Modelling towards a more holistic medicine: The Virtual Physiological Human (VPH).

The Virtual Physiological Human (VPH) is a European initiative, rooted in the international Physiome initiative, focusing on establishing a methodological and technological framework, enabling the collaborative investigation of the human body as a single complex system. This collective framework will facilitate the sharing of resources and observations formed by different institutions and organizations, and the creation of disparate but integrated computer models of the mechanical, physical and biochemical functions of a living human body. The VPH initiative has laid the foundation for integrating heterogeneous data sources into mechanistic computer models of most anatomical systems.

The combined mechanism of bone morphogenetic protein- and calcium phosphate-induced skeletal tissue formation by human periosteum derived cells.

When combining osteogenic progenitor cells such as human periosteum derived cells (hPDCs) with osteoconductive biomaterials like calcium phosphate (CaP)-scaffolds, in vivo bone formation can be achieved. This process is dependent on the early activation of Bone morphogenetic protein (BMP)-signalling. However, the bone forming process is slow and routinely only a limited amount of bone and bone marrow is formed. Therefore, we hypothesised that a robust clinically relevant outcome could be achieved by adding more physiological levels of potent BMP-ligands to these cell- and CaP-based constructs. For this, hPDCs were characterised for their responsiveness to BMP-ligands upon in vitro 2D stimulation. BMP-2, -4, -6 and -9 robustly induced osteochondrogenic differentiation. Subsequently, these ligands were coated onto clinically approved CaP-scaffolds, BioOss® and CopiOs®, followed by hPDC-seeding. Protein lysates and conditioned media were investigated for activation of BMP signalling pathways. Upon in vivo implantation, the most abundant bone formation was found in BMP-2 and BMP-6-coated scaffolds. Implanted cells actively contributed to the newly formed bone. Remnants of cartilage could be observed in BMP-coated CopiOs®-constructs. Computational analysis displayed that the type of BMP-ligand as well as the CaP-scaffold affects skeletal tissue formation, observed in a qualitative as well as quantitative manner. Furthermore, the in vitro mechanism appears to predict the in vivo outcome. This study presents further evidence for the potential of BMP-technology in the development of clinically relevant cell-based constructs for bone regenerative strategies.

A three-dimensional computational fluid dynamics model of shear stress distribution during neotissue growth in a perfusion bioreactor.

Bone tissue engineering strategies use flow through perfusion bioreactors to apply mechanical stimuli to cells seeded on porous scaffolds. Cells grow on the scaffold surface but also by bridging the scaffold pores leading a fully filled scaffold following the scaffold's geometric characteristics. Current computational fluid dynamic approaches for tissue engineering bioreactor systems have been mostly carried out for empty scaffolds. The effect of 3D cell growth and extracellular matrix formation (termed in this study as neotissue growth), on its surrounding fluid flow field is a challenge yet to be tackled. In this work a combined approach was followed linking curvature driven cell growth to fluid dynamics modeling. The level-set method (LSM) was employed to capture neotissue growth driven by curvature, while the Stokes and Darcy equations, combined in the Brinkman equation, provided information regarding the distribution of the shear stress profile at the neotissue/medium interface and within the neotissue itself during growth. The neotissue was assumed to be micro-porous allowing flow through its structure while at the same time allowing the simulation of complete scaffold filling without numerical convergence issues. The results show a significant difference in the amplitude of shear stress for cells located within the micro-porous neo-tissue or at the neotissue/medium interface, demonstrating the importance of taking along the neotissue in the calculation of the mechanical stimulation of cells during culture.The presented computational framework is used on different scaffold pore geometries demonstrating its potential to be used a design as tool for scaffold architecture taking into account the growing neotissue. Biotechnol. Bioeng. 2015;112: 2591-2600. © 2015 Wiley Periodicals, Inc.

In silico clinical trials for pediatric orphan diseases.

To date poor treatment options are available for patients with congenital pseudarthrosis of the tibia (CPT), a pediatric orphan disease. In this study we have performed an in silico clinical trial on 200 virtual subjects, generated from a previously established model of murine bone regeneration, to tackle the challenges associated with the small, pediatric patient population. Each virtual subject was simulated to receive no treatment and bone morphogenetic protein (BMP) treatment. We have shown that the degree of severity of CPT is significantly reduced with BMP treatment, although the effect is highly subject-specific. Using machine learning techniques we were also able to stratify the virtual subject population in adverse responders, non-responders, responders and asymptomatic. In summary, this study shows the potential of in silico medicine technologies as well as their implications for other orphan diseases.

