Transport and lymphatic uptake of monoclonal antibodies after subcutaneous injection

Autoinjector optimization through cavitation response and severity minimization

Abrupt acceleration of the syringe of an autoinjector (AI) upon rod-plunger impact may induce undesired severe cavitation events and impose extraneous stresses upon the device, leading to device failure. Cavitation results from a rapid and significant pressure drop in a liquid, leading to the formation and growth of small vapor-filled cavities. Upon collapse, these cavities generate an intense shock wave that may lead to protein aggregation and device container damage and shatter. Since the maximum acceleration of the syringe depends upon the operating conditions of the AI, the severity of cavitation will likewise depend on the operating conditions of the AI. Likewise, injection time and ensuring proper needle displacement before drug release also depend on operating conditions, making optimization of the autoinjector a multiobjective optimization problem. Therefore, in this study, optimization of an autoinjector to limit cavitation severity is pursued via an experimentally validated computational model for cavitation in spring-driven autoinjectors. Our goal is to locate AI design configurations that balance maximizing device performance and patient comfort and minimizing the risks of device damage and severe cavitation upon actuation. Relevant parameters of interest are the drive spring force, air gap height, solution viscosity, friction between the rod and spring, frictional force on the plunger, rates of change of frictional force on the plunger, elasticity of plunger, viscosity of the plunger, and initial displacement between the plunger and the driving rod. The kinematics of the syringe barrel, needle displacement (travel distance) at the start of drug delivery, and injection time are gathered using an experimentally validated autoinjector kinematics model. At the same time, cavitation bubble dynamics are resolved using an experimentally validated cavitation model that takes the temporal displacement of the syringe and temporal air gap pressure as inputs. We use our experimentally validated models to explore the parameter space and understand the driving factors of our desired outcomes. Subsequently, we pose the design problem as a multi-objective optimization problem and develop a deep neural network surrogate model supplemented with iterative learning to speed up optimization. A variance-based sensitivity analysis was performed to determine the sensitivity and influence of design parameters on the outcomes, and the main contributors to the outcomes of interest were isolated. Using a multi-objective optimization framework, we located 300 + successful candidates and evaluated them through uncertainty analysis to identify three promising candidates that meet all criteria for drug viscosities of interest. Finally, we show that this methodology can be used to conduct hypothesis testing, leading to novel design configurations.

The role of initial lymphatics in the absorption of monoclonal antibodies after subcutaneous injection

The subcutaneous injection is the most common method of administration of monoclonal antibodies (mAbs) due to the patient's comfort and cost-effectiveness. However, the available knowledge about the transport and absorption of this type of biotherapeutics 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 poro-hyperelastic model of the tissue is exploited to find the biomechanical response of the tissue together with a transport model based on an advection-diffusion equation in large-deformation poro-hyperelastic Media. The process of mAbs transport to the lymphatic system has two major parts. First is the initial phase, where mAbs are dispersed in the tissue due to momentum exerted by injection. This stage lasts for only a few minutes after the injection. Then there is the second stage, which can take tens of hours, and as a result, mAb molecules are transported from the subcutaneous layer towards initial lymphatics in the dermis to enter the lymphatic system. In this study, we investigate both stages. The process of plume formation, interstitial pressure, and velocity development is explored. Then, the effect of the injection delivery parameters, injection site, and sensitivity of long-term lymphatic uptake due to variability in permeability, diffusivity, viscosity, and binding of mAbs are investigated. Finally, we study two different injection scenarios with variable injection volume and drug concentration inside the syringe and evaluate them based on the rate of lymphatic uptake. We use our results to find an equivalent lymphatic uptake coefficient similar to the coefficient widely used in pharmacokinetic (PK) models to study the absorption of mAbs. Ultimately, we validate our computational model against available experiments in the literature.

