what the feasibility is, and they do that precompetitively, so the data is shared among everyone. Everyone has access to it, and then down the line they can be competitive. They can file their own patents based on work they would do in-house afterwards, and it's the same for the pharmaceutical companies in the Structural Genomics Consortium.
This is a model, and we can see companies doing more and more of this kind of work. It's not anti-IP, right? It's a precompetitive stage before the competition really starts, and it just speeds up the process. We know that pharmaceutical companies are struggling to get new products out the door, and sharing of data upstream will speed up that discovery process and allow them to compete down the value chain.