Integrating artificial intelligence with bioinformatics promotes public health
H Hong, W Slikker - Experimental Biology and Medicine, 2023 - journals.sagepub.com
1906 Experimental Biology and Medicine Volume 248 November 2023 research. Roberts3
writes a comprehensive review of the challenges and opportunities presented by data …
writes a comprehensive review of the challenges and opportunities presented by data …
Bidirectional Encoder Representations from Transformers-like large language models in patient safety and pharmacovigilance: A comprehensive assessment of …
Causality assessment is vital in patient safety and pharmacovigilance (PSPV) for safety
signal detection, adverse reaction management, and regulatory submission. Large …
signal detection, adverse reaction management, and regulatory submission. Large …
RxBERT: Enhancing drug labeling text mining and analysis with AI language modeling
The US drug labeling document contains essential information on drug efficacy and safety,
making it a crucial regulatory resource for Food and Drug Administration (FDA) drug …
making it a crucial regulatory resource for Food and Drug Administration (FDA) drug …
Data science in drug discovery safety: Challenges and opportunities
NJ Coltman, RA Roberts… - … Biology and Medicine, 2023 - journals.sagepub.com
Early de-risking of drug targets and chemistry is essential to provide drug projects with the
best chance of success. Target safety assessments (TSAs) use target biology, gene and …
best chance of success. Target safety assessments (TSAs) use target biology, gene and …
eTRANSAFE: data science to empower translational safety assessment
F Sanz, F Pognan, T Steger-Hartmann, C Díaz… - Nature Reviews Drug …, 2023 - nature.com
eTRANSAFE: data science to empower translational safety assessment Skip to main content
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Thank you for visiting nature.com. You are using a browser version with limited support for …
Translational bioinformatics: data‐driven drug discovery and development
Internet‐accessible computing power and data‐sharing mandates now enable researchers
to interrogate thousands of publicly available databases containing molecular, clinical, and …
to interrogate thousands of publicly available databases containing molecular, clinical, and …
A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database
The opioid epidemic has become a serious national crisis in the United States. An indepth
systematic analysis of opioid-related adverse events (AEs) can clarify the risks presented by …
systematic analysis of opioid-related adverse events (AEs) can clarify the risks presented by …
OnSIDES (ON-label SIDE effectS resource) Database: Extracting Adverse Drug Events from Drug Labels using Natural Language Processing Models
Adverse drug events (ADEs) are the fourth leading cause of death in the US and cost billions
of dollars annually in increased healthcare costs. However, few machine-readable …
of dollars annually in increased healthcare costs. However, few machine-readable …
Perspectives of data science in preclinical safety assessment
T Steger-Hartmann, A Kreuchwig, K Wang, F Birzele… - Drug Discovery …, 2023 - Elsevier
The data landscape in preclinical safety assessment is fundamentally changing because of
not only emerging new data types, such as human systems biology, or real-world data …
not only emerging new data types, such as human systems biology, or real-world data …
Challenges with risk mitigation in academic drug discovery: finding the best solution
A Roy - Expert opinion on drug discovery, 2019 - Taylor & Francis
A drug discovery program is initiated once a druggable target is unraveled through either
academic research or from clinical observations [1]. Academic research is all-encompassing …
academic research or from clinical observations [1]. Academic research is all-encompassing …