Landscape of Subcutaneous Administration Strategies for Monoclonal Antibodies in Oncology

In recent decades, subcutaneous (SC) administration of monoclonal antibodies (mAbs) has emerged as a promising alternative to intravenous delivery in oncology, offering comparable therapeutic efficacy while addressing patient preferences. This perspective article provides an in-depth analysis of the technological landscape surrounding SC mAb administration in oncology. It outlines various technologies under evaluation across developmental stages, spanning from preclinical investigations to the integration of established methodologies in clinical practice. Additionally, this perspective article explores emerging trends and prospective trajectories, shedding light on the evolving landscape of SC mAb administration. Furthermore, it emphasizes key checkpoints related to quality attributes essential for optimizing mAb delivery via the SC route. This review serves as a valuable resource for researchers, clinicians, and healthcare policymakers, offering insights into the advancement of SC mAb administration in oncology and its implications for patient care.

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.

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.

Inter-Antibody Variability in the Clinical Pharmacokinetics of Monoclonal Antibodies Characterized Using Population Physiologically Based Pharmacokinetic Modeling

The objective of this work was to develop a population physiologically based pharmacokinetic (popPBPK) model to characterize the variability in the clinical PK of monoclonal antibodies (mAbs) following intravenous (IV) and subcutaneous (SC) administration. An extensive literature search was conducted and clinical PK data for FDA-approved as well as non-approved mAbs were collected. Training and validation datasets of 44 and 9 mAbs exhibiting linear pharmacokinetics were used for model development. The variability in antibody PK was captured by accounting for different rate constants of pinocytosis (CLup) and intracellular degradation (kdeg) for different mAbs. Typical values for CLup and kdeg and their respective inter-antibody variabilities (ωClup, ωKdeg) were estimated to be 0.32 L/h/L and 26.1 h-1 (73% and 46%). Varied absorption profiles following SC dosing were characterized by incorporating inter-antibody variability in local degradation (kSC) and rate of lymphatic uptake (S_Lu) of mAbs. Estimates for typical kSC and S_Lu values, and ωKsc,ωS_Lu, were found to be 0.0015 h-1 and 0.54 (193%, and 49%). FDA-approved mAbs showed less local degradation (0.0014 h-1 vs. 0.0038 h-1) compared with other clinically tested mAbs, whereas no substantial differences in physiological processes involved in disposition were observed. To evaluate the generalizability of estimated PK parameters and model validation, the final popPBPK model was used to simulate the range of expected PK for mAbs following SC administration of nine different mAbs that were not used for model-building purposes. The predicted PK of all nine mAbs was within the expected range specified a priori. Thus, the popPBPK model presented here may serve as a tool to predict the clinical PK of mAbs with linear disposition before administering them to humans. The model may also support preclinical-to-clinical translation and 'first-in-human' dose determination for mAbs.

Poroelastic Characterization and Modeling of Subcutaneous Tissue Under Confined Compression

Subcutaneous tissue mechanics are important for drug delivery. Yet, even though this material is poroelastic, its mechanical characterization has focused on its hyperelastic response. Moreover, advancement in subcutaneous drug delivery requires effective tissue mimics such as hydrogels for which similar gaps of poroelastic data exist. Porcine subcutaneous samples and gelatin hydrogels were tested under confined compression at physiological conditions and strain rates of 0.01%/s in 5% strain steps with 2600 s of stress relaxation between loading steps. Force-time data were used in an inverse finite element approach to obtain material parameters. Tissues and gels were modeled as porous neo-Hookean materials with properties specified via shear modulus, effective solid volume fraction, initial hydraulic permeability, permeability exponent, and normalized viscous relaxation moduli. The constitutive model was implemented into an isogeometric analysis (IGA) framework to study subcutaneous injection. Subcutaneous tissue exhibited an initial spike in stress due to compression of the solid and fluid pressure buildup, with rapid relaxation explained by fluid drainage, and longer time-scale relaxation explained by viscous dissipation. The inferred parameters aligned with the ranges reported in the literature. Hydraulic permeability, the most important parameter for drug delivery, was in the rangek 0 ∈ [ 0.142 , 0.203 ] mm4 /(N s). With these parameters, IGA simulations showed peak stresses due to a 1-mL injection to reach 48.8 kPa at the site of injection, decaying after drug volume disperses into the tissue. The poro-hyper-viscoelastic neo-Hookean model captures the confined compression response of subcutaneous tissue and gelatin hydrogels. IGA implementation enables predictive simulations of drug delivery.

