Estimation of drug and tumor properties using novel hybrid meta-heuristic methods

Mirchi, Pedram; Soltani, M.

doi:10.1016/j.jtbi.2019.110121

Cited by 5 publications

(1 citation statement)

References 42 publications

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“…Numerous other mathematical approaches exist for optimizing model predictions that more efficiently explore the parameter space. These include genetic algorithms utilizing the rules that govern genetic evolution and have proven effective in a variety of related fields (Laranjeira et al, 2022 ; Mirchi & Soltani, 2020 ).…”

Section: Mathematical Modeling Of Drug Deliverymentioning

confidence: 99%

Perspectives on optimizing local delivery of drugs to peripheral nerves using mathematical models

Laranjeira

Roberton

Phillips

et al. 2023

WIREs Mechanisms of Disease

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Drug therapies for treating peripheral nerve injury repair have shown significant promise in preclinical studies. Despite this, drug treatments are not used routinely clinically to treat patients with peripheral nerve injuries. Drugs delivered systemically are often associated with adverse effects to other tissues and organs; it remains challenging to predict the effective concentration needed at an injured nerve and the appropriate delivery strategy. Local drug delivery approaches are being developed to mitigate this, for example via injections or biomaterialmediated release. We propose the integration of mathematical modeling into the development of local drug delivery protocols for peripheral nerve injury repair. Mathematical models have the potential to inform understanding of the different transport mechanisms at play, as well as quantitative predictions around the efficacy of individual local delivery protocols. We discuss existing approaches in the literature, including drawing from other research fields, and present a process for taking forward an integrated mathematical-experimental approach to accelerate local drug delivery approaches for peripheral nerve injury repair.

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Section: Mathematical Modeling Of Drug Deliverymentioning

confidence: 99%