Genetic algorithms as a tool for dosing guideline optimisation : application to intermittent infusion dosing for vancomycin in adults

This paper demonstrates the use of a genetic algorithm (GA) for the optimization of a dosing guideline. GAs are well-suited to derive combinations of doses and dosing intervals that go into a dosing guideline when the number of possible combinations rule out the calculation of all possible outcomes. GAs also allow for different constraints to be imposed on the optimization process to safeguard the clinical feasibility of the dosing guideline. In this work, we demonstrate the use of a GA for the optimization of intermittent vancomycin administration in adult patients. Constraints were placed on the dose strengths, the length of the dosing intervals, and the maximum infusion rate. In addition, flexibility with respect to the timing of the first maintenance dose was included in the optimization process. The GA-based optimal solution is compared with the Scottish Antimicrobial Prescribing Group vancomycin guideline

Gentamicin Administration in Dialysis Patients:Before or After Hemodialysis?

BACKGROUND: Gentamicin is used to treat severe infections and has a small therapeutic window. This study aimed to optimize the dosing strategy of gentamicin in intermittently hemodialyzed patients by simulating concentration/time profiles during pre- and post-dialysis dosing, based on a published pharmacokinetic model.METHODS: Pharmacokinetic simulations were performed with virtual patients, including septic patients, who were treated with gentamicin and received weekly hemodialysis with an interval of 48h-48h-72h. The following dosing regimens were simulated: for non-septic patients, 5 mg/kg gentamicin was given 1h/2h before dialysis, or a starting dose of 2.5 mg/kg and a maintenance dose of 1.5 mg/kg immediately after dialysis; for septic patients, 6 mg/kg gentamicin was given 1h/2h before dialysis, or a starting dose of 3 mg/kg and a maintenance dose of 1.8 mg/kg immediately after dialysis. The mean Cmax, AUC24h, and target attainment (TA) of pharmacodynamic targets were calculated and compared. The following targets were adopted from literature: Cmax &gt;8 mg/L and &lt;20 mg/L and AUC24h &gt;70 mg·h/L and &lt;120 mg·h/L.RESULTS: In non-septic patients, postdialysis dosing resulted in a TA of 35% for Cmax &gt;8 mg/L, 100% for &lt;20 mg/L and AUC24h &gt;70 mg·h/L, and 45% for &lt;120 mg·h/L. Dosing 2h prior to dialysis resulted in a TA of 100% for Cmax&gt; 8 mg/L, 40% for &lt;20 mg/L, 65% for AUC24h &gt;70 mg·h/L, and 77% for &lt;120 mg·h/L. Simulations of septic patients resulted in comparable outcomes with higher TAs for Cmax &lt;20 mg/L (96%), AUC24h &gt;70 mg·h/L (90%), and &lt;120 mg·h/L (53%) for dosing 1h prior to dialysis.CONCLUSIONS: Postdialysis dosing resulted in a low TA of Cmax &gt;8 mg/L; however, predialysis dosing ensured a high TA of Cmax &gt;8 mg/L and acceptable TA of Cmax &lt;20 mg/L, AUC24h &gt;70 mg·h/L, and &lt;120 mg·h/L, which could increase the efficacy of gentamicin. Therefore, clinicians should consider predialysis dosing of gentamicin in patients undergoing intermittent hemodialysis.</p

Mechanism-based pharmacodynamic model for propofol haemodynamic effects in healthy volunteers☆

Background: The adverse haemodynamic effects of the intravenous anaesthetic propofol are well known, yet few empirical models have explored the dose-response relationship. Evidence suggests that hypotension during general anaesthesia is associated with postoperative mortality. We developed a mechanism-based model that quantitatively characterises the magnitude of propofol-induced haemodynamic effects during general anaesthesia. Methods: Mean arterial pressure (MAP), heart rate (HR) and pulse pressure (PP) measurements were available from 36 healthy volunteers who received propofol in a step-up and step-down fashion by target-controlled infusion using the Schnider pharmacokinetic model. A mechanistic pharmacodynamic model was explored based on the Snelder model. To benchmark the performance of this model, we developed empirical models for MAP, HR, and PP. Results: The mechanistic model consisted of three turnover equations representing total peripheral resistance (TPR), stroke volume (SV), and HR. Propofol-induced changes were implemented by E-max models on the zero-order production rates of the turnover equations for TPR and SV. The estimated 50% effective concentrations for propofol-induced changes in TPR and SV were 2.96 and 0.34 mu g ml(-1), respectively. The goodness-of-fit for the mechanism-based model was indistinguishable from the empirical models. Simulations showed that predictions from the mechanism-based model were similar to previously published MAP and HR observations. Conclusions: We developed a mechanism-based pharmacodynamic model for propofol-induced changes in MAP, TPR, SV, and HR as a potential approach for predicting haemodynamic alterations

