Prof Damien Thompson is Director of SSPC, the Science Foundation Ireland research centre for pharmaceuticals. He leads the predictive materials modelling group at Bernal Institute University of Limerick, designing novel architectures based on directed self-assembly of nanoscale building blocks. In this interview he talks about his academic journey and what we can learn about computing by understanding more about the brain.
Tell us about your academic journey to date.
I took a circuitous route to my current position, yet it was a very natural progression for me. Let me try to explain that. I loved chemistry and physics equally in school and tossed a coin to decide which one to study at college. Chemistry won but I never stopped reading physics.
I remember John Gribbin’s books on quantum physics making a big impression. I ended up doing a PhD in quantum mechanical modelling of materials, so I combined my two loves.
However, once I realised how bad synthetic materials were at promoting chemical reactions, compared with the enzymes in our bodies, I then took a very deep dive in evolutionary biology, including a very happy two-year postdoc spent modelling biomolecules at Ecole Polytechnique in Paris.
Returning to Ireland I joined the Tyndall institute at University College Cork where I developed my own independent research in molecular and biomolecular materials. I started as a lecturer in UL in 2013 and joined SSPC as co-theme lead in Modelling in 2019. I stepped into the role of interim Director of SSPC in April of this year and it is my most stimulating and exciting role so far.
As Director of the Centre I am in the very privileged position of being able to work with a broad range of stakeholders to drive forward a highly successful academic and industry partnership. I work with our international scientific and industry advisory boards, our leadership team drawn from 10 research performing organisations across Ireland, our industry partners who are the co-creators of our new science, the UL research office and local operations team and, most importantly, our cohort of super talented researchers drawn from across Ireland.
We work at the bleeding edge of pharma and biopharma research, leveraging the collective expertise in the Centre to drive innovation and bring our new science into industry, supporting smart manufacturing of sustainable drug products. For pharma and biopharma, smart means more agile, leaner, more eco-friendly manufacturing and sustainable means more effective, safer, more affordable drug products. To take just one illustrative example, Prof Lidia Tajber’s SSPC research at TCD is producing new methods and materials for green chemistry formulations that do not require use of harsh solvents, which is a real gamechanger.
As well as our national and international industry partners, we collaborate with a tight network of world-leading researchers at top institutes. Throughout the centre, we work right across the spectrum from crystallisation of small molecule drugs to bioprocessing of therapeutic antibodies, with modelling and data underpinning and accelerating the research at every step.
You recently had a paper published about ‘brain like’ computing at a molecular level. Can you go through what exactly that means?
This paper is a nice culmination of a longstanding interest in how molecules can self-assemble into useful structures.
Our proteins and cells learning how to do this drove forward evolution of complex life. In SSPC, we use our understanding of molecular self-assembly to design organic nanocapsules that crumble and release their drug payload once they reach a tumour site. Learning how molecular assemblies can transmit information gives us another design lever. That combination of molecular chemistry and information flow is the basic operating principle of our brains. So, instead of trying to take pieces of silicon and whittle them ever smaller in driving miniaturisation of electrical components to reach down to the subcellular molecular level of proteins and DNA, we start with molecules and study their ability to perform logic operations when placed in a mild electrical field.
Working as part of an international team of brilliant researchers, we managed to develop intelligent molecules that learn from their behaviour, like Pavlov’s dogs salivating at the sound of the dinner bell, they modify their behaviour over time.
The devices show memory effects, their present state depends on their history, as their present voltage or current depends on their past voltage or current. That sounds a bit like how we work, how our brains work. It’s not just digital, these switches are more than just simply on or off. I’m not just happy or sad – like everyone else except who we call extremists – my brain tells me that I go between the two and how happy or sad I am today depends on how I felt yesterday. Overnight dramatic transformations are rare.
The molecules achieve this moderation and learning because we designed them to separate out the processes inside the molecule into fast and slow response to their environment. We use voltage, we zap them, but we can also use light or magnets or many other kinds of stimulus to teach them. As the molecules are charged, they gain electrons which are units of electrical charge, and electrons as we know are very small and very fast so this is the fast step. They also gain protons from water and that’s the slow step.
Along that path from starting to final fully protonated structure we get the learning – just like the synapses in our brains.
Since the electron transfer and proton coupling steps occur at very different time scales, the transformation can emulate the plastic behaviour of synapse neuronal junctions, Pavlovian learning, and all logic gates for digital circuits, simply by changing the applied voltage and the duration of voltage pulses during the synthesis.
To emulate the dynamical behaviour of synapses at the molecular level, we combined fast electron transfer with slow proton coupling limited by diffusion. It’s pure biomimetics with the fast electron transfer akin to action potentials and fast depolarisation processes in biology and the slow step akin to the role of biological calcium ions or neurotransmitters.
What kind of applications can you see this work having?
This method can in the future be applied to dynamic molecular systems driven by other stimuli such as light.
We are creating bonds between nitrogen and hydrogen, and more than 5 billion kg of N2 are fixed every year by lightning strikes. We can also couple our technology to different types of dynamic covalent bond formation. This breakthrough opens up a whole new range of adaptive and reconfigurable smart systems that can be controlled by external inputs and create bespoke outputs. This creates new opportunities in sustainable and green chemistry, from more efficient flow chemistry production of drug products to development of new organic materials for brain-inspired computing.
We have developed the first generation of these materials, and they sit in an emerging class of highly functional nanostructured materials. For example, my colleagues Mike Zaworotko and Kevin Ryan here the Bernal Institute in UL create beautifully structured materials for gas separations and energy storage.
Just as importantly for the ultra-efficient, brain-like materials we’ve designed now, we have the crucial large-area, high-density integration demonstrations that they work as device technologies, and this gives us the clout and authority to be upfront about the other pieces now needed to get right for mass deployment.
Our research will continue to drive up the manufacturability of the materials through the discovery of ever more sustainable and safe materials components, and increased knowledge of the charge transport mechanisms will improve the integration of the molecular layers with conventional silicon-based technology.
Subscribers 0
Fans 0
Followers 0
Followers