This post may be premature but I feel like writing down some thoughts about the roller coaster that this year has been. At the start of the year, with the number of reported cases rising in Europe the EMBL and our institute (EMBL-EBI) decided to send everyone home as precautionary measure. As most of our group is computational, this has meant we have been working from home for most of this year. Early on, somewhat frustrated by not being able to help, I emailed a few people that could be working on the virus. Nevan Krogan replied saying our help would be useful and we joined the global effort to contribute to solving this crisis.
Science at science fiction speed
Over the course of 9 months we took part in 4 projects, some of these being the most thrilling science I have ever taken part in. We condensed what would easily be a 3 to 5 years research project into something done in 3-4 months, involving typically 10-20 research groups with a few key people helping to direct the research. We were collecting data, analysing and suggesting new experiments in the span of days with some of the best scientists in the world. Contributing to the direction of this level of resources has been an amazing experience that I wish every scientist could try at least once in their life. These projects were all geared towards studying how SARS-CoV-2 takes control of its target cells to be able to suggest human targeting drugs that could counter the infection. Several of the compounds identified in these studies are in clinical trials for COVID-19 so I feel the projects met their main objective.
While this has been my perspective from working on these specific projects we are all aware of the amazing scientific progress that has been made over the course of this year. I remember seeing the movie Contagion and almost laughing at the unrealistically fast pace of research in the movie. However, SARS-CoV-2 research has in fact happened at an incredibly fast pace that probably matches the movie.
Why don't we do this for disease X?
One discussion point that has come up often is if we can learn from this period to apply it to research into other diseases. Science is an international endeavour but the degree of collaborations for SARS-CoV-2 research has been higher than usual. The effort put into this was also high among the projects I have seen personally but this eventually results in some exhaustion and it is not sustainable. I don't think this is easy to repeat for other diseases without the same external sense of urgency. Most scientists won't just drop what they are working on to fully focus on some other research question. Maybe it is an argument for even higher degree of collaboration, in particular between academia and biotech/pharma. There may be some small increase in productivity of collaborations through the use of online tools like slack and zoom but overall I don't see that the way we do science has been dramatically changed going forward.
The case for higher spending in research
![]() |
I'm gonna have to science the s**t out of this |
Over the last 10 years academic science budgets have been squeezed and a lot has been said about how academic science needs to be more applied and how much we should justify the investment it is being made. This week, DeepMind, a private research institute funded by what is essentially an advertising company (Alphabet/Google) has made headlines with their impressive research into predicting the structure of a protein from its sequence. An advertising company finds the money to invest into what are fundamental biological problems and in the middle of a pandemic that is being solved by a global scientific infrastructure we can't get the EU science budget to increase. We should be ready to make our case over the course of the next months.