Sessions Topics

The session will discuss an overview on the Egyptian Drug Authority (EDA).

Aiman S. El-Khatib , Ph.D.

Vice President of Egyptian Drug Authority (EDA)

Professor of Pharmacology and Toxicology, Faculty of Pharmacy, Cairo University, Egypt.

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The session will discuss the improvement of pharmacy education. The missing link between training and the competency-based education (CBE) of pharmacy in Egypt.

Ragia Ali Taha , Ph.D.

Vice President of The National Authority for Quality Assurance and Accreditation of Education “NAQAAE” 

Professor of Pharmacology and Toxicology, Faculty of Pharmacy, Al-Azhar University

The principle idea behind PBL is that the starting point for learning should be a problem, a query, or a puzzle that the learner wishes to solve. The inception and propagation of PBL in modern medical education is rightly credited to McMaster University Faculty of Health Sciences in Canada. PBL was first introduced in 1969. Many factors encouraged medical educators to adopt the revolutionary PBL system including the fact that traditional medical curricula were of highly lecture-based and discipline-oriented nature. This style of teaching rendered medical students into passive learners who failed to correlate basic science information during clinical years and students lacked motivation and preparation for life-long learning. Health care  students used to learn content independent of one another and then have difficulty seeing how it fits together. They were unable to apply their knowledge to real-life cases. This is where the disconnect happens in the traditional curriculum. PBL helps to connect what students are learning to the real world so they can react to it accordingly when they face it. This lecture will give tips ,  explain the PBL process, the classroom dynamics, PBL participants’ roles and the characteristics of a good PBL case.

Randa Mostafa , Senator, Ph.D.

Senator , Vice President of Education , Research and telecommunication at Egyptian senate 

Member of Pan African Parliament South Africa 

Fellow of Foundation for Advancement of Medical Education and Research

Professor of Physiology, Faculty of Medicine, Benha University

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DHFR inhibition is an important molecular target to combat cancer. A new series of 6-substituted amido, azo or thioureido-quinazolin-4(3H)-one was synthesized and tested for their in-vitro antitumor activity. Compounds 21, 53 and 60 showed broad spectrum antitumor activity with average IC50 values of 6.7, 7.6 and 9.1 mM, respectively compared with methotrexate (1, IC50 19.26 mM). As an attempt to reveal the mechanism of the antitumor potency, cell cycle analysis and DHFR inhibition were performed. Compounds 59 and 61 induced their cytotoxicity in Hela (IC50 10.6 μM) and HCT-116 (IC50 15.5 μM) cell lines, respectively through Pre-G1 apoptosis, inhibiting cell growth at G2-M phase. Compounds 29, 33, 59 and 61 showed DHFR inhibitory potency at IC50 0.2, 0.2, 0.3 and 0.3 mM, respectively. The active DHFR inhibitors showed high affinity binding toward the amino acid residues Thr56, Ser59 and Ser118. The active compounds obeyed Lipinski’s rule of five and could be used as template model for further optimization 

Hussein I. El-Subbagh, Ph.D, D.Sc

Professor of Medicinal Chemistry

Faculty of Pharmacy, Mansoura University

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Pharmacy as a dynamic sector of healthcare realm contributes significantly to societies and population thru interconnecting many fields of health sciences, technologies and demographics. Furthermore, pharmacy as a profession is multifaceted and knowledge-based with particular reference to medicine related pharmacological, ethical, legislative, economic, and sociologic contexts. Meantime, pharmacy practice constructs legitimate, theoretical and economic aspects underlying all professional practice models and processes. So, pharmacists are duly engaged with their societies in a tough challenging and ever-changing multisectoral environment that greatly overwhelmed with ethics and politics. Besides, a view through governance lens gives an instance that pharmacy is genuinely practiced within three main unique structures hold and sustain a set of three principal macro processes. The first one is the research and development macro process and subs; aimed at production of new pharmaceutical moieties based on medical practice and patient care needs. The second is manufacturing and profiling of the resulted new medicine products in the best form, formulation, package etc.., that comply with standards, regulations, and patient needs. Then the third is the on-ground utilisation macro process or the deployment and intervention with medicines and patients; it involves knowledge and outcomes of the preceding two structures in addition to supply chain logistics and particular interventions with healthcare spheres and workforce. Consequently, governance in pharmacy is now an evolving mandate as governance fundamentally defines fiduciary duties within these structures, helps setting and aligning the strategic direction for duty of care, functions and processes in the healthcare system. Uniformly, governance encourages and sustain excellence amid facilitating integration of macro/ meso / micro processes that help define authority, relationships and crossovers influences between several actors and bodies. In addition, governance strategies depict overseeing legal and functional compliance, through perpetual deployment and enforcement of tools and directives of partnership, audit, transparency and accountability as well as fighting corruption. Accordingly, governance assures the delivery of safe, responsive and integrated pharmacy services, that cope with individualised yet holistic needs in more appropriate and timely ways. And authorises care coordination and integration around the health system improving accessibility, affordability and quality of care.