Advancing osteochondral tissue engineering: bone morphogenetic protein, transforming growth factor, and fibroblast growth factor signaling drive ordered differentiation of periosteal cells resulting in stable cartilage and bone formation in vivo.

BACKGROUND: Chondrogenic mesenchymal stem cells (MSCs) have not yet been used to address the clinical demands of large osteochondral joint surface defects. In this study, self-assembling tissue intermediates (TIs) derived from human periosteum-derived stem/progenitor cells (hPDCs) were generated and validated for stable cartilage formation in vivo using two different animal models. METHODS: hPDCs were aggregated and cultured in the presence of a novel growth factor (GF) cocktail comprising of transforming growth factor (TGF)-ß1, bone morphogenetic protein (BMP)2, growth differentiation factor (GDF)5, BMP6, and fibroblast growth factor (FGF)2. Quantitative polymerase chain reaction (PCR) and immunohistochemistry were used to study in vitro differentiation. Aggregates were then implanted ectopically in nude mice and orthotopically in critical-size osteochondral defects in nude rats and evaluated by microcomputed tomography (µCT) and immunohistochemistry. RESULTS: Gene expression analysis after 28 days of in vitro culture revealed the expression of early and late chondrogenic markers and a significant upregulation of NOGGIN as compared to human articular chondrocytes (hACs). Histological examination revealed a bilayered structure comprising of chondrocytes at different stages of maturity. Ectopically, TIs generated both bone and mineralized cartilage at 8 weeks after implantation. Osteochondral defects treated with TIs displayed glycosaminoglycan (GAG) production, type-II collagen, and lubricin expression. Immunostaining for human nuclei protein suggested that hPDCs contributed to both subchondral bone and articular cartilage repair. CONCLUSION: Our data indicate that in vitro derived osteochondral-like tissues can be generated from hPDCs, which are capable of producing bone and cartilage ectopically and behave orthotopically as osteochondral units.

Erratum: Capturing the wide variety of impaired fracture healing phenotypes in Neurofibromatosis Type 1 with eight key factors: a computational study.

This corrects the article DOI: 10.1038/srep20010.

Mathematical modelling of the degradation behaviour of biodegradable metals.

A mathematical model for the biodegradation of magnesium is developed in this study to inspect the corrosion behaviour of biodegradable implants. The aim of this study was to provide a suitable framework for the assessment of the corrosion rate of magnesium which includes the process of formation/dissolution of the protective film. The model is intended to aid the design of implants with suitable geometries. The level-set method is used to follow the changing geometry of the implants during the corrosion process. A system of partial differential equations is formulated based on the physical and chemical processes that occur at the implant-medium boundary in order to simulate the effect of the formation of a protective film on the degradation rate. The experimental data from the literature on the corrosion of a high-purity magnesium sample immersed in simulated body fluid is used to calibrate the model. The model is then used to predict the degradation behaviour of a porous orthopaedic implant. The model successfully reproduces the precipitation of the corrosion products on the magnesium surface and the effect on the degradation rate. It can be used to simulate the implant degradation and the formation of the corrosion products on the surface of biodegradable magnesium implants with complex geometries.

The influence of micro-motion on the tissue differentiation around immediately loaded cylindrical turned titanium implants.

OBJECTIVE: The aim of this study was to evaluate the effect of various degrees of implant displacement on the tissue differentiation around immediately loaded cylindrical turned titanium implants. DESIGN: The experiments were conducted in repeated sampling bone chambers placed in the tibia of 10 rabbits. Tissues could grow into the bone chambers via perforations. Due to its double structure, tissues inside the chamber could be harvested leaving the chamber intact. This allowed several experiments within the same animal. The chambers contained a cylindrical turned titanium implant that was loaded in a well-controlled manner. In each of the 10 chambers, four experiments were conducted with the following test conditions: immediate implant loading by inducing 0 (control), 30, 60 and 90 microm implant displacement, 800 cycles per day at a frequency of 1 Hz, twice a week during a period of 6 weeks. Histological and histomorphometrical analyses were performed on methylmethacrylate histological sections. An ANOVA was conducted on the dataset. RESULTS: The total tissue volume was significantly lowest in the unloaded control condition. The bone volume fraction on the other hand, was significantly larger in the unloaded and 90 microm implant displacement, compared to the 30 microm implant displacement. Bone density increased with increasing micro-motion with significantly higher values for the 60 microm- and 90 microm-test conditions compared to the unloaded situation. The chance to have bone-to-implant contact decreased in case of micro-motion at the tissues-implant interface. CONCLUSION: The magnitude of implant displacement had a statistically significant effect on the tissue differentiation around immediately loaded cylindrical turned titanium implants. Implant micro-motion had a detrimental effect on the bone-to-implant contact in an immediate loading regimen.

