Towards a 21st-century roadmap for biomedical research and drug discovery:consensus report and recommendations

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and nongovernmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathway-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this

A multiscale model for collagen alignment in wound healing

It is thought that collagen alignment plays a significant part in scar tissue formation during dermal wound healing. We present a multiscale model for collagen deposition and alignment during this process. We consider fibroblasts as discrete units moving within an extracellular matrix of collagen and fibrin modelled as continua. Our model includes flux induced alignment of collagen by fibroblasts, and contact guidance of fibroblasts by collagen fibres. We can use the model to predict the effects of certain manipulations, such as varying fibroblast speed, or placing an aligned piece of tissue in the wound. We also simulate experiments which alter the TGF-β concentrations in a healing dermal wound and use the model to offer an explanation of the observed influence of this growth factor on scarring

Multiscale Modeling of Airway Inflammation Induced by Mechanical Ventilation

Mechanical ventilation (MV) is a system that partially or fully assists patients whose respiratory system fails to achieve a gas exchange function. However, MV can cause a ventilator-associated lung injury (VALI) or even contribute to a multiple organ dysfunction syndrome (MODS) in acute respiratory distress syndrome (ARDS) patients. Despite advances in today technologies, mortality rates for ARDS patient are still high. A better understanding of the interactions between airflow from mechanical ventilator and the airway could provide useful information used to develop a better strategy to ventilate patients. The mechanisms, which mechanical ventilation induces airway inflammation, are complex processes and cover a wide range of spatial scales. The multiscale model of the airway have been developed combining the computational models at organ, tissue, and cellular levels. A model at the organ level was used to study behaviors of the airway during mechanical ventilation. Strain distributions in each layer of the airway were investigated using a model at the tissue level. The cellular inflammatory responses during mechanical ventilation were investigated through the cellular automata (CA) model incorporating all biophysical processes during inflammatory responses. The multiscale modeling framework started by obtaining airway displacements from the organ-level model. They were then transferred to the tissue-level model for determining the strain distributions in each airway layer. The strain levels in each layer were then transferred to the cellular-level model for inflammatory responses due to strain levels. The ratio of the number of damage cells to healthy cells was obtained through the cellular-level model. This ratio, in turn, modulated changes in the Young’s modulus of elasticity at the tissue and organ levels. The simulation results showed that high tidal volume (1400 cc) during mechanical ventilation can cause tissue injury due to high concentration of activated immune cells and low tidal volume during mechanical ventilation (700 cc) can prevent tissue injury during mechanical ventilation and can mitigate tissue injury from the high tidal volume ventilation. The multiscale model developed in this research could provide useful information about how mechanical ventilation contributes to airway inflammation so that a better strategy to ventilate patients can be developed

Cancer modelling: Getting to the heart of the problem

Paradoxically, improvements in healthcare that have enhanced the life expectancy of humans in the Western world have, indirectly, increased the prevalence of certain types of cancer such as prostate and breast. It remains unclear whether this phenomenon should be attributed to the ageing process itself or the cumulative effect of prolonged exposure to harmful environmental stimuli such as ultraviolet light, radiation and carcinogens (Franks and Teich, 1988). Equally, there is also compelling evidence that certain genetic abnormalities can predispose individuals to specific cancers (Ilyas et al., 1999). The variety of factors that have been implicated in the development of solid tumours stems, to a large extent, from the fact that ‘cancer’ is a generic term, often used to characterize a series of disorders that share common features. At this generic level of description, cancer may be viewed as a cellular disease in which controls that usually regulate growth and maintain homeostasis are disrupted. Cancer is typically initiated by genetic mutations that lead to enhanced mitosis of a cell lineage and the formation of an avascular tumour. Since it receives nutrients by diffusion from the surrounding tissue, the size of an avascular tumour is limited to several millimeters in diameter. Further growth relies on the tumour acquiring the ability to stimulate the ingrowth of a new, circulating blood supply from the host vasculature via a process termed angiogenesis (Folkman, 1974). Once vascularised, the tumour has access to a vast nutrient source and rapid growth ensues. Further, tumour fragments that break away from the primary tumour, on entering the vasculature, may be transported to other organs in which they may establish secondary tumours or metastases that further compromise the host. Invasion is another key feature of solid tumours whereby contact with the tissue stimulates the production of enzymes that digest the tissue, liberating space into which the tumour cells migrate. Thus, cancer is a complex, multiscale process. The spatial scales of interest range from the subcellular level, to the cellular and macroscopic (or tissue) levels while the timescales may vary from seconds (or less) for signal transduction pathways to months for tumour doubling times The variety of phenomena involved, the range of spatial and temporal scales over which they act and the complex way in which they are inter-related mean that the development of realistic theoretical models of solid tumour growth is extremely challenging. While there is now a large literature focused on modelling solid tumour growth (for a review, see, for example, Preziosi, 2003), existing models typically focus on a single spatial scale and, as a result, are unable to address the fundamental problem of how phenomena at different scales are coupled or to combine, in a systematic manner, data from the various scales. In this article, a theoretical framework will be presented that is capable of integrating a hierarchy of processes occurring at different scales into a detailed model of solid tumour growth (Alarcon et al., 2004). The model is formulated as a hybrid cellular automaton and contains interlinked elements that describe processes at each spatial scale: progress through the cell cycle and the production of proteins that stimulate angiogenesis are accounted for at the subcellular level; cell-cell interactions are treated at the cellular level; and, at the tissue scale, attention focuses on the vascular network whose structure adapts in response to blood flow and angiogenic factors produced at the subcellular level. Further coupling between the different spatial scales arises from the transport of blood-borne oxygen into the tissue and its uptake at the cellular level. Model simulations will be presented to illustrate the effect that spatial heterogeneity induced by blood flow through the vascular network has on the tumour’s growth dynamics and explain how the model may be used to compare the efficacy of different anti-cancer treatment protocols

