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The potential of using ChatGPT in pharmacometrics was explored in this study, with a focus on developing a population pharmacokinetic (PK) model for standard half‐life factor VIII. Our results demonstrated that ChatGPT can be utilized to accurately obtain typical PK parameters from literature, generate a population PK model in R and develop an interactive Shiny application to visualize the results. ChatGPT's language generation capabilities enabled the development of R codes with minimal programming knowledge and helped to identify as well fix errors in the code. While ChatGPT presents several advantages, such as its ability to streamline the development process, its use in pharmacometrics also has limitations and challenges, including the accuracy and reliability of AI‐generated data, the lack of transparency and reproducibility regarding codes generated by ChatGPT. Overall, our study demonstrates the potential of using ChatGPT in pharmacometrics, but researchers must carefully evaluate its use for their specific needs. [ABSTRACT FROM AUTHOR]

There is a strong rationale for personalizing antibiotic dosing, based on the association between antibiotic exposure and bacterial killing, and observed between-patient variability of antibiotic concentrations in plasma and at the site of infection [[3]]. Sepsis remains a pressing challenge in intensive care medicine due to its high morbidity and mortality [[1]]. In the DOLPHIN study, MIPD relying on plasma concentration feedback (available 12-48 h after antibiotic initiation) was applied remotely by pharmacists for beta-lactam antibiotics and ciprofloxacin based on previously published PK models [[8]]. 4181663 4 Roberts JA, Paul SK, Akova M. DALI Study: DALI: defining antibiotic levels in intensive care unit patients: are current -lactam antibiotic doses sufficient for critically ill patients?. [Extracted from the article]

Pharmacometrics is a multidisciplinary field utilizing mathematical models of physiology, pharmacology, and disease to describe and quantify the interactions between medication and patient. As these models become more and more advanced, the need for advanced data analysis tools grows. Recently, there has been much interest in the adoption of machine learning (ML) algorithms. These algorithms offer strong function approximation capabilities and might reduce the time spent on model development. However, ML tools are not yet an integral part of the pharmacometrics workflow. The goal of this work is to discuss how ML algorithms have been applied in four stages of the pharmacometrics pipeline: data preparation, hypothesis generation, predictive modelling, and model validation. We will also discuss considerations before the use of ML algorithms with respect to each topic. We conclude by summarizing applications that hold potential for adoption by pharmacometricians. [ABSTRACT FROM AUTHOR]

In population pharmacokinetic (PK) models, interindividual variability is explained by implementation of covariates in the model. The widely used forward stepwise selection method is sensitive to bias, which may lead to an incorrect inclusion of covariates. Alternatives, such as the full fixed effects model, reduce this bias but are dependent on the chosen implementation of each covariate. As the correct functional forms are unknown, this may still lead to an inaccurate selection of covariates. Machine learning (ML) techniques can potentially be used to learn the optimal functional forms for implementing covariates directly from data. A recent study suggested that using ML resulted in an improved selection of influential covariates. However, how do we select the appropriate functional form for including these covariates? In this work, we use SHapley Additive exPlanations (SHAP) to infer the relationship between covariates and PK parameters from ML models. As a case‐study, we use data from 119 patients with hemophilia A receiving clotting factor VIII concentrate peri‐operatively. We fit both a random forest and a XGBoost model to predict empirical Bayes estimated clearance and central volume from a base nonlinear mixed effects model. Next, we show that SHAP reveals covariate relationships which match previous findings. In addition, we can reveal subtle effects arising from combinations of covariates difficult to obtain using other methods of covariate analysis. We conclude that the proposed method can be used to extend ML‐based covariate selection, and holds potential as a complete full model alternative to classical covariate analyses. [ABSTRACT FROM AUTHOR]