Coupling curvature-dependent and shear stress-stimulated neotissue growth in dynamic bioreactor cultures: a 3D computational model of a complete scaffold.

The main challenge in tissue engineering consists in understanding and controlling the growth process of in vitro cultured neotissues toward obtaining functional tissues. Computational models can provide crucial information on appropriate bioreactor and scaffold design but also on the bioprocess environment and culture conditions. In this study, the development of a 3D model using the level set method to capture the growth of a microporous neotissue domain in a dynamic culture environment (perfusion bioreactor) was pursued. In our model, neotissue growth velocity was influenced by scaffold geometry as well as by flow- induced shear stresses. The neotissue was modeled as a homogenous porous medium with a given permeability, and the Brinkman equation was used to calculate the flow profile in both neotissue and void space. Neotissue growth was modeled until the scaffold void volume was filled, thus capturing already established experimental observations, in particular the differences between scaffold filling under different flow regimes. This tool is envisaged as a scaffold shape and bioprocess optimization tool with predictive capacities. It will allow controlling fluid flow during long-term culture, whereby neotissue growth alters flow patterns, in order to provide shear stress profiles and magnitudes across the whole scaffold volume influencing, in turn, the neotissue growth.

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market.

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design.

Combining microCT-based characterization with empirical modelling as a robust screening approach for the design of optimized CaP-containing scaffolds for progenitor cell-mediated bone formation.

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely variable material characteristics and patient-specificities, however, current bone TE strategies still suffer from low repeatability and lack of robustness, which hamper clinical translation. Hence, optimal TE construct (i.e. cells and scaffold) characteristics are still under debate. This study aimed to reduce the material-specific variability for cell-based construct design, avoiding trial-and-error, by combining microCT characterization and empirical modelling as an innovative and robust screening approach. Via microCT characterization we have built a quantitative construct library of morphological and compositional properties of six CE approved CaP-based scaffolds (CopiOs®, BioOss™, Integra Mozaik™, chronOS Vivify, MBCP™ and ReproBone™), and of their bone forming capacity and in vivo scaffold degradation when combined with human periosteal derived cells (hPDCs). The empirical model, based on the construct library, allowed identification of the construct characteristics driving optimized bone formation, i.e. (a) the percentage of ß-TCP and dibasic calcium phosphate, (b) the concavity of the CaP structure, (c) the average CaP structure thickness and (d) the seeded cell amount (taking into account the seeding efficiency). Additionally, the model allowed to quantitatively predict the bone forming response of different hPDC-CaP scaffold combinations, thus providing input for a more robust design of optimized constructs and avoiding trial-and error. This could improve and facilitate clinical translation. STATEMENT OF SIGNIFICANCE: Biomaterials that support regenerative processes are a key ingredient for successful bone tissue engineering (TE). However, the optimal scaffold structure is still under debate. In this study, we have provided a useful innovative approach for robust screening of potential biomaterials or constructs (i.e. scaffolds seeded with cells and/or growth factors) by combining microCT characterization with empirical modelling. This novel approach leads to a better insight in the scaffold parameters influencing progenitor cell-mediated bone formation. Additionally, it serves as input for more controlled and robust design of optimized CaP-containing bone TE scaffolds. Hence, this novel approach could improve and facilitate clinical translation.

Capturing the wide variety of impaired fracture healing phenotypes in Neurofibromatosis Type 1 with eight key factors: a computational study.

Congenital pseudarthrosis of the tibia (CPT) is a rare disease which normally presents itself during early childhood by anterolateral bowing of the tibia and spontaneous tibial fractures. Although the exact etiology of CPT is highly debated, 40-80% of CPT patients are carriers of a mutation in the Neurofibromatosis Type 1 (NF1) gene, which can potentially result in an altered phenotype of the skeletal cells and impaired bone healing. In this study we use a computational model of bone regeneration to examine the effect of the Nf1 mutation on bone fracture healing by altering the parameter values of eight key factors which describe the aberrant cellular behaviour of Nf1 haploinsufficient and Nf1 bi-allelically inactivated cells. We show that the computational model is able to predict the formation of a hamartoma as well as a wide variety of CPT phenotypes through different combinations of altered parameter values. A sensitivity analysis by "Design of Experiments" identified the impaired endochondral ossification process and increased infiltration of fibroblastic cells as key contributors to the degree of severity of CPT. Hence, the computational model results have added credibility to the experimental hypothesis of a genetic cause (i.e. Nf1 mutation) for CPT.

