Observations on big and small collaborations

Its been a pretty hectic year to date with several grants coming to their conclusion and the need for writing up final reports and manuscripts. In addition it has provided just a little time for reflection. Pretty much everything I am involved in is a collaboration of some sort so I am just a tiny piece of a pretty complex puzzle. Some of the collaborations are small scale (one or two labs) while others are much bigger (MM4TB ~20 labs). In the latter case I have noticed as we got further into the project the sense of collaboration really took off. Which likely suggests that funding a group for 5 years is really too short because just as they get into their stride the project will end. I think this is probably natural as it takes a while for researchers to get to know each other and the more moving parts, the longer this takes. Initially within such a collaboration groups likely self organize with those they know already or feel comfortable with. But how do you get a big team to address a complex set of objectives, to think as one? Does this also suggest there is some optimal group size for collaboration? Possibly. What do you need as a core team for a drug discovery collaboration? Obviously it may depend on the disease to some extent. Take TB. You have in vitro screening, molecular biology, structural biology, medicinal chemistry, computational chemistry, ADME screening, in vivo testing skill sets / components. How many people are needed for each component? Do you need duplication of resources to verify what is seen in multiple labs or cover for illness or problems with experiments not progressing etc? There are a lot of questions. Ideally in a collaboration / project everyone should know each other before the start and be comfortable with your colleagues and this may mean understanding everyones strengths and weaknesses. It is also likely you need at least 2 of everything so this would suggest about 10 labs. This is much closer to the NIH ‘center grant’ type model. Too many groups and collaboration may only happen in small clusters, too few groups and everyone is overwhelmed.

If I was to do something like another large scale collaboration (e.g. MM4TB, which has been an amazing and productive experience to be involved in) I would probably tackle TB from my personally biased direction. Namely, use all the TB knowledge we have accumulated and use the computational models to identify new in vivo active compounds (start with in vivo and not in vitro). I would also combine with some structure based work, docking known in vitro whole cell actives into TB targets as a way to de-orphan compounds. There are literally thousands of HTS screening hits from whole cell screening but there have been minimal efforts to identify which of these have in vivo activity. For all the faults in the old in vivo TB literature data I would use it as a resource from the beginning. There would also be very tight loops between prediction and testing and then updating models. So future collaborations in TB should have a bigger computational and modeling component to compliment medicinal chemistry and biology aspects. While I think smaller scale collaborations do a better job of balancing the experimental and computational aspect, they often lack the breadth of the team you get in a big collaboration. You miss out on that accumulated knowledge. It will be interesting to see if any of these ideas are addressed at next weeks TB Gordon conference. Of course the team size pretty much depends on the grant source. STTR and SBIR funds will dictate small scale collaborations while bigger center grants and the past FP7 funding from the EC has lead to the larger scale TB collaborations. I am still learning from exposure to these kinds of projects and time will tell which will have long term impact. Either way, we need to focus training students to work well in collaborations.

It also occurred to me perhaps these observations could be useful for other diseases and drug discovery. For example in PubMed there are similar numbers of references on drug discovery for TB as for bigger diseases that we think of such as cancer, depression etc (see the rough figure). While admittedly much of my recent work has been on more neglected or rare diseases (Charcot-Marie-Tooth, Ebola, Chagas disease etc) , could the general ideas for a collaborative drug discovery team gleaned from TB be applicable to smaller and bigger diseases? This has implications because it may point to ways in which we can equalize out the effort to spread more resources to the thousands of rare diseases.  Perhaps young researchers will self organize and work on the rare and neglected diseases, but there has to be funding there for small molecule drug discovery. We cannot pull the money from such collaborations as we are seeing in Europe. This perhaps is something that could be expanded as a future topic. How do we learn the best ways to collaborate and pass these skills on to the next generation, and make sure that all diseases benefit from these efforts.

diseases fig


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