AIMC Topic: Drug Development
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Recent advances in antibody optimization based on deep learning methods.
Journal of Zhejiang University. Science. B
May 28, 2025
Antibodies currently comprise the predominant treatment modality for a variety of diseases; therefore, optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development. Inspired by the great success of a...
The Role of Artificial Intelligence in Drug Discovery and Pharmaceutical Development: A Paradigm Shift in the History of Pharmaceutical Industries.
AAPS PharmSciTech
May 14, 2025
In today's world, with an increasing patient population, the need for medications is increasing rapidly. However, the current practice of drug development is time-consuming and requires a lot of investment by the pharmaceutical industries. Currently,...
Leveraging large language models to compare perspectives on integrating QSP and AI/ML.
Journal of pharmacokinetics and pharmacodynamics
May 5, 2025
Two recent papers offer contrasting perspectives on integrating Quantitative Systems Pharmacology (QSP) and Artificial Intelligence/Machine Learning (AI/ML): one views QSP as the primary driver using AI/ML to enhance computational tasks, while the ot...
Advances and critical aspects in cancer treatment development using digital twins.
Briefings in bioinformatics
May 1, 2025
The emergence of digital twins (DTs) in the arena of anticancer treatment echoes the transformative impact of artificial intelligence in drug development. DTs provide dynamic, accessible platforms that may accurately replicate patient and tumor chara...
Artificial intelligence to predict inhibitors of drug-metabolizing enzymes and transporters for safer drug design.
Expert opinion on drug discovery
May 1, 2025
INTRODUCTION: Drug-metabolizing enzymes (DMEs) and transporters (DTs) play integral roles in drug metabolism and drug-drug interactions (DDIs) which directly impact drug efficacy and safety. It is well-established that inhibition of DMEs and DTs ofte...
AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference.
Clinical and translational science
Apr 1, 2025
Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical trials, and patient care. This review summarizes the key takeaways from the AI preconference at the...
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models.
Molecular informatics
Mar 1, 2025
The blood brain barrier (BBB) is an endothelial-derived structure which restricts the movement of certain molecules between the general somatic circulatory system to the central nervous system (CNS). While the BBB maintains homeostasis by regulating ...
A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications.
Clinical and translational science
Mar 1, 2025
Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field of drug development. A sound understanding of the underlying concepts and guiding principles of AI/ML implementation is a prerequisite to identifying ...
AI in fungal drug development: opportunities, challenges, and future outlook.
Frontiers in cellular and infection microbiology
Jan 1, 2025
The application of artificial intelligence (AI) in fungal drug development offers innovative strategies to address the escalating threat of fungal infections and the challenge of antifungal resistance. This review evaluates the current landscape of f...
Explainable Artificial Intelligence in the Field of Drug Research.
Drug design, development and therapy
Jan 1, 2025
In recent years, the widespread use of artificial intelligence (AI) and big data technologies in drug research has significantly accelerated the drug development process. However, their black-box nature makes it challenging to evaluate their effectiv...
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