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Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks

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Abstract

In this study, nanosuspension of stable iodine (127I) was prepared by nanoprecipitation process in microfluidic devices. Then, size of particles was optimized using artificial neural networks (ANNs) modeling. The size of prepared particles was evaluated by dynamic light scattering. The response surfaces obtained from ANNs model illustrated the determining effect of input variables (solvent and antisolvent flow rate, surfactant concentration, and solvent temperature) on the output variable (nanoparticle size). Comparing the 3D graphs revealed that solvent and antisolvent flow rate had reverse relation with size of nanoparticles. Also, those graphs indicated that the solvent temperature at low values had an indirect relation with size of stable iodine (127I) nanoparticles, while at the high values, a direct relation was observed. In addition, it was found that the effect of surfactant concentration on particle size in the nanosuspension of stable iodine (127I) was depended on the solvent temperature.

Nanoprecipitation process of stable iodine (127I) and optimization of particle size using ANNs modeling.

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ACKNOWLEDGMENTS

This project was supported by the vice-chancellor of research at Bushehr University of Medical Sciences and Health Services grant no 20-18-3-46333. The author wishes also to thank Dr. Afshin Ostovar for his support in this research.

Conflict of Interest

The authors express that they have no conflicts of interest declaration to display.

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Authors and Affiliations

  1. Faculty of Advanced Medical Technology, Golestan University of Medical Sciences, Gorgan, Iran

    Mohamad Hosein Aghajani

  2. Department of Nanotechnology, The Persian Gulf Nuclear Medicine Research Center, The Persian Gulf Biomedical Sciences Institute, Bushehr University of Medical Sciences, Bushehr, Iran

    Ali Mahmoud Pashazadeh, Majid Assadi & Mahdi Aghajani

  3. Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran

    Seyed Hossein Mostafavi & Mahdi Aghajani

  4. Nanotechnology Research Centre, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran

    Seyed Hossein Mostafavi

  5. Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran

    Shayan Abbasi

  6. Shohadaye Khalije Fars Hospital, Bushehr University of Medical Sciences, Bushehr, Iran

    Mohammad-Javad Hajibagheri-Fard

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  1. Mohamad Hosein Aghajani
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  2. Ali Mahmoud Pashazadeh
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  3. Seyed Hossein Mostafavi
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  5. Mohammad-Javad Hajibagheri-Fard
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  6. Majid Assadi
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  7. Mahdi Aghajani
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Correspondence to Mahdi Aghajani.

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Aghajani, M.H., Pashazadeh, A.M., Mostafavi, S.H. et al. Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks. AAPS PharmSciTech 16, 1059–1068 (2015). https://doi.org/10.1208/s12249-015-0293-1

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  • DOI: https://doi.org/10.1208/s12249-015-0293-1

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