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This study reports that C3H/HeJ mice and DEBR rats serve as effective models for screening potential treatments for human alopecia areata, despite certain challenges in predictability and cost.

This research developed new in vitro models for high-throughput screening of drugs that could protect or restore immune privilege in hair follicles, finding that Tofacitinib was effective in preventing inflammation-related marker upregulation, while Tacrolimus and αMSH worked specifically in outer root sheath keratinocytes.

This study found that incorporating PCL-based nanoscaffolds into liver spheroids enhances their viability and liver-specific biofunctionality, suggesting these scaffolds improve the model's potential for preclinical drug screening by increasing sensitivity to acetaminophen toxicity compared to traditional methods.

Innovative methods are reducing animal testing and improving biomedical research.

In this study, the researchers developed a deep learning framework to pre-emptively screen for adverse drug effects, showing strong predictive performance, including for increased bleeding risks with edoxaban compared to other anticoagulants.