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Artificial Intelligence (AI) and AI-driven technologies are transforming industries across the board, with the pharmaceutical sector emerging as a frontrunner beneficiary. This article explores the growing impact of AI and Machine Learning (ML) within pharmaceutical Regulatory Affairs, particularly in dossier preparation, compilation, documentation, submission, review, and regulatory compliance. By automating time-intensive tasks, these technologies streamline workflows, accelerate result generation, and shorten the product approval timeline.

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Improving Generalizability of Drug-Target Binding Prediction by Pre-trained Multi-view Molecular Representations.

Bioinformatics

January 2025

School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun, 130117, Jilin China.

Motivation: Most drugs start on their journey inside the body by binding the right target proteins. This is the reason that numerous efforts have been devoted to predicting the drug-target binding during drug development. However, the inherent diversity among molecular properties, coupled with limited training data availability, poses challenges to the accuracy and generalizability of these methods beyond their training domain.

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Unveiling cyclodextrin conjugation as multidentate excipients: An exploratory journey across industries.

Carbohydr Res

December 2024

Department of Physics, Rayat Shikshan Sanstha's Dada Patil Mahavidyalaya, Karjat, Dist - Ahemadnagar, M.S. 414 402, India.

The discovery of branched molecules like dextrin by Schardinger in 1903 marked the inception of cyclodextrin (CD) utilization, catalyzing its journey from laboratory experimentation to widespread commercialization within the pharmaceutical industry. CD, a cyclic oligosaccharide containing glucopyranose units, acts as a versatile guest molecule, forming inclusion complexes (ICs) with various host molecules. Computational studies have become instrumental in elucidating the intricate interactions between β-CD and guest molecules, enabling the prediction of binding energy, forces, affinity, and complex stability.

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Objective: To determine the relationships between psilocybin dose, psychedelic experiences, and therapeutic outcome in treatment-resistant depression.

Methods: For treatment-resistant depression, 233 participants received a single dose of 25, 10, or 1 mg of COMP360 psilocybin (a proprietary, pharmaceutical-grade synthesized psilocybin formulation, developed by the sponsor, Compass Pathfinder Ltd.) with psychological support.

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Impact of noradrenergic inhibition on neuroinflammation and pathophysiology in mouse models of Alzheimer's disease.

J Neuroinflammation

December 2024

Department of Neurosurgery, Stanford University School of Medicine, 1050 Arastradero Road, Building A, Palo Alto, Stanford, CA, 94304, United States of America.

Norepinephrine (NE) modulates cognitive function, arousal, attention, and responses to novelty and stress, and it also regulates neuroinflammation. We previously demonstrated behavioral and immunomodulatory effects of beta-adrenergic pharmacology in mouse models of Alzheimer's disease (AD). The current studies were designed to block noradrenergic signaling in 5XFAD mice through (1) chemogenetic inhibition of the locus coeruleus (LC), (2) pharmacologic blocking of β-adrenergic receptors, and (3) conditional deletion of β1- or β2-adrenergic receptors (adrb1 or adrb2) in microglia.

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