Pharmacodynamic Model Research Articles

Closed-loop control of anesthetic state in nonhuman primates.

Research in human volunteers and surgical patients has shown that unconsciousness under general anesthesia can be reliably tracked using real-time electroencephalogram processing. Hence, a closed-loop anesthesia delivery (CLAD) system that maintains precisely specified levels of unconsciousness is feasible and would greatly aid intraoperative patient management. The US Federal Drug Administration has approved no CLAD system for human use due partly to a lack of testing in appropriate animal models. To address this key roadblock, we implement a nonhuman primate (NHP) CLAD system that controls the level of unconsciousness using the anesthetic propofol. The key system components are a local field potential (LFP) recording system; propofol pharmacokinetics and pharmacodynamic models; the control variable (LFP power between 20 and 30 Hz), a programmable infusion system and a linear quadratic integral controller. Our CLAD system accurately controlled the level of unconsciousness along two different 125-min dynamic target trajectories for 18 h and 45 min in nine experiments in two NHPs. System performance measures were comparable or superior to those in previous CLAD reports. We demonstrate that an NHP CLAD system can reliably and accurately control in real-time unconsciousness maintained by anesthesia. Our findings establish critical steps for CLAD systems' design and testing prior to human testing.

P11.84.A PHASE 1 TRIAL OF MARIZOMIB ALONE AND IN COMBINATION WITH PANOBINOSTAT IN CHILDREN WITH DIFFUSE INTRINSIC PONTINE GLIOMA (DIPG)

Abstract BACKGROUND DIPG is an aggressive brainstem tumor with no effective therapy beyond the temporizing effects of radiation (RT). Preclinical studies demonstrated synergistic activity of marizomib (MRZ), an irreversible CNS-penetrant, pan-proteosome inhibitor, when administered with the HDAC inhibitor, panobinostat. In a study of adults with glioblastoma, MRZ was associated with significant CNS adverse events of interest (ataxia, balance disorder, dizziness, dysarthria, fall, gait disturbance, hallucination) in the majority of patients. We performed a novel Bayesian design, dual phase 1 trial of MRZ administered as a single agent and in combination with panobinostat to children with DIPG. Primary objectives were to determine the toxicity profile, dose limiting toxicities (DLT), and maximum tolerated dose (MTD) of MRZ at doses up to 0.8 mg/m2 alone and when administered in combination with panobinostat, and to characterize the plasma pharmacokinetics of MRZ as a single agent in children with DIPG. MATERIAL AND METHODS Eligible patients were <22 years with DIPG who received prior standard RT. When available, tumor tissue was centrally reviewed for molecular diagnosis. Patients initially received MRZ alone (Course A1). If tolerated, they received the combination of MRZ and panobinostat on subsequent courses (Course B1, B2, etc.). MRZ starting dose was 0.6 mg/m2IV on Days 1 and 15 of a 28-day cycle. If no DLT was observed during Course A1, patients received MRZ in combination with panobinostat 22 mg/m2/dose p.o. every other day, 3 times/week, on a one week on, one week off schedule. Dose escalation/ de-escalation for single agent and combination was guided using the Bayesian optimal interval design. RESULTS Four patients enrolled; one withdrew prior to initiating therapy due to disease progression (PD). Median age at study entry was 7.7 (range, 4.8-8.7)yrs. Three were evaluable for MRZ toxicities, two were evaluable for the combination MRZ + panobinostat. All patients were treated at dose level 1. No DLTs or CNS AEs attributed to MRZ were observed. Adverse events were related to disease/tumor progression or considered mild (grade 1 headache, emesis, diarrhea, fatigue, lymphopenia, thrombocytopenia) with the exception of sinus tachycardia and dyspnea (grade 2) (n=1). All patients died of PD; median time from on study to death for 3 treated patients was 95 days (range, 50-112). Pre- and post-study tissues were obtained where possible for qualitative exploratory pharmacokinetic, pharmacodynamic, molecular and patient model analyses. The study was terminated early due to withdrawal of support from BMS. CONCLUSION Children with DIPG tolerated single agent MRZ at a dose of 0.6 mg/m2/dose on Days 1 and 15 and in combination with panobinostat without any DLT or CNS toxicity. Target dose levels were not evaluated as clinical development program for marizomib ended and the study was discontinued early.

