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This article updates a prior work on pharmacophore modeling and highlights the advances in 3D database searching technologies for drug design, without presenting new research findings.

This study found that the DNN-DTIs prediction model achieved high accuracy in predicting drug-target interactions, suggesting its potential application in drug repositioning and the discovery of new uses for existing drugs.

In this paper, Chemistry42—a software integrating AI with computational and medicinal chemistry—demonstrated efficiency in designing novel molecular structures targeting DDR1 and CDK20, with properties validated in both in vitro and in vivo studies.

The researchers found that using hair analysis to detect past use of cannabinoids or amphetamines in individuals with psychosis was limited by individual variations in hair growth rates, affecting the method's reliability.

This article presents a biochemical model to explain how drug molecules are incorporated into hair, highlighting factors such as drug melanin affinity and the role of physico-chemical properties.

This source discusses the growing trend of drug repurposing, a strategy that seeks new uses for existing drugs to overcome challenges like lengthy timelines and high costs in the traditional drug development process.

This review discusses the increasing role of machine learning in drug repurposing, demonstrating how algorithms can reveal new therapeutic uses for existing drugs and predict side effects, with potential benefits for precision medicine, while also addressing ethical and privacy concerns.

This study models the pathways of nandrolone and its metabolites in the body and suggests methods to counteract finasteride's role in enabling PED users to cheat drug tests.

This review highlights the potential of drug repurposing to offer faster and more cost-effective solutions compared to traditional drug development methods by leveraging existing medications for new uses; however, regulatory and intellectual property challenges remain significant barriers.

This review highlights the current progress and application pros and cons of various cell-based screening platforms in drug discovery, discussing challenges and potential improvements for these innovative methods.

This study concluded that drug-distribution measurements using micro-segmental hair analysis are effective for drowned bodies, as natural water containing divalent ions prevents drug washout from hair.

This symposium reviewed strategies to advance stalled drug molecules, discussed common regulatory hurdles, and explored options for repurposing drugs, but it reported no new research findings.

This study suggests that using a new computational method to mine social media for side-effect data may enhance drug repositioning by recovering known and trial drug indications effectively.

This review examines the current landscape of drug repositioning, highlighting that computational methods expand possibilities for reusing existing drugs to treat unmet medical needs. The authors discuss both the potential of these methods and the challenges faced in identifying new therapeutic applications.

The conclusion is that a new method can measure caffeine and drugs in hair, finding caffeine abusers have 70 times more caffeine than normal, with a proposed cut-off value for abuse.

This study constructed a panel of pharmacokinetic and pharmacodynamic genes, revealing that current SNP chips insufficiently capture many drug-response gene variants, highlighting the need for complementary genetic approaches.

This review outlines the evolution and strategies of drug repurposing, highlighting its transformation from accidental discoveries to a predictive, data-driven discipline through the integration of bioinformatics and artificial intelligence, with notable applications during the COVID-19 pandemic.

This article discusses drug repurposing as a strategy to find new uses for existing medications, highlighting its potential benefits like faster development and lower costs, while also addressing challenges such as drug specificity, ethical concerns, and regulatory issues.

This review highlights the inadequacy of the "specificity paradigm" in drug design for complex diseases like Alzheimer's and cancer, suggesting a shift toward developing multitarget drugs to improve treatment efficacy by interacting with multiple targets through various mechanisms.

This review article discusses current trends and future perspectives in drug repurposing, highlighting its potential to discover novel treatments for unmet medical needs by identifying new uses for existing drugs, which benefits from faster development timelines and established safety profiles.

This study expands the Drug Ontology to include therapeutic indications for resistant hypertension, malaria, and opioid abuse research, providing a framework for additional drug use representations beyond their original design.

This review outlines the evolution of drug repurposing from accidental discoveries to a systematic approach enhanced by genomics and data analytics, emphasizing its accelerated relevance during the COVID-19 pandemic and exploring its global and Indian milestones, computational strategies, and future regulatory perspectives.

This discussion reviews the shift in pharmaceutical strategy towards evidence-based and structure-guided drug development, highlighting ongoing challenges and efforts in computer-aided drug design without presenting new clinical results.

This review suggests that the compound DRDE-07, originally a sulphur-mustard countermeasure candidate, could potentially be repurposed for skin protection due to its compatibility with pathways involved in oxidative stress and inflammation, though further experimental study is needed to confirm its therapeutic applicability in dermatology.

This paper discusses advancements in forensic hair analysis, emphasizing a novel DART–HRMS method that improves the accuracy and efficiency of detecting drug use timelines.

This study reports on a new semantic annotation approach used to identify substances in MEDLINE abstracts responsible for adverse drug reactions, with promising performance shown by a prototype system.

This study developed a new clustering model to improve detection of drug-induced cognitive disorder risk signals, finding that it identified drugs with moderate risk signals, like Carbidopa/Levodopa, missed by traditional methods, enhancing clinical assessment comprehensiveness.

In this study, the researchers reviewed psychiatric drugs approved between 2002 and 2022 to analyze trends in drug repurposing, finding an increased application of repurposing methods, especially through fixed-dose combinations, and highlighting technologies like SmartCube® to predict efficacy from animal models.