INTRODUCTION: Social media platforms serve as a valuable resource for users to share health-related information, aiding in the monitoring of adverse events linked to medications and treatments in drug safety surveillance. However, extracting drug-rel...
PURPOSE: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet their use is associated with immune-related adverse events (irAEs). Estimating the prevalence and patient impact of these irAEs in the real-world data setting is c...
INTRODUCTION: Current drug-drug interaction (DDI) detection methods often miss the aspect of temporal plausibility, leading to false-positive disproportionality signals in spontaneous reporting system (SRS) databases.
Detecting the unintended adverse reactions of drugs (ADRs) is a crucial concern in pharmacological research. The experimental validation of drug-ADR associations often entails expensive and time-consuming investigations. Thus, a computational model t...
Research in social & administrative pharmacy : RSAP
38637208
OBJECTIVE: Medication management of patients with polypharmacy is highly complex. We aimed to validate a novel Artificial Pharmacology Intelligence (API) algorithm to optimize the medication review process in a comprehensive, personalized, and scalab...
International journal of clinical pharmacy
38594470
The advent of artificial intelligence (AI) technologies has taken the world of science by storm in 2023. The opportunities of this easy to access technology for clinical pharmacy research are yet to be fully understood. The development of a custom-ma...
INTRODUCTION: The identification of a new adverse event (AE) caused by a drug product is one of the key activities in the pharmaceutical industry to ensure the safety profile of a drug product. Machine learning (ML) has the potential to assist with s...
Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate predic...
INTRODUCTION: Artificial intelligence or machine learning (AI/ML) based systems can help personalize prescribing decisions for individual patients. The recommendations of these clinical decision support systems must relate to the "label" of the medic...
Evaluating pharmacokinetic properties of small molecules is considered a key feature in most drug development and high-throughput screening processes. Generally, pharmacokinetics, which represent the fate of drugs in the human body, are described fro...