An improved PKPD modeling approach to characterize the pharmacodynamic interaction over time between ceftazidime/avibactam and colistin from in vitro time-kill experiments against multidrug-resistant Klebsiella pneumoniae isolates.

In contrast to the checkerboard method, bactericidal experiments [time-kill curves (TKCs)] allow an assessment of pharmacodynamic (PD) interactions over time. However, TKCs in combination pose interpretation problems. The objective of this study was to characterize the PD interaction over time between ceftazidime/avibactam (CZA) and colistin (CST) using TKC against four multidrug-resistant Klebsiella pneumoniae susceptible to both antibiotics and expressing a widespread carbapenemase determinant KPC-3. In vitro TKCs were performed and analyzed using pharmacokinetic/pharmacodynamic (PKPD) modeling. The general pharmacodynamic interaction model was used to characterize PD interactions between drugs. The 95% confidence intervals (95%CIs) of the expected additivity and of the observed interaction were built using parametric bootstraps and compared to evaluate the in vitro PD interaction over time. Further simulations were conducted to investigate the effect of the combination at varying concentrations typically observed in patients. Regrowth was observed in TKCs at high concentrations of drugs alone [from 4 to 32× minimum inhibitory concentrations (MIC)], while the combination systematically prevented the regrowth at concentrations close to the MIC. Significant synergy or antagonism were observed under specific conditions but overall 95%CIs overlapped widely over time indicating an additive interaction between antibiotics. Moreover, simulations of typical PK profile at standard dosages indicated that the interaction should be additive in clinical conditions. The nature of the PD interaction varied with time and concentration in TKC. Against the four K. pneumoniae isolates, the bactericidal effect of CZA + CST combination was predicted to be additive and to prevent the emergence of resistance at clinical concentrations.

Mind the Gap: Model-Based Switching from Selatogrel to Maintenance Therapy with Oral P2Y12 Receptor Antagonists.

Background: The P2Y12 receptor antagonist selatogrel is being developed for subcutaneous self-administration with a ready-to-use autoinjector at the onset of acute myocardial infarction (AMI) symptoms. The unique pharmacological profile of selatogrel (fast, potent, and short-acting) can bridge the time gap between the onset of AMI and first medical care. A clinical Phase 1 study showed a time-dependent pharmacodynamic interaction between selatogrel and loading doses of clopidogrel and prasugrel. As treatment switching is a common clinical practice, the assessment of subsequent switching from a clopidogrel loading dose to the first maintenance dose of oral P2Y12 receptor antagonists is highly relevant. Objectives: Model-based predictions of inhibition of platelet aggregation (IPA) for the drugs triggering pharmacodynamic interactions were to be derived to support clinical guidance on the transition from selatogrel to oral P2Y12 receptor antagonists. Methods: Scenarios with selatogrel 16 mg administration or placebo followed by a clopidogrel loading dose and, in turn, prasugrel or ticagrelor maintenance doses at different times of administration were studied. Population pharmacokinetic/pharmacodynamic modeling and simulations of different treatment scenarios were used to derive quantitative estimates for IPA over time. Results: Following selatogrel/placebo and a clopidogrel loading dose, maintenance treatment with ticagrelor or a prasugrel loading dose followed by maintenance treatment quickly achieved sustained IPA levels above 80%. Prior to maintenance treatment, a short time span from 18 to 24 h was identified where IPA levels were predicted to be lower with selatogrel than with placebo if clopidogrel was administered 12 h after selatogrel or placebo. Predicted IPA levels reached with placebo alone and a clopidogrel loading dose at 4 h were consistently lower than with selatogrel administration, followed by a clopidogrel loading dose at 12 h. If a clopidogrel loading dose is administered at 12 h, selatogrel maintains higher IPA levels up to 16 h. IPA levels are subsequently lower than on the placebo until the administration of the first maintenance dose. Conclusions: Model-based predictions informed the transition from selatogrel subcutaneous administration to oral P2Y12 therapy. The application of modeling techniques illustrates the value of employing pharmacokinetic and pharmacodynamic modeling for the simulation of various clinical scenarios of switching therapies.

