Modeling of porous scaffold deformation induced by medium perfusion

Modeling drug transport and absorption in subcutaneous injection of monoclonal antibodies: Impact of tissue deformation, devices, and physiology

The pharmaceutical industry has experienced a remarkable increase in the use of subcutaneous injection of monoclonal antibodies (mAbs), attributed mainly to its advantages in reducing healthcare-related costs and enhancing patient compliance. Despite this growth, there is a limited understanding of how tissue mechanics, physiological parameters, and different injection devices and techniques influence the transport and absorption of the drug. In this work, we propose a high-fidelity computational model to study drug transport and absorption during and after subcutaneous injection of mAbs. Our numerical model includes large-deformation mechanics, fluid flow, drug transport, and blood and lymphatic uptake. Through this computational framework, we analyze the tissue material responses, plume dynamics, and drug absorption. We analyze different devices, injection techniques, and physiological parameters such as BMI, flow rate, and injection depth. Finally, we compare our numerical results against the experimental data from the literature.

A multi-scale numerical study of monoclonal antibodies uptake by initial lymphatics after subcutaneous injection

This paper studies the transport of monoclonal antibodies through skin tissue and initial lymphatics, which impacts the pharmacokinetics of monoclonal antibodies. Our model integrates a macroscale representation of the entire skin tissue with a mesoscale model that focuses on the papillary dermis layer. Our results indicate that it takes hours for the drugs to disperse from the injection site to the papillary dermis before entering the initial lymphatics. Additionally, we observe an inhomogeneous drug distribution in the interstitial space of the papillary dermis, with higher drug concentrations near initial lymphatics and lower concentrations near blood capillaries. To validate our model, we compare our numerical simulation results with experimental data, finding a good alignment. Our parametric studies on the drug molecule properties and injection parameters suggest that a higher diffusion coefficient increases the transport and uptake rate while binding slows down these processes. Furthermore, shallower injection depths lead to faster lymphatic uptake, whereas the size of the injection plume has a minor effect on the uptake rate. These findings advance our understanding of drug transport and lymphatic absorption after subcutaneous injection, offering valuable insights for optimizing drug delivery strategies and the design of biotherapeutics.

MPET2: a multi-network poroelastic and transport theory for predicting absorption of monoclonal antibodies delivered by subcutaneous injection

Subcutaneous injection of monoclonal antibodies (mAbs) has attracted much attention in the pharmaceutical industry. During the injection, the drug is delivered into the tissue producing strong fluid flow and tissue deformation. While data indicate that the drug is initially uptaken by the lymphatic system due to the large size of mAbs, many of the critical absorption processes that occur at the injection site remain poorly understood. Here, we propose the MPET² approach, a multi-network poroelastic and transport model to predict the absorption of mAbs during and after subcutaneous injection. Our model is based on physical principles of tissue biomechanics and fluid dynamics. The subcutaneous tissue is modeled as a mixture of three compartments, i.e., interstitial tissue, blood vessels, and lymphatic vessels, with each compartment modeled as a porous medium. The proposed biomechanical model describes tissue deformation, fluid flow in each compartment, the fluid exchanges between compartments, the absorption of mAbs in blood vessels and lymphatic vessels, as well as the transport of mAbs in each compartment. We used our model to perform a high-fidelity simulation of an injection of mAbs in subcutaneous tissue and evaluated the long-term drug absorption. Our model results show good agreement with experimental data in depot clearance tests.

