Population pharmacokinetic-pharmacodynamic model of propofol in adolescents undergoing scoliosis surgery with intraoperative wake-up test: a study using Bispectral index and composite auditory evoked potentials as pharmacodynamic endpoints

Development and Evaluation of Ontogeny Functions of the Major UDP-Glucuronosyltransferase Enzymes to Underwrite Physiologically Based Pharmacokinetic Modeling in Pediatric Populations

Uridine 5'-diphospho-glucuronosyltransferases (UGTs) demonstrate variable expression in the pediatric population. Thus, understanding of age-dependent maturation of UGTs is critical for accurate pediatric pharmacokinetics (PK) prediction of drugs that are susceptible for glucuronidation. Ontogeny functions of major UGTs have been previously developed and reported. However, those ontogeny functions are based on in vitro data (i.e., enzyme abundance, in vitro substrate activity, and so on) and therefore, may not translate to in vivo maturation of UGTs in the clinical setting. This report describes meta-analysis of the literature to develop and compare ontogeny functions for 8 primary UGTs (UGT1A1, UGT1A4, UGT1A6, UGT1A9, UGT2B7, UGT2B10, UGT2B15, and UGT2B17) based on published in vitro and in vivo studies. Once integrated with physiologically based pharmacokinetics modeling models, in vivo activity-based ontogeny functions demonstrated somewhat greater prediction accuracy (mean squared error, MSE: 0.05) compared to in vitro activity (MSE: 0.104) and in vitro abundance-based ontogeny functions (MSE: 0.129).

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

New frontiers in intraoperative neurophysiologic monitoring: a narrative review

Background and Objective

Neurological insults during surgery arise from anatomic and/or physiologic perturbations. Intraoperative neurophysiologic monitoring (IONM) fills a critical role of ensuring that any neurological insults during certain surgical procedures are caught in real-time to prevent patient harm. IONM provides immediate feedback to the surgeon and anesthesiologist about the need for an intervention to prevent a neurologic deficit postoperatively. As important as it seems to have IONM available to any patient having surgery where a neurological injury is possible, the truth is that IONM is unavailable to large swaths of people around the world. This review is intended to bring attention to all of the ways IONM is critically important for a variety of surgeries and highlight the barriers preventing most patients around the world from benefiting from the technology. Expansion of IONM to benefit patients from all over the world is the new frontier.

Methods

We searched all English language original papers and reviews using Embase and MEDLINE/PubMed databases published from 1995 to 2022. Different combinations of the following search terms were used: intraoperative neuromonitoring, neurosurgery, low-income countries, cost, safety, and efficacy.

Key Content and Findings

We describe common IONM modalities used during surgery as well as explore barriers to implementation of IONM in resource-limited regions. Additionally, we describe ongoing efforts to establish IONM capabilities in new locations around the world.

Conclusions

In this paper, we performed a review of the literature on IONM with an emphasis on the basic understanding of clinical applications and the barriers for expansion into resource-limited settings. Finally, we provide our interpretation of "new frontiers" in IONM quite literally facilitating access to the tools and education so a hospital in Sub-Saharan Africa can incorporate IONM for their high-risk surgeries.

Pharmacokinetic pharmacodynamic modeling of analgesics and sedatives in children

Pharmacokinetic pharmacodynamic modeling is an important tool which uses statistical methodology to provide a better understanding of the relationship between concentration and effect of drugs such as analgesics and sedatives. Pharmacokinetic pharmacodynamic models also describe between-subject variability that allows identification of subgroups and dose adjustment for optimal pain management in individual patients. This approach is particularly useful in the pediatric population, where most drugs have received limited evaluation and dosing is extrapolated from adult practice. In children, the covariates of weight and age are used to describe size- and maturation-related changes in pharmacokinetics. It is important to consider both size and maturation in order to develop an accurate model and determine the optimal dose for different age groups. An adequate assessment of analgesic and sedative effect using pain scales or brain activity measures is essential to build reliable pharmacokinetic pharmacodynamic models. This is often challenging in children due to the multidimensional nature of pain and the limited sensitivity and specificity of some measurement tools. This review provides a summary of the pharmacokinetic and pharmacodynamic methodology used to describe the dose-concentration-effect relationship of analgesics and sedation in children, with a focus on the different pharmacodynamic endpoints and the challenges of pharmacodynamic modeling.

A Transformer-Based Prediction Method for Depth of Anesthesia During Target-Controlled Infusion of Propofol and Remifentanil

Accurately predicting anesthetic effects is essential for target-controlled infusion systems. The traditional (PK-PD) models for Bispectral index (BIS) prediction require manual selection of model parameters, which can be challenging in clinical settings. Recently proposed deep learning methods can only capture general trends and may not predict abrupt changes in BIS. To address these issues, we propose a transformer-based method for predicting the depth of anesthesia (DOA) using drug infusions of propofol and remifentanil. Our method employs long short-term memory (LSTM) and gate residual network (GRN) networks to improve the efficiency of feature fusion and applies an attention mechanism to discover the interactions between the drugs. We also use label distribution smoothing and reweighting losses to address data imbalance. Experimental results show that our proposed method outperforms traditional PK-PD models and previous deep learning methods, effectively predicting anesthetic depth under sudden and deep anesthesia conditions.

Midlatency auditory evoked potentials during anesthesia in children: A narrative review

The brain is considered as the major target organ of anesthetic agents. Despite that, a reliable means to monitor its function during anesthesia is lacking. Mid latency auditory evoked potentials are known to be sensitive to anesthetic agents and might therefore be a measure of hypnotic state in pediatric patients. This review investigates the available literature describing various aspects of mid latency auditory evoked potential monitoring in pediatric anesthesia.

Modelling the PSI response in general anesthesia

In anesthesia automation, one of the main important issues is the availability of a reliable measurement of the depth of consciousness level (hypnosis) of the patient. According to this value, the hypnotic drug dosage can be adequately calculated. One of the most studied hypnosis indexes is the bispectral index (BIS). In this article we analyzed an alternative called patient state index (PSI). The objectives of this study are, first, to validate the accuracy of the PSI describing the hypnosis level during the maintenance phase of general anesthesia, by comparing with the BIS and, second, to model the relationship between propofol infusion rate and PSI values, obtained from a SEDLine monitor. For this, real data from patients undergoing general anesthesia simultaneously monitored with both BIS and PSI signals was used. Results obtained are interesting for a correct interpretation of PSI signal in clinical practice.