Pharmacometrics: Application in Drug Development and Clinical Practice

In the last 4 years, pharmacometrics (PMX) has advanced to the point that it is now a crucial part of drug development. Drug delivery systems and molecules with more complex architecture are being developed as technology advances. Pharmacodynamic modelling is based on the quantitative integration of pharmacokinetics, pharmacological systems, and (patho-) physiological processes in order to comprehend the intensity and time course of drug effects on the body. As a result, the drug absorption and disposition processes after the administration of these drug delivery systems and engineered molecules become exceedingly complex. The research field of drug delivery focuses on the development of new techniques to manipulate drug absorption and disposition to achieve a desirable effect for the PMX model used. An opportunity to combine pharmacokinetic and pharmacodynamic model-based estimations with pharmacoeconomic models emerges given the unpredictability in the dose-concentration-effect relationship of medications. Model-based drug development (MBDD) has been found to address the underlying causes of medication failure, hence enhancing the productivity, effectiveness, and success of late-stage clinical research. The pharmacokinetic (PK) model principles in optimizing the drug dose to suit individual patient needs and achieving maximum therapeutic utility are called clinical pharmacology. Pharmacodynamics (PD) relates response to the concentration of drugs in the body. Disease progression model-based evaluation of disease progression is an important aspect of drug development and pharmacology. The future perspective of pharmacometrics in drug development and clinical practices is challenging.

Building an adaptive dose simulation framework to aid dose and schedule selection.

Establishing a dosing regimen that maximizes clinical benefit and minimizes adverse effects for novel therapeutics is a key objective for drug developers. Finding an optimal dose and schedule can be particularly challenging for compounds with a narrow therapeutic window such as in oncology. Modeling and simulation tools can be valuable to conduct in silico evaluations of various dosing scenarios with the goal to identify those that could minimize toxicities, avoid unscheduled dose interruptions, or minimize premature discontinuations, which all could limit the potential for therapeutic benefit. In this tutorial, we present a stepwise development of an adaptive dose simulation framework that can be used for dose optimization simulations. The tutorial first describes the general workflow, followed by a technical description with basic to advanced practical examples of its implementation in mrgsolve and is concluded with examples on how to use this in decision-making around dose and schedule optimization. The adaptive simulation framework is built with pharmacokinetic, pharmacodynamic (i.e., biomarkers, activity markers, target engagement markers, efficacy markers), and safety models that include evaluations of unexplained interindividual and intraindividual variability and covariate impact, which can be replaced and expanded (e.g., combination setting, comparator setting) with user-defined models. Subsequent adaptive simulations allow investigation of the impact of starting dose, dosing intervals, and event-driven (exposure or effect) dose modifications on any end point. The resulting simulation-derived insights can be used in quantitatively proposing dose and regimens that better balance benefit and adverse effects for further evaluation, aiding dose selection discussions, and designing dose modification recommendations, among others.

Selection of Nemolizumab Clinical Dosage for Atopic Dermatitis.

Nemolizumab is a monoclonal antibody directed against the interleukin-31 receptor A subunit, which is involved in the pathogenesis of pruritus and inflammation in atopic dermatitis (AD). Clinical trial results were combined with population PK (popPK) and pharmacokinetic/ pharmacodynamic (PK/PD) models to optimize nemolizumab dosing. Phase 1 and 2a clinical studies indicated that weight-based nemolizumab dosing reduced pruritus in patients with moderate-to-severe AD with good safety and tolerability even at the highest dose (3 mg/kg single dose and 2 mg/kg multiple doses). Nemolizumab PK profile was characterized by a slow absorption with peak serum concentrations reached 4.5-9.2 days post-dose, and a long terminal half-life ranging from 12.6 to 16.5 days. A change from weight-based dosing to flat dose was supported by an additional phase 2b study sponsored by Galderma. Flat dosing provides several practical advantages, including ease of preparation for self- or auto-injection and reduced chance of dosing errors. Doses of 10, 30, and 90 mg were selected based on popPK and PK/PD simulations to result in nemolizumab serum concentrations sufficient to achieve efficacy. Loading doses were administrated at the 2 lower doses in order to achieve target systemic concentrations from the first injection. The efficacy of Nemolizumab in improving cutaneous signs of inflammation and pruritus in AD and its safety profile, combined with popPK and PK/PD analyses, supported selection of the flat-dose regimen of 30 mg (with a 60 mg loading dose) given every 4 weeks subcutaneously for 16 weeks in the phase 3 ARCADIA studies sponsored by Galderma. J Drugs Dermatol. 2023;22(10):1017-1020 doi:10.36849/JDD.7437R1.

