Secure CheckoutPersonal information is secured with SSL technology.
Free ShippingFree global shipping
No minimum order.
Modeling and Control of Drug Delivery Systems provides comprehensive coverage of various drug delivery and targeting systems and their state-of-the-art related works, ranging from theory to real-world deployment and future perspectives. Various drug delivery and targeting systems have been developed to minimize drug degradation and adverse effect and increase drug bioavailability. Site-specific drug delivery may be either an active and/or passive process. Improving delivery techniques that minimize toxicity and increase efficacy offer significant potential benefits to patients and open up new markets for pharmaceutical companies.
This book will attract many researchers working in DDS field as it provides an essential source of information for pharmaceutical scientists and pharmacologists working in academia as well as in the industry. In addition, it has useful information for pharmaceutical physicians and scientists in many disciplines involved in developing DDS, such as chemical engineering, biomedical engineering, protein engineering, gene therapy.
- Presents some of the latest innovations of approaches to DDS from dynamic controlled drug delivery, modeling, system analysis, optimization, control and monitoring
- Provides a unique, recent and comprehensive reference on DDS with the focus on cutting-edge technologies and the latest research trends in the area
- Covers the most recent works, in particular, the challenging areas related to modeling and control techniques applied to DDS
Researchers, graduate students, engineers and practitioners in Biomedical Engineering, Control Engineering, Chemical Engineering, Computer Engineering and Computer Science. Researchers, graduate students, and practitioners in Electrical and Electronics Engineering; Mathematics and Applied Mathematics; Engineering Mathematics; Physics; Computational Physics; and Pharmaceutical Sciences
Part I: Modelling of Drug delivery systems:
1. A review of magnet systems for targeted drug delivery
2. Metabolic modelling of insulin delivery system
3. Applications of nanotechnology in drug delivery to the central nervous system
4. Modelling and design of Brain-Targeted Drug Delivery system
5. Nano-, micro-, and macroscale drug delivery systems for cancer immunotherapy
6. Dynamics of drug delivery to the healthy and diseased brain
7. Bioinspired and biomimetic systems for advanced drug and gene delivery
8. Smart Drug Delivery Systems for Cancer Treatment
9. Polymer-based platinum drug delivery systems
10. Drug delivery to retinal photoreceptors
11. 3D printed drug delivery systems
Part II: Control Methods of Drug Delivery systems
12. Bioresponsive closed-loop drug delivery systems
13. Closed-loop smart drug delivery system for diabetic therapy
14. Control of anesthetic drug delivery systems
15. Anaesthetic depth control using closed loop anaesthesia delivery system
16. Nonlinear adaptive controller design for drug delivery in cancerous tumor chemotherapy
17. Sliding mode control of drug delivery in cancerous tumour chemotherapy
18. Artificial intelligence in drug delivery system design
19. PID controllers of drug delivery system to control mean arterial blood pressure
20. An intelligent adaptive control scheme for postsurgical blood pressure regulation
21. Adaptive predictive controller for computerized drug delivery systems
22. Magnetic control of potential microrobotic drug delivery systems
23. Automated Drug Infusion System Based on Deep Convolutional Neural Networks
- No. of pages:
- © Academic Press 2021
- 1st February 2021
- Academic Press
- Paperback ISBN:
Prof. Ahmad Azar has received the M.Sc. degree in 2006 and Ph.D degree in 2009 from Faculty of Engineering, Cairo University, Egypt. He is a research associate Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is also an associate professor at the Faculty of Computers and Artificial intelligence, Benha University, Egypt. Prof. Azar is the Editor in Chief of International Journal of System Dynamics Applications (IJSDA) and International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) published by IGI Global, USA. Also, he is the Editor in Chief of International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. Prof. Azar has worked as associate editor of IEEE Trans. Neural Networks and Learning Systems from 2013 to 2017. He is currently Associate Editor of ISA Transactios, Elsevier and IEEE systems journal. Dr. Ahmad Azar has worked in the areas of Control Theory & Applications, Process Control, Chaos Control and Synchronization, Nonlinear control, Renewable Energy, Computational Intelligence and has authored/coauthored over 200 research publications in peer-reviewed reputed journals, book chapters and conference proceedings. He is an editor of many books in the field of fuzzy logic systems, modeling techniques, control systems, computational intelligence, chaos modeling and machine learning. Dr. Ahmad Azar is closely associated with several international journals as a reviewer. He serves as international programme committee member in many international and peer-reviewed conferences. Dr. Ahmad Azar has been a senior member of IEEE since December 2013 due to his significant contributions to the profession. Dr. Ahmad Azar is the recipient of several awards including: Benha University Prize for Scientific Excellence (2015, 2016, 2017 and 2018), the paper citation award from Benha University (2015, 2016, 2017 and 2018). In June 2018, Prof. Azar was awarded the Egyptian State Prize in Engineering Sciences, the Academy of Scientific Research and Technology of Egypt, 2017. In July 2018 he was selected as a member of Energy and Electricity Research council, Academy of Scientific Research, Ministry of Higher Education. In August 2018 he was selected as senior member of International Rough Set Society (IRSS).
Research Associate Professor, Prince Sultan University, Riyadh, Kingdom Saudi Arabia; Associate Professor, Faculty of Computers and Artificial intelligence, Benha University, Egypt
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.