Mechanisms of ischaemia-induced arrhythmias in hypertrophic cardiomyopathy: a large-scale computational study

AIMS

Lethal arrhythmias in hypertrophic cardiomyopathy (HCM) are widely attributed to myocardial ischaemia and fibrosis. How these factors modulate arrhythmic risk remains largely unknown, especially as invasive mapping protocols are not routinely used in these patients. By leveraging multiscale digital-twin technologies, we aim to investigate ischaemic mechanisms of increased arrhythmic risk in HCM.

METHODS AND RESULTS

Computational models of human HCM cardiomyocytes, tissue and ventricles were used to simulate outcomes of phase 1A acute myocardial ischaemia. Cellular response predictions were validated with patch-clamp studies of human HCM cardiomyocytes (n=12 cells, N=5 patients). Ventricular simulations were informed by typical distributions of subendocardial/transmural ischaemia as analysed in perfusion scans (N=28 patients). S1-S2 pacing protocols were used to quantify arrhythmic risk for scenarios in which regions of septal obstructive hypertrophy were affected by (i) ischaemia, (ii) ischaemia and impaired repolarisation, and (iii) ischaemia, impaired repolarisation, and diffuse fibrosis.HCM cardiomyocytes exhibited enhanced action potential and abnormal effective refractory period shortening to ischaemic insults. Analysis of c.a. 75,000 re-entry induction cases revealed that the abnormal HCM cellular response enabled establishment of arrhythmia at milder ischaemia than otherwise possible in healthy myocardium, due to larger refractoriness gradients that promoted conduction block. Arrhythmias were more easily sustained in transmural than subendocardial ischaemia. Mechanisms of ischaemia-fibrosis interaction were strongly electrophysiology dependent. Fibrosis enabled asymmetric re-entry patterns and break-up into sustained ventricular tachycardia.

CONCLUSIONS

HCM ventricles exhibited an increased risk to non-sustained and sustained re-entry, largely dominated by an impaired cellular response and deleterious interactions with the diffuse fibrotic substrate.

Effects of ranolazine on the arrhythmic substrate in hypertrophic cardiomyopathy

Introduction: Hypertrophic cardiomyopathy (HCM) is a leading cause of lethal arrhythmias in the young. Although the arrhythmic substrate has been hypothesised to be amenable to late Na+ block with ranolazine, the specific mechanisms are not fully understood. Therefore, this study aimed to investigate the substrate mechanisms of safety and antiarrhythmic efficacy of ranolazine in HCM. Methods: Computational models of human tissue and ventricles were used to simulate the electrophysiological behaviour of diseased HCM myocardium for variable degrees of repolarisation impairment, validated against in vitro and clinical recordings. S1-S2 pacing protocols were used to quantify arrhythmic risk in scenarios of (i) untreated HCM-remodelled myocardium and (ii) myocardium treated with 3µM, 6µM and 10µM ranolazine, for variable repolarisation heterogeneity sizes and pacing rates. ECGs were derived from biventricular simulations to identify ECG biomarkers linked to antiarrhythmic effects. Results: 10µM ranolazine given to models manifesting ventricular tachycardia (VT) at baseline led to a 40% reduction in number of VT episodes on pooled analysis of >40,000 re-entry inducibility simulations. Antiarrhythmic efficacy and safety were dependent on the degree of repolarisation impairment, with optimal benefit in models with maximum JTc interval <370 ms. Ranolazine increased risk of VT only in models with severe-extreme repolarisation impairment. Conclusion: Ranolazine efficacy and safety may be critically dependent upon the degree of repolarisation impairment in HCM. For moderate repolarisation impairment, reductions in refractoriness heterogeneity by ranolazine may prevent conduction blocks and re-entry. With severe-extreme disease substrates, reductions of the refractory period can increase re-entry sustainability.

Unpeeling the onion: Digital triage and monitoring of general practice, private psychiatry, and psychology

OBJECTIVE

The Australian federal government is considering a 'digital front door' to mental healthcare. The Brain and Mind Centre at the University of Sydney has published a discussion paper advocating that the government should adopt a comprehensive model of digital triage and monitoring (DTM) based on a government-funded initiative Project Synergy ($30 million). We critically examine the final report on Project Synergy, which is now available under a Freedom of Information request.

CONCLUSION

The DTM model is disruptive. Non-government organisations would replace general practitioners as care coordinators. Patients, private psychiatrists, and psychologists would be subjected to additional layers of administration, assessment, and digital compliance, which may decrease efficiency, and lengthen the duration of untreated illness. Only one patient was deemed eligible for DTM, however, during the 8-month regional trial of Project Synergy (recruitment rate = 1/500,000 across the region). Instead of an unproven DTM model, the proposed 'digital front door' to Australian mental healthcare should emphasise technology-enabled shared care (general practitioners and mental health professionals) for the treatment of moderate-to-severe illness.

Population pharmacokinetics of a novel PCSK9 antisense oligonucleotide

AIMS

The aim of this study was to characterize the population pharmacokinetics of AZD8233, an antisense oligonucleotide (ASO) that targets the PCSK9 transcript to reduce hepatocyte PCSK9 protein production and plasma levels. AZD8233 utilizes generation 2.5 S-constrained ethyl motif (cET) chemistry and is conjugated to a triantennary N-acetylgalactosamine (GalNAc3) ligand for targeted hepatocyte uptake.

METHODS

A non-linear mixed-effect modelling approach utilizing NONMEM software was applied to AZD8233 concentration-time data from 3416 samples in 219 participants from four phase 1-2 studies, one in healthy volunteers (NCT03593785) and three in patients with dyslipidaemia (NCT04155645, NCT04641299 and NCT04823611).

RESULTS

The final model described the AZD8233 plasma concentration-time profile from four phase 1-2 studies in healthy volunteers or participants with dyslipidaemia, covering a dose range of 4 to 120 mg. The pharmacokinetics of AZD8233 were adequately described by a two-compartment model with first-order absorption. The supra-proportional increase in maximum plasma concentration (Cmax ) across the observed dose range was described by non-linear Michaelis-Menten elimination (maximum elimination rate, 9.9 mg/h [12% relative standard error]; concentration yielding half-maximal elimination rate, 4.8 mg/L [18% relative standard error]). Body weight, sex, estimated glomerular filtration rate and disease status (healthy participant vs. patient with dyslipidaemia) were identified as factors affecting exposure to AZD8233.

CONCLUSIONS

Covariate analysis showed body weight to be the main factor affecting exposure to AZD8233, which largely explained the higher Cmax observed in the Asian population relative to non-Asians.

Decoupled optimal control of 3D biped for human voluntary motion

The sit-to-stand (STS) model from a biomechanical point of view is an enormously important subject, with motor controls simulating human intended behavior. Physiological motion-based biomechanical research is important for designing whole-body prosthetics and understanding physical disabilities. The control strategies for biomechanical models can effectively synergize with the central nervous system (CNS) to facilitate the desired movements of individuals with neurological disabilities. In this study, we present our novel 3D biped model by decoupling it into healthy and neurologically deficient joints. The developed 8-segment model (i.e., 2× feet, 2× shanks, 2× thighs, 1× pelvic, and 1× Head Arm Torso (HAT) segment) with 10 joints is decoupled into 6 healthy joints and 4 deficient joints. This decoupling mimics stroke patients or subjects with neuromuscular deficiency. This novel decoupling establishes through asymmetrical torques in frontal and sagittal plane joints on a bipedal design with one foot fixed and the other a sliding tilt joint. In this design, two decoupled controllers collaborate to stabilize the nonlinear model for biped STS transfer. Utilizing the xml files from SOLIDWORKS, the model is linearized in SIMSCAPE / SIMULINK. We further imply the Linear Quadratic Regulator (LQR) optimal controller design in MATLAB / SIMULINK for torques in both the sagittal and frontal planes, respectively, for six healthy and four deficient joints. We also comprehend the forward thrust velocity controls to pragmatically model the STS of stroke patients. This decoupling enhanced the overall stability of the system and simulated more relevant angular and velocity profiles for neurologically deficient substances.

ChatGPT in pharmacometrics? Potential opportunities and limitations

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.

Combined translational pharmacometrics approach to support the design and conduct of the first-in-human study of DWP16001

AIMS

The objective of this study was to characterize the pharmacokinetics (PK)/pharmacodynamics (PD) of DWP16001, a novel sodium-glucose cotransporter 2 inhibitor, and predict efficacious doses for the first-in-human study using various translational approaches.

METHODS

A mechanistic PK/PD model was developed for DWP16001 using nonlinear mixed-effect modelling to describe animal PK/PD properties. Using allometry and in silico physiologically based equations, human PK parameters were predicted. Human PD parameters were scaled by applying interspecies difference and in vitro drug-specific factors. Human parameters were refined using early clinical data. Model-predicted PK and PD outcomes were compared to observations before and after parameter refinement.

RESULTS

The PK/PD model of DWP16001 was developed using a 2-compartment model with first-order absorption and indirect response. Efficacious doses of 0.3 and 2 mg of DWP16001 were predicted using human half-maximal inhibitory concentration values translated from Zucker Diabetic Fatty rats and normal rats, respectively. After parameter refinement, doses of 0.2 and 1 mg were predicted to be efficacious for each disease model, which improved the prediction results to within a 1.2-fold difference between the model prediction and observation.

CONCLUSIONS

This study predicted efficacious human doses of DWP16001 using population PK/PD modelling and a combined translational pharmacometrics approach. Early clinical data allowed the methods used to translate in vitro and in vivo findings to clinical PK/PD values for DWP16001 to be optimized. This study has shown that a refinement step can be readily applied to improve model prediction and further support the study design and conduct of a first-in-human study.