Changes in bone macro- and microstructure in diabetic obese mice revealed by high resolution microfocus X-ray computed tomography.

High resolution microfocus X-ray computed tomography (HR-microCT) was employed to characterize the structural alterations of the cortical and trabecular bone in a mouse model of obesity-driven type 2 diabetes (T2DM). C57Bl/6J mice were randomly assigned for 14 weeks to either a control diet-fed (CTRL) or a high fat diet (HFD)-fed group developing obesity, hyperglycaemia and insulin resistance. The HFD group showed an increased trabecular thickness and a decreased trabecular number compared to CTRL animals. Midshaft tibia intracortical porosity was assessed at two spatial image resolutions. At 2 µm scale, no change was observed in the intracortical structure. At 1 µm scale, a decrease in the cortical vascular porosity of the HFD bone was evidenced. The study of a group of 8 week old animals corresponding to animals at the start of the diet challenge revealed that the decreased vascular porosity was T2DM-dependant and not related to the ageing process. Our results offer an unprecedented ultra-characterization of the T2DM compromised skeletal micro-architecture and highlight an unrevealed T2DM-related decrease in the cortical vascular porosity, potentially affecting the bone health and fragility. Additionally, it provides some insights into the technical challenge facing the assessment of the rodent bone structure using HR-microCT imaging.

Cell based advanced therapeutic medicinal products for bone repair: Keep it simple?

The development of cell based advanced therapeutic medicinal products (ATMPs) for bone repair has been expected to revolutionize the health care system for the clinical treatment of bone defects. Despite this great promise, the clinical outcomes of the few cell based ATMPs that have been translated into clinical treatments have been far from impressive. In part, the clinical outcomes have been hampered because of the simplicity of the first wave of products. In response the field has set-out and amassed a plethora of complexities to alleviate the simplicity induced limitations. Many of these potential second wave products have remained "stuck" in the development pipeline. This is due to a number of reasons including the lack of a regulatory framework that has been evolving in the last years and the shortage of enabling technologies for industrial manufacturing to deal with these novel complexities. In this review, we reflect on the current ATMPs and give special attention to novel approaches that are able to provide complexity to ATMPs in a straightforward manner. Moreover, we discuss the potential tools able to produce or predict 'goldilocks' ATMPs, which are neither too simple nor too complex.

Numerical simulation of tissue differentiation around loaded titanium implants in a bone chamber.

The application of a bone chamber provides a controlled environment for the study of tissue differentiation and bone adaptation. The influence of different mechanical and biological factors on the processes can be measured experimentally. The goal of the present work is to numerically model the process of peri-implant tissue differentiation inside a bone chamber, placed in a rabbit tibia. 2D and 3D models were created of the tissue inside the chamber. A number of loading conditions, corresponding to those applied in the rabbit experiments, were simulated. Fluid velocity and maximal distortional strain were considered as the stimuli that guide the differentiation process of mesenchymal cells into fibroblasts, chondrocytes and osteoblasts. Mesenchymal cells migrate through the chamber from the perforations in the chamber wall. This process is modelled by the diffusion equation. The predicted tissue phenotypes as well as the process of tissue ingrowth into the chamber show a qualitative agreement with the results of the rabbit experiments. Due to the limited number of animal experiments (four) and the observed inter-animal differences, no quantitative comparison could be made. These results however are a strong indication of the feasibility of the implemented theory to predict the mechano-regulation of the differentiation process inside the bone chamber.

Assessment of mechanobiological models for the numerical simulation of tissue differentiation around immediately loaded implants.

Nowadays, there is a growing consensus on the impact of mechanical loading on bone biology. A bone chamber provides a mechanically isolated in vivo environment in which the influence of different parameters on the tissue response around loaded implants can be investigated. This also provides data to assess the feasibility of different mechanobiological models that mathematically describe the mechanoregulation of tissue differentiation. Before comparing numerical results to animal experimental results, it is necessary to investigate the influence of the different model parameters on the outcome of the simulations. A 2D finite element model of the tissue inside the bone chamber was created. The differentiation models developed by Prendergast, et al. ["Biophysical stimuli on cells during tissue differentiation at implant interfaces", Journal of Biomechanics, 30(6), (1997), 539-548], Huiskes et al. ["A biomechanical regulatory model for periprosthetic fibrous-tissue differentiation", Journal of Material Science: Materials in Medicine, 8 (1997) 785-788] and by Claes and Heigele ["Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing", Journal of Biomechanics, 32(3), (1999) 255-266] were implemented and integrated in the finite element code. The fluid component in the first model has an important effect on the predicted differentiation patterns. It has a direct effect on the predicted degree of maturation of bone and a substantial indirect effect on the simulated deformations and hence the predicted phenotypes of the tissue in the chamber. Finally, the presence of fluid also causes time-dependent behavior. Both models lead to qualitative and quantitative differences in predicted differentiation patterns. Because of the different nature of the tissue phenotypes used to describe the differentiation processes, it is however hard to compare both models in terms of their validity.

