Mathematical Modeling of Vesicle Drug Delivery Systems 2: Targeted Vesicle Interactions with Cells, Tumors, and the Body

Ying, Chong T.; Wang, Juntian; Lamm, Robert J.; Kamei, Daniel T.

doi:10.1177/2211068212458265

Cited by 5 publications

(2 citation statements)

References 41 publications

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“…The total amount of drug Q(t) released from the polymer by the time t, which is an important characteristic of the process, can be found using (18) as…”

Section: ˆ( )mentioning

confidence: 99%

“…Anomalous diffusion in gels has potential applications in the problem of controlled drug delivery. Mathematical modeling of controlled drug delivery has been attracting much attention of scientists [13][14][15][16][17][18][19]. Analysis of the drug delivery process is often based on traditional models that typically involve a standard Fickian diffusion equation.…”

Section: Introductionmentioning

confidence: 99%

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Similarity solution of a Stefan drug-release subdiffusion problem

Volpert

Nepomnyashchy

2016

Phys. Scr.

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“…The total amount of drug Q(t) released from the polymer by the time t, which is an important characteristic of the process, can be found using (18) as…”

Section: ˆ( )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Similarity solution of a Stefan drug-release subdiffusion problem

Volpert

Nepomnyashchy

2016

Phys. Scr.

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Modeling bioaffinity‐based targeted delivery of antimicrobials to Escherichia coli biofilms using yeast microparticles. Part II: Parameter evaluation and validation

Huang

Nitin

2021

Biotech & Bioengineering

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The design of bioaffinity-based targeted delivery systems for biofilm inactivation may require a comprehensive understanding of physicochemical and biochemical properties of biobased antimicrobial particles and their interactions with biofilm. In this study, Escherichia coli biofilm inactivation by chlorine-charged yeast microparticles was numerically simulated, and the roles of chemical stability, binding affinity, and controlled release of this targeted delivery system were assessed using this numerical simulation. The simulation results were experimentally validated using two different types of yeast microparticles.The results of this study illustrate that chorine stability achieved by yeast microparticles was a key factor for improved biofilm inactivation in an organic-rich environment (>6 additional log reduction in 20 min compared to the free chlorine treatment). Moreover, the binding affinity of yeast microparticles to E. coli biofilms was another key factor for an enhanced inactivation of biofilm, as a 10-fold increase in binding rate resulted in a 4.2-fold faster inactivation. Overall, the mechanistic modeling framework developed in this study could guide the design and development of biobased particles for targeted inactivation of biofilms.

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