A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers

The muscle spindle is an essential proprioceptor, significantly involved in sensing limb position and movement. Although biological spindle models exist for years, the gold-standard for motor control in biomechanics are still sensors built of homogenized spindle output models due to their simpler combination with neuro-musculoskeletal models. Aiming to improve biomechanical simulations, this work establishes a more physiological model of the muscle spindle, aligned to the advantage of easy integration into large-scale musculoskeletal models. We implemented four variations of a spindle model in Matlab/Simulink®: the Mileusnic et al. (2006) model, Mileusnic model without mass, our enhanced Hill-type model, and our enhanced Hill-type model with parallel damping element (PDE). Different stretches in the intrafusal fibers were simulated in all model variations following the spindle afferent recorded in previous experiments in feline soleus muscle. Additionally, the enhanced Hill-type models had their parameters extensively optimized to match the experimental conditions, and the resulting model was validated against data from rats' triceps surae muscle. As result, the Mileusnic models present a better overall performance generating the afferent firings compared to the common data evaluated. However, the enhanced Hill-type model with PDE exhibits a more stable performance than the original Mileusnic model, at the same time that presents a well-tuned Hill-type model as muscle spindle fibers, and also accounts for real sarcomere force-length and force-velocity aspects. Finally, our activation dynamics is similar to the one applied to Hill-type model for extrafusal fibers, making our proposed model more easily integrated in multi-body simulations.

Population pharmacokinetic analysis of doravirine in real-world people with HIV

AIMS

The pharmacokinetics of doravirine has been studied in clinical trials but not in real-world settings. Our study aims to characterize and identify factors influencing doravirine (a CYP3A4 substrate) pharmacokinetics in real-world people with HIV (PWH).

METHODS

A total of 174 doravirine concentrations measured in 146 PWH followed up in the therapeutic drug monitoring (TDM) program at the University Hospital of Lausanne (Switzerland) between 2019 and 2023 were included in the analysis. Demographic data, clinical information and comedications were recorded during the routine SHCS visits (every 3-6 months). Population pharmacokinetic analysis and Monte Carlo simulations to investigate the clinical significance of the covariates retained in the final model were performed using NONMEM.

RESULTS

A one-compartment model with first-order absorption and linear elimination best described doravirine pharmacokinetics. Potent CYP3A4 inhibitors and, to a lesser extent age, were the only tested covariates to significantly impact doravirine clearance (CL). Potent CYP3A4 inhibitors reduced CL by 50%, and a 30% decrease in CL was observed in an 80-year-old compared with a 55-year-old PWH. The effect of potent CYP3A4 inhibitors was prominent, explaining 59% of between-subject variability in CL. Model-based simulations predicted 2.8-fold and 1.6-fold increases in median steady-state trough and maximum doravirine concentrations, respectively, when a potent CYP3A4 inhibitor was co-administered.

CONCLUSIONS

Our findings show that potent CYP3A4 inhibitors and age influence doravirine pharmacokinetics. However, given the good tolerability of doravirine, dosing adjustment of doravirine is probably not mandatory in those situations. TDM remains useful essentially in specific clinical situations, such as hepatic impairment, suspected nonadherence or pregnancy.

Non-compartmental and population pharmacokinetic analysis of dapsone in healthy NIGERIANS: A pilot study

Dapsone is employed for both non-dermatological and dermatological indications but with non-existent population pharmacokinetics (popPK) data in Nigerians. This study was therefore designed to develop a popPK model in Nigerians. Non-compartmental analysis and nonlinear mixed effects modelling were utilized for data analysis. Eleven participants administered 50 mg dapsone tablet were included in the analysis. Derived pharmacokinetic parameters were: Cmax  = 1.16 ± 0.32 μg/mL, Tmax  = 3.77 ± 2.40 h, and t1/2z  = 30.23 ± 11.76 h. PopPK model parameter estimates with inter-individual variability were Tlag = 0.40 h (10.0%, fixed); ka  = 1.78 h-1 (75.9%); V/F = 89.25 L (21.6%); and Cl/F = 1.32 Lh-1 (27.7%). Sex was significantly associated with Cl/F, and body weight with V/F. Best popPK model was one-compartment with lag time, and first-order absorption and elimination. Sex and body weight significantly influenced the clearance and distribution volume of dapsone respectively.

Predictive Potential of Cmax Bioequivalence in Pilot Bioavailability/Bioequivalence Studies, through the Alternative ƒ2 Similarity Factor Method

Pilot bioavailability/bioequivalence (BA/BE) studies are downsized trials that can be conducted prior to the definitive pivotal trial. In these trials, 12 to 18 subjects are usually enrolled, although, in principle, a sample size is not formally calculated. In a previous work, authors recommended the use of an alternative approach to the average bioequivalence methodology to evaluate pilot studies' data, using the geometric mean (Gmean) ƒ2 factor with a cut off of 35, which has shown to be an appropriate method to assess the potential bioequivalence for the maximum observed concentration (Cmax) metric under the assumptions of a true Test-to-Reference Geometric Mean Ratio (GMR) of 100% and an inter-occasion variability (IOV) in the range of 10% to 45%. In this work, the authors evaluated the proposed ƒ2 factor in comparison with the standard average bioequivalence in more extreme scenarios, using a true GMR of 90% or 111% for truly bioequivalent formulations, and 80% or 125% for truly bioinequivalent formulations, in order to better derive conclusions on the potential of this analysis method. Several scenarios of pilot BA/BE crossover studies were simulated through population pharmacokinetic modelling, accounting for different IOV levels. A redefined decision tree is proposed, suggesting a fixed sample size of 20 subjects for pilot studies in the case of intra-subject coefficient of variation (ISCV%) > 20% or unknown variability, and suggesting the assessment of study results through the average bioequivalence analysis, and additionally through Gmean ƒ2 factor method in the case of the 90% confidence interval (CI) for GMR is outside the regulatory acceptance bioequivalence interval of [80.00-125.00]%. Using this alternative approach, the certainty levels to proceed with pivotal studies, depending on Gmean ƒ2 values and variability scenarios tested (20-60% IOV), were assessed, which is expected to be helpful in terms of the decision to proceed with pivotal bioequivalence studies.

A Comparative Evaluation of Desoximetasone Cream and Ointment Formulations Using Experiments and In Silico Modeling

The administration of therapeutic drugs through dermal routes, such as creams and ointments, has emerged as an increasingly popular alternative to traditional delivery methods, such as tablets and injections. In the context of drug development, it is crucial to identify the optimal doses and delivery routes that ensure successful outcomes. Physiologically based pharmacokinetic (PBPK) models have been proposed to simulate drug delivery and optimize drug formulations, but the calibration of these models is challenging due to the multitude of variables involved and limited experimental data. One significant research gap that this article addresses is the need for more efficient and accurate methods for calibrating PBPK models for dermal drug delivery. This manuscript presents a novel approach and an integrated dermal drug delivery model to address this gap that leverages virtual in vitro release (IVRT) and permeation (IVPT) testing data to optimize mechanistic models. The proposed approach was demonstrated through a study involving Desoximetasone cream and ointment formulations, where the release kinetics and permeation profiles of Desoximetasone were determined experimentally, and a computational model was created to simulate the results. The experimental studies showed that, even though the cumulative permeation of Desoximetasone at the end of the permeation study was comparable, there was a significant difference seen in the lag time in the permeation of Desoximetasone between the cream and ointment. Additionally, there was a significant difference seen in the amount of Desoximetasone permeated through human cadaver skin at early time points when the cream and ointment were compared. The computational model was optimized and validated, suggesting that this approach has the potential to bridge the existing research gap by improving the accuracy and efficiency of drug development processes. The model results show a good fit between the experimental data and model predictions. During the model optimization process, it became evident that there was variability in both the permeability and the partition coefficient within the stratum corneum. This variability had a significant and noteworthy influence on the overall performance of the model, especially when it came to its capacity to differentiate between cream and ointment formulations. Leveraging virtual models significantly aids the comprehension of drug release and permeation, mitigating the demanding data requirements. The use of virtual IVRT and IVPT data can accelerate the calibration of PBPK models, streamline the selection of the appropriate doses, and optimize drug delivery. Moreover, this novel approach could potentially reduce the time and resources involved in drug development, thus making it more cost-effective and efficient.

Effect of stress on the dissolution/crystallization of apatite in aqueous solution: a thermochemical equilibrium study

Bone mineralization is critical to maintaining tissue mechanical function. The application of mechanical stress via exercise promotes bone mineralization via cellular mechanotransduction and increased fluid transport through the collagen matrix. However, due to its complex composition and ability to exchange ions with the surrounding body fluids, bone mineral composition and crystallization is also expected to respond to stress. Here, a combination of data from materials simulations, namely density functional theory and molecular dynamics, and experimental studies were input into an equilibrium thermodynamic model of bone apatite under stress in an aqueous solution based on the theory of thermochemical equilibrium of stressed solids. The model indicated that increasing uniaxial stress induced mineral crystallization. This was accompanied by a decrease in calcium and carbonate integration into the apatite solid. These results suggest that weight-bearing exercises can increase tissue mineralization via interactions between bone mineral and body fluid independent of cell and matrix behaviours, thus providing another mechanism by which exercise can improve bone health. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

Evaluation of treosulfan cumulative exposure in paediatric patients through population pharmacokinetics and dosing simulations

AIM

To investigate the pharmacokinetics (PK) of intravenous treosulfan in paediatric patients undergoing haematopoietic stem cell transplantation (HSCT) for a broad range of diseases and to explore the impact of different dosing regimens on treosulfan exposure (area under the concentration-time curve, AUC_0→∞ ) through dosing simulations.