Computational modeling of the effect of skin pinch and stretch on subcutaneous injection of monoclonal antibodies using autoinjector devices

Subcutaneous injection of monoclonal antibodies (mAbs) has experienced unprecedented growth in the pharmaceutical industry due to its benefits in patient compliance and cost-effectiveness. However, the impact of different injection techniques and autoinjector devices on the drug's transport and uptake is poorly understood. Here, we develop a biphasic large-deformation chemomechanical model that accounts for the components of the extracellular matrix that govern solid deformation and fluid flow within the subcutaneous tissue: interstitial fluid, collagen fibers and negatively charged proteoglycan aggregates. We use this model to build a high-fidelity representation of a virtual patient performing a subcutaneous injection of mAbs. We analyze the impact of the pinch and stretch methods on the injection dynamics and the use of different handheld autoinjector devices. The results suggest that autoinjector base plates with a larger device-skin contact area cause significantly lower tissue mechanical stress, fluid pressure and fluid velocity during the injection process. Our simulations indicate that the stretch technique presents a higher risk of intramuscular injection for autoinjectors with a relatively long needle insertion depth.

Morphological analysis and grain size distribution of SnO2 nanoparticles via digital image processing across diverse calcination temperatures

This study presents a comprehensive image analysis of the SnO2 nanoparticles synthesised through calcination at diverse temperatures, which enables an estimation of grain size distribution (GSD) from field-emission scanning electron microscopy (FE-SEM) images. Even though FE-SEM images could provide us with a lot of information about sample differences, we can learn more and perform a more accurate analysis of them by using quantitative data obtained by our image processing application. The digital image processing techniques used in this research provide a detailed analysis of the nanoparticles' size and shape, enabling a deeper understanding of their unique characteristics. The results reveal the significant impact of calcination temperature on the morphology of the nanoparticles, with changes in grain size and grain size distribution observed at varying temperatures.

Numerical studies of the lymphatic uptake rate

Lymphatic uptake is essential for transporting nutrients, wastes, immune cells, and therapeutic proteins. Despite its importance, the literature lacks a quantitative analysis of the factors that affect lymphatic uptake, including interstitial pressure, downstream pressure, and tissue deformation. In this paper, we present a coupled model of a poroelastic tissue with initial lymphatics and quantify the impact of these factors on the rate of lymphatic uptake. Our results indicate that the lymphatic uptake increases with the amplitude of the oscillating downstream pressure when the amplitude exceeds a threshold. Additionally, the cross-sectional area of initial lymphatics increases with the volumetric strain of the tissue, while the interstitial pressure increases when the strain rate becomes negative. Therefore, the lymphatic uptake reaches its maximum when the tissue has positive volumetric strain while being compressed. We have also investigated the effect of intersection angles and positions of two initial lymphatics and concluded that they have minor impacts on lymphatic uptake. However, the lymphatic uptake per unit length of initial lymphatics decreases with their total length. These findings advance our understanding of lymphatic uptake and can guide the development of strategies to accelerate the transport of therapeutics.

Modeling large-volume subcutaneous injection of monoclonal antibodies with anisotropic porohyperelastic models and data-driven tissue layer geometries

Subcutaneous injection of therapeutic monoclonal antibodies (mAbs) has become one of the fastest-growing fields in the pharmaceutical industry. The transport and mechanical processes behind large volume injections are poorly understood. Here, we leverage a large-deformation poroelastic model to study high-dose, high-speed subcutaneous injection. We account for the anisotropy of subcutaneous tissue using of a fibril-reinforced porohyperelastic model. We also incorporate the multi-layer structure of the skin tissue, generating data-driven geometrical models of the tissue layers using histological data. We analyze the impact of handheld autoinjectors on the injection dynamics for different patient forces. Our simulations show the importance of considering the large deformation approach to model large injection volumes. This work opens opportunities to better understand the mechanics and transport processes that occur in large-volume subcutaneous injections of mAbs.

