Parametric Approaches in Population Pharmacokinetics

Developing Parametric and Nonparametric Models for Model-Informed Precision Dosing: A Quality Improvement Effort in Vancomycin for Patients With Obesity

BACKGROUND

Both parametric and nonparametric methods have been proposed to support model-informed precision dosing (MIPD). However, which approach leads to better models remains uncertain. Using open-source software, these 2 statistical approaches for model development were compared using the pharmacokinetics of vancomycin in a challenging subpopulation of class 3 obesity.

METHODS

Patients on vancomycin at the University of Vermont Medical Center from November 1, 2021, to February 14, 2023, were entered into the MIPD software. The inclusion criteria were body mass index (BMI) of at least 40 kg/m 2 and 1 or more vancomycin levels. A parametric model was created using nlmixr2/NONMEM, and a nonparametric model was created using Pmetrics. Then, a priori and a posteriori predictions were evaluated using the normalized root mean squared error (nRMSE) for precision and the mean percentage error (MPE) for bias. The parametric model was evaluated in a simulated MIPD context using an external validation dataset.

RESULTS

In total, 83 patients were included in the model development, with a median age of 56.6 years (range: 24-89 years), and a median BMI of 46.3 kg/m 2 (range: 40-70.3 kg/m 2 ). Both parametric and nonparametric models were 2-compartmental, with creatinine clearance and fat-free mass as covariates to clearance and volume parameters, respectively. The a priori MPE and nRMSE for the parametric versus nonparametric models were -6.3% versus 2.69% and 27.2% versus 30.7%, respectively. The a posteriori MPE and RMSE were 0.16% and 0.84%, and 13.8% and 13.1%. The parametric model matched or outperformed previously published models on an external validation dataset (n = 576 patients).

CONCLUSIONS

Minimal differences were found in the model structure and predictive error between the parametric and nonparametric approaches for modeling vancomycin class 3 obesity. However, the parametric model outperformed several other models, suggesting that institution-specific models may improve pharmacokinetics management.

Population pharmacokinetics of nirmatrelvir/ritonavir in critically ill Chinese COVID-19 patients and recommendations for medication use: a two-center retrospective study

BACKGROUND

This study aimed to establish population pharmacokinetics (PPK) models of nirmatrelvir/ritonavir in critically ill Chinese patients with the coronavirus disease 2019 (COVID-19) infection, explore factors affecting the pharmacokinetics (PK) of nirmatrelvir/ritonavir.

METHODS

A total of 285 serum samples and clinical data were collected from 152 patients. The PPK models of nirmatrelvir/ritonavir were analyzed using nonlinear mixed-effect modeling (NONMEM) approach. The optimal dosing regimen for patients with different renal function was determined using Monte Carlo simulations.

RESULTS

The population typical values of apparent clearance (CL/F) and apparent volume of distribution (V/F) of nirmatrelvir were 2.26 L/h and 15.3 L, respectively. Notably, creatinine clearance (CrCL) significantly influenced the PK variation of nirmatrelvir. Monte Carlo simulations suggested that patients with mild-to-moderate renal impairment experienced a 22.0-59.9% increase in the area under the curve (AUC) when they were administered a standard dose of nirmatrelvir compared to those with normal renal function. The AUC in patients with severe renal impairment after administration of 150 mg q12h nirmatrelvir was similar to that in patients with normal renal function after administration of 300 mg q12h nirmatrelvir.

CONCLUSIONS

PPK modeling and simulation provided a reference for the rational clinical application of nirmatrelvir/ritonavir in critically ill Chinese patients.

