Liesbet Geris (DOB 04.06.1979) is Professor in Biomechanics and Computational Tissue Engineering at the Department of Aerospace and Mechanical Engineering at the University of Liège and Associate Professor at the Department of Mechanical Engineering of the KU Leuven, Belgium. From the KU Leuven, she received her MSc degree in Mechanical Engineering in 2002 and her PhD degree in Engineering in 2007, both summa cum laude. In 2007 she worked as a postdoctoral researcher at the Centre of Mathematical Biology of Oxford University.
Her research interests encompass the mathematical modeling of bone regeneration during fracture healing, implant osseointegration and tissue engineering applications. The phenomena described in these mathematical models reach from the tissue level, over the cell level, down to the molecular level. She works in close collaboration with experimental and clinical researchers from the university hospitals in Liège and Leuven, focusing on the development of mathematical models of impaired healing situations and the in silico design of novel treatment strategies. She is scientific coordinator of Prometheus, the skeletal tissue engineering division of the KU Leuven. Her research is financed by European, regional and university funding (up to date 3.5 M€ as PI and co-PI). In 2011 she was awarded an ERC starting grant to pursue her research.
Title: Estimating tibial fracture time in growing kids affected by neurofibromatosis type 1 (NF1)
Summary: Congenital pseudarthrosis of tibia (CPT) is observed within 3-5% of the kids diagnosed with Neurofibromatosis type I (NF1), a congenital disease primarily known for its cutaneous hallmarks. The objective of my research is to develop a valid computational model of the growing tibia to predict temporal variation of fracture risk in an NF1 tibia. A valid mechanobiological model of combined bone growth and bone remodeling will be developed and solved using finite element modeling to predict temporal variation of the bone strength. Key molecular and cellular factors influencing growing bone strength will be identified using design of experiments (DOE) and principal component analysis (PCA). Obtained results will help pediatric orthopedic surgeons to decide whether to plan a corrective surgery to minimize growth abnormalities e.g. short heightening and/or stiffened ankle joint or not to intervene to avoid risk of non-union and pseudarthrosis.
Title: Model assisted design of 3D printed biomaterials for optimized bone regeneration in alveolar bone
Summary: The goal of the modelling in biomechanics lab is to derive from historical data available within the consortium and the literature a set of parameters that are most important for dental bone regeneration. And then studying new design customized by computer modeling, at mill metric and micrometric scales by playing on pores and shapes. Based on a combination of previously developed models (on the influence of calcium on bone regeneration and the influence of 3D shape parameters on neo-tissue formation inside scaffolds) and these data, a new computational model will be developed specifically for the BIOPTOS application. An in-silico optimization routine will be implemented to come up with a series of designs that comply with the requirements of the chosen manufacturing technique and that should allow for a maximal regenerative response after implantation. The new product will form an effective alternative to bone grafts requiring rather serious surgical interventions. It consists of HA/TCP material of optimized shape, porosity and will be available in a range of different sizes in order to be compatible at best with the patient bone defect.
Title: Optimization of calcium phosphate-based biomaterials for intra-oral bone regeneration
Summary: Guided bone regeneration (GBR) is an ideal approach in dentistry and regarded as a promising clinical strategy to treat periodontal diseases, maxillofacial defects and bone atrophies following tooth extraction.There are many screening studies about the bone grafts used in GBR therapy, but a little has been done on the multiple physico-chemical aspects in the intra-oral bone regeneration. The general aim of this project is to explore the influence of physico-chemical characteristics on the bone formation capacity of calcium phosphate-based biomaterials in order to design optimized structures for intra-oral bone regeneration that can be produced by 3D printing methods.
Title: Optimization of patient-specific acetabular implants for larger bone defects
Summary: Arthroplasty is an operative procedure where a dysfunctional joint is resected and replaced with an orthopedic implant in order to improve function and/or relieve pain. The restored joint would ideally last for the lifetime of the patient, however, this is not the case yet. One of the main drawbacks of current orthopedic implants is the overtime degradation of implant stability, which leads to loosening of the implant and eventual joint failure. When this happens, a revision surgery has to performed. During revision surgeries not only does the implant have to be replaced, but also the defects that have developed in the remaining bone need to be corrected. Depending on the size and shape of the defects, patient specific revision implants may be required. Revision implants, whether patient specific or not, tend to have even shorter lifetimes than the implants they replace, which is a problem. Within the INTERREG project, PROSPEROS, which aims to develop personalized bioactive revision surgery implants, we will focus on improving patient specific acetabular implants for larger bone defects by means of optimization. To this purpose, the design optimization will be combined with a multiscale modeling approach. At organ scale, improving aspects like implant stability, integration and mechanical functionality will be the focus, while at tissue/cell scale, the main concern will be improving bone ingrowth. By taking such a multiscale approach for the design optimization we expect to obtain personalized acetabular implants that not only restore function in case of bigger defects, but that also improve implant integration and lifetime compared to the current state of the art, ultimately leading to an improvement of quality of life by enabling patients to maintain active mobility for longer.