METHODS

A prospective multicentre PK study was conducted using treosulfan concentration data (n = 423) collected from 53 children (median age 3.5, range 0.2-17.0 years) receiving three daily age-guided doses (10-14 g/m² ). Population PK modelling was performed using NONMEM software, utilising a stepwise forward selection backward elimination method and likelihood-ratio test for screening covariates to describe PK variability. Monte Carlo simulation was used to generate patient PK data for 10 000 virtual paediatric patients and cumulative AUC_0→∞ values were evaluated using age, body surface area (BSA) and model-based dosing regimens, targeting 4800 mg*h/L.

RESULTS

Treosulfan concentration data were described using a one-compartment PK model with first-order elimination. Population mean (95% CI) estimates for clearance (CL) and volume of distribution (V) were 16.3 (14.9-18.1) L/h and 41.9 (38.8-45.1) L, respectively. Allometrically scaled body weight was the best covariate descriptor for CL and V, and maturational age further explained variability in CL. Dosing simulations indicated that in young patient groups (<2 years), a model-based dosing regimen more accurately achieved the target AUC_0→∞ (58.3%) over the age (42.6%) and BSA-based (51.3%) regimens.

CONCLUSION

Treosulfan disposition was described through allometric body weight and maturational age descriptors. Model-informed dosing is recommended for patients under 2 years. Treosulfan PK parameters and AUC_0→∞ were not influenced by patient disease.

Use of In Vivo Imaging and Physiologically-Based Kinetic Modelling to Predict Hepatic Transporter Mediated Drug-Drug Interactions in Rats

Gadoxetate, a magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 and multidrug resistance-associated protein 2. Six drugs, with varying degrees of transporter inhibition, were used to assess gadoxetate dynamic contrast enhanced MRI biomarkers for transporter inhibition in rats. Prospective prediction of changes in gadoxetate systemic and liver AUC (AUCR), resulting from transporter modulation, were performed by physiologically-based pharmacokinetic (PBPK) modelling. A tracer-kinetic model was used to estimate rate constants for hepatic uptake (khe), and biliary excretion (kbh). The observed median fold-decreases in gadoxetate liver AUC were 3.8- and 1.5-fold for ciclosporin and rifampicin, respectively. Ketoconazole unexpectedly decreased systemic and liver gadoxetate AUCs; the remaining drugs investigated (asunaprevir, bosentan, and pioglitazone) caused marginal changes. Ciclosporin decreased gadoxetate khe and kbh by 3.78 and 0.09 mL/min/mL, while decreases for rifampicin were 7.20 and 0.07 mL/min/mL, respectively. The relative decrease in khe (e.g., 96% for ciclosporin) was similar to PBPK-predicted inhibition of uptake (97-98%). PBPK modelling correctly predicted changes in gadoxetate systemic AUCR, whereas underprediction of decreases in liver AUCs was evident. The current study illustrates the modelling framework and integration of liver imaging data, PBPK, and tracer-kinetic models for prospective quantification of hepatic transporter-mediated DDI in humans.

Population pharmacokinetics and dosing regimen optimization of levetiracetam in epilepsy during pregnancy

AIMS

The pharmacokinetics of levetiracetam (LEV) significantly changed during pregnancy. It is a great challenge to predict the adjusted doses of LEV to reach the preconception target concentrations. This study aimed to establish a population pharmacokinetic model of LEV in women with epilepsy (WWE) during pregnancy to analyse the factors of pharmacokinetic variability and to develop a model-based individualized dosing regimen.

METHODS

A total of 166 concentration-time points from 37 WWE during pregnancy treated with LEV were collected to analyse LEV pharmacokinetics with nonlinear mixed-effects modelling. The dosing regimen was optimized by Monte Carlo simulations based on the final model.

RESULTS

The LEV pharmacokinetics in pregnant WWE were best described by a 1-compartment model of first-order absorption and elimination. The population typical value of apparent clearance (CL/F) in the final model was estimated to be 3.82 L/h (95% confidence interval 3.283-4.357 L/h) with a relative standard error of 7.2%. Both total body weight (TBW) and trimester of pregnancy were significantly associated with LEV-CL/F during pregnancy; LEV-CL/F increased by 42.72% when TBW increased from 55 to 65 kg from the first trimester to the second trimester. Monte Carlo simulations showed that dosing regimens for LEV should be individualized based on the patient's TBW and trimester of pregnancy to maximize the likelihood of achieving the therapeutic range.

CONCLUSION

This first population pharmacokinetic study of LEV in WWE during pregnancy supports the use of a weight-based and pregnancy-based dosing regimen and can lay a foundation for further optimizing the individualized dosing regimens.

Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study

AIM

nlmixr offers first-order conditional estimation (FOCE), FOCE with interaction (FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin's pharmacokinetic data using nlmixr and investigated SAEM and FOCEi's performance with respect to bias and precision of parameter estimates, and robustness to initial estimates.

METHOD

Compartmental models were fitted. The final model was determined based on the objective function value and inspection of goodness-of-fit plots. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100 times and resultant changes evaluated.

RESULTS

The absorption kinetics of metformin depend significantly on food status. Under the fasted state, the first-order absorption into the central compartment was preceded by zero-order infusion into the depot compartment, whereas for the fed state, the absorption into the depot was instantaneous followed by first-order absorption from depot into the central compartment. The means of relative mean estimation error (rMEE) ( ME E SAEM ME E FOCEi ) and rRMSE ( RMS E SAEM RMS E FOCEi ) were 0.48 and 0.35, respectively. All parameter estimates given by SAEM appeared to be narrowly distributed and were close to the true value used for simulation. In contrast, the distribution of estimates from FOCEi were skewed and more biased. When initial estimates were perturbed, FOCEi estimates were more biased and imprecise.

DISCUSSION

nlmixr is reliable for NLMEM. SAEM was superior to FOCEi in terms of bias and precision, and more robust against initial estimate perturbations.

Physiologically Based Pharmacokinetic Model for Older Adults and Its Application in Geriatric Drug Research

Drug-related adverse events are higher in older patients than in non-older patients, increasing the risk of medication and reducing compliance. Aging is accompanied by a decline in physiological functions and metabolic weakening. Most tissues and organs undergo anatomical and physiological changes that may affect the pharmacokinetic (PK) and pharmacodynamic (PD) characteristics of drugs. Clinical trials are the gold standard for selecting appropriate dosing regimens. However, older patients are generally underrepresented in clinical trials, resulting in a lack of evidence for establishing an optimal dosing regimen for older adults. The physiologically based pharmacokinetic (PBPK) model is an effective approach to quantitatively describe the absorption, distribution, metabolism, and excretion of drugs in older adults by integrating physiological parameters, drug physicochemical properties, and preclinical or clinical PK data. The PBPK model can simulate the PK/PD characteristics of clinical drugs in different scenarios, ultimately compensating for inadequate clinical trial data in older adults, and is recommended by the Food and Drug Administration for clinical pharmacology studies in older adults. This review describes the effects of physiological changes on the PK/PD process in older adults and summarises the research progress of PBPK models. Future developments of PBPK models are also discussed, together with the application of PBPK models in older adults, aiming to assist the development of clinical study strategies in older adults.

Population pharmacokinetics of nadroparin for thromboprophylaxis in COVID-19 intensive care unit patients

AIMS

Nadroparin is administered to COVID-19 intensive care unit (ICU) patients as thromboprophylaxis. Despite existing population pharmacokinetic (PK) models for nadroparin in literature, the population PK of nadroparin in COVID-19 ICU patients is unknown. Moreover, optimal dosing regimens achieving anti-Xa target levels (0.3-0.7 IU/mL) are unknown. Therefore, a population PK analysis was conducted to investigate different dosing regimens of nadroparin in COVID-19 ICU patients.

METHODS

Anti-Xa levels (n = 280) from COVID-19 ICU patients (n = 65) receiving twice daily (BID) 5700 IU of subcutaneous nadroparin were collected to perform a population PK analysis with NONMEM v7.4.1. Using Monte Carlo simulations (n = 1000), predefined dosing regimens were evaluated.

RESULTS

A 1-compartment model with an absorption compartment adequately described the measured anti-Xa levels with interindividual variability estimated for clearance (CL). Inflammation parameters C-reactive protein, D-dimer and estimated glomerular filtration rate based on the Chronic Kidney Disease Epidemiology Collaboration equation allowed to explain the interindividual variability of CL. Moreover, CL was decreased in patients receiving corticosteroids (22.5%) and vasopressors (25.1%). Monte Carlo simulations demonstrated that 5700 IU BID was the most optimal dosing regimen of the simulated regimens for achieving prespecified steady-state t = 4 h anti-Xa levels with 56.7% on target (0.3-0.7 IU/mL).

CONCLUSION

In our study, clearance of nadroparin is associated with an increase in inflammation parameters, use of corticosteroids, vasopression and renal clearance in critically ill patients. Furthermore, of the simulated regimens, targeted anti-Xa levels were most adequately achieved with a dosing regimen of 5700 IU BID. Future studies are needed to elucidate the underlying mechanisms of found covariate relationships.

