Biophysics Research Center
Biophysics applies the principles and methods of physics to understand and characterise living systems across scales 鈥� from molecules and cells to tissues, organs, and the human body. Situated at the interface of physics, engineering, biology, and medicine, it provides increasingly precise ways to measure physiology and disease, develop new technologies, and translate fundamental discoveries into biomedical innovation.
The Center
麻w豆传媒 is a young, dynamic, and internationally oriented institution based in Milan, where medical education, biomedical research, and clinical practice are closely integrated.
Within the Department of Biomedical Sciences, the strong links between the University and the IRCCS Humanitas Research Hospital create a fertile environment for collaborations across basic, translational, and clinical research. In this context, the 麻w豆传媒 Biophysics Research Center addresses the growing need for quantitative and physics-based approaches to biological and medical challenges.
Director
Research Areas
The research of the Center builds on expertise established at 麻w豆传媒 in two major areas: the biophysics of microbial and cellular systems, and physics-based approaches for medical imaging. Rooted in these strengths, the Center is designed to evolve through academic, clinical, and industrial collaborations, emerging technologies, and new scientific opportunities.
Research area
This area investigates how physical principles shape the behaviour, organisation, and functional reconstruction of microbial communities, mammalian cells, and cell-free biochemical systems, with particular attention to biological, material, and host interfaces.
Ongoing activities
- Biomechanical analysis of microbial and cellular responses to surfaces, including the role of flow, motility, surface topography, and surface chemistry in bacterial attachment, biofilm formation, cellular mechanosensing, and device-associated infections.
- Quantitative and mechanistic studies of microbial population dynamics, focusing on how physiology, spatial structure, stress, nutrient availability, and microbial metabolism shape ecological interactions, colonisation resistance, antibiotic responses, and microbiome鈥揾ost communication.
- Use of correlative light and electron microscopy to investigate the structural phenotypes of materials and biological or pathological interfaces at tissue, cellular, and molecular levels, providing high-resolution insights into pathogens, diseased tissues, and abnormal protein formations.
- Bottom-up assembly of autonomous cell-free systems capable of sustaining their own biochemical activity through synthetic metabolic networks, with the aim of engineering advanced therapeutic platforms inspired by the fundamental principles that govern life.
Members
- Simone Giaveri
Research area
This area develops physics-based and computational methods to extract reliable and clinically meaningful information from medical imaging and radiation therapy technologies. By combining quantitative imaging, modelling, artificial intelligence, image analysis, and treatment planning, it supports the in vivo characterisation of biological processes, imaging-based diagnosis and interventions, radiation treatment optimisation, and precision medicine across a broad range of clinical applications.
Ongoing activities
- Development and clinical translation of quantitative PET methodologies, integrating clinically feasible dynamic imaging, kinetic modelling, radiomics, automated image analysis, and artificial intelligence to derive imaging biomarkers for diagnosis, lesion characterisation, and treatment response assessment.
- Development and clinical translation of advanced CT image-analysis algorithms and tissue-characterisation methods, including ultra-high-resolution acquisitions, spectral reconstruction approaches, radiomics, automated image analysis, and artificial intelligence, with applications in quantitative imaging biomarkers for diagnosis and treatment response assessment.
- Development and application of AI-driven medical image-analysis pipelines based on machine learning and deep learning for automated segmentation, tissue characterisation, and advanced interpretation of medical images. This activity includes the integration of multimodal MRI and CT data, the extraction of clinically relevant quantitative imaging biomarkers, and the design of reproducible and scalable workflows for clinical imaging datasets, including DICOM data management.
- Development and clinical translation of advanced quantitative MRI methodologies, integrating multiparametric MRI, diffusion modelling, perfusion imaging, tractography, and quantitative image analysis to derive biomarkers of tissue microstructure, vascular physiology, metabolism, and structural connectivity. Current applications include brain tumors, image-guided functional neurosurgery, chronic pain, inflammatory bowel disease, and quantitative spinal cord imaging in degenerative cervical myelopathy.
- Development and application of physics-based and computational methods for radiation therapy, including treatment planning optimisation and automation, quality assurance, risk analysis, stereotactic body radiotherapy, proton therapy, total marrow irradiation, and AI-assisted clinical decision support.