Transport and distribution of biotherapeutics in different tissue layers after subcutaneous injection

The subcutaneous injection is the main route of administration for monoclonal antibodies (mAbs) and several other biotherapeutics due to the patient comfort and cost-effectiveness. However, their transport and distribution after subcutaneous injection is poorly understood. Here, we exploit a three-dimensional poroelastic model to find the biomechanical response of the tissue, including interstitial pressure and tissue deformation during the injection. We quantify the drug concentration inside the tissue. We start with a single-layer model of the tissue. We show that during injection, the difference between the permeability of the solvent and solute will result in a higher drug concentration proportional to the inverse permeability ratio. Then we study the role of tissue layered properties with primary layers, including epidermis, dermis, subcutaneous (SQ), and muscle layers, on tissue biomechanical response to injection and drug transport. We show that the drug will distribute mainly in the SQ layer due to its lower elastic moduli. Finally, we study the effect of secondary tissue elements like the deep fascia layer and the network of septa fibers inside the SQ tissue. We use the Voronoi algorithm to create random geometry of the septa network. We show how drugs accumulate around these tissue components as observed in experimental SQ injection. Next, we study the effect of injection rate on drug concentration. We show how higher injection rates will slightly increase the drug concentration around septa fibers. Finally we demonstrate how the concentration dependent viscosity will increase the concentration of biotherapeutics in the direction of septa fibers. .

Comparative evaluation of mesenchymal stromal cell growth and osteogenic differentiation on a shape memory polymer scaffold

Trauma-induced, critical-size bone defects pose a clinical challenge to heal. Albeit autografts are the standard-of-care, they are limited by their inability to be shaped to various defect geometries and often incur donor site complications. Herein, the combination of a "self-fitting" shape memory polymer (SMP) scaffold and seeded mesenchymal stromal cells (MSCs) was investigated as an alternative. The porous SMP scaffold, prepared from poly(ε-caprolactone) diacrylate (PCL-DA) and coated with polydopamine, provided conformal shaping and cell adhesion. MSCs from five tissues, amniotic (AMSCs), chorionic tissue (CHSCs), umbilical cord (UCSCs), adipose (ADSCs), and bone marrow (BMSCs) were evaluated for viability, density, and osteogenic differentiation on the SMP scaffold. BMSCs exhibited the fastest increase in cell density by day 3, but after day 10, CHSCs, UCSCs, and ADSCs approached similar cell density. BMSCs also showed the greatest calcification among the cell types, followed closely by ADSCs, CHSCs and AMSCs. Alkaline phosphatase (ALP) activity peaked at day 7 for AMSCs, UCSCs, ADSCs and BMSCs, and at day 14 for CHSCs, which had the greatest overall ALP activity. Of all the cell types, only scaffolds cultured with ADSCs in osteogenic media had increased hardness and local modulus as compared to blank scaffolds after 21 days of cell culture and osteogenic differentiation. Overall, ADSCs performed most favorably on the SMP scaffold. The SMP scaffold was able to support key cellular behaviors of MSCs and could potentially be a viable, regenerative alternative to autograft.

Optimization and Validation of a Custom-Designed Perfusion Bioreactor for Bone Tissue Engineering: Flow Assessment and Optimal Culture Environmental Conditions

Various perfusion bioreactor systems have been designed to improve cell culture with three-dimensional porous scaffolds, and there is some evidence that fluid force improves the osteogenic commitment of the progenitors. However, because of the unique design concept and operational configuration of each study, the experimental setups of perfusion bioreactor systems are not always compatible with other systems. To reconcile results from different systems, the thorough optimization and validation of experimental configuration are required in each system. In this study, optimal experimental conditions for a perfusion bioreactor were explored in three steps. First, an in silico modeling was performed using a scaffold geometry obtained by microCT and an expedient geometry parameterized with porosity and permeability to assess the accuracy of calculated fluid shear stress and computational time. Then, environmental factors for cell culture were optimized, including the volume of the medium, bubble suppression, and medium evaporation. Further, by combining the findings, it was possible to determine the optimal flow rate at which cell growth was supported while osteogenic differentiation was triggered. Here, we demonstrated that fluid shear stress up to 15 mPa was sufficient to induce osteogenesis, but cell growth was severely impacted by the volume of perfused medium, the presence of air bubbles, and medium evaporation, all of which are common concerns in perfusion bioreactor systems. This study emphasizes the necessity of optimization of experimental variables, which may often be underreported or overlooked, and indicates steps which can be taken to address issues common to perfusion bioreactors for bone tissue engineering.

