Fiscal Year 2018 National Defense Authorization Act, Section 734, Weapon Systems Line of Inquiry: Overview and Blast Overpressure Tool-A Module for Human Body Blast Wave Exposure for Safer Weapons Training.

INTRODUCTION: Experiences by service members in recent conflicts and training environments illuminate concerns about the possible effects of blast overpressure (BOP) exposure on brain health. Section 734 of the National Defense Authorization Act for Fiscal Year (FY) 2018 (Public Law 115-91) requires that the Secretary of Defense conducts a longitudinal medical study on blast pressure exposure of members of the Armed Forces during combat and training, and the Assistant Secretary of Defense for Health Affairs was assigned responsibility for fulfilling requirements. The study's goal is to improve DoD's understanding of the impact of BOP exposure from weapon systems on service members' brain health and inform policy for risk mitigation, unit readiness, and health care decisions. This article focuses on the activities of the Weapon Systems Line of Inquiry (LOI) and the development of a prototype BOP Tool. MATERIALS AND METHODS: The DoD established the Section 734 Workgroup, which developed a program structure with five LOIs. The Weapon Systems LOI coordinated, collated, and analyzed information on BOP resulting from heavy weapons and blast events to inform strategies, and accounted for emerging research on health effects and performance. Ongoing research was leveraged to develop a BOP Tool as a standalone module and for integration into the Range Managers Toolkit. RESULTS: The effort identified opportunities for the DoD to improve the clarity of communications about BOP exposure, risk, and safety; establish methods to leverage emerging research; and develop a prototype BOP Tool to predict exposure loads when firing heavy weapons in training. CONCLUSIONS: It is recommended that the DoD revises requirements and policy to improve and standardize safety guidance throughout research, development, testing, and evaluation; acquisition; and training. The validated BOP Tool allows users to generate a scenario to predict BOP exposure and allows service members to modify them during planning for safer training.

A Comparative Evaluation of Desoximetasone Cream and Ointment Formulations Using Experiments and In Silico Modeling.

The administration of therapeutic drugs through dermal routes, such as creams and ointments, has emerged as an increasingly popular alternative to traditional delivery methods, such as tablets and injections. In the context of drug development, it is crucial to identify the optimal doses and delivery routes that ensure successful outcomes. Physiologically based pharmacokinetic (PBPK) models have been proposed to simulate drug delivery and optimize drug formulations, but the calibration of these models is challenging due to the multitude of variables involved and limited experimental data. One significant research gap that this article addresses is the need for more efficient and accurate methods for calibrating PBPK models for dermal drug delivery. This manuscript presents a novel approach and an integrated dermal drug delivery model to address this gap that leverages virtual in vitro release (IVRT) and permeation (IVPT) testing data to optimize mechanistic models. The proposed approach was demonstrated through a study involving Desoximetasone cream and ointment formulations, where the release kinetics and permeation profiles of Desoximetasone were determined experimentally, and a computational model was created to simulate the results. The experimental studies showed that, even though the cumulative permeation of Desoximetasone at the end of the permeation study was comparable, there was a significant difference seen in the lag time in the permeation of Desoximetasone between the cream and ointment. Additionally, there was a significant difference seen in the amount of Desoximetasone permeated through human cadaver skin at early time points when the cream and ointment were compared. The computational model was optimized and validated, suggesting that this approach has the potential to bridge the existing research gap by improving the accuracy and efficiency of drug development processes. The model results show a good fit between the experimental data and model predictions. During the model optimization process, it became evident that there was variability in both the permeability and the partition coefficient within the stratum corneum. This variability had a significant and noteworthy influence on the overall performance of the model, especially when it came to its capacity to differentiate between cream and ointment formulations. Leveraging virtual models significantly aids the comprehension of drug release and permeation, mitigating the demanding data requirements. The use of virtual IVRT and IVPT data can accelerate the calibration of PBPK models, streamline the selection of the appropriate doses, and optimize drug delivery. Moreover, this novel approach could potentially reduce the time and resources involved in drug development, thus making it more cost-effective and efficient.