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.

A biomimetic chip to assess subcutaneous bioavailability of monoclonal antibodies in humans

Subcutaneous (subQ) injection is a common route for delivering biotherapeutics, wherein pharmacokinetics is largely influenced by drug transport in a complex subQ tissue microenvironment. The selection of good drug candidates with beneficial pharmacokinetics for subQ injections is currently limited by a lack of reliable testing models. To address this limitation, we report here a Subcutaneous Co-Culture Tissue-on-a-chip for Injection Simulation (SubCuTIS). SubCuTIS possesses a 3D coculture tissue architecture, and it allows facile quantitative determination of relevant scale independent drug transport rate constants. SubCuTIS captures key in vivo physiological characteristics of the subQ tissues, and it differentiates the transport behavior of various chemically distinct molecules. We supplemented the transport measurements with theoretical modeling, which identified subtle differences in the local absorption rate constants of seven clinically available mAbs. Accounting for first-order proteolytic catabolism, we established a mathematical framework to assess clinical bioavailability using the local absorption rate constants obtained from SubCuTIS. Taken together, the technology described here broadens the applicability of organs-on-chips as a standardized and easy-to-use device for quantitative analysis of subQ drug transport.

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.

Damage and Fracture Mechanics of Porcine Subcutaneous Tissue Under Tensile Loading

Subcutaneous injection, which is a preferred delivery method for many drugs, causes deformation, damage, and fracture of the subcutaneous tissue. Yet, experimental data and constitutive modeling of these dissipation mechanisms in subcutaneous tissue remain limited. Here we show that subcutaneous tissue from the belly and breast anatomical regions in the swine show nonlinear stress-strain response with the characteristic J-shaped behavior of collagenous tissue. Additionally, subcutaneous tissue experiences damage, defined as a decrease in the strain energy capacity, as a function of the previously experienced maximum deformation. The elastic and damage response of the tissue are accurately described by a microstructure-driven constitutive model that relies on the convolution of a neo-Hookean material of individual fibers with a fiber orientation distribution and a fiber recruitment distribution. The model fit revealed that subcutaneous tissue can be treated as initially isotropic, and that changes in the fiber recruitment distribution with loading are enough to explain the dissipation of energy due to damage. When tested until failure, subcutaneous tissue that has undergone damage fails at the same peak stress as virgin samples, but at a much larger stretch, overall increasing the tissue toughness. Together with a finite element implementation, these data and constitutive model may enable improved drug delivery strategies and other applications for which subcutaneous tissue biomechanics are relevant.

Solute Transport across the Lymphatic Vasculature in a Soft Skin Tissue

Convective transport of drug solutes in biological tissues is regulated by the interstitial fluid pressure, which plays a crucial role in drug absorption into the lymphatic system through the subcutaneous (SC) injection. In this paper, an approximate continuum poroelasticity model is developed to simulate the pressure evolution in the soft porous tissue during an SC injection. This poroelastic model mimics the deformation of the tissue by introducing the time variation of the interstitial fluid pressure. The advantage of this method lies in its computational time efficiency and simplicity, and it can accurately model the relaxation of pressure. The interstitial fluid pressure obtained using the proposed model is validated against both the analytical and the numerical solution of the poroelastic tissue model. The decreasing elasticity elongates the relaxation time of pressure, and the sensitivity of pressure relaxation to elasticity decreases with the hydraulic permeability, while the increasing porosity and permeability due to deformation alleviate the high pressure. An improved Kedem-Katchalsky model is developed to study solute transport across the lymphatic vessel network, including convection and diffusion in the multi-layered poroelastic tissue with a hybrid discrete-continuum vessel network embedded inside. At last, the effect of different structures of the lymphatic vessel network, such as fractal trees and Voronoi structure, on the lymphatic uptake is investigated. In this paper, we provide a novel and time-efficient computational model for solute transport across the lymphatic vasculature connecting the microscopic properties of the lymphatic vessel membrane to the macroscopic drug absorption.