Title: Multiscale integration of bioinformatics tools in tissue engineering modeling
Summary: The osteoarthritis challenge is a multi-partner consortium project funded by FNRS and FWO (Excellence of Science) addressing the question of preservation and repair of the joints (cartilaginous junctions between bones) in a multiscale approach (molecular, cellular and tissue differentiated structures that are all interacting in a complex way).
The essential concern of many -omics studies is gene expression profiling between samples of interests and association profiling of metabolites and gene transcripts for evolving and co-operating cells toward their fully differentiated states in a particular environment. Understanding these transitions, co-operations and evolutions is the Holy Grail in tissue engineering as it will deliver in silico mechanistic models on which better engineered in vitro human cell cultures will eventually be developed for regenerative medicine purposes.
Off-line big data from various –omics technologies (RNA microarray-like transcriptomics, single cell RNAseq, metabolomics, proteomics) have shown that it is not always straightforward to apply the wide range of existing software tools to all real life datasets or biological particular situations. Moreover, differential expression analysis of –omics data, be it parametric (DESeq, EdgeR), non- parametric (SAMseq), transformation (voom+limma) or Bayesian (EBSeq) need to be incorporated in time evolutive and co-operative approaches. More importantly the –omics analysis methods should be improved with priors and fully integrated into the pursued mechanistic model of the tissue of interest. In our work, our objective is to establish and improve a practical workflow that allows to better handle off-line big data in the pipeline of tissue engineering mechanistic modeling.
Title: Computational strategies to bring in silico bone tissue engineering models from the bench to the bed side
Summary: Bone tissue engineering (TE), the field that combines knowhow from medical and engineering sciences to come up with solutions for large or non-healing fractures, is struggling to make the transition from the bench to the bedside. Various reasons exist and they come down to the fact that the field is not able to translate the scientific progress into robust and high-quality products tailored to specific patient needs. Computational models are interesting tools to aid in this translation. Currently, a variety of models has been developed for various TE processes such as the biological processes taking place inside the bioreactor used for preparation of the TE products or the bone regeneration model inside the patient itself. This PhD project aims to bring both aforementioned computational models one step closer to the end-user, being the TE product manufacturers and the clinicians. The bioreactor model will be used in an optimization setting that will allow to determine the optimal bioreactor settings for a maximal desired biological response. The fracture healing model will be firstly reduced and subsequently used in an optimization setting to allow the clinician to determine, based on clinical data, the optimal treatment strategies for specific patients (personalized health care) or for a group of patients (in silico clinical trial).
Title: Biomimetic process design for tissue regeneration : modeling the growth plate biology
Summary: Endochondral ossification is a complex process involving a myriad of influencing factors. Signalling pathways precisely navigate mesenchymal stem cells trough the correct cascades. A detailed understanding of these cascades will enable us to develop efficient and robust tissue engineering products. A mathematical model is an interesting tool to study the different pathways involved in endochondral ossification as well as their interactions. In this project we will focus in particular on the BMP and Wnt pathways, their interactions and the way they determine the switch between the proliferation and hypertrophy program in growth plate chondrocytes.
Niki D. Loverdou
Title: Metabolomics as a high-throughput tool for the optimization in stem cell bioprocessing in the context of Bone Tissue Engineering
Summary: The creation of successful cell-based solutions for bone tissue engineering questions depends on the quality of the ground substances as well as the biomanufacturing process bringing these ground substances together. One of these ground substances are the cells and a good control of cell state and fate is important to arrive at robust constructs. High throughput techniques generate massive amounts of data that could be used for control purposes, however, it is not straightforward to derive the proper conclusions from the deluge of data. Computational models can assist in endeavor. Previously, modeling efforts have focused on the simulation of gene regulatory networks to monitor and control the differentiation process of the cells. In this PhD, the metabolic aspects will be studied in depth as growing evidence places metabolic regulation at the heart of many cellular processes. Adding a metabolic component to the existing models should allow for a much more comprehensive study of cell state and fate.
