Analysis of the in vitro nanoparticle-cell interactions via a smoothing-splines mixed-effects model
A mixed-effects statistical model has been developed to understand the nanoparticle (NP)-cell interactions and predict the rate of cellular uptake of NPs. NP-cell interactions are crucial for targeted drug delivery systems, cell-level diagnosis, and cancer treatment. The cellular uptake of NPs depen...
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Published in | Artificial cells, nanomedicine, and biotechnology Vol. 44; no. 3; pp. 800 - 810 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
Taylor & Francis
01.05.2016
Taylor & Francis Ltd |
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Abstract | A mixed-effects statistical model has been developed to understand the nanoparticle (NP)-cell interactions and predict the rate of cellular uptake of NPs. NP-cell interactions are crucial for targeted drug delivery systems, cell-level diagnosis, and cancer treatment. The cellular uptake of NPs depends on the size, charge, chemical structure, and concentration of NPs, and the incubation time. The vast number of combinations of these variable values disallows a comprehensive experimental study of NP-cell interactions. A mathematical model can, however, generalize the findings from a limited number of carefully designed experiments and can be used for the simulation of NP uptake rates, to design, plan, and compare alternative treatment options. We propose a mathematical model based on the data obtained from in vitro interactions of NP-healthy cells, through experiments conducted at the Nanomedicine and Advanced Technologies Research Center in Turkey. The proposed model predicts the cellular uptake rate of silica, polymethyl methacrylate, and polylactic acid NPs, given the incubation time, size, charge and concentration of NPs. This study implements the mixed-model methodology in the field of nanomedicine for the first time, and is the first mathematical model that predicts the rate of cellular uptake of NPs based on sound statistical principles. Our model provides a cost-effective tool for researchers developing targeted drug delivery systems. |
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AbstractList | A mixed-effects statistical model has been developed to understand the nanoparticle (NP)-cell interactions and predict the rate of cellular uptake of NPs. NP-cell interactions are crucial for targeted drug delivery systems, cell-level diagnosis, and cancer treatment. The cellular uptake of NPs depends on the size, charge, chemical structure, and concentration of NPs, and the incubation time. The vast number of combinations of these variable values disallows a comprehensive experimental study of NP-cell interactions. A mathematical model can, however, generalize the findings from a limited number of carefully designed experiments and can be used for the simulation of NP uptake rates, to design, plan, and compare alternative treatment options. We propose a mathematical model based on the data obtained from in vitro interactions of NP-healthy cells, through experiments conducted at the Nanomedicine and Advanced Technologies Research Center in Turkey. The proposed model predicts the cellular uptake rate of silica, polymethyl methacrylate, and polylactic acid NPs, given the incubation time, size, charge and concentration of NPs. This study implements the mixed-model methodology in the field of nanomedicine for the first time, and is the first mathematical model that predicts the rate of cellular uptake of NPs based on sound statistical principles. Our model provides a cost-effective tool for researchers developing targeted drug delivery systems. |
Author | Budak, Gurer Dogruoz, Elifnur Dayanik, Savas Sabuncuoglu, Ihsan |
Author_xml | – sequence: 1 givenname: Elifnur surname: Dogruoz fullname: Dogruoz, Elifnur organization: Department of Industrial Engineering, Bilkent University – sequence: 2 givenname: Savas surname: Dayanik fullname: Dayanik, Savas organization: Department of Industrial Engineering, Bilkent University – sequence: 3 givenname: Gurer surname: Budak fullname: Budak, Gurer email: drgurerbudak@yahoo.com organization: Nanomedicine and Advanced Technologies Research Center – sequence: 4 givenname: Ihsan surname: Sabuncuoglu fullname: Sabuncuoglu, Ihsan organization: Department of Industrial Engineering, Abdullah Gul University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25962529$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Animals Cancer Cell interactions Cellular structure Computer simulation Drug delivery Drug delivery systems Humans In vitro methods and tests linear mixed model Mathematical analysis Mathematical models Models, Chemical nanomedicine nanoparticle uptake rate Nanoparticles Nanoparticles - chemistry Nanotechnology Polyesters - chemistry Polylactic acid Polymethyl methacrylate Polymethyl Methacrylate - chemistry Polymethylmethacrylate Silica Silicon dioxide Silicon Dioxide - chemistry Smoothing smoothing splines Splines System effectiveness targeted drug delivery |
Title | Analysis of the in vitro nanoparticle-cell interactions via a smoothing-splines mixed-effects model |
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