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Recently, the CIE has adopted a range of 15 standard sky distributions covering the whole spectrum of usual skies found in nature. In a dense urban region, the external environment plays a significant role in daylighting designs. This paper studies an approach to calculating the average daylight factor for rooms facing heavily obstructed environments under overcast and non-overcast skies. The modelled vertical sky components under the various unobstructed and obstructed CIE Standard General Skies were determined. The performance of the proposed method was evaluated against the results obtained by computer simulations. The proposed approach provides a simple alternative for comparing daylighting designs for buildings facing different obstructed environments under various sky conditions. [ABSTRACT FROM PUBLISHER]

A recent consensus guideline recommends migrating the therapeutic drug monitoring practice for intravenous vancomycin for the treatment of methicillin-resistant Staphylococcus aureus infection from the traditional trough-based approach to the Bayesian approach based on area under curve to improve clinical outcomes. To support the implementation of the new strategy for hospitals under Hospital Authority, Hong Kong, this study is being proposed to (1) estimate and validate a population pharmacokinetic model of intravenous vancomycin for local adults, (2) develop a web-based individual dose optimization application for clinical use, and (3) evaluate the performance of the application by comparing the treatment outcomes and clinical satisfaction against the traditional approach. 300 adult subjects prescribed with intravenous vancomycin and not on renal replacement therapy will be recruited for population pharmacokinetic model development and validation. Sex, age, body weight, serum creatinine level, intravenous vancomycin dosing records, serum vancomycin concentrations etc. will be collected from several electronic health record systems maintained by Hospital Authority. Parameter estimation will be performed using non-linear mixed-effect modeling techniques. The web-based individual dose optimization application is based on a previously reported application and is built using R and the package shiny. Data from another 50 subjects will be collected during the last three months of the study period and treated as informed by the developed application and compared against historical control for clinical outcomes. Since the study will incur extra blood-taking procedures from patients, informed consent is required. Other than that, recruited subjects should receive medical treatments as usual. Identifiable patient data will be available only to site investigators and clinicians in each hospital. The study protocol and informed consent forms have been approved by the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (reference number: NTEC-2021-0215) and registered at the Chinese Clinical Trial Registry (registration number: ChiCTR2100048714)., Competing Interests: The authors have declared that no competing interests exist.

Background: Intravenous (IV) vancomycin is used in the treatment of severe infection in neonates. However, its efficacy is compromised by elevated risks of acute kidney injury. The risk is even higher among neonates admitted to the neonatal intensive care unit (NICU), in whom the pharmacokinetics of vancomycin vary widely. Therapeutic drug monitoring is an integral part of vancomycin treatment to balance efficacy against toxicity. It involves individual dose adjustments based on the observed serum vancomycin concentration (VC s ). However, the existing trough-based approach shows poor evidence for clinical benefits. The updated clinical practice guideline recommends population pharmacokinetic (popPK) model-based approaches, targeting area under curve, preferably through the Bayesian approach. Since Bayesian methods cannot be performed manually and require specialized computer programs, there is a need to provide clinicians with a user-friendly interface to facilitate accurate personalized dosing recommendations for vancomycin in critically ill neonates., Objective: We used medical data from electronic health records (EHRs) to develop a popPK model and subsequently build a web-based interface to perform model-based individual dose optimization of IV vancomycin for NICU patients in local medical institutions., Methods: Medical data of subjects prescribed IV vancomycin in the NICUs of Prince of Wales Hospital and Queen Elizabeth Hospital in Hong Kong were extracted from EHRs, namely the Clinical Information System, In-Patient Medication Order Entry, and electronic Patient Record. Patient demographics, such as body weight and postmenstrual age (PMA), serum creatinine (SCr), vancomycin administration records, and VC s were collected. The popPK model employed a 2-compartment infusion model. Various covariate models were tested against body weight, PMA, and SCr, and were evaluated for the best goodness of fit. A previously published web-based dosing interface was adapted to develop the interface in this study., Results: The final data set included EHR data extracted from 207 subjects, with a total of 689 VC s measurements. The final model chosen explained 82% of the variability in vancomycin clearance. All parameter estimates were within the bootstrapping CIs. Predictive plots, residual plots, and visual predictive checks demonstrated good model predictability. Model approximations showed that the model-based Bayesian approach consistently promoted a probability of target attainment (PTA) above 75% for all subjects, while only half of the subjects could achieve a PTA over 50% with the trough-based approach. The dosing interface was developed with the capability to optimize individual doses with the model-based empirical or Bayesian approach., Conclusions: Using EHRs, a satisfactory popPK model was verified and adopted to develop a web-based individual dose optimization interface. The interface is expected to improve treatment outcomes of IV vancomycin for severe infections among critically ill neonates. This study provides the foundation for a cohort study to demonstrate the utility of the new approach compared with previous dosing methods., (©Ka Ho Matthew Hui, Hugh Simon Lam, Cheuk Hin Twinny Chow, Yuen Shun Janice Li, Pok Him Tom Leung, Long Yin Brian Chan, Chui Ping Lee, Celeste Lom Ying Ewig, Yin Ting Cheung, Tai Ning Teddy Lam. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 31.01.2022.)

Drug solubility and permeability are two major challenges affecting oral delivery, the most popular route of drug administration. Polymeric micelles is an emerging technology for overcoming the current oral drug delivery hurdles. Previous study primarily focused on developing new polymers or new micellar systems and a systematic investigation of the impact of the polymer block length on solubility and permeability enhancement; and their subsequent effect on oral bioavailability is lacking. Herein, by using paclitaxel, a poorly soluble P-glycoproteins (P-gp) substrate, as a model, we aim to assess and compare the drug-loaded micelles prepared with two different molecular weight of poly(ethylene glycol)-block-poly(ε-caprolactone) (PEG-b-PCL), with the ultimate goal of establishing a strong scientific rationale for proper design of formulations for oral drug delivery. PEG-b-PCL (750:570) (PEG 17 -b-PCL 5 ) and PEG-b-PCL (5k:10k) (PEG 114 -b-PCL 88 ) effectively enhanced the solubility of paclitaxel compared to the free drug. PEG-b-PCL (750:570) increased both P-gp and non P-gp substrate cellular uptake and increased the apparent permeability coefficient of a P-gp substrate. In vivo animal study showed that PEG-b-PCL micelles efficiently enhanced the oral bioavailability of paclitaxel. In addition to solubility enhancement, polymer choice also plays a pivotal role in determining the oral bioavailability improvement, probably via permeation enhancement. In conclusion, the knowledge gained in this study enables rational design of polymeric micelles to overcome the current challenges of oral drug delivery and it also provides a basis for future clinical translation of the technology., (Copyright © 2019 Elsevier B.V. All rights reserved.)