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This review outlines drug repurposing as an efficient, low-cost strategy to identify new uses for existing drugs, highlighting various computational and experimental approaches as well as publicly available databases to aid in personalized pharmacotherapy.

This article discusses how drug molecules integrate into hair fibers, focusing on biological transport mechanisms and physicochemical factors, but reports no new experimental findings.

This study presents a rapid method for detecting multiple xenobiotics in urine, effectively identifying 45 compounds banned in sports with detection limits below WADA's performance levels.

This study describes a computational method using side-effect data from social media to identify new drug indications, suggesting it could be effective for drug repositioning.

This study found that a new computational method using side-effect data from social media can successfully identify known and potential new drug indications for repositioning efforts.

In this study, researchers developed a computational method called iEdgePathDDA that prioritizes anticancer drug candidates by analyzing changes in gene interactions, demonstrating superior performance compared to existing methods across colorectal, breast, and lung cancer datasets.

This review introduces pharmacophore technology and discusses its applications in toxicity prediction and limits, but reports no new clinical results.

In this article, the authors describe how drug repurposing, supported by large-scale data and artificial intelligence, can make drug discovery more cost-effective and expedient compared to traditional methods, despite certain regulatory challenges.

This study suggests that a novel computational method using side-effect data from social media might aid in drug repositioning by identifying known and potential therapeutic indications.

This study found that analyzing hair samples in young children for drug exposure can indicate environmental drug exposure or in-utero exposure, but cannot definitively confirm deliberate drug administration.

Homemade hair treatments can significantly lower drug levels in hair, possibly causing false-negative drug tests.

This review discusses the use of hair analysis for detecting misuse of drugs in livestock, covering hair biology, drug incorporation, sampling methods, and analytical techniques, but reports no new findings.

This study presents a computational approach, CATNIP, which repurposes drugs using only their biological and chemical information, predicting new uses like adrenergic uptake inhibitors for Parkinson's and vandetanib for Type 2 Diabetes.

This article discusses hair follicle testing as an alternative method for drug abuse screening but reports no new research findings.

This review discusses the data resources and computational models used in drug repositioning, highlighting their role in discovering unknown drug mechanisms and reports no new empirical results.

This study used a zebrafish model and advanced mass spectrometry to identify 11 metabolites of epristeride, revealing significant effects on purine metabolism and aromatic amino acid biosynthesis, which may aid in developing anti-doping detection methods.

This study explores the complexities of interpreting single drug exposure in hair, emphasizing factors like drug distribution variability and suggests methods to validate single exposure findings in forensic cases.

This study reports that a new DART-HRMS method can effectively analyze intact hair for drug use timelines, with cocaine detection aligning with forensic standards and identifying multiple drugs from high-resolution data.

This study outlines the potential of drug repurposing to discover new uses for existing medications, emphasizing its cost-effectiveness, efficiency, and ability to address rare diseases by targeting novel biological mechanisms and relying on established safety profiles.

This review discusses the use of different biological samples, including hair, for drug testing and highlights the complexities and considerations involved in interpreting results; it reports no new findings.

The researchers reported that a new computational method using side-effect data from social media effectively recovers known drug indications and identifies trial indications, suggesting utility for computational drug repositioning.

This review reports on the use of nails as an alternative biological matrix to hair for assessing long-term drug consumption, emphasizing that while there are clear differences between nail and hair samples, more standardized research is necessary for definitive conclusions.

This study found that the cyanoacrylate biopsy method could effectively evaluate drug distribution in hair follicles, suggesting its potential utility for assessing topically applied chemicals targeting hair follicles.

This study developed the CATNIP computational model, which uses biological and chemical information to successfully identify drug repurposing opportunities for various conditions, including Parkinson’s disease and Type 2 Diabetes.

This review outlines computational strategies, including chemogenomics and drug repositioning, for coronavirus drug discovery and reports no new clinical findings; the authors highlight the advantages of these methods in rapidly identifying therapeutic candidates.

This study suggests a decision tree using in vitro metabolic clearance to identify early drug candidates likely to experience nonlinear pharmacokinetics due to intestinal CYP3A-related metabolism.

This study concluded that QSPR models effectively predict drug skin penetration, with the Potts-Guy model showing the highest predictive accuracy for the drugs tested.

This study developed a computational method using side-effect data from social media to identify potential new drug indications, showing that it successfully recovered known and trial indications.

This review highlights the need for methodologies to understand and quantify drug penetration into hair follicles as significant drug pathways, noting this area lacks comprehensive articles and reports no new results.