Pharmacodynamic mechanism-based interaction model for the haemodynamic effects of remifentanil and propofol in healthy volunteers

BACKGROUND: Propofol and remifentanil are frequently combined for the induction and maintenance of general anaesthesia. Both propofol and remifentanil cause vasodilation and potentially reduce arterial BP. We aimed to develop a mechanism-based model that characterises the haemodynamic interactions between remifentanil and propofol.METHODS: Data from two clinical trials in healthy volunteers were analysed using remifentanil-alone, propofol-alone, and combination groups. We evaluated remifentanil effects on haemodynamics using a previously developed mechanism-based haemodynamic model of propofol. The interaction between propofol and remifentanil was explored using the principles of the general pharmacodynamic interaction (GPDI) model.RESULTS: Remifentanil alone increased the dissipation rate of total peripheral resistance by 50% at 3.0 ng ml-1. Additionally, the dissipation rates of HR and stroke volume were attenuated by 4.8% and 4.9% per 1 ng ml-1 increase in remifentanil concentration, respectively. The maximal effect of propofol alone in decreasing the production rate of total peripheral resistance was 78%, which decreased to 32% when combined with remifentanil 4 ng ml-1. The effects of remifentanil on HR and stroke volume were attenuated by propofol with maximum decreases of 11.9% and 21.2%, respectively. Goodness-of-fit plots and prediction-corrected visual predictive check plots showed good predictive performance of the models.CONCLUSIONS: The structure of the previous mechanism-based haemodynamic model for propofol was able to describe the effects of remifentanil alone on haemodynamic variables. The GPDI model provided a good framework for characterising the pharmacodynamic interaction between remifentanil and propofol on haemodynamic properties.CLINICAL TRIAL REGISTRATION: NCT02043938; NCT03143972.</p

Comment on Morse et al. A Universal Pharmacokinetic Model for Dexmedetomidine in Children and Adults. J. Clin. Med. 2020, 9, 3480

We read with interest the recently published manuscript [...]

Target-Controlled Continuous Infusion for Antibiotic Dosing:Proof-of-Principle in an In-silico Vancomycin Trial in Intensive Care Unit Patients

Objectives: In this in-silico study, we investigate the clinical utility of target-controlled infusion for antibiotic dosing in an intensive care unit setting using vancomycin as a model compound. We compared target-controlled infusion and adaptive target-controlled infusion, which combines target-controlled infusion with data from therapeutic drug monitoring, with conventional (therapeutic drug monitoring-based) vancomycin dosing strategies. Methods: A clinical trial simulation was conducted. This simulation was based on a comprehensive database of clinical records of intensive care unit patients and a systematic review of currently available population-pharmacokinetic models for vancomycin in intensive care unit patients. Dosing strategies were compared in terms of the probability of achieving efficacious concentrations as well as the potential for inducing toxicity. Results: Adaptive target-controlled infusion outperforms rule-based dosing guidelines for vancomycin. In the first 48h of treatment, the probability of target attainment is significantly higher for adaptive target-controlled infusion than for the second-best method (Cristallini). Probability of target attainments of 54 and 72% and 47 and 59% for both methods after 24 and 48h, respectively. Compared to the Cristallini method, which is characterized by a probability of attaining concentrations above 30mg.L-1>65% in the first few hours of treatment, adaptive target-controlled infusion shows negligible time at risk and a probability of attaining concentrations above 30mg.L-1 not exceeding 25%. Finally, in contrast to the other methods, the performance of target-controlled infusion is consistent across subgroups within the population. Conclusions: Our study shows that adaptive target-controlled infusion has the potential to become a practical tool for patient-tailored antibiotic dosing in the intensive care unit