Pharmacodynamic Model of the Dynamic Response of Pseudomonas aeruginosa Biofilms to Antibacterial Treatments.

Accurate pharmacokinetic-pharmacodynamic (PK-PD) models of biofilm treatment could be used to guide formulation and administration strategies to better control bacterial lung infections. To this end, we developed a detailed pharmacodynamic model of P. aeruginosa treatment with the front-line antibiotics, tobramycin and colistin, and validated it on a detailed dataset of killing dynamics. A compartmental model structure was developed in which the key features are the diffusion of the drug through a boundary layer to the bacteria, concentration-dependent interactions with bacteria, and the passage of the bacteria through successive transit states before death. The number of transit states employed was greater for tobramycin, which is a ribosomal inhibitor, than for colistin, which disrupts bacterial membranes. For both drugs, the experimentally observed delay in the killing of bacteria following drug exposure was consistent with the sum of the diffusion time and the time for passage through the transit states. For each drug, the PD model with a single set of parameters described data across a ten-fold range of concentrations and for both continuous and transient exposure protocols, as well as for combined drug treatments. The ability to predict drug response over a range of administration protocols allows this PD model to be integrated with PK descriptions to describe in vivo antibiotic response dynamics and to predict drug delivery strategies for the improved control of bacterial lung infections.

Exploring the complex relationship between vitamin K, gut microbiota, and warfarin variability in cardiac surgery patients.

Due to the high individual variability of anticoagulant warfarin, this study aimed to investigate the effects of vitamin K concentration and gut microbiota on individual variability of warfarin in 246 cardiac surgery patients. The pharmacokinetics and pharmacodynamics (PKPD) model predicted international normalized ratio (INR) and warfarin concentration. Serum and fecal samples were collected to detect warfarin and vitamin K [VK1 and menaquinone-4 (MK4)] concentrations and gut microbiota diversity, respectively. In addition, the patient's medical records were reviewed for demographic characteristics, drug history, and CYP2C9, VKORC1, and CYP4F2 genotypes. The PKPD model predicted ideal values of 62.7% for S-warfarin, 70.4% for R-warfarin, and 76.4% for INR. The normal VK1 level was 1.34±1.12nmol/ml (95% CI: 0.33-4.08nmol/ml), and the normal MK4 level was 0.22±0.18nmol/ml (95% CI: 0.07-0.63nmol/ml). The MK4 to total vitamin K ratio was 16.5±9.8% (95% CI: 4.3-41.5%). The S-warfarin concentration of producing 50% of maximum anticoagulation and the half-life of prothrombin complex activity tended to increase with vitamin K. Further, Prevotella and Eubacterium of gut microbiota identified as the main bacteria associated with individual variability of warfarin. The results suggest that an increase in vitamin K concentration can decrease anticoagulation, and gut microbiota may influence warfarin anticoagulation through vitamin K2 synthesis. This study highlights the importance of considering vitamin K concentration and gut microbiota when prescribing warfarin. The findings may have significant implications for the personalized use of warfarin. Further research is needed to understand better the role of vitamin K and gut microbiota in warfarin anticoagulation.