Computational Model of In Vivo Corneal Pharmacokinetics and Pharmacodynamics of Topically Administered Ophthalmic Drug Products.

INTRODUCTION: Although the eye is directly accessible on the surface of the human body, drug delivery can be extremely challenging due to the presence of multiple protective barriers in eye tissues. Researchers have developed complex formulation strategies to overcome these barriers to ophthalmic drug delivery. Current development strategies rely heavily on in vitro experiments and animal testing to predict human pharmacokinetics (PK) and pharmacodynamics (PD). OBJECTIVE: The primary objective of the study was to develop a high-fidelity PK/PD model of the anterior eye for topical application of ophthalmic drug products. METHODS: Here, we present a physiologically-based in silico approach to predicting PK and PD in rabbits after topical administration of ophthalmic products. A first-principles based approach was used to describe timolol dissolution, transport, and distribution, including consideration of ionized transport, following topical instillation of a timolol suspension. RESULTS: Using literature transport and response parameters, the computational model described well the concentration-time and response-time profiles in rabbit. Comparison of validated rabbit model results and extrapolated human model results demonstrate observable differences in the distribution of timolol at multiple time points. CONCLUSION: This modeling framework provides a tool for model-based prediction of PK in eye tissues and PD after topical ophthalmic drug administration to the eyes.

Mathematical model of mechanobiology of acute and repeated synaptic injury and systemic biomarker kinetics.

Background: Blast induced Traumatic Brain Injury (bTBI) has become a signature casualty of military operations. Recently, military medics observed neurocognitive deficits in servicemen exposed to repeated low level blast (LLB) waves during military heavy weapons training. In spite of significant clinical and preclinical TBI research, current understanding of injury mechanisms and short- and long-term outcomes is limited. Mathematical models of bTBI biomechanics and mechanobiology of sensitive neuro-structures such as synapses may help in better understanding of injury mechanisms and in the development of improved diagnostics and neuroprotective strategies. Methods and results: In this work, we formulated a model of a single synaptic structure integrating the dynamics of the synaptic cell adhesion molecules (CAMs) with the deformation mechanics of the synaptic cleft. The model can resolve time scales ranging from milliseconds during the hyperacute phase of mechanical loading to minutes-hours acute/chronic phase of injury progression/repair. The model was used to simulate the synaptic injury responses caused by repeated blast loads. Conclusion: Our simulations demonstrated the importance of the number of exposures compared to the duration of recovery period between repeated loads on the synaptic injury responses. The paper recognizes current limitations of the model and identifies potential improvements.

Mechanistic modeling of generic orally inhaled drug products: A workshop summary report.

In silico mechanistic modeling approaches have been designed by various stakeholders with the goal of supporting development and approval of generic orally inhaled drug products in the United States. This review summarizes the presentations and panel discussion that comprised a workshop session concentrated on the use of in silico models to predict various outcomes following orally inhaled drug product administration, including the status of such models and how model credibility may be effectively established.

A multi-organ chip with matured tissue niches linked by vascular flow.

Engineered tissues can be used to model human pathophysiology and test the efficacy and safety of drugs. Yet, to model whole-body physiology and systemic diseases, engineered tissues with preserved phenotypes need to physiologically communicate. Here we report the development and applicability of a tissue-chip system in which matured human heart, liver, bone and skin tissue niches are linked by recirculating vascular flow to allow for the recapitulation of interdependent organ functions. Each tissue is cultured in its own optimized environment and is separated from the common vascular flow by a selectively permeable endothelial barrier. The interlinked tissues maintained their molecular, structural and functional phenotypes over 4 weeks of culture, recapitulated the pharmacokinetic and pharmacodynamic profiles of doxorubicin in humans, allowed for the identification of early miRNA biomarkers of cardiotoxicity, and increased the predictive values of clinically observed miRNA responses relative to tissues cultured in isolation and to fluidically interlinked tissues in the absence of endothelial barriers. Vascularly linked and phenotypically stable matured human tissues may facilitate the clinical applicability of tissue chips.

Evaluating Drug Deposition Patterns from Turbuhaler® in Healthy and Diseased Lung Models of Preschool Children.

