AI approaches for the development of drug delivery systems

Shahiwala, Aliasgar

doi:10.1016/b978-0-323-89925-3.00004-6

Cited by 2 publications

References 52 publications

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Advancements and Perspectives in Folate‐Based Anticancer Drugs: Bridging Quantum and Classical Mechanics in Folate Receptor Research

Josiah,

Govender,

Govender

et al. 2024

Advcd Theory and Sims

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This review highlights the role of computational chemistry, specifically quantum and molecular mechanics, in the development of folate‐based anticancer drugs. Folate receptors (FRs) are overexpressed in cancerous cells, rendering these receptors a key focus in the design of targeted drug delivery systems. These computational tools are fundamental for analyzing drug–receptor interactions and overcoming the limitations of traditional drug development processes. A 10‐year literature survey demonstrated advancements in employing FRs for targeted cancer therapy. Key findings reveal that structural modifications to folate derivatives consistently enhance binding affinities and specificity toward FRα and FRβ. Computational methodologies predicted and analyzed molecular interactions, validated by experimental data. Functional groups play a crucial role in enhancing binding stability and interaction strength within FR binding pockets. Detailed structural insights into folate derivatives and antifolates interacting with FRs have identified critical residues involved in binding, aiding the design of targeted therapeutics.

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Advancements and Perspectives in Folate‐Based Anticancer Drugs: Bridging Quantum and Classical Mechanics in Folate Receptor Research

Josiah,

Govender,

Govender

et al. 2024

Advcd Theory and Sims

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An Overview of Artificial Intelligence (AI) In Drug Delivery and Development

Mutha,

Bagul,

Tade

et al. 2024

AI Innovations in Drug Delivery and Pharmaceutical Sciences; Advancing Therapy Through Technology

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The integration of Artificial Intelligence (AI) into pharmaceutical research represents a transformative leap in drug development, addressing the challenges posed by complex diseases and traditional methodologies. In this comprehensive overview, we explore the historical evolution of AI's role in pharmaceutical research and its crucial importance in drug delivery and development. The foundational elements of AI in drug delivery and development are elucidated through an in-depth analysis of machine learning (ML) algorithms, deep learning techniques, and natural language processing in bioinformatics. These form the bedrock for understanding the subsequent chapters that unravel the emerging roles of AI in drug discovery, formulation, and delivery. An insightful examination of drug repurposing and interaction reveals AIdriven strategies, providing new therapeutic avenues. The chapters further unravel AI's impact on pharmacokinetics, pharmacodynamics, and its data-driven approaches for dose optimization. Clinical trials and patient recruitment witness a revolution through AI, optimizing design and ensuring regulatory compliance and safety. This chapter promises a holistic understanding of the symbiotic relationship between AI and pharmaceuticals, offering a roadmap for innovation and efficiency in the pursuit of advanced healthcare solutions.

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AI approaches for the development of drug delivery systems

Cited by 2 publications

References 52 publications

Advancements and Perspectives in Folate‐Based Anticancer Drugs: Bridging Quantum and Classical Mechanics in Folate Receptor Research

Advancements and Perspectives in Folate‐Based Anticancer Drugs: Bridging Quantum and Classical Mechanics in Folate Receptor Research

An Overview of Artificial Intelligence (AI) In Drug Delivery and Development

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