Transport and lymphatic uptake of monoclonal antibodies after subcutaneous injection

The subcutaneous injection has emerged to become a feasible self-administration practice for biotherapeutics due to the patient comfort and cost-effectiveness. However, the available knowledge about transport and absorption of these agents after subcutaneous injection is limited. Here, a mathematical framework to study the subcutaneous drug delivery of mAbs from injection to lymphatic uptake is presented. A three-dimensional poroelastic model is exploited to find the biomechanical response of the tissue by taking into account tissue deformation during the injection. The results show that including tissue deformability noticeably changes tissue poromechanical response due to the significant dependence of interstitial pressure on the tissue deformation. Moreover, the importance of the amount of lymph fluid at the injection site and the injection rate on the drug uptake to lymphatic capillaries is highlighted. Finally, variability of lymphatic uptake due to uncertainty in parameters including tissue poromechanical and lymphatic absorption parameters is evaluated. It is found that interstitial pressure due to injection is the major contributing factor in short-term lymphatic absorption, while the amount of lymph fluid at the site of injection determines the long-term absorption of the drug. Finally, it is shown that the lymphatic uptake results are consistent with experimental data available in the literature.

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.

Multiple approaches to predicting oxygen and glucose consumptions by HepG2 cells on porous scaffolds in an axial-flow bioreactor

In this study, the distribution of oxygen and glucose was evaluated along with consumption by hepatocytes using three different approaches. The methods include (i) Computational Fluid Dynamics (CFD) simulation, (ii) residence time distribution (RTD) analysis using a step-input coupled with segregation model or dispersion model, and (iii) experimentally determined consumption by HepG2 cells in an open-loop. Chitosan-gelatin (CG) scaffolds prepared by freeze-drying and polycaprolactone (PCL) scaffolds prepared by salt leaching technique were utilized for RTD analyses. The scaffold characteristics were used in CFD simulations i.e. Brinkman's equation for flow through porous medium, structural mechanics for fluid induced scaffold deformation, and advection-diffusion equation coupled with Michaelis-Menten rate equations for nutrient consumption. With the assumption that each hepatocyte behaves like a micro-batch reactor within the scaffold, segregation model was combined with RTD to determine exit concentration. A flow rate of 1 mL/min was used in the bioreactor seeded with 0.6 × 10(6) HepG2 cells/cm(3) on CG scaffolds and oxygen consumption was measured using two flow-through electrodes located at the inlet and outlet. Glucose in the spent growth medium was also analyzed. RTD results showed distribution of nutrients to depend on the surface characteristics of scaffolds. Comparisons of outlet oxygen concentrations between the simulation results, and experimental results showed good agreement with the dispersion model. Outlet oxygen concentrations from segregation model predictions were lower. Doubling the cell density showed a need for increasing the flow rate in CFD simulations. This integrated approach provide a useful strategy in designing bioreactors and monitoring tissue regeneration.

Regenerative orthopaedics: in vitro, in vivo...in silico

In silico, defined in analogy to in vitro and in vivo as those studies that are performed on a computer, is an essential step in problem-solving and product development in classical engineering fields. The use of in silico models is now slowly easing its way into medicine. In silico models are already used in orthopaedics for the planning of complicated surgeries, personalised implant design and the analysis of gait measurements. However, these in silico models often lack the simulation of the response of the biological system over time. In silico models focusing on the response of the biological systems are in full development. This review starts with an introduction into in silico models of orthopaedic processes. Special attention is paid to the classification of models according to their spatiotemporal scale (gene/protein to population) and the information they were built on (data vs hypotheses). Subsequently, the review focuses on the in silico models used in regenerative orthopaedics research. Contributions of in silico models to an enhanced understanding and optimisation of four key elements-cells, carriers, culture and clinics-are illustrated. Finally, a number of challenges are identified, related to the computational aspects but also to the integration of in silico tools into clinical practice.