Emad ElAzazy , PhD, PharmD, MPA, MBA

Professor of Governance Practices 

C.E.O. Arab Academy for Excellence in Governance 

Managing Director of the Arab Alliance for Governance 

Secretary General of Egyptian Healthcare Society (EHS) 

Board Member of Arab Union for Combating Counterfeiting & Forgery (AUCCF)

The ability to sequence whole plant and human genomes has taught us that our knowledge with respect to gene function is rather limited. Functional genomics analyses include investigations at the level of gene expression (transcriptomics), protein translation (proteomics) and more recently the metabolite network (metabolomics). Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. The analysis of the metabolome is particularly challenging due to the diverse chemical nature of metabolites in a cell and the massive number of molecules detected which warrants the use of bioinformatics for its analysis. This presentation provides an overview of metabolomics and discusses its complementary role within system biology. It highlights how metabolome analyses are being conducted using different spectroscopic techniques, and how the highly complex data generated are analyzed using bioinformatics tools. Specific examples will then be presented to illustrate how metabolomics can lead to valuable information relative to natural products biosynthesis, herbal medicines quality control analysis and  lastly analysis of ancient Pharaonic food.

Mohamed A. Farag, Ph.D.

TWAS fellow in Agriculture 

Alexander von Humboldt fellow 

Visiting Professor, American University in Cairo (AUC)  

Professor, Faculty of Pharmacy, Cairo University, Egypt.

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Zwitterionic polymer nanoparticles of diverse morphologies (spherical, cylindrical, and platelet-like) constructed from biocompatible sugar-based polymers are designed to extend the pharmacological activities of short- and long-acting insulin peptides, thereby providing potential for therapeutic systems capable of reducing the frequency of administration and improving patient compliance. Laser scanning confocal microscopy imaging of three-dimensional spheroids of vascular smooth muscle cells and fibroblasts after treatment with LIVE/DEAD® stain and FITC-insulin-loaded nanoparticles demonstrated high biocompatibility for the nanoconstructs of the various morphologies and significant intracellular uptake of insulin in both cell lines, respectively.  Binding of short-acting insulin and long-acting insulin glargine to nanoparticles resulted in extended hypoglycemic activities in rat models of diabetes, thus providing evidence of biocompatible nanoconstructs that are poised for further development toward the management of diabetes.       

1Elsabahy, M. et al. J Control Release, 334, 1 (2021).

Mahmoud Fahmy Elsabahy , Ph.D.

 Director of the BUC Science Academy 

Vice Dean of Faculty of Biotechnology 

Professor of Pharmaceutics Badr University in Cairo 

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Machine learning methods are a branch of artificial intelligence that utilizes certain software algorithms in order to make computers “learn” and to make hard and critical decision functions from representative data samples. They are specifically useful when certain software that is needed to perform a specific task or reach a targeted goal is unavailable or unfeasible. With the advent of the internet and the enormous growth of data that are obtained from huge number of sources, the recent advances in various statistical and programming tools and the continuous innovations in machine learning algorithms have resulted in a rapid increase in new applications in the different areas of pharmaceutics and drug delivery disciplines. Over the past 20 years, this new approach of data analysis has been extensively used in drug development and delivery. Machine learning methods offer several advantages over the other conventional statistical methods. First, the majority of these methods can model nonlinear relationships that are hard-to-model using the common quantitative structure-bioavailability or structure–property relationships methods. Second, they can model incomplete data or nontrending data and the users do not have to suggest any models or particular deigns before use. In other words, no restrictions are encountered while implementing machine learning algorithms where all types of data whether binary classification, multiple classes and continuous data can be analyzed and modeled. And finally, these methods can they offer. Integrating the machine learning methods into drug delivery saves costs, resources, time, and effort. In this talk, different types of the machine learning methods that were exploited in drug delivery aspects and applications will be demonstrated and discussed. These methods are currently considered important elements of the new approach of computer-aided drug formulation design (CADFD) and computer- aided pharmaceutical technology. The cross-disciplinary integration of drug delivery and machine learning methods as a branch of artificial intelligence may shift the paradigm of pharmaceutical research from experience-dependent investigations to data-driven studies.

Rania Mohammed Hathout , Ph.D.

 Professor and Head of Department of Pharmaceutics and Industrial Pharmacy – Faculty of Pharmacy – Ain Shams University.

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Health and insurance reform plans necessitate rigorous economic and clinical evaluations when considering new health technologies to optimize health resource allocation. Cost-utility analysis (CUA) is a vital tool in economic evaluations that uses utilities from Preference-Based Measurements such as Short form 6 Dimensions version 2 (SF-6Dv2). Eliciting public preferences can be done using several techniques the require optimization. Herein, I plan in my talk to display, examine and compare the feasibility of using an online population sample to elicit preference utility values for the SF-6Dv2 from Best-Worst Scaling case 2 (BWS), Discrete Choice Experiment (DCE), and Time Trade-Off (TTO).

Ahmed M.Y. Osman , Ph.D.

 School of Pharmaceutical Science and Technology, Tianjin University, China

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