MPGES-1 Inhibitor Discovery Based on Computer-Aided Screening: Pharmacophore Models, Molecular Docking, ADMET, and MD Simulations.

mPGES-1 is an enzyme, which, when activated by inflammatory factors, can cause prostaglandin E synthesis. Traditional non-steroidal anti-inflammatory drugs are capable of inhibiting prostaglandin production, yet they can also cause gastrointestinal reactions and coagulation disorders. mPGES-1, the enzyme at the conclusion of prostaglandin production, does not cause any adverse reactions when inhibited. Numerous studies have demonstrated that mPGES-1 is more abundant in cancerous cells than in healthy cells, indicating that decreasing the expression of mPGES-1 could be a potential therapeutic strategy for cancer. Consequently, the invention of mPGES-1 inhibitors presents a fresh avenue for the treatment of inflammation and cancer. Incorporating a database of TCM compounds, we collected a batch of compounds that had an inhibitory effect on mPGES-1 and possessed IC50 value. Firstly, a pharmacophore model was constructed, and the TCM database was screened, and the compounds with score cut-off values of more than 1 were retained. Then, the compounds retained after being screened via the pharmacodynamic model were screened for docking at the mPGES-1 binding site, followed by high-throughput virtual screening [HTVS] and standard precision [SP] and super-precision [XP] docking, and the compounds in the top 20% of the XP docking score were selected to calculate the total free binding energy of MM-GBSA. The best ten compounds were chosen by comparing their score against the reference ligand 4U9 and the MM-GBSA_dG_Bind score. ADMET analysis resulted in the selection of ten compounds, three of which had desirable medicinal properties. Finally, the binding energy of the target protein mPGES-1 and the candidate ligand compound was analyzed using a 100 ns molecular dynamics simulation of the reference ligand 4U9 and three selected compounds. After a gradual screening study and analysis, we identified a structure that is superior to the reference ligand 4U9 in all aspects, namely compound 15643. Taken together, the results of this study reveal a structure that can be used to inhibit mPGES-1 compound 15643, thereby providing a new option for anti-inflammatory and anti-tumor drugs.

Population pharmacokinetic/pharmacodynamic modeling of nifekalant injection with varies dosing plan in Chinese volunteers: a randomized, blind, placebo-controlled study.

Nifekalant hydrochloride is a class III antiarrhythmic agent which could increase the duration of the action potential and the effective refractory period of ventricular and atrial myocytes by blocking the K+ current. Nifekalant is used to prevent ventricular tachycardia/ventricular fibrillation. QT interval prolongation is the main measurable drug effect. However, due to the complicated dosing plan in clinic,the relationship among dosage, time, drug concentration and efficacy is not fully understood. In this study, a single-center, randomized, blind, dose-ascending, placebo-controlled study was conducted to explore the intrinsic characteristics of nifekalant injection in healthy Chinese volunteers by a population pharmacokinetic (PK)-pharmacodynamic (PD) model approach. 42 subjects were enrolled in this study and received one of three dose plans (loading dose on Day 1 (0.15, 0.3 or 0.5mg/kg), loading dose followed by maintenance dose (0.2, 0.4 or 0.8mg/kg/h) on Day 4) or vehicle. Blood samples were drawn for PK evaluation, and ECGs were recorded for QTc calculation at the designed timepoints. No Torsades de Pointes occurred during the study. The popPK model of nifekalant injection could be described by a two-compartment model with first-order elimination. The population mean clearance (CL) was 53.8L/h. The population mean distribution volume of the central (Vc) and peripheral (Vp) compartments was 8.27L and 45.6L, respectively. A nonlinear dose-response (Emax) model well described the pharmacodynamic effect (QTc interval prolongation) of nifekalant. The Emax and EC50 from current study were 101ms and 342ng/mL, respectively.

Semimechanistic pharmacokinetic-pharmacodynamic model of tripegfilgrastim for pediatric patients after chemotherapy.