A computational model for cell/ECM growth on 3D surfaces using the level set method: a bone tissue engineering case study.

Three-dimensional open porous scaffolds are commonly used in tissue engineering (TE) applications to provide an initial template for cell attachment and subsequent cell growth and construct development. The macroscopic geometry of the scaffold is key in determining the kinetics of cell growth and thus in vitro 'tissue' formation. In this study, we developed a computational framework based on the level set methodology to predict curvature-dependent growth of the cell/extracellular matrix domain within TE constructs. Scaffolds with various geometries (hexagonal, square, triangular) and pore sizes (500 and 1,000 [Formula: see text]m) were produced in-house by additive manufacturing, seeded with human periosteum-derived cells and cultured under static conditions for 14 days. Using the projected tissue area as an output measure, the comparison between the experimental and the numerical results demonstrated a good qualitative and quantitative behavior of the framework. The model in its current form is able to provide important spatio-temporal information on final shape and speed of pore-filling of tissue-engineered constructs by cells and extracellular matrix during static culture.

A mechanobiological model of orthodontic tooth movement.

Orthodontic tooth movement is achieved by the process of repeated alveolar bone resorption on the pressure side and new bone formation on the tension side. In order to optimize orthodontic treatment, it is important to identify and study the biological processes involved. This article presents a mechanobiological model using partial differential equations to describe cell densities, growth factor concentrations, and matrix densities occurring during orthodontic tooth movement. We hypothesize that such a model can predict tooth movement based on the mechanobiological activity of cells in the PDL. The developed model consists of nine coupled non-linear partial differential equations, and two distinct signaling pathways were modeled: the RANKL-RANK-OPG pathway regulating the communication between osteoblasts and osteoclasts and the TGF-ß pathway mediating the differentiation of mesenchymal stem cells into osteoblasts. The predicted concentrations and densities were qualitatively validated by comparing the results to experiments reported in the literature. In the current form, the model supports our hypothesis, as it is capable of conceptually simulating important features of the biological interactions in the alveolar bone-PDL complex during orthodontic tooth movement.

Mechanobiological modeling can explain orthodontic tooth movement: three case studies.

Progress in medicine and higher expectation of quality of life has led to a higher demand for several dental and medical treatments. This increases the occurrence of situations in which orthodontic treatment is complicated by pathological conditions, medical therapies and drugs. Together with experiments, computer models might lead to a better understanding of the effect of pathologies and medical treatment on tooth movement. This study uses a previously presented mechanobiological model of orthodontic tooth displacement to investigate the effect of pathologies and (medical) therapies on the result of orthodontic treatment by means of three clinically relevant case studies looking at the effect of estrogen deficiency, the effect of OPG injections and the influence of fluoride intake. When less estrogen was available, the model predicted bone loss and a rise in the number of osteoclasts present at the compression side, and a faster bone resorption. These effects were also observed experimentally. Experiments disagreed on the effect of estrogen deficiency on bone formation, while the mechanobiological model predicted very little difference between the pathological and the non-pathological case at formation sites. The model predicted a decrease in tooth movement after OPG injections or fluoride intake, which was also observed in experiments. Although more experiments and model analysis is needed to quantitatively validate the mechanobiological model used in this study, its ability to conceptually describe several pathological conditions is an important measure for its validity.

Mechanisms of cell migration in the adult brain: modelling subventricular neurogenesis.

Neurogenesis has been the subject of active research in recent years. Although the majority of neurons form during the embryonic period, neurogenesis continues in restricted regions of the mammalian brain well into adulthood. In rodent brains, neuronal migration is present in the rostral migratory stream (RMS), connecting the subventricular zone to the olfactory bulb (OB). The migration in the RMS is characterised by a lack of dispersion of neuroblasts into the surrounding tissues and a highly directed motion towards the OB. This study uses a simple mathematical model to investigate several theories of migration of neuroblasts through the RMS proposed in the literature, including chemo-attraction, chemorepulsion, general inhibition and the presence of a migration-inducing protein. Apart from the general inhibition model, all the models were able to provide results in good qualitative correspondence with the experimental observations.