Role of nanotechnology in the prolonged release of drugs by the subcutaneous route

INTRODUCTION

Subcutaneous physiology is distinct from other parenteral routes that benefit the administration of prolonged-release formulations. A prolonged-release effect is particularly convenient for treating chronic diseases because it is associated with complex and often prolonged posologies. Therefore, drug-delivery systems focused on nanotechnology are proposed as alternatives that can overcome the limitations of current therapeutic regimens and improve therapeutic efficacy.

AREAS COVERED

This review presents an updated systematization of nanosystems, focusing on their applications in highly prevalent chronic diseases. Subcutaneous-delivered nanosystem-based therapies comprehensively summarize nanosystems, drugs, and diseases and their advantages, limitations, and strategies to increase their translation into clinical applications. An outline of the potential contribution of quality-by-design (QbD) and artificial intelligence (AI) to the pharmaceutical development of nanosystems is presented.

EXPERT OPINION

Although recent academic research and development (R&D) advances in the subcutaneous delivery of nanosystems have exhibited promising results, pharmaceutical industries and regulatory agencies need to catch up. The lack of standardized methodologies for analyzing in vitro data from nanosystems for subcutaneous administration and subsequent in vivo correlation limits their access to clinical trials. There is an urgent need for regulatory agencies to develop methods that faithfully mimic subcutaneous administration and specific guidelines for evaluating nanosystems.

Hydrodynamic considerations for spring-driven autoinjector design

In recent years, significant progress has been made in the studies of the spring-driven autoinjector, leading to an improved understanding of this device and its interactions with tissue and therapeutic proteins. The development of simulation tools that have been validated against experiments has also enhanced the prediction of the performance of spring-driven autoinjectors. This paper aims to address critical hydrodynamic considerations that impact the design of spring-driven autoinjectors, with a specific emphasis on sloshing and cavitation. Additionally, we present a framework that integrates simulation tools to predict the performance of spring-driven autoinjectors and optimize their design. This work is valuable to the pharmaceutic industry, as it provides crucial insights into the development of spring-driven autoinjectors and therapeutic proteins. This work can also enhance the efficacy and safety of the delivery of therapeutic proteins, ultimately improving patient outcomes.

Optimizing autoinjector devices using physics-based simulations and Gaussian processes

Autoinjectors are becoming a primary drug delivery option to the subcutaneous space. These devices need to work robustly and autonomously to maximize drug bio-availability. However, current designs ignore the coupling between autoinjector dynamics and tissue biomechanics. Here we present a Bayesian framework for optimization of autoinjector devices that can account for the coupled autoinjector-tissue biomechanics and uncertainty in tissue mechanical behavior. The framework relies on replacing the high fidelity model of tissue insertion with a Gaussian process (GP). The GP model is accurate yet computationally affordable, enabling a thorough sensitivity analysis that identified tissue properties, which are not part of the autoinjector design space, as important variables for the injection process. Higher fracture toughness decreases the crack depth, while tissue shear modulus has the opposite effect. The sensitivity analysis also shows that drug viscosity and spring force, which are part of the design space, affect the location and timing of drug delivery. Low viscosity could lead to premature delivery, but can be prevented with smaller spring forces, while higher viscosity could prevent premature delivery while demanding larger spring forces and increasing the time of injection. Increasing the spring force guarantees penetration to the desired depth, but it can result in undesirably high accelerations. The Bayesian optimization framework tackles the challenge of designing devices with performance metrics coupled to uncertain tissue properties. This work is important for the design of other medical devices for which optimization in the presence of material behavior uncertainty is needed.