Tripegfilgrastim is a long-acting granulocyte colony-stimulating factor (G-CSF) that has been used to prevent chemotherapy-induced neutropenia in adults. This study aimed to establish a pharmacokinetic (PK)-pharmacodynamic (PD) model to explore the impact of chemotherapy and tripegfilgrastim on absolute neutrophil counts (ANCs) and to further propose a fixed-dose regimen in pediatric patients. Because neutrophils affect the clearance of tripegfilgrastim, the semimechanistic PK-PD model was developed simultaneously by using data from 40 healthy adults and 27 pediatric patients with solid tumors. Tripegfilgrastim PK and ANC dynamics were described with a pharmacodynamics-mediated drug disposition model assuming quasi-equilibrium with five transit compartments mimicking neutrophil granulopoiesis. The effect of chemotherapy on neutrophils was included by stimulating the elimination of the G-CSF receptor at the mitotic cells. Healthy adult and pediatric patients showed significantly different value for dissociation constant of the tripegfilgrastim-G-CSF receptor complex (Kd ) and apparent volume of distribution (Vd /F). Patients treated with chemotherapy had a higher Vd /F and 62% lower Kd than healthy adults. As the age increased, the absorption rate of tripegfilgrastim was decreased. Body weight affected the G-CSF receptor-mediated internalization of tripegfilgrastim, and the baseline ANC value impacted the production rate of G-CSF receptors. Simulations from the developed model suggested that 1.5, 2.5, 4, and 6 mg single subcutaneous tripegfilgrastim doses for the respective weight groups of 10-20, 21-30, 31-44, and more than 45 kg significantly reduced the duration of Grade 4 neutropenia similar to tripegfilgrastim weight-based treatment with 100 μg/kg.

Targeted dosing for susceptible heteroresistant subpopulations may improve rational dosage regimen prediction for colistin in broiler chickens

The dosage of colistin for the treatment of enteric E. coli in animals necessitates considering the heteroresistant (HR) nature of the targeted inoculum, described by the presence of a major susceptible population (S1, representing 99.95% of total population) mixed with an initial minor subpopulation of less susceptible bacteria (S2). Herein, we report the 1-compartment population pharmacokinetics (PK) of colistin in chicken intestine (jejunum and ileum) and combined it with a previously established pharmacodynamic (PD) model of HR in E. coli. We then computed probabilities of target attainment (PTA) with a pharmacodynamic target (AUC24h/MIC) that achieves 50% of the maximal kill of bacterial populations (considering inoculums of pure S1, S2 or HR mixture of S1 + S2). For an MIC of 1 mg/L, PTA > 95% was achieved with the registered dose (75,000 IU/kg BW/day in drinking water) for the HR mixture of S1 + S2 E. coli, whether they harboured mcr or not. For an MIC of 2 mg/L (ECOFF), we predicted PTA > 90% against the dominant susceptible sub-population (S1) with this clinical dose given (i) over 24 h for mcr-negative isolates or (ii) over 6 h for mcr-positive isolates (pulse dosing). Colistin clinical breakpoint S ≤ 2 mg/L (EUCAST rules) should be confirmed clinically.

Neuromuscular end-point predictive capability of published rocuronium pharmacokinetic/pharmacodynamic models: An observational trial

BackgroundObjective neuromuscular monitoring remains the single most reliable method to ensure optimal perioperative neuromuscular management. Nevertheless, the prediction of clinical neuromuscular endpoints by means of Pharmacokinetic (PK) and Pharmacodynamic (PD) modelling has the potential to complement monitoring and improve perioperative neuromuscular management.s Study objectiveThe present study aims to assess the performance of published Rocuronium PK/PD models in predicting intraoperative Train-of-four (TOF) ratios when benchmarked against electromyographic TOF measurements. DesignObservational trial. SettingTertiary Belgian hospital, from August 2020 up to September 2021. Patients and interventionsSeventy-four patients undergoing general anaesthesia for elective surgery requiring the administration of rocuronium and subject to continuous EMG neuromuscular monitoring were included. PK/PD-simulated TOF ratios were plotted and synchronised with their measured electromyographic counterparts and their differences analysed by means of Predictive Error derivatives (Varvel criteria). Main resultsPublished rocuronium PK/PD models overestimated clinically registered TOF ratios. The models of Wierda, Szenohradszky, Cooper, Alvarez-Gomez and McCoy showed significant predictive consistency between themselves, displaying Median Absolute Performance Errors between 38% and 41%, and intra-individual differences (Wobble) between 14 and 15%. The Kleijn model outperformed the former with a lower Median Absolute Performance Error (16%, 95%CI [0.01; 57]) and Wobble (11%, 95%CI [0.01; 34]). All models displayed considerably wide 95% confidence intervals for all performance metrics, suggesting a significantly variable performance. ConclusionsSimulated TOF ratios based on published PK/PD models do not accurately predict real intraoperative TOF ratio dynamics. Trial registrationNCT04518761 (clinicaltrials.gov), registered on 19 August 2020.