The efficacy of pediatric oral drug delivery using dry powder inhalers, such as Turbuhaler®, is dependent on the age and health of the test subjects. The available clinical data for these studies is scant and rarely provide correlations between the health condition and the regional lung deposition. In particular, the data and the correlations for pre-school children are minimal. Deposition simulations were performed using the newly developed Quasi-3D whole lung model to analyze the effect of health conditions on the regional lung deposition from the Turbuhaler® in 3-year-old children. The healthy lung model was created from CT scan data. Cystic-fibrosis models were created by uniformly constricting the airways to various degrees. The simulated drug deposition outcomes were validated against the available experimental data. The results show that, while the dose deposited in the lungs exhibits minor variations, the Peripheral:Central (P/C) ratio is strongly affected by both the health condition and the inflow variations. The above ratio is reduced by ~30% for the severely diseased case, compared to its healthy counterpart, for the same inhalation profile. This indicates that lower doses reach the peripheral lung, in pediatric cystic-fibrosis subjects, thus requiring a larger therapeutic dose.

An integrated biophysical model for predicting the clinical pharmacokinetics of transdermally delivered compounds.

The delivery of therapeutic drugs through the skin is a promising alternative to oral or parenteral delivery routes because dermal drug delivery systems (D3Ss) offer unique advantages, such as controlled drug release over sustained periods and a significant reduction in first-pass effects, thus reducing the required dosing frequency and the level of patient noncompliance. Furthermore, D3Ss find applications in multiple therapeutic areas, including drug repurposing. This article presents an integrated biophysical model of dermal absorption for simulating the permeation and absorption of compounds delivered transdermally. The biophysical model is physiologically/biologically inspired and combines a holistic model of healthy skin with whole-body physiology-based pharmacokinetics through the dermis microcirculation. The model also includes the effects of chemical penetration enhancers and hair follicles on transdermal transport. The model-predicted permeation and pharmacokinetics of select compounds were validated using in vivo data reported in the literature. We conjecture that the integrated model can be used to gather insights into the permeation and systemic absorption of transdermal formulations (including cosmetic products) released from novel depots and to optimize delivery systems. Furthermore, the model can be extended to diseased skin with parametrization and structural adjustments specific to skin diseases.

A quasi-3D model of the whole lung: airway extension to the tracheobronchial limit using the constrained constructive optimization and alveolar modeling, using a sac-trumpet model.

Existing computational models used for simulating the flow and species transport in the human airways are zero-dimensional (0D) compartmental, three-dimensional (3D) computational fluid dynamics (CFD), or the recently developed quasi-3D (Q3D) models. Unlike compartmental models, the full CFD and Q3D models are physiologically and anatomically consistent in the mouth and the upper airways, since the starting point of these models is the mouth-lung surface geometry, typically created from computed tomography (CT) scans. However, the current resolution of CT scans limits the airway detection between the 3rd-4th and 7th-9th generations. Consequently, CFD and the Q3D models developed using these scans are generally limited to these generations. In this study, we developed a method to extend the conducting airways from the end of the truncated Q3D lung to the tracheobronchial (TB) limit. We grew the lung generations within the closed lung lobes using the modified constrained constructive optimization, creating an aerodynamically optimized network aiming to produce equal pressure at the distal ends of the terminal segments. This resulted in a TB volume and lateral area of ∼165 cc and ∼2000 cm2, respectively. We created a "sac-trumpet" model at each of the TB outlets to represent the alveoli. The volumes of the airways and the individual alveolar generations match the anatomical values by design: with the functional residual capacity at 2611 cc. Lateral surface areas were scaled to match the physiological values. These generated Q3D whole lung models can be efficiently used for conducting multiple breathing cycles of drug transport and deposition simulations.

Fast-Running Tools for Personalized Monitoring of Blast Exposure in Military Training and Operations.