An algebraic framework for structured epidemic modelling

Pandemic management requires that scientists rapidly formulate and analyse epidemiological models in order to forecast the spread of disease and the effects of mitigation strategies. Scientists must modify existing models and create novel ones in light of new biological data and policy changes such as social distancing and vaccination. Traditional scientific modelling workflows detach the structure of a model-its submodels and their interactions-from its implementation in software. Consequently, incorporating local changes to model components may require global edits to the code base through a manual, time-intensive and error-prone process. We propose a compositional modelling framework that uses high-level algebraic structures to capture domain-specific scientific knowledge and bridge the gap between how scientists think about models and the code that implements them. These algebraic structures, grounded in applied category theory, simplify and expedite modelling tasks such as model specification, stratification, analysis and calibration. With their structure made explicit, models also become easier to communicate, criticize and refine in light of stakeholder feedback. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Amiodarone/N-desethylamiodarone population pharmacokinetics in pediatric patients

The population pharmacokinetics (PK) of amiodarone and its active metabolite, N-desethylamiodarone (DEA) were investigated in pediatric patients with arrhythmias, mainly supraventricular tachycardias. A total of 55 patients from the department of pediatric intensive care and pediatric cardiology at Necker Enfants-malades Hospital (Paris, France) provided 72 concentrations for both amiodarone and DEA following repeated oral or intravenous administration. Blood samples drawn for biological analyses were used for drug concentrations. Plasma amiodarone concentrations were measured by a liquid chromatography method coupled with mass spectrometry (LC-MS/MS) and the data were modelled using the software Monolix 2019R2. Parent pharmacokinetics was described with a two-compartment open model and the metabolite formation was connected to the central parent compartment. Parameter estimates scaled allometrically on body weight (normalized to 70 kg) were respectively (% relative standard errors or RSE) 6.32 (31%) and 7.14 L/h (26%) for elimination (CL) and intercompartmental clearances and 167 (31%) and 3930 (32%) L for V₁ and V₂ . Oral bioavailability was 0.362 (21.5%). The clearance between subject variability (ω, square root of the variance) was 0.462 (RSE 21%). The proportional residual variabilities were respectively 0.453 (RSE 13%) and 0.423 (RSE 12%) for amiodarone and DEA respectively. The terminal half-lives were 34 and 14.5 days for amiodarone and DEA respectively. A dosage schedule was established for 3 weight bands along 2 time periods. The high pharmacokinetic variability suggests that therapeutic drug monitoring (TDM) might be useful to improve individual efficacy and safety.

The influence of biological, epidemiological, and treatment factors on the establishment and spread of drug-resistant Plasmodium falciparum

The effectiveness of artemisinin-based combination therapies (ACTs) to treat Plasmodium falciparum malaria is threatened by resistance. The complex interplay between sources of selective pressure-treatment properties, biological factors, transmission intensity, and access to treatment-obscures understanding how, when, and why resistance establishes and spreads across different locations. We developed a disease modelling approach with emulator-based global sensitivity analysis to systematically quantify which of these factors drive establishment and spread of drug resistance. Drug resistance was more likely to evolve in low transmission settings due to the lower levels of (i) immunity and (ii) within-host competition between genotypes. Spread of parasites resistant to artemisinin partner drugs depended on the period of low drug concentration (known as the selection window). Spread of partial artemisinin resistance was slowed with prolonged parasite exposure to artemisinin derivatives and accelerated when the parasite was also resistant to the partner drug. Thus, to slow the spread of partial artemisinin resistance, molecular surveillance should be supported to detect resistance to partner drugs and to change ACTs accordingly. Furthermore, implementing more sustainable artemisinin-based therapies will require extending parasite exposure to artemisinin derivatives, and mitigating the selection windows of partner drugs, which could be achieved by including an additional long-acting drug.

Muscle mass affects paclitaxel systemic exposure and may inform personalized paclitaxel dosing

AIMS

Patients with low muscle mass have increased risk of paclitaxel-induced peripheral neuropathy, which is dependent on systemic paclitaxel exposure. Dose optimization may be feasible through the secondary use of radiologic data for body composition. The objective of this study was to interrogate morphomic parameters as predictors of paclitaxel pharmacokinetics to identify alternative dosing strategies that may improve treatment outcomes.

METHODS

This was a secondary analysis of female patients with breast cancer scheduled to receive 80 mg/m² weekly paclitaxel infusions. Paclitaxel was measured at the end of initial infusion to estimate maximum concentration (C_max ). Computed tomography (CT) scans were used to measure 29 body composition features for inclusion in pharmacokinetic modelling. Monte Carlo simulations were performed to identify infusion durations that limit the probability of exceeding C_max  > 2885 ng/mL, which was selected based on prior work linking this to an unacceptable risk of peripheral neuropathy.

RESULTS

Thirty-nine patients were included in the analysis. The optimal model was a two-compartment pharmacokinetic model with T11 skeletal muscle area as a covariate of paclitaxel volume of distribution (Vd). Simulations suggest that extending infusion of the standard paclitaxel dose from 1 hour to 2 and 3 hours in patients who have skeletal muscle area 4907-7080 mm² and <4907 mm² , respectively, would limit risk of C_max  > 2885 ng/mL to <50%, consequently reducing neuropathy, while marginally increasing overall systemic paclitaxel exposure.

CONCLUSION

Extending paclitaxel infusion duration in ~25% of patients who have low skeletal muscle area is predicted to reduce peripheral neuropathy while maintaining systemic exposure, suggesting that personalizing paclitaxel dosing based on body composition may improve treatment outcomes.

Experimental and Simulation Investigation of Nd Additions on As-Cast Microstructure and Precipitate Development in Mg-Nd System Alloys

The microstructure and precipitate evolution of as-cast Mg–Nd alloys with different contents of Nd was investigated via experimental and simulation methods. The research showed that the as-cast microstructure of Mg–Nd alloy consisted of α-Mg dendrites and the intermetallic phases. A metastable β phase precipitated, followed by α-Mg dendrites that could be confirmed as Mg₁₂Nd by X-ray diffraction (XRD) analysis. The amount of β-Mg₁₂Nd presented a rising trend with increasing Nd additions. In addition, the tertiary phase was also observed in as-cast Mg–Nd alloy when Nd content was greater than 3 wt.%, which precipitated from the oversaturated α-Mg matrix. The tertiary phase should be β₁-Mg₃Nd, which is also a metastable phase with a face-centered cubic lattice. However, it is a pity that the tertiary phase was not detected by the XRD technique. Moreover, an effective cellular automaton (CA) model was explored and applied to simulate the time-dependent α-Mg/β₁-Mg₃Nd eutectic growth. The simulated results of α-Mg/β₁-Mg₃Nd eutectic growth in Mg-3Nd presented that the growth of α-Mg dendrites was accompanied by the nucleation and growth of β₁-Mg₃Nd precipitates and eventually formed a eutectic structure. The eutectic morphologies for Mg–Nd system alloys with different Nd contents were also simulated using the proposed model, and the results revealed that α-Mg dendrite was a refinement, and the amount of α-Mg/β₁-Mg₃Nd eutectic was promoted, with increasing Nd content.

Joint modelling and simulation of M-protein dynamics and progression-free survival for alternative isatuximab dosing with pomalidomide/dexamethasone

AIMS

Addition of isatuximab (Isa) to pomalidomide/dexamethasone (Pd) significantly improved progression-free survival (PFS) in patients with relapsed/refractory multiple myeloma (RRMM). We aimed to characterize the relationship between serum M-protein kinetics and PFS in the phase 3 ICARIA-MM trial (NCT02990338), and to evaluate an alternative dosing regimen of Isa by simulation.

METHODS

Data from the ICARIA-MM trial comparing Isa 10 mg/kg weekly for 4 weeks then every 2 weeks (QW-Q2W) in combination with Pd versus Pd in 256 evaluable RRMM patients were used. A joint model of serum M-protein dynamics and PFS was developed. Trial simulations were then performed to evaluate whether efficacy is maintained after switching to a monthly dosing regimen.

RESULTS

The model identified instantaneous changes (slope) in serum M-protein as the best on-treatment predictor for PFS and baseline patient characteristics impacting serum M-protein kinetics (albumin and β2-microglobulin on baseline levels, non-IgG type on growth rate) and PFS (presence of plasmacytomas). Trial simulations demonstrated that switching to a monthly Isa regimen at 6 months would shorten median PFS by 2.3 weeks and induce 42.3% patients to progress earlier.

CONCLUSIONS

Trial simulations supported selection of the approved Isa 10 mg/kg QW-Q2W regimen and showed that switching to a monthly regimen after 6 months may reduce clinical benefit in the overall population. However, patients with good prognostic characteristics and with a stable, very good partial response may switch to a monthly regimen after 6 months without compromising the risk of disease progression. This hypothesis will be tested in a prospective clinical trial.

Evaluation of the drug-drug interaction potential of treosulfan using a physiologically-based pharmacokinetic modelling approach

AIMS

The aim of this work is the development of a mechanistic physiologically-based pharmacokinetic (PBPK) model using in vitro to in vivo extrapolation to conduct a drug-drug interaction (DDI) assessment of treosulfan against two cytochrome p450 (CYP) isoenzymes and P-glycoprotein (P-gp) substrates.

METHODS

A PBPK model for treosulfan was developed de novo based on literature and unpublished clinical data. The PBPK DDI analysis was conducted using the U.S. Food and Drug Administration (FDA) DDI index drugs (probe substrates) midazolam, omeprazole and digoxin for CYP3A4, CYP2C19 and P-gp, respectively. Qualified and documented PBPK models of the probe substrates have been adopted from an open-source online model database.

RESULTS

The PBPK model for treosulfan, based on both in vitro and in vivo data, was able to predict the plasma concentration-time profiles and exposure levels of treosulfan applied for a standard conditioning treatment. Medium and low potentials for DDI on CYP3A4 (maximum area under the concentration-time curve ratio (AUCR_max  = 2.23) and CYP2C19 (AUCR_max  = 1.6) were predicted, respectively, using probe substrates midazolam and omeprazole. Treosulfan was not predicted to cause a DDI on P-gp.

