ERC FUNDED PROJECTS

Microscale robotic devices, or microrobots, could someday enable revolutionary non-invasive medical procedures. However, fundamental limitations still hinder the realisation of this vision. Current microrobots have very limited functionalities: they strongly rely on wireless operation by external fields, which impedes the execution of sophisticated movements and tasks. As a consequence, despite their intended medical use, microrobots cannot move effectively in bodily fluids and tissues. This project addresses exactly this challenge: realising self-contained microrobots that autonomously move in complex 3D biological environments (such as soft body tissues). Our sources of inspiration are biological cells that naturally move through body tissues, such as immune cells. These cells move by continuously changing their shape, a strategy known as ‘amoeboid movement’. Such shape changes are powered by the self-organized flows and stresses of their intracellular filaments and motor proteins. Analogously, we will realise microrobots that each consist of a swarm of active particles: each microrobot will have a liquid body containing self-propelled particles and different sensitive particles; moreover, the particles swarm will be engineered to exhibit desired collective behaviours. These cell-inspired particle-based microrobots, or celloids, will spontaneously adapt their morphology, generate large body-shape changes, sense environmental cues and control signals, and autonomously navigate soft tissue-like environments. This project will establish a radically new method to design microrobots, and will result in microrobots capable of autonomous navigation of body tissues. The celloids will also constitute a robophysical model for studying the migration of immune and cancer cells, and will enable a number of revolutionary medical procedures, including long-term monitoring and non-invasive interventions in delicate organs (e.g. brain).

1 499 375 €

Start date: 2021-02-01, End date: 2026-01-31

Currently, haemophilia A cannot be cured. To prevent major bleeding episodes in haemophilia, human Factor VIII (FVIII) protein must be frequently administered as prophylaxis or on demand. This treatment is complicated by its high cost and development of antibodies that neutralize FVIII activity in 20 to 30% of the patients. Therefore, permanent solutions in the form of cell and gene therapy are very attractive for haemophilia A. Recently, we demonstrated in a murine model that liver sinusoidal endothelial cells (LSEC) produce and secrete FVIII, although not exclusively. We have also found that these mice can be treated by reconstitution with wild-type bone marrow, indicating that bone marrow-derived cells, of hematopoietic, mesenchymal or even endothelial origin, can produce and secrete FVIII. Based on these findings in mice, I propose that human LSEC, umbilical cord blood cells, and bone marrow cells might be suitable sources of FVIII to be used for cell replacement therapy for haemophilia A. To advance opportunities for cell and gene therapies in haemophilia A and for identifying additional cell sources of FVIII, I intend to explore whether replacement of liver endothelium and bone marrow in immnocompromised Haemophilia A mice with healthy human cells will provide therapeutic correction. Recently, the possibility of reprogramming mature somatic cells to generate induced pluripotent stem (iPS) cells has enabled the derivation of disease-specific pluripotent cells, thus providing unprecedented experimental platforms to treat human diseases. Therefore, I intend to study whether the generation of patient-specific iPS cells may be applied to cell and gene therapy of coagulation disorders and in particular for the treatment of Haemophilia A. Studies with these novel target cells may impact significantly the future course of Haemophilia A by providing proof-of feasibility of a novel therapy strategies.

1 123 000 €

Start date: 2011-05-01, End date: 2017-04-30

"The eruption of volcanoes appears one of the most unpredictable phenomena on Earth. Yet the situation is rapidly changing. Quantification of the eruptive record constrains what is possible in a given volcanic system. Timing is the hardest part to quantify. The main process triggering an eruption is the refilling of a sub-volcanic magma chamber by a new magma coming from depth. This process results in magma mixing and provokes a time-dependent diffusion of chemical elements. Understanding the time elapsed from mixing to eruption is fundamental to discerning pre-eruptive behaviour of volcanoes to mitigate the huge impact of volcanic eruptions on society and the environment. The CHRONOS project proposes a new method that will cut the Gordian knot of the presently intractable problem of volcanic eruption timing using a surgical approach integrating textural, geochemical and experimental data on magma mixing. I will use the compositional heterogeneity frozen in time in the rocks the same way a broken clock at a crime scene is used to determine the time of the incident. CHRONOS will aim to: 1) be the first study to reproduce magma mixing, by performing unique experiments constrained by natural data and using natural melts, under controlled rheological and fluid-dynamics conditions; 2) obtain unprecedented high-quality data on the time dependence of chemical exchanges during magma mixing; 3) derive empirical relationships linking the extent of chemical exchanges and the mixing timescales; 4) determine timescales of volcanic eruptions combining natural and experimental data. CHRONOS will open a new window on the physico-chemical processes occurring in the days preceding volcanic eruptions providing unprecedented information to build the first inventory of eruption timescales for planet Earth. If these timescales can be linked with geophysical signals occurring prior to eruptions, this inventory will have an immense value, enabling precise prediction of volcanic eruptions."

1 993 813 €

Start date: 2014-05-01, End date: 2019-04-30

Every second, our smart phones deliver a wealth of information that can be used to monitor the traffic, the financial transactions, and even the spread of a dangerous disease. The processing of these big data into a meaningful information requires specific machine learning (ML) algorithms, which essentially consist of regression techniques for inference, classification and prediction. The conventional digital computers are not designed to optimally solve these problems with efficient time and energy consumption, which is one of the reasons why the power consumption by data centers worldwide is expected to triple in the next decade. Such a poor energy efficiency is essentially due to the physical separation between the central processing unit (CPU), where data are computed, and the memory, where data are stored, according to classical von Neumann computer architecture. In the frame of our ERC-CoG RESCUE, my group has developed a new paradigm to efficiently execute ML tasks in just one step within the memory. Instead of moving data from the memory to the digital CPU, an analogue computation is directly operated within the data, thus breaking all previous limits of time and energy consumption (10.000x reduction in the number of operations, hence time, and 1.000x in energy). Our in-memory technology is modular and universal, thus can be implemented in any existing memory and computing technology to accelerate ML tasks in future smartphones and data centers. In the ERC-PoC CIRCUS, we aim at bringing this technology to a higher maturity level, demonstrating its scalability and technical feasibility by simulations and realization of a small-scale prototype. In the meantime, we will also perform a comprehensive market search to recognize opportunities and draft an investor-ready business plan for raising future investments to further advance the solution toward industrial exploitation.

149 464 €

Start date: 2019-05-01, End date: 2020-10-31