Title: Computational modeling to integrate complex knowledge underlying chondrocyte differentiation and help identifying new therapeutic targets for inhibition of osteoarthritis or stimulation of bone repair
Summary: Chondrogenic differentiation in the context of the growth plate development or osteochondral pathologies is a process that is thoroughly regulated with inputs from multiple regulators active at multiple time/length scales. A previously developed intracellular regulatory model of chondrogenic differentiation will be extended to integrate the secretome data obtained in the Marie-Sklodowska Curie project entitled CarBon. We will aim to understand the interplay between different biological components and biomechanical factors in the onset and progression of endochondral ossification as well as on the pathological differentiation of chondrocyte occurring in adult articular cartilage. Additionally, specific attention will be paid to the influence of extracellular matrix, and mechanics on the regulatory network dynamics. The ultimate goal of this project is the development of a tool that can be used both to investigate fundamental questions on osteoarthritis and bone healing but also to suggest potential therapeutic strategies that might be used for inhibition of osteoarthritis or for stimulation of bone repair. Please click here for more information on the CarBon project.
Title: Multiscale modeling of osteochondrogenic differentiation in a bioreactor environment and other experimental set-ups typically used in skeletal tissue engineering
Summary: The aim of my thesis is to develop a multiscale model of osteochondrogenic differentiation in a bioreactor environment and other experimental set-ups typically used in skeletal tissue engineering. The state of mechanical loading around the tibia, knee joint and growing skeletal tissue in a bioreactor is to be calculated from computational models using finite element method. Subsequently, a computer model of tissue regeneration in osteochondral and large bone defects is to be developed with appropriate mechanical properties of the involved biological tissue. After this, the tissue regeneration model is to be coupled through a multiscale approach to an intracellular network model capturing the biological regulation of the chondrocyte. This multiscale model developed can be used to suggest interesting and therapeutic targets for osteochondral problems.
Title: 4D non-destructive characterization of tissue formation during dynamic bioreactor processes using a model-supported contrast enhanced computed tomography approach
Summary: Tissue engineering (TE) is still facing challenges with respect to the quality of its products. Advancing engineering aspects lacking in the field will be crucial in order to tackle these challenges. Bioreactor technology is one of these enabling technologies that helps to obtain high TE product quality as it allows for controlled in vitro formation of 3D neo-tissues (cells + extracellular matrix). As these neotissue are 3D dynamic structures with complex spatial heterogeneity, traditional 2D imaging techniques are insufficient to characterize them, assess their quality or investigate their formation dynamics. This PhD project aims to incorporate a novel (in-house designed) stand-alone automated perfusion bioreactor system within a nanofocus computed tomography (CT) device for 4D imaging (space + time) of neo-tissue formation. To visualize the soft tissues a range of noninvasive contrast agents will be evaluated for their staining potential and binding kinetics to the biological tissues. Novel in silico models, incorporating the dynamic aspects of bioreactor culture, will be developed to better interpret imaging read-outs and optimize the contrast-enhanced CT imaging process.
Title: In silico lymphangiogenesis : Development of new tools to generate novel insights in the fundamental mechanisms regulating lymphangiogenesis.
Summary: Lymphangiogenesis (LA) is the formation of lymphatic vessels by lymphatic endothelial cells (LECs) broken away from pre-existing lymphatic vessels. This process, along with its counterpart for blood vessels (angiogenesis), allows cancer cells to have enough oxygen and nutrients to develop, as well as to form metastasis. Both phenomena of angiogenesis and lymphangiogenesis are therefore crucial in cancer development. On the contrary, lymphedema is linked to a defect in lymphangiogenesis. Vascular Endothelial Growth Factor (VEGF) is a growth factor playing a critical role in these processes of angiogenesis and lymphangiogenesis. Its receptors, VEGF Receptor type 2 and 3 (VEGFR-2/-3), are two important therapeutic targets in anti-(lymph)angiogenic therapies. In-house data revealed that the endocytic receptor, uPARAP (urokinase Plasminogen Activator Receptor-Associated Protein), is a master regulator of these two receptors. The overall goal of this multidisciplinary project is to create computational (in silico) models that allow to generate novel insights into the biological dysregulation of LEC functionality during cancer progression and metastasis formation, paying particular attention to the roles of uPARAP, its partners and its mediators. The originality of this project lies in its multidisciplinary character, combining classical biomedical approaches using in vitro and in vivo models, with engineering approaches using in silico (computer) models. These in silico models will allow testing hypotheses that might not be easy to verify experimentally due to financial, timing or ethical constraints. Furthermore, they will allow performing large-scale screening experiments into possible therapeutic targets. These simulation results can then be compared to results from dedicated in vitro or in vivo experiments, confirming the in silico findings or guiding a next iteration of the in silico modelling process.
Title: Coming soon
Summary: Coming soon