Human In Silico Trials for Parametric Computational Fluid Dynamics Investigation of Cerebrospinal Fluid Drug Delivery: Impact of Injection Location, Injection Protocol, and Physiology

Abstract BackgroundIntrathecal drug delivery has a significant role in pain management and CNS disease therapeutics. A fluid-physics based tool to assist clinicians in choosing specific drug doses to the spine or brain may help improve treatment schedules. MethodsThis study applied computational fluid dynamics (CFD) and in vitro model verification to assess intrathecal drug delivery in an anatomically realistic model of the human CSF system. Key parameters analyzed included the role of a) injection location including lumbar puncture (LP), cisterna magna (CM) and intracerebroventricular (ICV), b) LP injection rate, injection volume, and flush volume, c) physiologic factors including cardiac-induced and deep respiration-induced CSF stroke volume increase. Simulations were conducted for 3-hours post-injection and used to quantify spatial-temporal tracer concentration, regional area under the curve (AUC), time to maximum concentration (T max ), and maximum concentration (C max ), for each case. ResultsCM and ICV increased AUC to brain regions by ~2 logs compared to all other simulations. A 3X increase in bolus volume and addition of a 5 mL flush both increased intracranial AUC to the brain up to 2X compared to a baseline 5 mL LP injection. In contrast, a 5X increase in bolus rate (25 mL/min) did not improve tracer exposure to the brain. An increase in cardiac and respiratory CSF movement improved tracer spread to the brain, basal cistern, and cerebellum up to ~2 logs compared to the baseline LP injection. ConclusionThe computational modeling approach provides ability to conduct in silico trials representative of CSF injection protocols. Taken together, the findings indicate a strong potential for delivery protocols to be optimized to reach a target region(s) of the spine and/or brain with a needed therapeutic dose. Parametric modification of bolus rate/volume and flush volume was found to have impact on tracer distribution; albeit to a smaller degree than injection location, with CM and ICV injections resulting in greater therapeutic dose to brain regions compared to LP. CSF stroke volume and frequency both played an important role and may potentially have a greater impact than the modest changes in LP injection protocols analyzed such as bolus rate, volume, and flush.

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Management of Glioblastoma Multiforme by Phytochemicals: Applications of Nanoparticle Based Targeted Drug Delivery System

Current Drug Targets ◽

10.2174/1389450121666200727115454 ◽

2020 ◽

Vol 21 ◽

Author(s):

Sayed Md Mumtaz ◽

Gautam Bhardwaj ◽

Shikha Goswami ◽

Rajiv Kumar Tonk ◽

Ramesh K. Goyal ◽

...

Keyword(s):

Drug Delivery ◽

Glioblastoma Multiforme ◽

Drug Delivery System ◽

Delivery System ◽

Genetic Disorder ◽

Drug Regimen ◽

Brain Regions ◽

Radio Therapy ◽

Novel Drug ◽

The Brain

: The Glioblastoma Multiforme (GBM; grade IV astrocytoma) exhort tumor of star-shaped glial cell in the brain. It is a fast-growing tumor that spreads to nearby brain regions specifically to cerebral hemispheres in frontal and temporal lobes. The etiology of GBM is unknown, but major risk factors are genetic disorder like neurofibromatosis and schwanomatosis which develop the tumor in the nervous system. The management of GBM with chemo-radio therapy leads to resistance and current drug regimen like Temozolomide (TMZ) is less efficacious. The reasons behind failure of drugs are due to DNA alkylation in cell cycle by enzyme DNA guanidase and mitochondrial dysfunction. Naturally occurring bio-active compounds from plants known as phytochemicals, serve as vital sources for anti-cancer drugs. Some typical examples include taxol analogs, vinca alkaloids such as vincristine, vinblastine, podophyllotoxin analogs, camptothecin, curcumin, aloe emodin, quercetin, berberine e.t.c. These phytochemicals often act via regulating molecular pathways which are implicated in growth and progression of cancers. However the challenges posed by the presence of BBB/BBTB to restrict passage of these phytochemicals, culminates in their low bioavailability and relative toxicity. In this review we integrated nanotech as novel drug delivery system to deliver phytochemicals from traditional medicine to the specific site within the brain for the management of GBM.

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Coupled in silico platform: Computational fluid dynamics (CFD) and physiologically-based pharmacokinetic (PBPK) modelling

European Journal of Pharmaceutical Sciences ◽

10.1016/j.ejps.2017.10.022 ◽

2018 ◽

Vol 113 ◽

pp. 171-184 ◽

Cited By ~ 8

Author(s):

Aleksandra Vulović ◽

Tijana Šušteršič ◽

Sandra Cvijić ◽

Svetlana Ibrić ◽

Nenad Filipović

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

In Silico ◽

Pbpk Modelling ◽

Physiologically Based Pharmacokinetic ◽

Physiologically Based ◽

Computational Fluid Dynamics Cfd

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Evaluation of Pulmonary Arterial Hypertension Using Computational Fluid Dynamics Simulation

Volume 3: Biomedical and Biotechnology Engineering ◽

10.1115/imece2017-70193 ◽

2017 ◽

Author(s):

Shahab Taherian ◽

Hamid Rahai ◽

Jamie Shin ◽

Jeremy Feldman ◽

Thomas Waddington

Keyword(s):

Fluid Dynamics ◽

Boundary Condition ◽

Computational Fluid Dynamics ◽

Pulmonary Arterial Hypertension ◽

Arterial Hypertension ◽

In Silico ◽

Lumped Parameter Model ◽

Lumped Parameter ◽

Pulmonary Arterial ◽

Outlet Boundary Condition

In silico study of the relationships between flow conditions, arterial surface shear stress, and pressure was investigated in a patient with pulmonary arterial hypertension (PAH), using multi-detector Computed Tomography Angiography (CTA) images and Computational Fluid Dynamics (CFD). The CTA images were converted into 3D models and transferred to CFD software for simulations, allowing for patient-specific comparisons between in silico results with clinical right heart catheterization pressure data. The simulations were performed using two different methods of outlet boundary conditions: zero traction and lumped parameter model (LPM) methods. Outlet pressures were set to a constant value in zero traction method, which can produce flow characteristics solely based on the segmented distal arteries, while the lumped parameter model used a three-element Windkessel lumped model to represent the distal vasculature by accounting for resistance, compliance, and impedance of the vasculature. Considering existing limitations with both approaches, it was found that the lumped parameter Windkessel outlet boundary condition provides a better correlation with the clinical RHC pressure results than the zero traction constant pressure outlet boundary condition.