CONCLUSION

Medicinal products with a narrow therapeutic index (eg, digoxin) that are substrates for CYP3A4, CYP2C19 or P-gp should not be given during treatment with treosulfan. However, considering the comprehensive treosulfan-based conditioning treatment schedule and the respective pharmacokinetic properties of the concomitantly used drugs (eg, half-life), the potential for interaction on all evaluated mechanisms would be low (AUCR < 1.25), if concomitantly administered drugs are dosed either 2 hours before or 8 hours after the 2-hour intravenous infusion of treosulfan.

Dosing regimen optimisation for oseltamivir in immunocompromised paediatric patients with influenza: Extrapolation of efficacy

AIMS

To optimise the dosing regimen of oseltamivir for immunocompromised (IC) paediatric patients (<18 years) with influenza, we used an extrapolation approach alongside clinical data.

METHODS

Efficacy was extrapolated from adult IC patients to paediatric IC patients by leveraging existing efficacy, safety, pharmacokinetic (PK)/pharmacodynamic (PD), and disease-progression models of oseltamivir and oseltamivir carboxylate (OC). Data of IC paediatric patients from two studies (NV25719 and NV20234) were included in the population PK (n = 30), PK/PD analysis (n = 22) and disease modelling approach (n = 36). Simulations were performed to identify the optimal dosing regimen.

RESULTS

Clearance of oseltamivir (CL) and OC (CL_M ) were similar in IC and otherwise-healthy (OwH) patients <10 years, but decreased by 44.4% (95% CI: 26.8-62.0) and 49.1% (95% CI: 34.5-63.8), respectively, in IC patients aged 10-17 years versus OwH patients. There were no notable exposure-response relationships for any of the virologic PD analyses. Thus, no additional benefit was seen with oseltamivir carboxylate exposures higher than achieved with the conventional dose (75 mg twice daily, age- and weight-adjusted for children <13 years). The disease model illustrated that doses above the conventional oseltamivir dose had limited impact on viral kinetics in IC paediatric patients and a prolonged treatment duration of 10 days was favoured to limit potential viral rebound.

CONCLUSION

An oseltamivir dosage recommendation (conventional dose, twice daily for 10 days) was established in IC paediatric patients with influenza, based on extrapolation of efficacy from IC adults, leveraging population PK, PK/PD, and disease modelling, whilst taking resistance and safety data into account.

Comparison of Y-90 and Ho-166 Dosimetry Using Liver Phantom: A Monte Carlo Study

BACKGROUND

It is estimated that more than 1 million people are diagnosed with liver malignancy each year and one of the treatments is radioembolization with Y-90 and Ho-166. <P> Objective: The aim of this study is to calculate the absorbed doses caused by Y-90 and Ho-166 in tumor and liver parenchyma using a phantom via Monte Carlo method. <P> Methods: A liver model phantom including a tumor imitation of sphere (r =1.5cm) was defined in GATE. The total activity of 40 mCi Y-90 and Ho-166 was prescribed into tumor imitation as source and 2x2x2 mm3 voxel-sized DoseActors were identified at 30 locations. The simulation, performed to calculate the absorbed doses left by particles during 1 second for Y-90 and Ho-166, was run for a total of 10 days and 11 days, respectively. Total doses were calculated by taking the doses occurring in 1 second as a reference. <P> Results: The maximum absorbed doses were found to be 2.334E+03±1.576E+01 Gy for Y-90 and 7.006E+02±6.013E-01 Gy for Ho-166 at the center of tumor imitation. The minimum absorbed doses were found to be 2.133E-03±1.883E-01 Gy for Y-90 and 1.152E-02±1.036E-03 Gy for Ho-166 at the farthest location from source. The mean absorbed doses in tumor imitation were found to be 1.50E+03±1.36E+00 Gy and 4.58E+02±4.75E-01 Gy for Y-90 and Ho-166, respectively. And, the mean absorbed doses in normal parenchymal tissue were found to be2.07E+01±9.58E-02 Gy and 3.79E+00±2.63E-02 Gy for Y-90 and Ho-166, respectively. <P> Conclusion: Based on the results, Ho-166 is a good alternative to Y-90 according to dosimetric evaluation.

Assessment of the safe and efficacious dose of the selective progesterone receptor modulator vilaprisan for the treatment of patients with uterine fibroids by exposure-response modelling and simulation

AIMS

We report population pharmacokinetic (popPK) and exposure-response (E-R) analyses for efficacy (induced amenorrhoea [IA]) and safety (unbound oestradiol [E2] concentrations) of the selective progesterone receptor modulator vilaprisan. Results were used to inform the dose for the Phase 3 programme in patients with uterine fibroids.

METHODS

A popPK model was developed using data from Phase 1 and 2 studies (including ASTEROID 1 and 2). The relationship between vilaprisan exposure (steady-state AUC) and IA after oral administration of 0.5, 1, 2 or 4 mg/day over 3 months was analysed in ASTEROID 1 using logistic regression and qualified in ASTEROID 2 by comparing simulated and observed probability for IA after 2 mg/day. The exposure-E2 relationship was analysed visually.

RESULTS

Vilaprisan clearance was 22.7% lower in obese vs non-obese patients. The E-R relationship for IA in ASTEROID 1 was steep and consistent with ASTEROID 2, with a maximum probability (P_max ) of 59% (95% CI: 49-68%). The exposure at which 50% of P_max is obtained was 36.9 μg*h/L (95% CI: 27.7-48.7 μg*h/L). Simulations showed that 36% of the patients will be below 90% of P_max for IA after 1 mg/day compared to 2% after 2 mg/day. E2 levels tended to decrease with increasing exposure. While E2 levels remained largely within the physiologic follicular phase range, the clinical relevance of this decrease will be evaluated in long-term studies.

CONCLUSIONS

A 2 mg/day dose was selected for Phase 3 as E-R analyses show this dose results in a close to maximum probability for IA, without any safety concerns noted.

Applicability of the Cox-Merz Rule to High-Density Polyethylene Materials with Various Molecular Masses

The Cox-Merz rule is an empirical relationship that is commonly used in science and industry to determine shear viscosity on the basis of an oscillatory rheometry test. However, it does not apply to all polymer melts. Rheological data are of major importance in the design and dimensioning of polymer-processing equipment. In this work, we investigated whether the Cox-Merz rule is suitable for determining the shear-rate-dependent viscosity of several commercially available high-density polyethylene (HDPE) pipe grades with various molecular masses. We compared the results of parallel-plate oscillatory shear rheometry using the Cox-Merz empirical relation with those of high-pressure capillary and extrusion rheometry. To assess the validity of these techniques, we used the shear viscosities obtained by these methods to numerically simulate the pressure drop of a pipe head and compared the results to experimental measurements. We found that, for the HDPE grades tested, the viscosity data based on capillary pressure flow of the high molecular weight HDPE describes the pressure drop inside the pipe head significantly better than do data based on parallel-plate rheometry applying the Cox-Merz rule. For the lower molecular weight HDPE, both measurement techniques are in good accordance. Hence, we conclude that, while the Cox-Merz relationship is applicable to lower-molecular HDPE grades, it does not apply to certain HDPE grades with high molecular weight.

Food constituent- and herb-drug interactions in oncology: Influence of quantitative modelling on Drug labelling

AIMS

Herbal products, spices and/or fruits are perceived as inherently healthy; for instance, St. John's wort (SJW) is marketed as a natural antidepressant and patients often self-administer it concomitantly with oncology medications. However, food constituents/herbs can interfere with drug pharmacokinetics, with risk of altering pharmacodynamics and efficacy. The objective of this work was to develop a strategy to prioritize herb- or food constituent-drug interactions (FC-DIs) to better assess oncology drug clinical risk.

METHODS

Physiologically based pharmacokinetic (PBPK) models were developed by integrating in vitro parameters with the clinical pharmacokinetics of food constituents in grapefruit juice (bergamottin), turmeric (curcumin) or SJW (hyperforin). Perpetrator files were linked to verified victim PBPK models through appropriate interaction mechanisms (cytochrome P450 3A, breast cancer resistance protein, P-glycoprotein) and applied in prospective PBPK simulations to inform the likelihood and magnitude of changes in exposure to osimertinib, olaparib or acalabrutinib.

RESULTS

Reported FC-DIs with oncology drugs were well recovered, with absolute average fold error values of 1.10 (bergamottin), 1.05 (curcumin) and 1.01 (hyperforin). Prospective simulations with grapefruit juice and turmeric showed clinically minor to insignificant changes in exposure (<1.50-fold) to acalabrutinib, osimertinib and olaparib, but predicted 1.57-fold FC-DI risk between acalabrutinib and curcumin. Moderate DDI risk was expected when acalabrutinib, osimertinib or olaparib were dosed with SJW.

CONCLUSIONS

A model-informed decision tree based on mechanistic understanding of transporter and/or enzyme-mediated FC-DI is proposed based on bergamottin, curcumin and hyperforin FC-DI clinical data. Adopting this quantitative modelling approach should streamline herbal product safety assessments, assist in FC-DI management, and ultimately promote safe clinical use of oncology drugs.

Machine learning in pharmacometrics: Opportunities and challenges

The explosive growth in medical devices, imaging and diagnostics, computing, and communication and information technologies in drug development and healthcare has created an ever-expanding data landscape that the pharmacometrics (PMX) research community must now traverse. The tools of machine learning (ML) have emerged as a powerful computational approach in other data-rich disciplines but its effective utilization in the pharmaceutical sciences and PMX modelling is in its infancy. ML-based methods can complement PMX modelling by enabling the information in diverse sources of big data, e.g. population-based public databases and disease-specific clinical registries, to be harnessed because they are capable of efficiently identifying salient variables associated with outcomes and delineating their interdependencies. ML algorithms are computationally efficient, have strong predictive capabilities and can enable learning in the big data setting. ML algorithms can be viewed as providing a computational bridge from big data to complement PMX modelling. This review provides an overview of the strengths and weaknesses of ML approaches vis-à-vis population methods, assesses current research into ML applications in the pharmaceutical sciences and provides perspective for potential opportunities and strategies for the successful integration and utilization of ML in PMX.

