Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition.

Most drugs are mainly metabolized by cytochrome P450 (CYP450), which can lead to drug-drug interactions (DDI). Specifically, time-dependent inhibition (TDI) of CYP3A4 isoenzyme has been associated with clinically relevant DDI. To overcome potential DDI issues, high-throughput assays were established to assess the TDI of CYP3A4 during the discovery and lead optimization phases.

Flying high?-Exploring the effect of red bull on blood pressure after microsurgical breast reconstruction in a randomized controlled trial.

Background: A sufficiently high blood pressure (BP) is essential for flap perfusion after microsurgical breast reconstruction. However, postoperative hypotension is common after these procedures. Perioperative volume overload may increase flap-related complications, and postoperative vasopressor use may be limited depending on institutions.

Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects.

Medicinal chemistry and drug design efforts can be assisted by machine learning (ML) models that relate the molecular structure to compound properties. Such quantitative structure-property relationship models are generally trained on large data sets that include diverse chemical series (global models). In the pharmaceutical industry, these ML global models are available across discovery projects as an "out-of-the-box" solution to assist in drug design, synthesis prioritization, and experiment selection.

Comparing complications and perioperative teams in microsurgical breast reconstruction: retrospective cohort study.

Background: Subspecialization with dedicated perioperative teams has become common practice in some surgical disciplines. While surgeon experience, the number of surgeons involved, and enhanced recovery after surgery (ERAS) pathways are known factors affecting the outcome after microsurgical breast reconstruction, the impact of the perioperative team has not been studied.

Methods: We conducted a retrospective cohort study consisting of a chart review of all patients who underwent microsurgical breast reconstruction from January 2019-April 2020.