Name: Dr. Zahraa Khalifa
Research interest: Advanced delivery systems, nanotechnology, vaccine adjuvants, drug discovery
Presenting By: 17th Global Digital Pharma, Clinical Trials & Drug Delivery Conference, taking place December 17–19, 2025, in Dubai, UAE, and virtually.
Introduction: Artificial intelligence (AI) is reshaping the pharmaceutical industry, offering new ways to make drug discovery and development more efficient and innovative. This presentation provides a practical overview of how AI is being used across the entire drug development pipeline, from identifying potential targets to optimizing formulations and predicting clinical outcomes.
We begin with how AI helps make sense of complex genomic data to identify disease-related genes and proteins. Deep learning and network-based models are increasingly being used to discover promising drug targets that might otherwise be overlooked [1]. From there, we explore how AI supports virtual screening, predicting how potential drug molecules interact with their targets, simulating molecular docking, and improving early-stage drug design. Generative models even allow for the creation of entirely new molecules with desired properties [2].
In the development stage, AI enables in-silico prediction of ADMET (absorption, distribution, metabolism, excretion, toxicity) to streamline lead optimization and reduce the need for animal testing [3]. AI also plays a growing role in formulation design, helping select excipients that enhance solubility and stability, and in process simulation to predict how manufacturing conditions affect product quality. Modeling drug release kinetics and establishing IVIVC (in-vitro/in-vivo correlation) further supports efficient development. Lastly, AI is being used to forecast clinical trial outcomes, guide patient selection, and support personalized medicine through pharmacogenomics.
Throughout the pipeline, we also demonstrate how a variety of open-source and specialized tools such as Python-based libraries (RDKit, DeepChem), STRING, and Open Targets are used to implement these AI approaches in research applications.
This talk offers a real-world look at how AI is not just a research tool, but a transformative force across the entire pharmaceutical R&D pipeline, along with the ethical, regulatory, and technical challenges that still lie ahead.
Keywords: Artificial intelligence, drug discovery, virtual screening, molecular design, formulation optimization, in-silico modeling, pharmacogenomics, DeepChem, RDKit, STRING, Open Targets.
References:
[1] Y. Wu et al. (2024) “The role of artificial intelligence in drug screening, drug design, and clinical trials,” Front. Pharmacol., vol. 15.[2] Z. Wu et al. (2018) “MoleculeNet: a benchmark for molecular machine learning,” Chem. Sci., vol. 9, pp. 513–530.[3] S. S. Shinde et al. (2025) “Chapter Four – ADMET tools in the digital era: Applications and limitations,” Advances in Pharmacology, vol. 103, vol. 103., pp. 65–80.
Biography: Dr. Zahraa has completed her PhD in Pharmaceutical Sciences (Drug Delivery) from the University of Strathclyde, UK. She is currently a Lecturer at the Pharmaceutical Sciences Department, Dubai Medical University. With over a decade of experience in teaching and research, her expertise lies in drug delivery and the development of advanced delivery systems. She has authored several Scopus-indexed publications and is committed to advancing pharmaceutical education and innovation. Dr. Zahraa also holds a Postgraduate Certificate in Artificial Intelligence in Drug Discovery from the London School of International Business.
Speaker Page: https://pharmacy.utilitarianconferences.com/speaker/dr-zahraa-khalifa
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