Population pharmacokinetic modelling and simulation of tafamidis in healthy subjects and patients with transthyretin amyloidosis

AIMS

Since the first approval for transthyretin amyloid polyneuropathy patients, new formulations and different strength of tafamidis have been developed and tested in a different population (transthyretin amyloid cardiomyopathy). The objective of this analysis was to develop a unified population pharmacokinetic (PK) model of tafamidis, which can describe the PK of various different formulations in healthy subjects as well as patients with TTR amyloidosis, and to understand effects of intrinsic and extrinsic factors on the PK variability.

METHODS

Pooled data from 23 clinical studies (17 Phase 1 and 6 Phase 2/3 studies) were used for the analysis. The plasma concentration-time data were analysed using a nonlinear mixed effects modelling methodology. Covariate analysis was performed using a stepwise covariate model building procedure.

RESULTS

The final model was a 2-compartment model with first-order absorption and elimination coupled with an absorption lag time for nonsolution formations. Body weight, food and tafamidis formulations were incorporated as structural covariates on PK parameters. Covariate analysis further identified age ≥65 years (14.5% decrease) and moderate hepatic impairment effects (57.6% increase) on apparent clearance and transthyretin amyloid polyneuropathy effect (17.3% decrease) on F. However, model-based clinical trial simulation results indicated that tafamidis steady-state exposure changes were not clinically meaningful under the tested conditions.

CONCLUSIONS

The unified population PK model of tafamidis was developed based on 23 studies. Subsequent clinical trial simulations indicated that no significant changes in tafamidis exposure necessitating a dose modification are expected due to either extrinsic or intrinsic factors. The model was used to support labelling statements for dose recommendations in special populations.

Dielectric Elastomer Actuator Driven Soft Robotic Structures With Bioinspired Skeletal and Muscular Reinforcement

Natural motion types found in skeletal and muscular systems of vertebrate animals inspire researchers to transfer this ability into engineered motion, which is highly desired in robotic systems. Dielectric elastomer actuators (DEAs) have shown promising capabilities as artificial muscles for driving such structures, as they are soft, lightweight, and can generate large strokes. For maximum performance, dielectric elastomer membranes need to be sufficiently pre-stretched. This fact is challenging, because it is difficult to integrate pre-stretched membranes into entirely soft systems, since the stored strain energy can significantly deform soft elements. Here, we present a soft robotic structure, possessing a bioinspired skeleton integrated into a soft body element, driven by an antagonistic pair of DEA artificial muscles, that enable the robot bending. In its equilibrium state, the setup maintains optimum isotropic pre-stretch. The robot itself has a length of 60 mm and is based on a flexible silicone body, possessing embedded transverse 3D printed struts. These rigid bone-like elements lead to an anisotropic bending stiffness, which only allows bending in one plane while maintaining the DEA's necessary pre-stretch in the other planes. The bones, therefore, define the degrees of freedom and stabilize the system. The DEAs are manufactured by aerosol deposition of a carbon-silicone-composite ink onto a stretchable membrane that is heat cured. Afterwards, the actuators are bonded to the top and bottom of the silicone body. The robotic structure shows large and defined bimorph bending curvature and operates in static as well as dynamic motion. Our experiments describe the influence of membrane pre-stretch and varied stiffness of the silicone body on the static and dynamic bending displacement, resonance frequencies and blocking forces. We also present an analytical model based on the Classical Laminate Theory for the identification of the main influencing parameters. Due to the simple design and processing, our new concept of a bioinspired DEA based robotic structure, with skeletal and muscular reinforcement, offers a wide range of robotic application.

Population pharmacokinetics of ganciclovir and valganciclovir in paediatric solid organ and stem cell transplant recipients

AIMS

Ganciclovir (GCV) and its prodrug valganciclovir (VGCV) are first-line agents to prevent and treat cytomegalovirus in transplant recipients. There is high pharmacokinetic (PK) interindividual variability and PK data are scarce, especially in paediatric stem cell transplant (SCT) recipients. We sought to determine the optimal GCV and VGCV dosing in transplanted children.

METHODS

We conducted a single-centre retrospective population PK (POPPK) study of IV GCV and enteral VGCV in paediatric solid organ transplant (SOT) and SCT recipients. We included children who were transplanted and had available plasma GCV concentrations, done per standard of care. POPPK analysis was performed using a nonlinear mixed effects modelling approach with NONMEM. Optimal dosing was determined based on the achievement of the surrogate efficacy target: GCV 24 h area under the concentration-time curve (AUC_0-24h ) of 40-60 mg.h.L^-1 .

RESULTS

Fifty children with a median [range] age of 7.5 years [0.5-17.4] contributed 580 PK samples. A two-compartment model with first-order absorption with a lag time and first-order elimination fit the data well. Creatinine clearance and body weight (WT) were significant covariates for GCV clearance (CL); and WT for the volumes of distribution. IV GCV 15-20 mg.kg^-1 .day^-1 divided every 12 hours achieved the highest probability of target achievement (PTA) (33.0-33.8%). Enteral VGCV 30 and 40 mg.kg^-1 .day^-1 divided every 12 hours in children 0-<6 years, and 6-18 years, respectively, achieved the highest PTA (29.1-33.0%).

CONCLUSION

This is the first POPPK model developed in children with either SOT or SCT. Concentration target achievement was low, suggesting a potential benefit for therapeutic drug monitoring to ensure optimal exposure.

Pharmacometric analyses to characterize the effect of CSL112 on apolipoprotein A-I and cholesterol efflux capacity in acute myocardial infarction patients

AIMS

To characterize relationships between apolipoprotein A-I (apoA-I) exposure and cholesterol efflux capacity (CEC) and covariate effects following CSL112 (apoA-I [human]) administration in an integrated population including acute myocardial infarction (AMI) patients.

METHODS

A pharmacometric analysis utilized data from seven clinical trials, including patients with AMI, subjects with renal impairment and healthy subjects. A population pharmacokinetic (PK) analysis was performed to relate CSL112 doses to changes in apoA-I plasma concentrations. Covariate analysis was conducted to identify sources of variability in apoA-I exposure. Exposure-response modeling was conducted to describe the relationship between apoA-I exposure and total or ATP binding cassette transporter A1-(ABCA1)-dependent CEC and to identify clinical predictors of CEC.

RESULTS

A two-compartment model described apoA-I PK. ApoA-I clearance was slightly lower in subjects with AMI, whereas baseline apoA-I was marginally higher in female and Japanese subjects. Covariate effects on apoA-I exposure were in the order of 10% and thus not clinically relevant. The relationships between apoA-I exposure and CECs were described by nonlinear models. Simulations showed CEC elevation resulting from apoA-I exposure increment was comparable in AMI and non-AMI subjects; no covariate had clinically meaningful effects on CEC. Simulations also demonstrated that CEC in patients with AMI post 6 g CSL112 dosing was substantially elevated compared to placebo and lower dose levels.

CONCLUSIONS

The model-based exposure-response analysis demonstrated, irrespective of body weight, sex and race, that fixed 6 g CSL112 dosing causes a desired CEC elevation, which may benefit AMI patients by potentially reducing early recurrent cardiovascular event risk.

Dosing of factor VIII concentrate by ideal body weight is more accurate in overweight and obese haemophilia A patients

Aims

Under‐ and, especially, overdosing of replacement therapy in haemophilia A patients may be prevented by application of other morphometric variables than body weight (BW) to dose factor VIII (FVIII) concentrates. Therefore, we aimed to investigate which morphometric variables best describe interindividual variability (IIV) of FVIII concentrate pharmacokinetic (PK) parameters.

Methods

PK profiling was performed by measuring 3 FVIII levels after a standardized dose of 50 IU kg⁻¹ FVIII concentrate. A population PK model was constructed, in which IIV for clearance (CL) and central volume of distribution (V1) was quantified. Relationships between CL, V1 and 5 morphometric variables (BW, ideal BW [IBW], lean BW, adjusted BW, and body mass index [BMI]) were evaluated in normal weight (BMI < 25 kg m⁻²), overweight (BMI 25–30 kg m⁻²) and obese haemophilia A patients (BMI > 30 kg m⁻²).

Results

In total, 57 haemophilia A patients (FVIII≤0.05 IU mL⁻¹) were included with median BW of 83 kg (range: 53–133) and median age of 48 years (range: 18–77). IBW best explained observed variability between patients, as IIV for CL and V1 was reduced from 45.1 to 37.6 and 26.% to 14.1%, respectively. CL, V1 and half‐life were similar for all BMI categories. The national recommended dosing schedule did not result in adequate trough levels, both in case of dosing based on BW and IBW. However, dosing based on IBW prevented unnecessary high FVIII peaks.

Conclusion

IBW is the most suitable morphometric variable to explain interindividual FVIII PK variability and is more appropriate to dose overweight and obese patients.

Assessing via Simulation the Operating Characteristics of the WHO Scale for COVID-19 Endpoints

Many clinical trials of treatments for patients hospitalised for COVID-19 use an ordinal scale recommended by the World Heath Organisation. The scale represents intensity of medical intervention, with higher scores for interventions more burdensome for the patient, and highest score for death. There is uncertainty about use of this ordinal scale in testing hypotheses. With the objective of assessing the power and Type I error of potential endpoints and analyses based on the ordinal scale, trajectories of the score over 28 days were simulated for scenarios based closely on results of two trials recently published. The simulation used transition probabilities for the ordinal scale over time. No one endpoint was optimal across scenarios, but a ranked measure of trajectory fared moderately well in all scenarios. Type I error was controlled at close to the nominal level for all endpoints. Because not tied to a particular population with regard to baseline severity, the use of transition probabilities allows plausible assessment of endpoints in populations with configurations of baseline score for which data is not yet published, provided some data on the relevant transition probabilities are available. The results could support experts in the choice of endpoint based on the ordinal scale.