A theoretical model of inflammation- and mechanotransduction- driven asthmatic airway remodelling

Inflammation, airway hyper-responsiveness and airway remodelling are well-established hallmarks of asthma, but their inter-relationships remain elusive. In order to obtain a better understanding of their inter-dependence, we develop a mechanochemical morphoelastic model of the airway wall accounting for local volume changes in airway smooth muscle (ASM) and extracellular matrix in response to transient inflammatory or contractile agonist challenges. We use constrained mixture theory, together with a multiplicative decomposition of growth from the elastic deformation, to model the airway wall as a nonlinear fibre-reinforced elastic cylinder. Local contractile agonist drives ASM cell contraction, generating mechanical stresses in the tissue that drive further release of mitogenic mediators and contractile agonists via underlying mechanotransductive signalling pathways. Our model predictions are consistent with previously described inflammation-induced remodelling within an axisymmetric airway geometry. Additionally, our simulations reveal novel mechanotransductive feedback by which hyper-responsive airways exhibit increased remodelling, for example, via stress-induced release of pro-mitogenic and procontractile cytokines. Simulation results also reveal emergence of a persistent contractile tone observed in asthmatics, via either a pathological mechanotransductive feedback loop, a failure to clear agonists from the tissue, or a combination of both. Furthermore, we identify various parameter combinations that may contribute to the existence of different asthma phenotypes, and we illustrate a combination of factors which may predispose severe asthmatics to fatal bronchospasms

The role of mathematical models in designing mechanopharmacological therapies for asthma

Healthy lung function depends on a complex system of interactions which regulate the mechanical and biochemical environment of individual cells to the whole organ. Perturbations from these regulated processes give rise to significant lung dysfunction such as chronic inflammation, airway hyperresponsiveness and airway remodelling characteristic of asthma. Importantly, there is ongoing mechanobiological feedback where mechanical factors including airway stiffness and oscillatory loading have considerable influence over cell behavior. The recently proposed area of mechanophar-macology recognises these interactions and aims to highlight the need to consider mechanobiology when identifying and assessing pharmacological targets. However, these multiscale interactions can be difficult to study experimentally due to the need for measurements across a wide range of spatial and temporal scales. On the other hand, integrative multiscale mathematical models have begun to show success in simulating the interactions between different mechanobiological mechanisms or cell/tissue-types across multiple scales. When appropriately informed by experimental data, these models have the potential to serve as extremely useful predictive tools, where physical mechanisms and emergent behaviours can be probed or hypothesised and, more importantly, exploited to propose new mechanopharmacological therapies for asthma and other respiratory diseases. In this review, we first demonstrate via an exemplar, how a multiscale mathematical model of acute bron-choconstriction in an airway could be exploited to propose new mechanopharmacological therapies. We then review current mathematical modelling approaches in respiratory disease and highlight hypotheses generated by such models that could have significant implications for therapies in asthma, but that have not yet been the subject of experimental attention or investigation. Finally we highlight modelling approaches that have shown promise in other biological systems that could be brought to bear in developing mathematical models for optimisation of mechanopharmacolog-ical therapies in asthma, with discussion of how they could complement and accelerate current experimental approaches