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Using Computational Fluid Dynamics to Design and Optimize a Novel Endovascular Procedure for Carotid Stenosis Repair

ASME 2008 Summer Bioengineering Conference, Parts A and B ◽

10.1115/sbc2008-193042 ◽

2008 ◽

Author(s):

Victoria Yeh ◽

C. Alberto Figueroa ◽

Andrea Les ◽

Jacqueline P. Ho ◽

Ronald Dalman ◽

...

Keyword(s):

United States ◽

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Carotid Artery ◽

Carotid Arteries ◽

The United States ◽

The Third ◽

Cerebral Blood Supply ◽

The Brain ◽

Over Time

The carotid arteries, located in both sides of the neck, are critical to supplying oxygenated blood to the brain. Over time, atherosclerotic plaque may accumulate in these vessels, causing them to narrow, which results in a reduced cerebral blood supply. This condition is known as carotid artery stenosis. In addition, small pieces of this plaque may become dislodged and travel to the brain, resulting in a stroke. Seven hundred thousand Americans suffer a stroke in the United States each year, and 150,000 cases are fatal, making it the third leading cause of death in the United States.

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Use of computational fluid dynamics deposition modeling in respiratory drug delivery

Expert Opinion on Drug Delivery ◽

10.1080/17425247.2019.1551875 ◽

2018 ◽

Vol 16 (1) ◽

pp. 7-26 ◽

Cited By ~ 11

Author(s):

P. Worth Longest ◽

Karl Bass ◽

Rabijit Dutta ◽

Vijaya Rani ◽

Morgan L. Thomas ◽

...

Keyword(s):

Fluid Dynamics ◽

Drug Delivery ◽

Computational Fluid Dynamics ◽

Respiratory Drug Delivery ◽

Deposition Modeling

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Abstract 4263: Characterization of patient-specific drug delivery for breast cancer using image-guided computational fluid dynamics

10.1158/1538-7445.am2020-4263 ◽

2020 ◽

Author(s):

Chengyue Wu ◽

David A. Hormuth ◽

Federico Pineda ◽

Gregory S. Karczmar ◽

Robert D. Moser ◽

...

Keyword(s):

Breast Cancer ◽

Fluid Dynamics ◽

Drug Delivery ◽

Computational Fluid Dynamics ◽

Patient Specific ◽

Specific Drug ◽

Image Guided

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Leatherbacks Swimming In Silico: Modeling and Verifying Their Momentum and Heat Balance Using Computational Fluid Dynamics

PLoS ONE ◽

10.1371/journal.pone.0110701 ◽

2014 ◽

Vol 9 (10) ◽

pp. e110701 ◽

Cited By ~ 4

Author(s):

Peter N. Dudley ◽

Riccardo Bonazza ◽

T. Todd Jones ◽

Jeanette Wyneken ◽

Warren P. Porter

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Heat Balance ◽

In Silico ◽

In Silico Modeling

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Computational Fluid Dynamics Analysis of Early Embryonic Aortic Arch-Ligation

Volume 1A: Abdominal Aortic Aneurysms; Active and Reactive Soft Matter; Atherosclerosis; BioFluid Mechanics; Education; Biotransport Phenomena; Bone, Joint and Spine Mechanics; Brain Injury; Cardiac Mechanics; Cardiovascular Devices, Fluids and Imaging; Cartilage and Disc Mechanics; Cell and Tissue Engineering; Cerebral Aneurysms; Computational Biofluid Dynamics; Device Design, Human Dynamics, and Rehabilitation; Drug Delivery and Disease Treatment; Engineered Cellular Environments ◽

10.1115/sbc2013-14470 ◽

2013 ◽

Author(s):

Prahlad G. Menon ◽

William Kowalski ◽

Kerem Pekkan

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

In Silico ◽

Great Artery ◽

Short Term ◽

Vascular Morphogenesis ◽

Computational Fluid Dynamics Analysis ◽

The Us ◽

Computational Fluid Dynamics Cfd ◽

Biomechanical Forces

Congenital heart disease occurs in 8 out of every 1000 live births in the US and more than half of this population is associated with great artery lesions. Selective remodeling of the paired, bilaterally symmetric embryonic aortic arches (AA) is a crucial stage in vascular morphogenesis and has known association with biomechanical forces [1]. Fetal cardiac interventions are currently explored clinically as an alternative repair technique for congenital anomalies, in-utero [2]. Several computational fluid dynamics (CFD) studies have been performed focusing on subject specific embryonic cardiovascular anatomies [3–5]. These developments could benefit fetal interventions that are planned in-silico before execution. To demonstrate this possibility, we computed the hemodynamic variation and wall shear stress (WSS) patterns resulting from systematic in-silico AA ligation intervention performed on normal chick AA models viz. Hamburger Hamilton (HH) stage 18 and 24 (3 and 4 days, respectively). A unique methodology employing CFD-computed WSS for modeling short-term biological growth response on AA morphogenesis is also presented.

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