Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 179, P. 108734 - 108734

Published: July 3, 2024

Language: Английский

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A Review of Large Language Models and Autonomous Agents in Chemistry

Chemical Science, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 9, 2024

Large language models (LLMs) have emerged as powerful tools in chemistry, significantly impacting molecule design, property prediction, and synthesis optimization. This review highlights LLM capabilities these domains their potential to accelerate scientific discovery through automation. We also LLM-based autonomous agents: LLMs with a broader set of interact surrounding environment. These agents perform diverse tasks such paper scraping, interfacing automated laboratories, planning. As are an emerging topic, we extend the scope our beyond chemistry discuss across any domains. covers recent history, current capabilities, design agents, addressing specific challenges, opportunities, future directions chemistry. Key challenges include data quality integration, model interpretability, need for standard benchmarks, while point towards more sophisticated multi-modal enhanced collaboration between experimental methods. Due quick pace this field, repository has been built keep track latest studies: https://github.com/ur-whitelab/LLMs-in-science.

Language: Английский

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Deep learning and generative artificial intelligence in aging research and healthy longevity medicine

Aging, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 16, 2025

With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep clock development, geroprotector identification generation of dual-purpose therapeutics targeting disease. The paper explores emergence multimodal, multitasking research systems highlighting promising future directions for GenAI human animal research, as well clinical application longevity medicine.

Language: Английский

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Embracing the changes and challenges with modern early drug discovery

Expert Opinion on Drug Discovery, Journal Year: 2025, Volume and Issue: unknown

Published: March 17, 2025

The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs discovered. As traditional faces growing challenges terms time, cost, efficacy, there a pressing need to integrate these emerging technologies enhance process. In this perspective, authors explore role AI ML modern discuss their application target identification, compound screening, biomarker discovery. This article based on thorough literature search using PubMed database identify relevant studies that highlight use AI/ML models computational chemistry, systems biology, data-driven approaches development. Emphasis placed how address key such as data integration, predictive performance, cost-efficiency pipeline. have potential revolutionize improving accuracy speed identifying viable candidates. However, successful integration requires overcoming related quality, model interpretability, for interdisciplinary collaboration.

Language: Английский

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Virtual laboratories: transforming research with AI

Data-Centric Engineering, Journal Year: 2024, Volume and Issue: 5

Published: Jan. 1, 2024

Abstract New scientific knowledge is needed more urgently than ever, to address global challenges such as climate change, sustainability, health, and societal well-being. Could artificial intelligence (AI) accelerate science meet these in time? AI already revolutionizing individual disciplines, but we argue here that it could be holistic encompassing. We introduce the concept of virtual laboratories a new perspective on generation means incentivize research development. Despite often perceived domain-specific practices inherent tacit knowledge, many elements process recur across domains even common software platforms for serving different may possible. outline how will make easier researchers contribute broad range domains, highlight mutual benefits offer both domain scientists.

Language: Английский

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Application of Artificial Intelligence In Drug-target Interactions Prediction: A Review

npj Biomedical Innovations., Journal Year: 2025, Volume and Issue: 2(1)

Published: Jan. 13, 2025

Abstract Predicting drug-target interactions (DTI) is a complex task. With the introduction of artificial intelligence (AI) methods such as machine learning and deep learning, AI-based DTI prediction can significantly enhance speed, reduce costs, screen potential drug design options before conducting actual experiments. However, application AI also faces several challenges that need to be addressed. This article reviews various approaches suggests possible future directions.

Language: Английский

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Foundations and Emerging Trends in Generative Artificial Intelligence (AI) for Industrial Applications

Published: Jan. 1, 2025

Language: Английский

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Artificial Intelligence, Machine Learning, and the Revival of Big Data in Pharmaceutical Sciences

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 275 - 310

Published: Feb. 5, 2025

The integration of Artificial Intelligence (AI), Machine Learning (ML), and Big Data is transitioning the pharmaceutical industry, specifically in drug discovery, process optimization, clinical development. This revolution enhances target identification through advanced data analytics, empowering discovery novel biomarkers compounds. AI-driven high-throughput virtual screening methods accelerate promising candidates, while predictive modeling improves accuracy efficacy predictions. In manufacturing, AI optimizes supply chain management quality control real-time monitoring maintenance, ensuring efficient production processes.

Language: Английский

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PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implicit Variables

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 214 - 225

Published: Jan. 1, 2025

Language: Английский

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Advancing drug discovery and development through GPT models: A review on challenges, innovations and future prospects

Intelligence-Based Medicine, Journal Year: 2025, Volume and Issue: 11, P. 100233 - 100233

Published: Jan. 1, 2025

Language: Английский

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