INTRODUCTION: During training and combat operations, military personnel may be exposed to repetitive low-level blast while using explosives to gain entry or by firing heavy weapon systems such as recoilless weapons and high-caliber sniper rifles. This repeated exposure, even within allowable limits, has been associated with cognitive deficits similar to that of accidental and sports concussion such as delayed verbal memory, visual-spatial memory, and executive function. This article presents a novel framework for accurate calculation of the human body blast exposure in military heavy weapon training scenarios using data from the free-field and warfighter wearable pressure sensors. MATERIALS AND METHODS: The CoBi human body model generator tools were used to reconstruct multiple training scenes with different weapon systems. The CoBi Blast tools were used to develop the weapon signature and estimate blast overpressure exposure. The authors have used data from the free-field and wearable pressure sensors to evaluate the framework. RESULTS: Carl-Gustav and 0.50 caliber sniper training scenarios were used to demonstrate and validate the developed framework. These simulations can calculate spatially and temporally resolved blast loads on the whole human body and on specific organs vulnerable to blast loads, such as head, face, and lungs. CONCLUSIONS: This framework has numerous advantages including easier model setup and shorter simulation times. The framework is an important step towards developing an advanced field-applicable technology to monitor low-level blast exposure during heavy weapon military training and combat scenarios.

Washing hands and the face may reduce COVID-19 infection.

The contribution of various modes of transmission of SARS-CoV-2 has been the subject of recent intensive debate. The predominant route of the viral transmission is via exhaled droplets of different sizes which can be inhaled by nearby exposed individuals or deposited on peoples and surfaces. Touching contaminated surfaces followed by hand to facial transfer has been identified as a potential infection route. As humans involuntarily touch their faces over 20 times per hour a hand washing with soap and water is recommended to avoid hands to face transmission. To date however, there is no clear explanation how the viruses arrive form the face into the nose and the lung. Our hypothesis is that during the physiological nasal air inspiration the virion particles attached on the face close to the nose are resuspended in the air and then are inhaled into the nose. Our preliminary fluid dynamics simulations confirm our hypothesis. Further experimental and computational studies are warranted.

A multiscale absorption and transit model for oral delivery of hydroxychloroquine: Pharmacokinetic modeling and intestinal concentration prediction to assess toxicity and drug-induced damage in healthy subjects.

Hydroxychloroquine (HCQ) is commonly used in the treatment of malaria and rheumatic diseases. Recently it has also been identified as possible therapeutic option in combating COVID-19. However, the use of HCQ is known to induce cytotoxicity. In 2020, we developed a multiscale absorption and transit (MAT) toolkit to simulate the dissolution, transport, absorption, distribution, metabolism, and elimination of orally administered drugs in the human GIT at multiple levels. MAT was constructed by integrating the spatially accurate first-principles driven high-fidelity drug transport, dissolution, and absorption model in the human stomach and GIT using the recently published Quasi-3D framework. The computational results showed that MAT was able to match the experimental concentration results better than the traditional compartmental models. In this study, we adapted MAT, to predict the pharmacokinetics of orally delivered HCQ in healthy subjects. The computational results matched the experimental concentration results. The simulated stomach and intestinal fluid and enterocyte concentrations were compared with the in vitro CC50 values. While the peak enterocyte concentrations were several orders lower than the in vitro CC50 values, the peak stomach and the intestinal fluid concentrations were only one order smaller than the in vitro CC50 values. In particular, the peak stomach and the duodenum fluid concentrations were just 3× smaller than the in vitro CC50 values. This implies that the lumen walls are much more susceptible to cytotoxicity-based damage than the enterocyte layers. We envision that MAT can be used to optimize the dosing regimen of HCQ by maximizing its bioavailability, while simultaneously minimizing the cytotoxic damage.

A multiscale absorption and transit model for oral drug delivery: Formulation and applications during fasting conditions.