A minimal model to describe short-term haemodynamic changes of the cardiovascular system

AIMS

Current pharmacokinetic-pharmacodynamic models describing the haemodynamic changes often do not include necessary feedback mechanisms. These models provide adequate description of current data but may fail to adequately extrapolate to additional scenarios. This study aims to develop a minimal model to describe the short-term changes of haemodynamics that can be used as the basis for model development by future researchers.

METHODS

A minimal haemodynamic model was developed to describe the influence of drugs on blood pressure components. The model structure was defined based on known mechanisms and previously published models. The model was evaluated under 2 different simulation settings. The model parameters were calibrated to describe (without estimation) the haemodynamics of 2 antihypertensive drugs with data extracted from the literature. Structural identifiability analysis was done using various combinations of the observed variable.

RESULTS

The proposed model structure includes mean arterial pressure, heart rate and stroke volume and is composed of 4 states described by differential equations. Model evaluation showed flexibility in describing the haemodynamics at different target perturbations. Overlay plots of model predictions and literature data showed a good description without data fitting. The structural identifiability analysis revealed all model parameters and initial conditions were identifiable only when heart rate, mean arterial pressure and cardiac output were measured together.

CONCLUSIONS

A minimal model of the haemodynamic system was developed and evaluated. The model accounted for short-term haemodynamic feedback processes. We propose that this model can be used as the basis for future pharmacometric analyses of drugs acting on the haemodynamic system.

Pharmacologic effects of oseltamivir in immunocompromised adult patients as assessed by population PK/PD analysis and drug-disease modelling for dosing regimen optimization

Aim

Pharmacologic effects were analysed to determine a dose recommendation for oseltamivir in immunocompromised (IC) adults with influenza.

Methods

Quantitative clinical pharmacology methods were applied to data from 160 adult IC patients (aged 18‐78 years) from two studies (NV20234, 150 patients; NV25118, 10 patients) who received oseltamivir 75‐200 mg twice daily for up to 10 days. An established population‐pharmacokinetic (PK) model with additional effects on oseltamivir and oseltamivir carboxylate (OC) clearance described the PK characteristics of oseltamivir in IC patients versus otherwise healthy (OwH) patients from previous clinical trials. Estimated PK parameters were used to evaluate exposure‐response relationships for virologic endpoints (time to cessation of viral shedding, viral load measures and treatment‐emergent resistance). A drug‐disease model characterized the viral kinetics of influenza accounting for the effect of OC on viral production.

Results

Oseltamivir clearance was 32.5% lower (95% confidence interval [CI], 26.1‐38.8) and OC clearance was 33.7% lower (95% CI, 23.2‐44.1) in IC versus OwH patients. No notable exposure‐response relationships were identified for exposures higher than those achieved after conventional dose oseltamivir 75 mg, which appeared to be close to the maximum effect of oseltamivir. Simulations of the drug‐disease model predicted that initiating treatment within 48 hours of symptom onset had maximum impact, and a treatment duration of 10 days was favourable over 3‐5 days to limit viral rebound.

Conclusions

Our findings support the use of conventional‐dose oseltamivir 75 mg twice daily for 10 days in the treatment of IC adult patients with influenza.

Exposure-response characterisation of tildrakizumab in chronic plaque psoriasis: Pooled analysis of 3 randomised controlled trials

AIMS

In this exposure-response analysis, the dosing regimen for tildrakizumab, an antibody for treating moderate-to-severe chronic plaque psoriasis, was determined using data from 3 randomised controlled trials (P05495/NCT01225731: phase 2b, n = 355; reSURFACE 1/NCT01722331: phase 3, n = 772; reSURFACE 2/NCT01729754: phase 3, n = 1090).

METHODS

A maximum drug effect (Emax ) logistic-regression exposure-efficacy model was used to describe the week 12 Psoriasis Area and Severity Index (PASI) responses with average concentration of tildrakizumab during weeks 1-12 (Cavg12 ) as exposure metric. The impact of covariates (e.g., body weight, region) was tested. Exposure-safety, longitudinal pharmacokinetic-pharmacodynamic and risk-benefit analyses were also conducted.

RESULTS

At week 12, Emax was estimated at 62.2, 37.9 and 14.6% of responders for PASI75/90/100, respectively. Exposure-response curves plateaued at exposures >5 μg mL-1 . Heavier subjects had a lower response rate to placebo as measured by PASI75/90/100 than lighter subjects. PASI100 placebo response was less in subjects with higher baseline PASI score and older age. Simulated week 12 PASI75 increased by ≤4% on increasing the dose from 100 to 200 mg every 12 weeks (Q12W). The pharmacokinetic-pharmacodynamic model adequately described the time course of PASI change after treatment in the entire population and in each subject. Risk-benefit profiles were favourable for the 100- and 200-mg doses in different weight subgroups.

CONCLUSIONS

Patients with moderate-to-severe psoriasis should receive 100-mg subcutaneous tildrakizumab Q12W. Patients with high body weight (>90 kg) may benefit from a higher dose (200-mg Q12W).

Quantitative prediction of bone mineral density by using bone turnover markers in response to antiresorptive agents in postmenopausal osteoporosis: A model-based meta-analysis

AIMS

This study aimed to predict time course of bone mineral density (BMD) by using corresponding response of bone turnover markers (BTMs) in women with postmenopausal osteoporosis under antiresorptive treatments.

METHODS

Data were extracted from literature searches in accessible public database. Time courses of percent change from baseline in serum C-telopeptide of type 1 collagen (sCTX) and N-telopeptide of type 1 collagen were described by complex exponential onset models. The relationship between BTM changes and BMD changes at lumbar spine and total hip was described using a multiscale indirect response model.

RESULTS

The dataset included 41 eligible published trials of 5 US-approved antiresorptive agents (alendronate, ibandronate, risedronate, zoledronic acid and denosumab), containing over 28 800 women with postmenopausal osteoporosis. The time courses of BTM changes for different drugs were differentiated by maximal effect and onset rate in developed model, while sCTX responses to zoledronic acid and denosumab were captured by another model formation. Furthermore, asynchronous relationship between BTMs and BMD was described by a bone remodelling-based semimechanistic model, including zero-order production and first-order elimination induced by N-telopeptide of type 1 collagen and sCTX, separately. After external and informative validations, the developed models were able to predict BMD increase using 1-year data.

CONCLUSION

This exploratory analysis built a quantitative framework linking BTMs and BMD among antiresorptive agents, as well as a modelling approach to enhance comprehension of dynamic relationship between early and later endpoints among agents in a certain mechanism of action. Moreover, the developed models can offer predictions of BMD from BTMs supporting early drug development.

Effect of ageing on antiretroviral drug pharmacokinetics using clinical data combined with modelling and simulation

AIMS

The impact of ageing on antiretroviral pharmacokinetics remains uncertain, leading to missing dosing recommendations for elderly people living with human immunodeficiency virus (HIV: PLWH). The objective of this study was to investigate whether ageing leads to clinically relevant pharmacokinetic changes of antiretrovirals that would support a dose adjustment based on the age of the treated PLWH.

METHODS

Plasma concentrations for 10 first-line antiretrovirals were obtained in PLWH ≥55 years, participating in the Swiss HIV Cohort Study, and used to proof the predictive performance of our physiologically based pharmacokinetic (PBPK) model. The verified PBPK model predicted the continuous effect of ageing on HIV drug pharmacokinetics across adulthood (20-99 years). The impact of ethnicity on age-related pharmacokinetic changes between whites and other races was statistically analysed.

RESULTS

Clinically observed concentration-time profiles of all investigated antiretrovirals were generally within the 95% confidence interval of the PBPK simulations, demonstrating the predictive power of the modelling approach used. The predicted decline in drug clearance drove age-related pharmacokinetic changes of antiretrovirals, resulting in a maximal 70% [95% confidence interval: 40%, 120%] increase in antiretrovirals exposure across adulthood. Peak concentration, time to peak concentration and apparent volume of distribution were predicted to be unaltered by ageing. There was no statistically significant difference of age-related pharmacokinetic changes between studied ethnicities.

CONCLUSION

Dose adjustment for antiretrovirals based on the age of male and female PLWH is a priori not necessary in the absence of severe comorbidities considering the large safety margin of the current first-line HIV treatments.

Physiologically-Based Pharmacokinetic Predictions of the Effect of Curcumin on Metabolism of Imatinib and Bosutinib: In Vitro and In Vivo Disconnect

PURPOSE

This study aimed to investigate the potential pharmacokinetic interactions between curcumin, imatinib and bosutinib, combining In Vitro and in silico methods.

METHODS

In Vitro metabolism of imatinib and bosutinib were investigated in pooled human liver microsomes and recombinant CYP3A4 enzyme in the presence and absence of curcumin and curcumin glucuronide using an LC-MS/MS assay for N-desmethyl metabolites. A physiologically-based pharmacokinetic (PBPK) model for curcumin formulated as solid lipid nanoparticles (SLN) was constructed using In Vitro glucuronidation kinetics and published clinical pharmacokinetic data. The potential effects of curcumin coadministration on systemic exposures of imatinib and bosutinib were predicted in silico using PBPK simulations.