Nonlinear mixed effect (NLME) models are the gold standard for the analysis of patient response following drug exposure. However, these types of models are complex and time‐consuming to develop. There is great interest in the adoption of machine‐learning methods, but most implementations cannot be reliably extrapolated to treatment strategies outside of the training data. In order to solve this problem, we propose the deep compartment model (DCM), a combination of neural networks and ordinary differential equations. Using simulated datasets of different sizes, we show that our model remains accurate when training on small data sets. Furthermore, using a real‐world data set of patients with hemophilia A receiving factor VIII concentrate while undergoing surgery, we show that our model more accurately predicts a priori drug concentrations compared to a previous NLME model. In addition, we show that our model correctly describes the changing drug concentration over time. By adopting pharmacokinetic principles, the DCM allows for simulation of different treatment strategies and enables therapeutic drug monitoring. [ABSTRACT FROM AUTHOR]

Introduction: Directional deep brain stimulation (DBS) and pulse with <60μs increase side-effects threshold, enlarging the therapeutic window. However, new systems allowing these advanced features are more expensive and often available only for a limited number of patients in some centers. It is unknown how many and which DBS patients actually need the advanced features because of an insufficient improvement with standard parameters.Methods: We included in the analysis all patients with Parkinson's disease, dystonia and tremor who were selected to receive implantation of advanced DBS systems based on specific preoperative or intraoperative clinical features.Results: After a median follow-up of 15 months, 54.9% of the 51 patients implanted with directional leads were using the advanced features in one or both leads (n = 42 leads, 42%), meaning these leads were programmed either with directional stimulation (n = 9, 9%), a shorter pw (n = 20, 20%) or both (n = 13, 13%). This included 92% of patients implanted in the Vim, 44% of those implanted in the STN, and 40% of those implanted in the GPi.Conclusions: DBS systems with advanced features may be particularly indicated for selected patients based on some clinical characteristics and the chosen target. This data may help clinicians allocate resources in a more informed way. [ABSTRACT FROM AUTHOR]

Atlantoaxial rotatory subluxation (AARS) is a rare pathological condition of the upper cervical spine. It can be caused by multiple mechanisms, including minor neck manipulations. Children are more prone owing to the weaker periarticular soft tissue and a steeper slant of the C1 facet plane against the vertical axis of the dens. If AARS does not resolve spontaneously, a normal position of the atlantoaxial joint must be achieved by reduction and stabilization. A 15-year-old girl had presented with a painful torticollis that had already been present for 4 weeks after trimaxillary jaw correction for skeletal class II malocclusion. A computed tomography (CT) scan of the cervical spine showed AARS Field and Hawkins classification type I. We first attempted 1 week of conservative treatment with a soft collar and the prescription of a muscular relaxant. However, because the AARS persisted, we performed transoral closed reduction with the patient under general anesthesia, as previously described. During the procedure, we used intraoperative cone-beam CT to evaluate the degree of reduction. After obtaining complete reduction, immobilization with a halo-vest was applied. Complete reduction of the AARS was achieved with closed intraoral reduction. We used intraoperative cone-beam CT to confirm complete reduction. We found cone-beam CT to be a very useful tool. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate equations for estimation of glomerular filtration rate (GFR) and measured urinary creatinine clearance, compared to measured GFR in critically ill patients. Methods: GFR was measured using inulin clearance. Multiple blood samples were collected per patient for determination of serum creatinine, cystatin C and inulin. GFR was estimated by the use of the following estimation equations (eGFR): four commonly used creatinine-based equations [Cockcroft-Gault, Modification of Diet in Renal Disease (both the short and long formula) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)], five cystatin C based estimation equations (Hoek, Larsson, Filler, Le Bricon, CKD-EPIcys) and one equation combining cystatin C and serum creatinine (CKD-EPIcr-cys). In addition we measured urinary creatinine clearance. Bias, precision and accuracy of all estimates were compared to those of the inulin clearance. Results: Data were collected from 83 patients, of whom 68 were considered evaluable. The median age was 58 years [interquartile range (IQR) 39-68]. The median inulin clearance was 80 mL/min/1.73 m (IQR 31-114). Equations based on creatinine had much bias and poor precision and accuracy. Measured urinary creatinine clearances overestimated GFR. Equations based on cystatin C were free of bias, but also had limited precision and accuracy. Conclusions: In this cohort of patients, estimates of GFR had low accuracy and precision. Cystatin C based formulas, especially CKD-EPIcr-cys, showed limited bias; however, the accuracy and precision of these estimates were still insufficient. Measured urinary creatinine clearance overestimates GFR, but may provide a cheap alternative, when this is taken into account. [ABSTRACT FROM AUTHOR]

