Neural networks approach to optimization of aerosolized nanocolloidal carrier system containing quercetin for pulmonary delivery of lung cancer

Abstract

Event Abstract Back to Event Neural networks approach to optimization of aerosolized nanocolloidal carrier system containing quercetin for pulmonary delivery of lung cancer Mohd Basyaruddin Abdul Rahman1*, Noor Hafizah Arbain1, Norazlinaliza Salim1 and Wong Tin Hui2 1 Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, Malaysia 2 Non-Destructive Biomedical and Pharmaceutical Research Centre, Integrative Pharmacogenomics Institute, Universiti Teknologi MARA, Malaysia Background Globally, lung cancer has become the most common type of cancer cases. Quercetin (QT) has been extensively investigated for its pharmacological effects on lung cancer. However, clinical applications of QT are limited due to poor solubility and low stability in aqueous medium. Hence, this study focused on the development of nanocolloidal carrier system to enhance the solubility of QT by pulmonary administration. Methods The artificial neural networks (ANNs) was carried out for development of a predictive model of aerosolized quercetin (QT) nanoemulsions to achieve minimum volume median diameter for targetting lung cancer by pulmonary delivery. The effects of the amount of the mixture of palm oil esters:ricinoleic acid (1.5–4.5 wt.%), lecithin (1.5–2.5 wt.%), Tween 80 (0.5–1 wt.%), glycerol (1.5–3 wt.%), and water (88–94.95 wt.%) on the volume median diameter were considered as inputs to the network. The volume median diameter of the samples with various compositions was measured as an output. The incremental back propagation (IBP), batch back propagation (BBP), quick propagation (QP), and genetic algorithm (GA) were used in the network. Results It was found that the optimal algorithm and topology were the genetic algorithm (GA) and the configuration with 5 inputs, 14 hidden, and 1 output nodes, respectively. The model obtained indicated the high-quality performance of the neural network and its capability to identify the critical composition factors for the nanoemulsion. The formulation containing quercetin was then successfully prepared using optimum composition and volume median diameter of 4.266 μm was obtained. The QT-loaded nanoemulsion induced cytotoxic response with an IC50 value of 300 μg/mL against A549 lung cancer cells at 48 hours. Conclusion These results suggest that the nanocolloidal formulation containing QT could be successful carrier system for pulmonary drug delivery application. Acknowledgements The financial assistances received from Ministry of Higher Education Malaysia through MyBRAIN 15 for Arbain N.H. This work was supported by Universiti Malaya, LRGS NanoMITe-Ministry of Higher Education, Malaysia (RU029-2014/5526306). Keywords: Aerosols, Quercetin, Nanoemulsions, Pulmonary delivery, artificial neural network Conference: International Conference on Drug Discovery and Translational Medicine 2018 (ICDDTM '18) “Seizing Opportunities and Addressing Challenges of Precision Medicine”, Putrajaya, Malaysia, 3 Dec - 5 Feb, 2019. Presentation Type: Poster Presentation Topic: Cancer Citation: Abdul Rahman M, Arbain N, Salim N and Tin Hui W (2019). Neural networks approach to optimization of aerosolized nanocolloidal carrier system containing quercetin for pulmonary delivery of lung cancer. Front. Pharmacol. Conference Abstract: International Conference on Drug Discovery and Translational Medicine 2018 (ICDDTM '18) “Seizing Opportunities and Addressing Challenges of Precision Medicine”. doi: 10.3389/conf.fphar.2018.63.00151 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Nov 2018; Published Online: 17 Jan 2019. * Correspondence: Prof. Mohd Basyaruddin Abdul Rahman, Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, Serdang, Malaysia, basya@upm.edu.my Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Mohd Basyaruddin Abdul Rahman Noor Hafizah Arbain Norazlinaliza Salim Wong Tin Hui Google Mohd Basyaruddin Abdul Rahman Noor Hafizah Arbain Norazlinaliza Salim Wong Tin Hui Google Scholar Mohd Basyaruddin Abdul Rahman Noor Hafizah Arbain Norazlinaliza Salim Wong Tin Hui PubMed Mohd Basyaruddin Abdul Rahman Noor Hafizah Arbain Norazlinaliza Salim Wong Tin Hui Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.