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

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

Aghajani MH¹ ; Pashazadeh AM² ; Mostafavi SH^{3, 4} ; Abbasi S⁵ ; Hajibagherifard MJ⁶ ; Assadi M² ; Aghajani M^{2, 3}

Show Affiliations

1. Golestan University of Medical Sciences, Gorgan, Iran
2. Department of Nanotechnology, The Persian Gulf Nuclear Medicine Research Center, The Persian Gulf Biomedical Sciences Institute, Bushehr University of Medical Sciences, Bushehr, Iran
3. Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
4. Nanotechnology Research Centre, Tehran University of Medical Sciences, Tehran, Iran
5. Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
6. Shohadaye Khalije Fars Hospital, Bushehr University of Medical Sciences, Bushehr, Iran

Source: AAPS PharmSciTech Published:2015

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. © 2015, American Association of Pharmaceutical Scientists.

Related Docs

View other Related Docs

1. Optimizing Microfluidic Preparation Parameters of Nanosuspension to Evaluate Stability in Nanoprecipitation of Stable-Iodine (127I), SN Applied Sciences (2019)

2. Genotoxicity of Noscapine Nanosuspension Prepared by Microfluidic Reactors on Hepg2 Cell Line, Iranian Journal of Chemistry and Chemical Engineering (2020)

3. Design and Optimization of Noscapine Nanosuspensions and Study of Its Cytotoxic Effect, Journal of Biomolecular Structure and Dynamics (2019)

4. Formation of Nanosuspensions in Bottom-Up Approach: Theories and Optimization, DARU# Journal of Pharmaceutical Sciences (2019)

5. Optimization of Paclitaxel-Loaded Poly (D,L-Lactide-Co-Glycolide-N-P-Maleimido Benzoic Hydrazide) Nanoparticles Size Using Artificial Neural Networks, Pharmaceutical Development and Technology (2015)

6. Optimization of Cefixime Nanosuspension to Improve Drug Dissolution, Pharmaceutical Sciences (2015)

7. Spray Drying of Nanoparticles to Form Fast Dissolving Glipizide, Asian Journal of Pharmaceutics (2015)

8. Development and Characterization of a Novel Spray-Dried Powder for Inhalation of Cinacalcet Hcl Nanoparticles, Pharmaceutical Sciences (2024)

Experts (# of related papers)

View all Related Experts

Alireza Vatanara (6)

Rassoul Dinarvand (3)

Style	Citing Format
MLA	Aghajani MH, et al.. "Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks." AAPS PharmSciTech, vol. 16, no. 5, 2015, pp. 1059-1068.
APA	Aghajani MH, Pashazadeh AM, Mostafavi SH, Abbasi S, Hajibagherifard MJ, Assadi M, Aghajani M (2015). Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks. AAPS PharmSciTech, 16(5), 1059-1068.
Chicago	Aghajani MH, Pashazadeh AM, Mostafavi SH, Abbasi S, Hajibagherifard MJ, Assadi M, Aghajani M. "Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks." AAPS PharmSciTech 16, no. 5 (2015): 1059-1068.
Harvard	Aghajani MH et al. (2015) 'Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks', AAPS PharmSciTech, 16(5), pp. 1059-1068.
Vancouver	Aghajani MH, Pashazadeh AM, Mostafavi SH, Abbasi S, Hajibagherifard MJ, Assadi M, et al.. Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks. AAPS PharmSciTech. 2015;16(5):1059-1068.
BibTex	@article{ author = {Aghajani MH and Pashazadeh AM and Mostafavi SH and Abbasi S and Hajibagherifard MJ and Assadi M and Aghajani M}, title = {Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks}, journal = {AAPS PharmSciTech}, volume = {16}, number = {5}, pages = {1059-1068}, year = {2015} }
RIS	TY - JOUR AU - Aghajani MH AU - Pashazadeh AM AU - Mostafavi SH AU - Abbasi S AU - Hajibagherifard MJ AU - Assadi M AU - Aghajani M TI - Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks JO - AAPS PharmSciTech VL - 16 IS - 5 SP - 1059 EP - 1068 PY - 2015 ER -

Science Communicator Platform

Authors

Authors Affiliations

Abstract