AIMC Topic: Administration, Oral

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Retrospective study of onychomycosis patients treated with ciclopirox 8% HPCH and oral antifungals applying artificial intelligence to electronic health records.

Scientific reports Jul 31, 2025
We conducted a multicenter retrospective analysis of 408 patients diagnosed with onychomycosis who attended three tertiary care Spanish hospitals. The study was conducted to assess the clinical characteristics and outcomes of onychomycosis patients u...
Terbinafine Ciclopirox Adult Male Middle Aged Treatment Outcome Antifungal Agents Administration, Oral Fluconazole Onychomycosis Retrospective Studies Electronic Health Records Female Aged Humans Artificial Intelligence
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Prediction of Internal Exposures after Virtual Oral Doses of Disparate Chemicals in Rats and Humans Using Simplified Physiologically Based Pharmacokinetic Models with Generated Input Parameters.

Chemical research in toxicology Jul 8, 2025
Toxicological evaluation of industrial chemicals with a broad range of chemical structures, for example, bioactive food components, toxic food-derived compounds, and drugs, usually involves the estimation of human clearance by allometric extrapolatio...
Humans Computer Simulation Animals Rats Models, Biological Administration, Oral
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Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.

Nature communications May 23, 2025
Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appears limited. In this study, we use several artificial intelligence techniques and patient-based mult...
Nucleotides, Cyclic Drug Design Cell Line, Tumor Mice Membrane Proteins Mice, Inbred C57BL Administration, Oral Phosphoric Diester Hydrolases Pyrophosphatases Artificial Intelligence Female Animals Neoplasms Humans
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Can ChatGPT provide parent education for oral immunotherapy?

Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology Apr 24, 2025
BACKGROUND: Oral Immunotherapy (OIT) has exhibited great potential in the treatment of food allergy. However, there is no global consensus on best practices of OIT. Parents of allergic children often struggle with concerns regarding OIT methodology, ...
Male Surveys and Questionnaires Child Generative Artificial Intelligence Humans Artificial Intelligence Female Desensitization, Immunologic Parents Patient Education as Topic Food Hypersensitivity Administration, Oral
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An oral robotic pill reliably and safely delivers teriparatide with high bioavailability in healthy volunteers: A phase 1 study.

British journal of clinical pharmacology Apr 7, 2025
AIMS: The incidence of osteoporosis is projected to exceed 70 million people over the age of 65 years by 2030. Osteoanabolic agents, such as teriparatide and abaloparatide, are not only effective in reducing fracture incidence but also improve skelet...
Aged Young Adult Adult Drug Delivery Systems Humans Administration, Oral Middle Aged Female Biological Availability Healthy Volunteers Injections, Subcutaneous Bone Density Conservation Agents Robotics Teriparatide Tablets
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Safety assessment of the ethanolic extract of Siparuna guianensis: Cell viability, molecular risk predictions and toxicity risk for acute and sub-chronic oral ingestion.

Journal of ethnopharmacology Apr 5, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: The species Siparuna guianensis Aublet (family Siparunaceae) is traditionally used by indigenous peoples and riverine communities in Central and South America to treat migraines, flu, respiratory diseases, fever, pain,...
Toxicity Tests, Subchronic Ethanol Dose-Response Relationship, Drug Administration, Oral Cell Survival Mice Female Solvents Plant Leaves Plant Extracts Animals Lethal Dose 50 Rats, Wistar Male Toxicity Tests, Acute Rats Risk Assessment
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Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

The American journal of cardiology Feb 25, 2025
Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alternatives like left atrial appendage closure devices lower stroke risk with fewer nonprocedural blee...
Administration, Oral Atrial Fibrillation Hemorrhage Female Risk Factors Hospitalization Aged Risk Assessment Anticoagulants Stroke Humans Male Machine Learning Middle Aged Retrospective Studies
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Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs.

Scientific reports Jan 4, 2025
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally ac...
Humans Machine Learning Algorithms Quantitative Structure-Activity Relationship Kidney Kidney Diseases Pharmaceutical Preparations Administration, Oral
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Residual risk prediction in anticoagulated patients with atrial fibrillation using machine learning: A report from the GLORIA-AF registry phase II/III.

European journal of clinical investigation Dec 11, 2024
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
Humans Thrombosis Administration, Oral Atrial Fibrillation Aged Ischemic Attack, Transient Aged, 80 and over Thromboembolism Male Middle Aged Risk Assessment Anticoagulants Machine Learning ROC Curve Registries Algorithms Logistic Models Stroke Female Ischemic Stroke Myocardial Infarction Risk Factors Area Under Curve
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Development and validation of a machine learning model for predicting drug-drug interactions with oral diabetes medications.

Methods (San Diego, Calif.) Nov 1, 2024
Diabetes management is often complicated by comorbidities, requiring complex medication regimens that increase the risk of drug-drug interactions (DDIs), potentially compromising treatment outcomes or causing toxicity. Although machine learning (ML) ...
Diabetes Mellitus Drug Interactions Administration, Oral Humans Machine Learning Hypoglycemic Agents
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