Modeling The Spatiotemporal Dynamics Of Cells In The Lung

Multiple research problems related to the lung involve a need to take into account the spatiotemporal dynamics of the underlying component cells. Two such problems involve better understanding the nature of the allergic inflammatory response to explore what might cause chronic inflammatory diseases such as asthma, and determining the rules underlying stem cells used to engraft decellularized lung scaffolds in the hopes of growing new lungs for transplantation. For both problems, we model the systems computationally using agent-based modeling, a tool that enables us to capture these spatiotemporal dynamics by modeling any biological system as a collection of agents (cells) interacting with each other and within their environment. This allows to test the most important pieces of biological systems together rather than in isolation, and thus rapidly derive biological insights from resulting complex behavior that could not have been predicted beforehand, which we can then use to guide wet lab experimentation. For the allergic response, we hypothesized that stimulation of the allergic response with antigen results in a response with formal similarity to a muscle twitch or an action potential, with an inflammatory phase followed by a resolution phase that returns the system to baseline. We prepared an agent-based model (ABM) of the allergic inflammatory response and determined that antigen stimulation indeed results in a twitch-like response. To determine what might cause chronic inflammatory diseases where the twitch presumably cannot resolve back to baseline, we then tested multiple potential defects to the model. We observed that while most of these potential changes lessen the magnitude of the response but do not affect its overall behavior, extending the lifespan of activated pro-inflammatory cells such as neutrophils and eosinophil results in a prolonged inflammatory response that does not resolve to baseline. Finally, we performed a series of experiments involving continual antigen stimulation in mice, determining that there is evidence in the cytokine, cellular and physiologic (mechanical) response consistent with our hypothesis of a finite twitch and an associated refractory period. For stem cells, we made a 3-D ABM of a decellularized scaffold section seeded with a generic stem cell type. We then programmed in different sets of rules that could conceivably underlie the cell\u27s behavior, and observed the change in engraftment patterns in the scaffold over selected timepoints. We compared the change in those patterns against the change in experimental scaffold images seeded with C10 epithelial cells and mesenchymal stem cells, two cell types whose behaviors are not well understood, in order to determine which rulesets more closely match each cell type. Our model indicates that C10s are more likely to survive on regions of higher substrate while MSCs are more likely to proliferate on regions of higher substrate

Evaluating Small Airways Disease in Asthma and COPD using the Forced Oscillation Technique and Magnetic Resonance Imaging

Obstructive lung disease, including asthma and chronic obstructive pulmonary disease (COPD), is characterized by heterogeneous ventilation. Unfortunately, the underlying structure-function relationships and the relationships between measurements of heterogeneity and patient quality-of-life in obstructive lung disease are not well understood. Hyperpolarized noble gas MRI is used to visualize and quantify ventilation distribution and the forced oscillation technique (FOT) applies a multi-frequency pressure oscillation at the mouth to measure respiratory impedance to airflow (including resistance and reactance). My objective was to use FOT, ventilation MRI and computational airway tree modeling to better understand ventilation heterogeneity in asthma and COPD. FOT-measured respiratory system impedance was correlated with MRI ventilation heterogeneity and both were related to quality-of-life in asthma and COPD. FOT-measurements and model-predictions of reactance and small-airways resistance were correlated in asthma and COPD respectively. This study is the first to demonstrate the relationships between FOT-measured impedance, MRI ventilation heterogeneity, and patient quality-of-life

Extended Quantitative Computed Tomography Analysis of Lung Structure and Function

Computed tomography (CT) imaging and quantitative CT (QCT) analysis for the study of lung health and disease have been rapidly advanced during the past decades, along with the employment of CT-based computational fluid dynamics (CFD) and machine learning approaches. The work presented in this thesis was devoted to extending the QCT analysis framework from three different perspectives.First, to extend the advanced QCT analysis to more data with undesirably protocolized CT scans, we developed a new deep learning-based automated segmentation of pulmonary lobes, in- corporating z-axis information into the conventional UNet segmentation. The proposed deep learn- ing segmentation, named ZUNet, was successfully applied for QCT analysis of silicosis patients with thick (5 or 10 mm) slices, which used to be excluded in QCT analysis since three-dimensional (3D) volumetric segmentation of the lungs and lobes were hardly successful or not automated. ZUNet outperformed UNet in lobe segmentation of human lungs. In addition, we extended the application of the QCT framework, combining CFD simulations for the entire subjects of the QCT analysis. One-dimensional (1D) CFD simulations of tidal breath- ing have been added to the inspiratory-expiratory CT image matching analysis of 66 asthma pa- tients (M:F=23:43, age=64.4±10.7) for pre- and post-bronchodilator comparison. We aimed to characterize comprehensive airway and lung structure and function relationship in the entire group response and patient-specific response to the bronchodilator. Along with the evidence of large air- way dilatation in the entire asthmatics, the CFD analysis revealed that improvements in regional flow rate fraction, particularly in the right lower lobe (RLL), airway pressure drop, airway resis- tance, and workload of breathing were significantly associated with the degree of large airway dilatation. Finally, we extended the approach using machine learning analysis to integrate numerous QCT variables with clinical features and additional information such as environmental exposure. In pursuit of investigating the effects of particulate matter (PM) exposure on human lung struc- ture and function alteration, principal component analysis (PCA) and k-means clustering iden- tified low, mid, and high exposure groups from directly measured air pollution exposure data of 270 healthy (age=68±10, M:F=15:51), asthma (age=60±12, M:F=39:56), chronic obstructive pulmonary disease (COPD) (age=69±7, M:F=66:10), and idiopathic pulmonary fibrosis (IPF) (age=72±7, M:F=43:10) subjects. Based on the exposure clusters, the RLL segmental airway narrowing was observed in the high exposure group. Various associations were found between the exposure data and about 200 multiscale lung features, from quantitative inspiratory and ex- piratory CT image matching and 1D CFD tidal breathing simulations. To highlight, small PM increases small airway disease in asthma. PM at all sizes decreases inspiratory low attenuation area in COPD and diseases luminal diameter of the RLL segmental airways in IPF