Propanteline bromide-treated (PBT) dog model would be useful to evaluate at least prototype enteric-coated granules in order to develop the human conscious clinical formulations, although normal dog model could not evaluate modified release formulations such as enteric-coated granules.

The optimized betulinic acid-loaded nanostructured lipid carrier hydrogel offered nanometric size, controlled drug release, and greater permeation. The developed formulation can provide a better delivery option in substantial amounts to various skin layers.

Drug–drug interactions (DDIs) pose significant risks to patient safety in clinical practice and drug development, making accurate prediction essential for effective medication management. This work introduces the MobileNetV2 with simplicial attention network based parallel convolutional neural network with narwhal optimizer (MV2SAPCN-NO) for DDI prediction. After preprocessing DDI datasets to eliminate noise, the model extracts local and global features using MobileNetV2 and simplicial attention. The parallel convolutional neural network is optimised with the narwhal optimiser to enhance accuracy and reduce computational complexity, outperforming existing methods based on accuracy, precision, recall and F-score metrics.

In our study we report that OATP2B1 does not mediate pregnenolone sulfate transport across the blood–brain barrier in rats and in a human cell model, thus suggesting alternative mechanisms involved in pregnenolone sulfate brain uptake.