Quantification of five antineoplastic agents in swab samples using UPLC-ESI-MS/MS: Method development and validation.

Background: Antineoplastic agents are hazardous drugs used in cancer treatment and consequently can be present at the workplace (e.g. hospital), but also in a home-setting in case of treatment at home.

An Assessment of Surface Contamination and Dermal Exposure to 5-Fluorouracil in Healthcare Settings by UPLC-MS/MS Using a New Atmospheric Pressure Ionization Source.

5-Fluorouracil (5-FU) is a well-known cytostatic drug, which is often used in cancer treatments. Yet, it is also a very dangerous compound for people who are occupationally exposed to it for a long time, such as pharmacy employees, nurses and cleaning staff. We aimed to improve and implement a LC-MS/MS method for 5-FU quantification on surface contamination samples collected with swabs in a pharmacy department and outpatient nursing station of a university hospital.

Cognitive Fatigue, Humor, and Physical Activity: A Field Experiment Testing Whether Humorous Messages Promote Walking in Cognitively Fatigued Individuals.

Despite the success of humorous messages in various health interventions, its role in promoting physical activity (PA) remains understudied. This study addresses this gap by investigating the effectiveness of humorous messages in a 2-week smartphone-based intervention aimed at promoting walking behavior, particularly amongst cognitively fatigued individuals. Female participants ( = 57; = 32.

An integrated quantitative systems pharmacology virtual population approach for calibration with oncology efficacy endpoints.

In drug development, quantitative systems pharmacology (QSP) models are becoming an increasingly important mathematical tool for understanding response variability and for generating predictions to inform development decisions. Virtual populations are essential for sampling uncertainty and potential variability in QSP model predictions, but many clinical efficacy endpoints can be difficult to capture with QSP models that typically rely on mechanistic biomarkers. In oncology, challenges are particularly significant when connecting tumor size with time-to-event endpoints like progression-free survival while also accounting for censoring due to consent withdrawal, loss in follow-up, or safety criteria.