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According to the World Health Organization (WHO) data from 2000 to 2019, the number of people living with Diabetes Mellitus and Chronic Kidney Disease (CKD) is increasing rapidly. It is observed that Diabetes Mellitus increased by 70% and ranked in the top 10 among all causes of death, while the rate of those who died from CKD increased by 63% and rose from the 13th place to the 10th place. In this work, we combined the drug dose prediction model, drug-drug interaction warnings and drugs that potassium raising (K-raising) warnings to create a novel and effective ontology-based assistive prescription recommendation system for patients having both Type-2 Diabetes Mellitus (T2DM) and CKD. Although there are several computational solutions that use ontology-based systems for treatment plans for these type of diseases, none of them combine information analysis and treatment plans prediction for T2DM and CKD. The proposed method is novel: (1) We develop a new drug-drug interaction model and drug dose ontology called DIAKID (for drugs of T2DM and CKD). (2) Using comprehensive Semantic Web Rule Language (SWRL) rules, we automatically extract the correct drug dose, K-raising drugs, and drug-drug interaction warnings based on the Glomerular Filtration Rate (GFR) value of T2DM and CKD patients. The proposed work achieves very competitive results, and this is the first time such a study conducted on both diseases. The proposed system will guide clinicians in preparing prescriptions by giving necessary warnings about drug-drug interactions and doses., Competing Interests: Competing interestsThe authors have no relevant financial or non-financial interests to disclose., (© The Author(s) 2024.)

Background : Neonates may require higher doses of micafungin than adults to reach the therapeutic effect for increased plasma clearance. Only poor and inconclusive data are available still now to support this hypothesis, especially with regard to central nervous system micafungin concentrations. To assess the pharmacokinetics of increased doses (8 to 15 mg/kg/day) of micafungin in preterm and term neonates with invasive candidiasis and to complete previously presented results, we analyzed the pharmacokinetic data on a total of 53 newborns treated with micafungin, whereby 3 of them had Candida meningitis and hydrocephalus. Methods : Fifty-three neonates with systemic candidiasis, three of them with meningitis, were treated for at least 14 days with intravenous micafungin (Mycamine ® ) at a dosage ranging from 8 to 15 mg/kg/day. Plasma and cerebrospinal fluid (CSF) concentrations of micafungin were measured before the drug administration and at 1, 2, and 8 h after the end of the infusion using high-performance liquid chromatography (HPLC). Systemic exposure was assessed according to AUC 0-24 , plasma clearance (CL), and half-life measured in 52/53 patients, divided by chronological age. Results and conclusions : The mean micafungin clearance is higher in neonates than in older infants (0.036 L/h/kg before 28 days of life versus 0.028 L/h/kg after 120 days). The drug half-life is shorter in neonates than in older patients (13.5 h before 28 days of life versus 14.4 h after 120 days). With doses ranging between 8 and 15 mg/kg/day, micafungin crosses the blood-brain barrier reaching therapeutic levels in CSF.