First, I want to thank you all for your contribution and for making my doctorate possible. It has always been difficult for scientists to find funding for their research (though not always without good reason), but the current global economic situation has made it substantially more difficult in almost all countries. Some people in the BOINC/crunching community expressed strong reservation when the donate@home project was first proposed. I assure you that the idea and the ethical considerations were not taken lightly on this end either. Ultimately, we chose to proceed with the project in the form you see it now, with the goal of funding fellowships for PhDs. It’s disheartening to see governments cut investment in future innovation, but very heartening to see that you have chosen to help us persevere. With your contribution, we can continue to push the boundaries of human knowledge.
So, what will I be working on for my PhD, and how am I going to push the boundaries of human knowledge? Well, at GPUGRID our ultimate goal is to better understand biological systems in ways that will lead to better cures and therapies. The current outlook for the future of medicine is rather uncertain. Over the past decade or two, the pharmaceutical and biotechnology industries have slowly and reluctantly accepted the fact that many methods they had traditionally used to cure disease have hit a wall. The probability of success for a new drug or therapy have diminished substantially, making the return on investment for them each time smaller. The specific details for why this has happened are various and complex. Some are fundamental issues with the science and technology, while others include the stricter safety standards required for new drugs. For those interested in specifics, I provide here a few links which you can follow to further educate yourself, if desired.
1. Book on the history and obstacles over the last century of drug design, easily accessible for laymen.
2. Great WIRED article covering the issue of reductionism in the sciences, with some good examples given in the pharmaceutical industry.
3. Article discussing the staggering cost to develop a new drugs.
4. New York Times article discussing a new research center in the USA for drug development, with interesting coverage of the debate of its necessity.
5. Editorial in the journal Nature Drug Discovery about the last decode in the pharma industry.
The main cause for this, however, is ultimately biological, and is essentially due to the fact that biological systems are incredibly complex at almost any level of magnification--from the interaction of two proteins, to the regulation of the cell cycle, all the way up to the homeostasis of the human body. This makes coming up with highly targeted cures that will not cause unwanted side-effects incredibly challenging. While humanity has had a fair amount of success over the last century with improved medical technology and small-molecule drugs, the path ahead is less clear as the fundamental issues become more complex.
That’s where I, the rest of the GPUGRID team, and countless other public researchers around the world come in. We have embraced the complexity of biological systems, and have begun to use new methodologies and perpetually increasing computational power to try to tackle these issues. At GPUGRID, we have traditionally worked on the atomic scale of magnification, using what are known as molecular dynamics simulations to simulate proteins and their interactions with other molecules (drugs, other proteins, etc.). This allows us to understand things like the fundamental dynamics of proteins, how drugs interact with their target proteins, and what things are important when proteins interact with each other. You can see an overview of our work and some publications here. In my time at GPUGRID, I will continue this kind of work while also looking into broadening the types and kinds of magnifications on which we look (in other words, doing different kinds of simulations), but have yet to decide anything specific yet.
I’ll post more specifics on what I’ll be working on in later posts, especially after bodies of work have been published. I will also further discuss general issues I’ve hinted at in this message. Once again, thank you for your contribution and for making it possible for me to continue my work.