Early‐diagenetic cementation of tropical carbonates results from the combination of numerous physico‐chemical and biological processes. In the marine phreatic environment it represents an essential mechanism for the development and stabilization of carbonate platforms. However, diagenetic cements that developed early in the marine phreatic environment are likely to become obliterated during later stages of meteoric or burial diagenesis. When lithified sediment samples are studied, this complicates the recognition of processes involved in early cementation, and their geological implications. In this contribution, a petrographic microfacies analysis of Holocene Halimeda segments collected on a coral island in the Spermonde Archipelago, Indonesia, is presented. Through electron microscopical analyses of polished samples, this study shows that segments are characterized by intragranular cementation of fibrous aragonite, equant High‐Mg calcite (3.9 to 7.2 Mol% Mg), bladed Low‐Mg calcite (0.4 to 1.0 Mol% Mg) and mini‐micritic Low‐Mg calcite (3.2 to 3.3 Mol% Mg). The co‐existence and consecutive development of fibrous aragonite and equant High‐Mg calcite results initially from the flow of oversaturated seawater along the aragonite template of the Halimeda skeleton, followed by an adjustment of cement mineralogy towards High‐Mg calcite as a result of reduced permeability and fluid flow rates in the pores. Growth of bladed Low‐Mg calcite cements on top of etched substrates of equant High‐Mg calcite is explained by shifts in pore water pH and alkalinity through microbial sulphate reduction. Microbial activity appears to be the main trigger for the precipitation of mini‐micritic Low‐Mg calcite as well, based on the presumable detection of an extracellular polymeric matrix during an early stage of mini‐micrite Low‐Mg calcite cement precipitation. Radiocarbon analyses of five Halimeda segments furthermore indicate that virtually complete intragranular cementation in the marine phreatic environment with thermodynamically/kinetically controlled aragonite and High‐Mg calcite takes place in about 100 years. Collectively, this study shows that early‐diagenetic cements are highly diverse and provides new quantitative constraints on the rate of diagenetic cementation in tropical carbonate factories. [ABSTRACT FROM AUTHOR]

The use of natural fibres for components subjected to higher mechanical requirements tends to be limited by the high price of high-quality semi-finished products. Therefore, the present study deals with the development of more cost-effective staple fibre yarns made from flax tow. In the subsequent processing stage, the yarns were processed into quasi-unidirectional (UD) fabrics. The results of the fibre characterisation along the process chain have shown that no significant mechanical fibre damage occurs after slivers' production. Fibres prepared from yarns and fabrics show comparable characteristics. The yarns were processed to composites by pultrusion to verify the reinforcement effect. The mechanical properties were comparable to those of composites made from a high-quality UD flax roving. The fabrics were industrially processed into composite laminates using a vacuum infusion and an autoclave injection process (vacuum injection method in an autoclave). While impact strength compared to a reference laminate based on the UD flax roving was achieved, tensile and flexural properties were not reached. An analysis showed that the staple fibre yarns in the fabric show an undulation, leading to a reorientation of the fibres and lower characteristic values, which show 86–92% of the laminate made from the flax roving. Hybrid laminates with outer glass and inner flax layers were manufactured for the intended development of a leaf spring for the bogie of a narrow-gauge railroad as a demonstrator. The hybrid composites display excellent mechanical properties and showed clear advantages over a pure glass fibre-reinforced composite in lightweight construction potential, particularly flexural stiffness. [ABSTRACT FROM AUTHOR]