Fleck: quantum computing for the life sciences

Fleck will be a digital platform composed of three layers; from the bottom up: (i) hardware and hybrid solutions; (ii) open-source community; (iii) end-users.

At the bottom of the stack we are building Switzerland's first quantum computer based on novel, scalable 2D ion-trap architecture. User access will be provided through the platform, which will also contribute additional quantum and classical resources (CPU, GPU). New open-source software developed by the project will allow users to submit hybrid quantum-AI jobs as single workloads via a centralized system. In the layer above (public domain) contributors will be able to upload their code to execute on the hardware underneath, with the first contributions coming from the project. Finally, in the top layer, end-users can take the code and outputs from the open-source community and use them to pioneer their own projects or industrial use cases.

Our partners populate each layer of the platform: from hardware producers/providers to software developers (ZuriQ, QuantumBasel, Phoenix Technologies), algorithms designers (University of Basel, University of Fribourg, ETH) and end-users (Multiwave Technologies, Novartis Pharma). Together we will address three key application domains: quantum computing for drug design, brain cancer detection and ultra-low field (ULF) MRI imaging. The correlated nature of our collaboration spans the spectrum from fundamental research to tech transfer. Our team will be the first in the world to create a 2D Penning trap quantum computer (ZuriQ) and connect it for external use (QuantumBasel, Phoenix). Our quantum calculations (Uni Fribourg, Uni Basel) will suggest: metal-based contrast agents (which image at improved resolution), and anticancer drugs (with high specificity towards target proteins). We will rank the candidates using quantum-AI methods (ETH) and select the best ones to be sent for fabrication in the lab (Novartis). After synthesis, the contrast agent drug complexes will be empirically tested in Switzerland's first ULF MRI scanner (Multiwave).

The beneficiaries of our platform fall into four classes of end-user groups: (1) pharmaceutical companies; (2) medical imaging community; (3) public organizations; (4) open-source community. We envisage several commercialization paths for after the project’s completion, but the code for one-job hybrid workflows will remain open-source, ensuring that the next generation of researchers inherit barrier-free access to scientific tools.