A preclinical study on online monitoring of exhaled ciprofol concentration by the ultraviolet time-of-flight spectrometer and prediction of anesthesia depth in beagles

BackgroundExhaled air has been demonstrated as a reliable medium for monitoring propofol concentration. However, online monitoring of exhaled ciprofol have not been reported. MethodsThirty-six beagles undergoing mechanical ventilation were divided into 6 groups, including bolus injection of low (Group BL, n = 6), medium (Group BM, n = 6), and high dose of ciprofol (Group BH, n = 6) groups; as well as 1 h continuous infusion of low (Group IL, n = 6), medium (Group IM, n = 6), and high dose of ciprofol (Group IH, n = 6) groups. The ciprofol concentration in exhaled air (CE) was determined by the ultraviolet time-of-flight mass spectrometer (UV-TOFMS). The correlations of CE and plasma concentration (Cp), CE and the bispectral index (BIS) were explored. Additionally, the pharmacokinetics (PK) models of CE and Cp, the pharmacodynamics (PD) models of CE and BIS were also established. ResultsOnline monitoring of exhaled ciprofol can be achieved with the UV-TOFMS instrument. The CE of ciprofol in beagles was found at parts per billion by volume (ppbv) level. The linear correlation of CE and Cp was weak in bolus injection groups (R2 = 0.01) nonetheless moderate in continuous infusion groups (R2 = 0.53). The i.v. bolus PK model of CE and Cp can be fitted with the non-compartment models. Additionally, the the PD models of CE and BIS can be well fitted with the inhibitory sigmoid Emax model with the estimate values of IC50 = 0.05 ± 0.01 ppbv, γ = 4.74 ± 1.51, E0 = 81.40 ± 3.75, Imax = 16.35 ± 4.27 in bolus injection groups; and IC50 = 0.05 ± 0.01 ppbv, γ = 6.92 ± 1.30, E0 = 83.08 ± 1.62, Imax = 12.58 ± 1.65 in continuous infusion groups. ConclusionsOnline monitoring of exhaled ciprofol concentration in beagles can be achieved with the UV-TOFMS instrument. Good correlations can be observed between exhaled ciprofol concentration and its cerebral effects reflected by the BIS value, demonstrating the potential of exhaled ciprofol monitoring for titrating depth of anesthesia in future clinical setting.

Hydrogel device for analgesic drugs with in-situ loading and polymerization

The high prevalence of opioid addiction and the shortcomings of systemic opioids has increased the pace of the search for alternative methods of pain management. The local delivery of pain medications has started to be used as a tool for pain management and to decrease the use of systemic opioids for these patients. Here, we explored an in-situ polymerizable hydrogel system for the local delivery of analgesics and nonsteroid anti-inflammatory drugs (NSAID) for orthopaedic applications. We synthesized a series of methacrylated oligomeric polyethylene glycol-co-lactic acid polymer using microwave radiation for the delivery of bupivacaine hydrochloride as an analgesic and ketorolac tromethamine as an NSAID. We determined drug elution and gel degradation profiles in vitro. Biocompatibility was assessed against osteoblasts in vitro and by histological analysis after subcutaneous implantation for 4 weeks in vivo. Intra-articular and systemic concentrations and pharmacokinetic parameters were estimated using a two-compartment pharmacodynamic model based on in-vitro elution profiles. This type of in-situ applicable hydrogels is promising for extending the local efficacy of pain medication and further reducing the need for opioids.