Pharmacokinetic properties of remimazolam in subjects with hepatic or renal impairment

BACKGROUND: Remimazolam is a new benzodiazepine for procedural sedation and general anaesthesia. The aim of this study was to characterise its pharmacokinetic properties and safety in renally and hepatically impaired subjects. METHODS: Two separate trials were conducted in patients with hepatic (n=11) or renal impairment (n=11) compared with matched healthy subjects (n=9 and n=12, respectively). The hepatic impairment trial was an open-label adaptive 'Reduced Design' trial, using a single bolus of remimazolam 0.1 mg kg-1 i.v., whereas the renal impairment trial was an open-label trial of a single bolus dose of remimazolam 1.5 mg i.v. Remimazolam plasma concentrations over time were analysed by population pharmacokinetic modelling. RESULTS: Remimazolam pharmacokinetic properties were adequately described by a three-compartment, recirculatory model. Exposure in subjects with severe hepatic impairment was 38.1% higher (i.e. clearance was 38.1% lower) compared with healthy volunteers. This increase caused a slightly delayed recovery (8.0 min for healthy, 12.1 min for moderate, and 16.7 min for severe hepatic impairment). With renal impairment, plasma clearance was comparable with that measured in healthy subjects. Simulations of Cmax after a bolus dose of 10 mg showed no relevant impact of hepatic or renal impairment. The overall incidence of adverse events was low, and all adverse events were mild. CONCLUSIONS: As Cmax after a remimazolam bolus i.v. was not affected by hepatic or renal impairment, no dose adjustments are required. No unexpected adverse events related to remimazolam were seen in subjects with renal or hepatic impairment. CLINICAL TRIAL REGISTRATION: Hepatic impairment trial: ClinicalTrials.gov, NCT01790607 (https://clinicaltrials.gov/ct2/show/NCT01790607). Renal impairment trial: EudraCT Number: 2014-004575-23

Clinical validation of pharmacokinetic/pharmacodynamic models for propofol infusion. Response to Br J Anaesth 2021:126: e172-4

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A Joint Pharmacokinetic Model for the Simultaneous Description of Plasma and Whole Blood Tacrolimus Concentrations in Kidney and Lung Transplant Recipients

BACKGROUND AND OBJECTIVE: Historically, dosing of tacrolimus is guided by therapeutic drug monitoring (TDM) of the whole blood concentration, which is strongly influenced by haematocrit. The therapeutic and adverse effects are however expected to be driven by the unbound exposure, which could be better represented by measuring plasma concentrations.OBJECTIVE: We aimed to establish plasma concentration ranges reflecting whole blood concentrations within currently used target ranges.METHODS: Plasma and whole blood tacrolimus concentrations were determined in samples of transplant recipients included in the TransplantLines Biobank and Cohort Study. Targeted whole blood trough concentrations are 4-6 ng/mL and 7-10 ng/mL for kidney and lung transplant recipients, respectively. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. Simulations were performed to infer plasma concentration ranges corresponding to whole blood target ranges.RESULTS: Plasma (n = 1973) and whole blood (n = 1961) tacrolimus concentrations were determined in 1060 transplant recipients. A one-compartment model with fixed first-order absorption and estimated first-order elimination characterised observed plasma concentrations. Plasma was linked to whole blood using a saturable binding equation (maximum binding 35.7 ng/mL, 95% confidence interval (CI) 31.0-40.4 ng/mL; dissociation constant 0.24 ng/mL, 95% CI 0.19-0.29 ng/mL). Model simulations indicate that patients within the whole blood target range are expected to have plasma concentrations (95% prediction interval) of 0.06-0.26 ng/mL and 0.10-0.93 ng/mL for kidney and lung transplant recipients, respectively.CONCLUSION: Whole blood tacrolimus target ranges, currently used to guide TDM, were translated to plasma concentration ranges of 0.06-0.26 ng/mL and 0.10-0.93 ng/mL for kidney and lung transplant recipients, respectively.</p