From today’s NYT, here. We have a long way to go in neuroscience.

One of my colleagues asked me the other day what I thought the opportunities were for using quantum computing in the biomedical application space. My answer was pretty skeptical. It’s easy to see how AI has paid off for life sciences. Not so on how quantum computing will make a big difference. I’d love to be wrong though. Could quantum computing allow us to predict the trajectory of a viral phenotype accurately? Could we automate rational small-molecule design? How will we use our quantum computers?

The question I’m asking is whether universities and academic medical centers actually make money on federally-funded sponsored research through the recovery of indirect costs. It’s a fair question: indirect cost rates vary greatly by institution. They are nominally paid by the US government to allow institutions to recover the costs of keeping the laboratory space functioning as a venue for conducting experiments. The indirect cost rate for a given institution is the product of a bi-lateral negotiation between government and the university guided by a formula which takes various factors into account. Is there arbitrage going on? I don’t know. But I do know that various administrators that I’ve talked to across the country have described the entire enterprise as a loss leader for universities. That is: their story to me is that they are actually loosing money on their research activities. And…I can see why a school would do that. Research success is very prestigious and can attract other revenue-creating activities such as students paying tuition. But it also seems that, because of the one-on-one nature of the negotiation for each institution, the balance could be the other way: institutions could be making a profit on research. It would be useful to see the hard data for this.

…just asking for a friend (smile)

Evan Frick’s paper in this week’s science, here. What’s really interesting to me is not so much the result (which isn’t really surprising: that terrestrial mammal food webs have been collapsing) but the use of AI to address the complexity of how the ‘phenotype’ of the biosphere changes over time.

Our newly minted center at George Mason’s Schar School, here. With my co-director, Naoru Koizumi, we are building a new nexus between the clinic, the bench and policy makers.

Loyal readers know that I am fascinated with the red planet. Hat tip to Tyler on this blogpost from Casey Handmer. Casey worked at Hyperloop and NASA’s Jet Propulsion Laboratory before founding his own company. A Caltech PhD, he knows his stuff.

The story from SCIENCE, is here. The upshot is that journal articles that result from US-funded research have to be made available for free to the public as soon as published. No more year-long paywall. The idea, is that the taxpayer already paid for the work once and that having to pay again for access is double-billing. Apparently this also goes for the data. I’m for this, but how this will actually be implemented isn’t clear. Someone has to pay for the editorial labor. Will the publishing fees now be written into a grant proposal budget as allowable direct costs? A lot of business models are going to have to change I think.

One caveat: all of this is reversible by a successor Administration.