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.

Lymphatic uptake of biotherapeutics through a 3D hybrid discrete-continuum vessel network in the skin tissue

Subcutaneous administration is a common approach for the delivery of biotherapeutics, which is achieved mainly through the absorption across lymphatic vessels. In this paper, the drug transport and lymphatic uptake through a three-dimensional hybrid discrete-continuum vessel network in the skin tissue are investigated through high-fidelity numerical simulations. We find that the local lymphatic uptake through the explicit vessels significantly affects macroscopic drug absorption. The diffusion of drug solute through the explicit vessel network affects the lymphatic uptake after the injection. This effect, however, cannot be captured using previously developed continuum models. The lymphatic uptake is dominated by the convection due to lymphatic drainage driven by the pressure difference, which is rarely studied in experiments and simulations. Furthermore, the effects of injection volume and depth on the lymphatic uptake are investigated in a multi-layered domain. We find that the injection volume significantly affects the rate of lymphatic uptake through the heterogeneous vessel network, while the injection depth has little influence, which is consistent with the experimental results. At last, the binding and metabolism of drug molecules are studied to bridge the simulations to the drug clearance experients. We provide a new approach to study the diffusion and convection of drug molecules into the lymphatic system through the hybrid vessel network.

Mixed-dimensional multi-scale poroelastic modeling of adipose tissue for subcutaneous injection

Subcutaneous injection of therapeutic monoclonal antibodies (mAbs) has gained increasing interest in the pharmaceutical industry. The transport, distribution and absorption of mAbs in the skin after injection are not yet well-understood. Experiments have shown that fibrous septa form preferential channels for fluid flow in the tissue. The majority of mAbs can only be absorbed through lymphatics which follow closely the septa network. Therefore, studying drug transport in the septa network is vital to the understanding of drug absorption. In this work, we present a mixed-dimensional multi-scale (MDMS) poroelastic model of adipose tissue for subcutaneous injection. More specifically, we model the fibrous septa as reduced-dimensional microscale interfaces embedded in the macroscale tissue matrix. The model is first verified by comparing numerical results against the full-dimensional model where fibrous septa are resolved using fine meshes. Then, we apply the MDMS model to study subcutaneous injection. It is found that the permeability ratio between the septa and matrix, volume capacity of the septa network, and concentration-dependent drug viscosity are important factors affecting the amount of drug entering the septa network which are paths to lymphatics. Our results show that septa play a critical role in the transport of mAbs in the subcutaneous tissue, and this role was previously overlooked.

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. .

A framework to optimize spring-driven autoinjectors

The major challenges in the optimization of autoinjectors lie in developing an accurate model and meeting competing requirements. We have developed a computational model for spring-driven autoinjectors, which can accurately predict the kinematics of the syringe barrel, needle displacement (travel distance) at the start of drug delivery, and injection time. This paper focuses on proposing a framework to optimize the single-design of autoinjectors, which deliver multiple drugs with different viscosity. We replace the computational model for spring-driven autoinjectors with a surrogate model, i.e., a deep neural network, which improves computational efficiency 1,000 times. Using this surrogate, we perform Sobol sensitivity analysis to understand the effect of each model input on the quantities of interest. Additionally, we pose the design problem within a multi-objective optimization framework. We use our surrogate to discover the corresponding Pareto optimal designs via Pymoo, an open source library for multi-objective optimization. After these steps, we evaluate the robustness of these solutions and finally identify two promising candidates. This framework can be effectively used for device design optimization as the computation is not demanding, and decision-makers can easily incorporate their preferences into this framework.