Most Food and Drug Administration (FDA)-approved drugs are administered orally, despite the complex process of oral drug absorption that is difficult to analyze experimentally. Oral bioavailability is dependent on the drug compound as well as the physiological and anatomical states of the user. Thus, computational models have emerged to mechanistically capture and predict the oral absorption process. The current models are generally 0D compartmental models and are limited by (a) simplified physiological characteristics of the gastrointestinal tract (GIT), (b) semiempirical/analytical dissolution profiles of the tested drugs, (c) incorrect absorption for some drug BCS classes (class IIa, for example), (d) GITs size variability among population, (e) incorrectly predicting the absorption of drugs that are GIT target specific, and (f) erroneous mixing in the domain. In this study, we have developed a multiscale absorption and transit (MAT) toolkit to simulate the dissolution, transport, absorption, distribution, metabolism, and elimination of orally administered drugs in the human GIT at multiple levels. MAT was constructed by integrating the spatially accurate first-principles driven high-fidelity drug transport, dissolution, and absorption model in the human stomach and GIT using our recently published quasi-3D (Q3D) framework. The process integrated the multilayer intestine physiologically based pharmacokinetics models with the whole-body compartmental models to predict the systemic pharmacokinetics of oral drugs. The computational results showed that this multiscale tool was able to match the experimental concentration results (individual and population) better than the traditional compartmental models. Ultimately, MAT will be developed into a commercial product to meet urgent demands from pharmaceutical and biomedical industries.

Anthropometry-based generation of personalized and population-specific human airway models.

Understanding aerosol deposition in the human lung is of great significance in pulmonary toxicology and inhalation pharmacology. Adverse effects of inhaled environmental aerosols and pharmacological efficacy of inhaled therapeutics are dependent on aerosol properties as well as person-specific respiratory tract anatomy and physiology. Anatomical geometry and physiological function of human airways depend on age, gender, weight, fitness, health, and disease status. Tools for the generation of the population- and subject-specific virtual airway anatomical geometry based on anthropometric data and physiological vitals are invaluable in respiratory diagnostics, personalized pulmonary pharmacology, and model-based management of chronic respiratory diseases. Here we present a novel protocol and software framework for the generation of subject-specific airways based on anthropometric measurements of the subject's body, using the anatomical input, and the conventional spirometry, providing the functional (physiological) data. This model can be used for subject-specific simulations of respiration physiology, gas exchange, and aerosol inhalation and deposition.

Quantitative prediction of human pharmacokinetic responses to drugs via fluidically coupled vascularized organ chips.

Analyses of drug pharmacokinetics (PKs) and pharmacodynamics (PDs) performed in animals are often not predictive of drug PKs and PDs in humans, and in vitro PK and PD modelling does not provide quantitative PK parameters. Here, we show that physiological PK modelling of first-pass drug absorption, metabolism and excretion in humans-using computationally scaled data from multiple fluidically linked two-channel organ chips-predicts PK parameters for orally administered nicotine (using gut, liver and kidney chips) and for intravenously injected cisplatin (using coupled bone marrow, liver and kidney chips). The chips are linked through sequential robotic liquid transfers of a common blood substitute by their endothelium-lined channels (as reported by Novak et al. in an associated Article) and share an arteriovenous fluid-mixing reservoir. We also show that predictions of cisplatin PDs match previously reported patient data. The quantitative in-vitro-to-in-vivo translation of PK and PD parameters and the prediction of drug absorption, distribution, metabolism, excretion and toxicity through fluidically coupled organ chips may improve the design of drug-administration regimens for phase-I clinical trials.

Computational framework for predictive PBPK-PD-Tox simulations of opioids and antidotes.

The primary goal of this work was to develop a computational tool to enable personalized prediction of pharmacological disposition and associated responses for opioids and antidotes. Here we present a computational framework for physiologically-based pharmacokinetic (PBPK) modeling of an opioid (morphine) and an antidote (naloxone). At present, the model is solely personalized according to an individual's mass. These PK models are integrated with a minimal pharmacodynamic model of respiratory depression induction (associated with opioid administration) and reversal (associated with antidote administration). The model was developed and validated on human data for IV administration of morphine and naloxone. The model can be further extended to consider different routes of administration, as well as to study different combinations of opioid receptor agonists and antagonists. This work provides the framework for a tool that could be used in model-based management of pain, pharmacological treatment of opioid addiction, appropriate use of antidotes for opioid overdose and evaluation of abuse deterrent formulations.

