AIMC Topic: Dose-Response Relationship, Drug
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EC and EC of Remifentanil for Inhibiting Bronchoscopy Responses in Elderly Patients During Fiberoptic Bronchoscopy Under Ciprofol Sedation: An Up-and-Down Sequential Allocation Trial.
Drug design, development and therapy
Dec 31, 2024
BACKGROUND: Opioids are used to suppress cough during fiberoptic bronchoscopy (FOB). However, evidence regarding the optimal dose of remifentanil during FOB under ciprofol sedation is limited. This study aimed to investigate the effective concentrati...
Improving the prediction of chemotherapy dose-limiting toxicity in colon cancer patients using an AI-CT-based 3D body composition of the entire L1-L5 lumbar spine.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Dec 21, 2024
PURPOSE: Chemotherapy dose-limiting toxicities (DLT) pose a significant challenge in successful colon cancer treatment. Body composition analysis may enable tailored interventions thereby supporting the mitigation of chemotherapy toxic effects. This ...
The Effect of Intravenous Lidocaine on EC50 of Remifentanil for Preventing Cough During Emergence in Female for Thyroid Surgery Anesthesia.
Drug design, development and therapy
Dec 20, 2024
OBJECTIVE: To evaluate the effect of intravenous lidocaine injection on the half-maximum effective concentration (EC50) of remifentanil in preventing cough due to tracheal extubation in female patients undergoing thyroid surgery by Dixon's sequential...
Cubosomes as Delivery System to Repositioning Nitrofurantoin in Breast Cancer Management.
Drug design, development and therapy
Dec 19, 2024
PURPOSE: Nitrofurantoin (NITRO), a long-standing antibiotic to treat urinary tract infections, is activated by Nitro reductases. This activation mechanism has led to its exploration for repositioning applications in controlling and treating breast ca...
Toward Dose Prediction at Point of Design.
Journal of medicinal chemistry
Dec 12, 2024
Human dose prediction (HDP) is a useful tool for compound optimization in preclinical drug discovery. We describe here our exclusively in silico HDP strategy to triage compound designs for synthesis and experimental profiling. Our goal is a model tha...
Assessing the effects of 5-HT and 5-HT receptor antagonists on DOI-induced head-twitch response in male rats using marker-less deep learning algorithms.
Pharmacological reports : PR
Nov 27, 2024
BACKGROUND: Serotonergic psychedelics, which display a high affinity and specificity for 5-HT receptors like 2,5-dimethoxy-4-iodoamphetamine (DOI), reliably induce a head-twitch response in rodents characterized by paroxysmal, high-frequency head rot...
Wee1 inhibitor optimization through deep-learning-driven decision making.
European journal of medicinal chemistry
Sep 29, 2024
Deep learning has gained increasing attention in recent years, yielding promising results in hit screening and molecular optimization. Herein, we employed an efficient strategy based on multiple deep learning techniques to optimize Wee1 inhibitors, w...
Dose Individualisation of Antimicrobials from a Pharmacometric Standpoint: The Current Landscape.
Drugs
Sep 6, 2024
Successful antimicrobial therapy depends on achieving optimal drug concentrations within individual patients. Inter-patient variability in pharmacokinetics (PK) and differences in pathogen susceptibility (reflected in the minimum inhibitory concentra...
Leveraging multiple data types for improved compound-kinase bioactivity prediction.
Nature communications
Aug 31, 2024
Machine learning provides efficient ways to map compound-kinase interactions. However, diverse bioactivity data types, including single-dose and multi-dose-response assay results, present challenges. Traditional models utilize only multi-dose data, o...
Discovery of AMPs from random peptides via deep learning-based model and biological activity validation.
European journal of medicinal chemistry
Aug 26, 2024
The ample peptide field is the best source for discovering clinically available novel antimicrobial peptides (AMPs) to address emerging drug resistance. However, discovering novel AMPs is complex and expensive, representing a major challenge. Recent ...
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