3R-Refinement principles: elevating rodent well-being and research quality.

This review article delves into the details of the 3R-Refinement principles as a vital framework for ethically sound rodent research laboratory. It highlights the core objective of the refinement protocol, namely, to enhance the well-being of laboratory animals while simultaneously improving the scientific validity of research outcomes. Through an exploration of key components of the refinement principles, the article outlines how these ethics should be implemented at various stages of animal experiments.

hERG-toxicity prediction using traditional machine learning and advanced deep learning techniques.

The rise of artificial intelligence (AI) based algorithms has gained a lot of interest in the pharmaceutical development field. Our study demonstrates utilization of traditional machine learning techniques such as random forest (RF), support-vector machine (SVM), extreme gradient boosting (XGBoost), deep neural network (DNN) as well as advanced deep learning techniques like gated recurrent unit-based DNN (GRU-DNN) and graph neural network (GNN), towards predicting human ether-á-go-go related gene (hERG) derived toxicity. Using the largest hERG dataset derived to date, we have utilized 203,853 and 87,366 compounds for training and testing the models, respectively.

Safety and Efficacy of ApTOLL in Patients With Ischemic Stroke Undergoing Endovascular Treatment: A Phase 1/2 Randomized Clinical Trial.

Importance: ApTOLL is a TLR4 antagonist with proven preclinical neuroprotective effect and a safe profile in healthy volunteers.

Objective: To assess the safety and efficacy of ApTOLL in combination with endovascular treatment (EVT) for patients with ischemic stroke.

Design, Setting, And Participants: This phase 1b/2a, double-blind, randomized, placebo-controlled study was conducted at 15 sites in Spain and France from 2020 to 2022.

Prediction of Eye Irritation Using Hansen Solubility Parameters and Predicted pKa Values.

An method has been developed that permits the binary differentiation between pure liquids causing serious eye damage or eye irritation, and pure liquids with no need for such classification, according to the UN GHS system. The method is based on the finding that the Hansen Solubility Parameters (HSP) of a liquid are collectively important predictors for eye irritation. Thus, by applying a two-tier approach in which -predicted pKa values (firstly) and a trained model based solely on -predicted HSP data (secondly) were used, we have developed, and validated, a fully approach for predicting the outcome of a Draize test (in terms of UN GHS Cat.

APRIL: A double-blind, placebo-controlled, randomized, Phase Ib/IIa clinical study of ApTOLL for the treatment of acute ischemic stroke.

Unlabelled: In the reperfusion era, a new paradigm of treating patients with endovascular treatment (EVT) and neuroprotective drugs is emerging as a promising therapeutic option for patients with acute ischemic stroke (AIS). In this context, ApTOLL, a Toll-like receptor 4 (TLR4) antagonist with proven neuroprotective effect in preclinical models of stroke and a very good pharmacokinetic and safety profile in healthy volunteers, is a promising first-in-class aptamer with the potential to address this huge unmet need. This protocol establishes the clinical trial procedures to conduct a Phase Ib/IIa clinical study (APRIL) to assess ApTOLL tolerability, safety, pharmacokinetics, and biological effect in patients with AIS who are eligible for EVT.