RESULTS

Curcumin demonstrated potent reversible inhibition of cytochrome P450 (CYP)3A4-mediated N-demethylation of imatinib and bosutinib and CYP2C8-mediated metabolism of imatinib with inhibitory constants (k_i,u) of ≤1.5 μmol. L^-1. A confirmatory In Vitro study with paclitaxel, the 6α-hydroxylation of which is exclusively mediated by CYP2C8, was consistent with a potent inhibition of this enzyme by curcumin. Curcumin glucuronide also inhibited both CYP enzymes In Vitro, albeit to a lesser extent than that of curcumin. PBPK model simulations predicted that at recommended dosing regimens of SLN curcumin, coadministration would result in an increase in systemic exposures of imatinib and bosutinib of up to only 10%.

CONCLUSION

A PBPK model for curcumin in a SLN formulation was successfully developed. Although curcumin possesses a strong In Vitro inhibitory activity towards CYP3A4 and CYP2C8 enzymes, its interactions with imatinib and bosutinib were unlikely to be of clinical importance due to curcumin's poor bioavailability.

Impact of granulocyte colony-stimulating factor on FOLFIRINOX-induced neutropenia prevention: A population pharmacokinetic/pharmacodynamic approach

AIMS

Granulocyte colony-stimulating factor (G-CSF) is frequently prescribed to prevent chemotherapy-induced neutropenia, but the administration schedule remains empirical in case of bimonthly chemotherapy such as FOLFIRINOX regimen. This pharmacokinetic/pharmacodynamic (PK/PD) study was performed to determine the effect of different G-CSF regimens on the incidence and duration of neutropenia following FOLFIRINOX administration in order to propose an optimal G-CSF dosing schedule.

METHODS

A population PK/PD model was developed to describe individual neutrophil time course from absolute neutrophil counts (ANC) obtained in 40 advanced cancer patients receiving FOLFIRINOX regimen. The structural model considered ANC dynamics, neutropenic effect of cytotoxics and the stimulating effect of G-CSF on neutrophils. Final model estimates were used to simulate different G-CSF dosing schedules for 1000 virtual subjects. The incidence and duration of neutropenia were then calculated for different G-CSF dosing schedules.

RESULTS

The final model successfully described the myelosuppressive effect induced by the 3 cytotoxics for all patients. Simulations showed that pegfilgrastim administration reduced the risk of severe neutropenia by 22.9% for subjects with low ANC at the start of chemotherapy. Median duration in this group was also shortened by 3.1 days when compared to absence of G-CSF. Delayed G-CSF administration was responsible for higher incidence and longer duration of neutropenia compared to absence of administration.

CONCLUSION

The PK/PD model well described our population's ANC data. Simulations showed that pegylated-G-CSF administration 24 hours after the end of chemotherapy seems to be the optimal schedule to reduce FOLFIRINOX-induced neutropenia. We also underline the potential negative effect of G-CSF maladministration.

Potential for pharmacokinetic interactions between Schisandra sphenanthera and bosutinib, but not imatinib: in vitro metabolism study combined with a physiologically-based pharmacokinetic modelling approach

AIMS

This study aimed to investigate the potential interaction between Schisandra sphenanthera, imatinib and bosutinib combining in vitro and in silico methods.

METHODS

In vitro metabolism of imatinib and bosutinib using recombinant enzymes and human liver microsomes were investigated in the presence and absence of Schisandra lignans. Physiologically-based pharmacokinetic (PBPK) models for the lignans accounting for reversible and mechanism-based inhibitions and induction of CYP3A enzymes were built in the Simcyp Simulator (version 17) and evaluated for their capability to predict interactions with midazolam and tacrolimus. Their potential effect on systemic exposures of imatinib and bosutinib were predicted using PBPK in silico simulations.

RESULTS

Schisantherin A and schisandrol B, but not schisandrin A, potently inhibited CYP3A4-mediated metabolism of imatinib and bosutinib. All three compounds showed a strong reversible inhibition on CYP2C8 enzyme with k_i of less than 0.5 μmol L^-1 . The verified PBPK models were able to describe the increase in systemic exposure of midazolam and tacrolimus due to co-administration of S. sphenanthera, consistent with the reported changes in the corresponding clinical interaction study (AUC ratio of 2.0 vs 2.1 and 2.4 vs 2.1, respectively). The PBPK simulation predicted that at recommended dosing regimens of S. sphenanthera, co-administration would result in an increase in bosutinib exposure (AUC ratio 3.0) but not in imatinib exposure.

CONCLUSION

PBPK models for Schisandra lignans were successfully developed. Interaction between imatinib and Schisandra lignans was unlikely to be of clinical importance. Conversely, S. sphenanthera at a clinically-relevant dose results in a predicted three-fold increase in bosutinib systemic exposure.

The Critical Raw Materials in Cutting Tools for Machining Applications: A Review

A variety of cutting tool materials are used for the contact mode mechanical machining of components under extreme conditions of stress, temperature and/or corrosion, including operations such as drilling, milling turning and so on. These demanding conditions impose a seriously high strain rate (an order of magnitude higher than forming), and this limits the useful life of cutting tools, especially single-point cutting tools. Tungsten carbide is the most popularly used cutting tool material, and unfortunately its main ingredients of W and Co are at high risk in terms of material supply and are listed among critical raw materials (CRMs) for EU, for which sustainable use should be addressed. This paper highlights the evolution and the trend of use of CRMs) in cutting tools for mechanical machining through a timely review. The focus of this review and its motivation was driven by the four following themes: (i) the discussion of newly emerging hybrid machining processes offering performance enhancements and longevity in terms of tool life (laser and cryogenic incorporation); (ii) the development and synthesis of new CRM substitutes to minimise the use of tungsten; (iii) the improvement of the recycling of worn tools; and (iv) the accelerated use of modelling and simulation to design long-lasting tools in the Industry-4.0 framework, circular economy and cyber secure manufacturing. It may be noted that the scope of this paper is not to represent a completely exhaustive document concerning cutting tools for mechanical processing, but to raise awareness and pave the way for innovative thinking on the use of critical materials in mechanical processing tools with the aim of developing smart, timely control strategies and mitigation measures to suppress the use of CRMs.

Population pharmacokinetics, efficacy, and safety of moxetumomab pasudotox in patients with relapsed or refractory hairy cell leukaemia

AIMS

To characterize the pharmacokinetics (PK) of moxetumomab pasudotox, an anti-CD22 recombinant immunotoxin, in adults with relapsed or refractory hairy cell leukaemia, we examined data from a phase 1 study (Study 1001; n = 49) and from the pivotal clinical study (Study 1053; n = 74).

METHODS

Data from both studies were pooled (n = 123) to develop a population PK model. Covariates included demographics, disease state, liver and kidney function, prior treatment, and antidrug antibodies (ADAs). Exposure-response and exposure-safety were analysed separately by study. A 1-compartment model with linear elimination from the central compartment and 2 clearance (CL) rates was developed.

RESULTS

Moxetumomab pasudotox was cleared more rapidly after cycle 1, day 1 (CL₁ = 24.7 L/h) than subsequently (CL₂ = 3.76 L/h), with high interindividual variability (116 and 109%, respectively). In Study 1053, patients with ADA titres >10 240 showed ~4-fold increase in CL. Higher exposures (≥median) were related to higher response rates, capillary leak syndrome and increased creatinine (Study 1053 only), or grade ≥3 adverse events (Study 1001 only). Clinical benefits were still observed in patients with lower exposure or high ADA titres.

CONCLUSION

Despite a high incidence of immunogenicity with increased clearance, moxetumomab pasudotox demonstrated efficacy in hairy cell leukaemia.

Exascale applications: skin in the game

As noted in Wikipedia, skin in the game refers to having 'incurred risk by being involved in achieving a goal', where 'skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

PITX2 upregulation increases the risk of chronic atrial fibrillation in a dose-dependent manner by modulating IKs and ICaL -insights from human atrial modelling

Background

Functional analysis has shown that the paired-like homeodomain transcription factor 2 (PITX2) overexpression associated with atrial fibrillation (AF) leads to the slow delayed rectifier K⁺ current (I_Ks) increase and the L-type Ca²⁺ current (I_CaL) reduction observed in isolated right atrial myocytes from chronic AF (CAF) patients. Through multiscale computational models, this study aimed to investigate the functional impact of the PITX2 overexpression on atrial electrical activity.

Methods

The well-known Courtemanche-Ramirez-Nattel (CRN) model of human atrial action potentials (APs) was updated to incorporate experimental data on alterations in I_Ks and I_CaL due to the PITX2 overexpression. These cell models for sinus rhythm (SR) and CAF were then incorporated into homogeneous multicellular one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) tissue models. The proarrhythmic effects of the PITX2 overexpression were quantified with ion current profiles, AP morphology, AP duration (APD) restitution, conduction velocity restitution (CVR), wavelength (WL), vulnerable window (VW) for unidirectional conduction block, and minimal substrate size required to induce re-entry. Dynamic behaviors of spiral waves were characterized by measuring lifespan (LS), tip patterns and dominant frequencies.

Results

The I_Ks increase and the I_CaL decrease arising from the PITX2 overexpression abbreviated APD and flattened APD restitution (APDR) curves in single cells. It reduced WL and increased CV at high excitation rates at the 1D tissue level. Although it had no effects on VW for initiating spiral waves, it decreased the minimal substrate size necessary to sustain re-entry. It also stabilized and accelerated spiral waves in 2D and 3D tissue models.

Conclusions

Electrical remodeling (I_Ks and I_CaL) due to the PITX2 overexpression increases susceptibility to AF due to increased tissue vulnerability, abbreviated APD, shortened WL and altered CV, which, in combination, facilitate initiation and maintenance of spiral waves.