Artificial intelligence in drug discovery and development

KK Mak, YH Wong, MR Pichika - Drug discovery and evaluation: safety …, 2024 - Springer
This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

A review of chatgpt applications in education, marketing, software engineering, and healthcare: Benefits, drawbacks, and research directions

M Fraiwan, N Khasawneh - arXiv preprint arXiv:2305.00237, 2023 - arxiv.org
ChatGPT is a type of artificial intelligence language model that uses deep learning
algorithms to generate human-like responses to text-based prompts. The introduction of the …

Artificial intelligence-based text generators in hepatology: ChatGPT is just the beginning

J Ge, JC Lai - Hepatology communications, 2023 - journals.lww.com
Since its release as a “research preview” in November 2022, ChatGPT, the conversational
interface to the Generative Pretrained Transformer 3 large language model built by OpenAI …

Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery

AI Visan, I Negut - Life, 2024 - mdpi.com
Drug development is expensive, time-consuming, and has a high failure rate. In recent
years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery …

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning

G Serna García, R Al Khalaf, F Invernici, S Ceri… - …, 2023 - academic.oup.com
Abstract Background Literature about SARS-CoV-2 widely discusses the effects of variations
that have spread in the past 3 years. Such information is dispersed in the texts of several …

SUSIE: Pharmaceutical CMC ontology-based information extraction for drug development using machine learning

V Mann, S Viswanath, S Vaidyaraman… - Computers & Chemical …, 2023 - Elsevier
Automatically extracting information from unstructured text in pharmaceutical documents is
important for drug discovery and development. This information can be integrated with …

[HTML][HTML] Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation

JD Murray, JJ Lange, H Bennett-Lenane… - European Journal of …, 2023 - Elsevier
Artificial intelligence is a rapidly expanding area of research, with the disruptive potential to
transform traditional approaches in the pharmaceutical industry, from drug discovery and …

Machine learning and natural language processing in clinical trial eligibility criteria parsing: a scoping review

K Kantor, M Morzy - Drug Discovery Today, 2024 - Elsevier
Highlights•Generative LLMs are slowly adopted in clinical trial eligibility
parsing.•Standardized benchmarks for parsing eligibility criteria are urgently needed.•The …

[HTML][HTML] AI and the Evolution of Personalized Medicine in Pharmacogenomics

H Taherdoost, A Ghofrani - Intelligent Pharmacy, 2024 - Elsevier
This paper examines the transformative impact of artificial intelligence (AI) on
pharmacogenomics, signaling a paradigm shift in personalized medicine. With a focus on …

Adera2. 0: a drug repurposing workflow for neuroimmunological investigations using neural networks

M Lazarczyk, K Duda, ME Mickael, O Ak, J Paszkiewicz… - Molecules, 2022 - mdpi.com
Drug repurposing in the context of neuroimmunological (NI) investigations is still in its
primary stages. Drug repurposing is an important method that bypasses lengthy drug …