Biomechanics of Blast TBI With Time-Resolved Consecutive Primary, Secondary, and Tertiary Loads.

Blast-induced traumatic brain injury (bTBI) has become a signature casualty of recent military operations. In spite of significant clinical and preclinical TBI research, current understanding of injury mechanisms and short- and long-term outcomes is limited. Mathematical models of bTBI biomechanics may help in better understanding of injury mechanisms and in the development of improved neuroprotective strategies. Until present, bTBI has been analyzed as a single event of a blast pressure wave propagating through the brain. In many bTBI events, the loads on the body and the head are spatially and temporarily distributed, involving the primary intracranial pressure wave, followed by the head rotation and then by head impact on the ground. In such cases, the brain microstructures may experience time/space distributed (consecutive) damage and recovery events. The paper presents a novel multiscale simulation framework that couples the body/brain scale biomechanics with micro-scale mechanobiology to study the effects of micro-damage to neuro-axonal structures. Our results show that the micro-mechanical responses of neuro-axonal structures occur sequentially in time with "damage" and "relaxation" periods in different parts of the brain. A new integrated computational framework is described coupling the brain-scale biomechanics with micro-mechanical damage to axonal and synaptic structures.

Do blast induced skull flexures result in axonal deformation?

Subject-specific computer models (male and female) of the human head were used to investigate the possible axonal deformation resulting from the primary phase blast-induced skull flexures. The corresponding axonal tractography was explicitly incorporated into these finite element models using a recently developed technique based on the embedded finite element method. These models were subjected to extensive verification against experimental studies which examined their pressure and displacement response under a wide range of loading conditions. Once verified, a parametric study was developed to investigate the axonal deformation for a wide range of loading overpressures and directions as well as varying cerebrospinal fluid (CSF) material models. This study focuses on early times during a blast event, just as the shock transverses the skull (< 5 milliseconds). Corresponding boundary conditions were applied to eliminate the rotation effects and the resulting axonal deformation. A total of 138 simulations were developed- 128 simulations for studying the different loading scenarios and 10 simulations for studying the effects of CSF material model variance-leading to a total of 10,702 simulation core hours. Extreme strains and strain rates along each of the fiber tracts in each of these scenarios were documented and presented here. The results suggest that the blast-induced skull flexures result in strain rates as high as 150-378 s-1. These high-strain rates of the axonal fiber tracts, caused by flexural displacement of the skull, could lead to a rate dependent micro-structural axonal damage, as pointed by other researchers.

A Quasi-3D compartmental multi-scale approach to detect and quantify diseased regional lung constriction using spirometry data.

Spirometry is a widely used pulmonary function test to detect the airflow limitations associated with various obstructive lung diseases, such as asthma, chronic obstructive pulmonary disease, and even obesity-related complications. These conditions arise due to the change in the airway resistance, alveolar compliance, and inductance values. Currently, zero-dimensional compartmental models are commonly used for calibrating these resistance, compliance, and inductance values, ie, solving the inverse spirometry problem. However, zero-dimensional compartments cannot capture the flow physics or the spatial geometry effects, thereby generating a low fidelity prediction of the diseased lung. Computational fluid dynamics (CFD) models offer higher fidelity solutions but may be impractical for certain applications due to the duration of these simulations. Recently, a novel, fast-running, and robust Quasi-3D (Q3D) wire model for simulating the airflow in the human lung airway was developed by CFD Research Corporation. This Q3D method preserved the 3D spatial nature of the airways and was favorably validated against CFD solutions. In the present study, the Q3D compartmental multi-scale combination is further improved to predict regional lung constriction of diseased lungs using spirometry data. The Q3D mesh is resolved up to the eighth lung airway generation. The remainder of the airways and the alveoli sections are modeled using a compartmental approach. The Q3D geometry is then split into different spatial sections, and the resistance values in these regions are obtained using parameter inversion. Finally, the airway diameter values are then reduced to create the actual diseased lung model, corresponding to these resistance values. This diseased lung model can be used for patient-specific drug deposition predictions and the subsequent optimization of the orally inhaled drug products.