Koopman-based Impulsive Model Predictive Control of BCG Immunotherapy.

Bacillus of Calmette and Guerin (BCG) is the most effective immunologic treatment for non-muscle-invasive bladder cancer by stimulating the immune response of patients. The therapeutic performance of BCG treatment is limited by the dosing scheme, which is difficult to design due to nonlinear dynamics and constraints in the pharmacodynamic model. Here we present a computational method that combines linearization, impulsive control, and constrained optimization to design optimal drug dosing. We do so by first adopting Koopman theory to map the nonlinear pharmacodynamic model into linear space. Then we use model predictive control to design drug dosing schemes based on the transformed linear model with impulsive drug instillation, constrained by drug concentration. With this pipeline, we find that the Koopman-based linear system has almost identical dynamic behaviors to the original model based on numerical simulations. Also, the designed drug doses stay within the constraints and cancerous cell proliferation is effectively suppressed by driving the uninfected tumor cell population to a descending reference trajectory. Robustness tests are performed to show the proposed controller is robust to a certain level of model uncertainty. The method is expected to be generalized to the design of other model-based drug dosing schemes because of its optimality, impulsivity, and linearity.

Pharmacokinetic–pharmacodynamic modeling of maintenance therapy for childhood acute lymphoblastic leukemia

In the treatment of childhood acute lymphoblastic leukemia (ALL), current protocols combine initial high-dose multiagent chemotherapy with prolonged oral therapy with 6-mercaptopurine (6MP) and low-dose methotrexate (MTX) maintenance therapy. Decades of research on ALL treatment have resulted in survival rates of approximately 90%. However, dose-response relationships vary widely between patients and insight into the influencing factors, that would allow for improved personalized treatment management, is insufficient. We use a detailed data set with measurements of thioguanine nucleotides and MTX in red blood cells and absolute neutrophil count (ANC) to develop pharmacokinetic models for 6MP and MTX, as well as a pharmacokinetic–pharmacodynamic (PKPD) model capable of predicting individual ANC levels and thus contributing to the development of personalized treatment strategies. Here, we show that integrating metabolite measurements in red blood cells into the full PKPD model improves results when less data is available, but that model predictions are comparable to those of a fixed pharmacokinetic model when data availability is not limited, providing further evidence of the quality of existing models. With this comprehensive model development leading to dynamics similar to simpler models, we validate the suitability of this model structure and provide a foundation for further exploration of maintenance therapy strategies through simulation and optimization.

Special Issue on “Pharmacodynamics Modeling of Anti-Inflammatory Drugs”

Immuno-inflammatory responses are essential for defending the host against pathogenic infections [...]

Anti-inflammatory effects of dexamethasone in COVID-19 patients: Translational population PK/PD modeling and simulation.

Dexamethasone (DEX) given at a dose of 6 mg once-daily for 10 days is a recommended dosing regimen in patients with coronavirus disease 2019 (COVID-19) requiring oxygen therapy. We developed a population pharmacokinetic and pharmacodynamic (PopPK/PD) model of DEX anti-inflammatory effects in COVID-19 and provide simulations comparing the expected efficacy of four dosing regimens of DEX. Nonlinear mixed-effects modeling and simulations were performed using Monolix Suite version 2021R1 (Lixoft, France). Published data for DEX PK in patients with COVID-19 exhibited moderate variability with a clearance of about half that in healthy adults. No accumulation of the drug was expected even with daily oral doses of 12 mg. Indirect effect models of DEX inhibition of TNFα, IL-6, and CRP plasma concentrations were enacted and simulations performed for DEX given at 1.5, 3, 6, and 12 mg daily for 10 days. The numbers of individuals that achieved specified reductions in inflammatory biomarkers were compared among the treatment groups. The simulations indicate the need for 6 or 12 mg daily doses of DEX for 10 days for simultaneous reductions in TNFα, IL-6, and CRP. Possibly beneficial is DEX given at a dose of 12 mg compared to 6 mg. The PopPK/PD model may be useful in the assessment of other anti-inflammatory compounds as well as drug combinations in the treatment of cytokine storms.