AIMC Topic: Pharmacology, Clinical

Clear Filters Showing 21 to 24 of 24 articles

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

Clinical and translational science
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized...

AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference.

Clinical and translational science
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...

Agents for Change: Artificial Intelligent Workflows for Quantitative Clinical Pharmacology and Translational Sciences.

Clinical and translational science
Artificial intelligence (AI) is making a significant impact across various industries, including healthcare, where it is driving innovation and increasing efficiency. In the fields of Quantitative Clinical Pharmacology (QCP) and Translational Science...