Pharmacokinetic Models of Tafenoquine: Insights for Optimal Malaria Treatment Strategies

Tafenoquine (TQ) is a new 8-aminoquinoline antimalarial drug developed by the US Army for Plasmodium vivax malaria treatment. Modeling and simulation are essential tools for drug development and improving rationality in pharmacotherapy, and different modeling approaches are used. This study aims to summarize and explore the pharmacokinetic (PK) models available for tafenoquine in the literature. An integrative methodology was used to collect and review published data. Fifteen articles were identified using three modeling approaches: non-compartmental analysis (NCA), population pharmacokinetic analysis (popPK), and pharmacokinetic/pharmacodynamic analysis (PK/PD). An NCA was mainly used to describe the PK profile of TQ and to compare its PK profile alone to those obtained in association with other drugs. PopPK was used to assess TQ population PK parameters, covariates' impact, and dose selection. PK/PD helped understand the relationship between TQ concentrations, some adverse events common for 8-aminoquilones, and the efficacy assessment for Plasmodium falciparum. In summary, pharmacokinetic models were widely used during TQ development. However, there is still a need for different modeling approaches to support further therapeutic questions, such as treatment for special populations and potential drug-drug interactions.

Model-informed precision dosing: State of the art and future perspectives

Model-informed precision dosing (MIPD) stands as a significant development in personalized medicine to tailor drug dosing to individual patient characteristics. MIPD moves beyond traditional therapeutic drug monitoring (TDM) by integrating mathematical predictions of dosing, and considering patient-specific factors (patient characteristics, drug measurements) as well as different sources of variability. For this purpose, rigorous model qualification is required for the application of MIPD in patients. This review delves into new methods in model selection and validation, also highlighting the role of machine learning in improving MIPD, the utilization of biosensors for real-time monitoring, as well as the potential of models integrating biomarkers for efficacy or toxicity for precision dosing. The clinical evidence of TDM and MIPD is discussed for various medical fields including infection medicine, oncology, transplant medicine, and inflammatory bowel diseases, thereby underscoring the role of pharmacokinetics/pharmacodynamics and specific biomarkers. Further research, particularly randomized clinical trials, is warranted to corroborate the value of MIPD in enhancing patient outcomes and advancing personalized medicine.

In Silico Pharmacokinetics Evaluation of Forgiveness for Doravirine and Rilpivirine

BACKGROUND

This study aimed to evaluate the concentrations of rilpivirine (RLP) and doravirine (DOR) after 3 days-off using simulations from population pharmacokinetics models.

METHODS

The authors conducted a series of 500 sets of 10,000 Monte Carlo simulations to examine the steady-state conditions for 2 common dosage levels: 25 mg/d for RLP and 100 mg/d for DOR. These simulations were conducted under 2 scenarios: 1 without drug cessation and another after a 3-day break. The validity of the implementation was established through a comparison of median trough concentrations (C24h) with previously reported data. Subsequently, the proportion of simulated patients with C24h and C72h after 3 days-off (C72h/3do) that exceeded the inhibitory concentration 50 (IC50), 5.2 mcg/L for DOR and 20.5 mcg/L for RLP respectively, was calculated. The inhibitory quotient (IQ) was also computed, which was 6 times IC50 for DOR and 4.5 times IC50 for RLP. Finally, nomograms were constructed to estimate the probability of having C72h/3do > IC50 or > IQ for different ranges of C24h.

RESULTS

Simulated C24h median ± SD for RLP were 61.8 ± 0.4 mcg/L and for DOR 397 ± 0 mcg/L. For RLP, 99.3 ± 0.1% exceeded IC50 at C24h, 16.4 ± 0.4% at C72h/3do, and none surpassed the IQ threshold. In contrast, DOR had 100% ± 0% above IC50 at C24h, 93.6 ± 0.2% at C72h/3do, and 58.6 ± 0.5% exceeded the IQ.

CONCLUSIONS

These findings suggest that treatment with DOR may offer a more forgiving therapeutic profile than RLP, given the larger proportion of patients achieving effective drug exposure with DOR. However, it is important to acknowledge a significant limitation of this study, namely, the assumption that drug concentration is a perfect surrogate for drug effectiveness.

Population Pharmacokinetic/Pharmacodynamic Models for P2Y12 Inhibitors: A Systematic Review and Clinical Appraisal Using Exposure Simulation

BACKGROUND AND OBJECTIVE

Recent research indicates a correlation between plasma concentration of P2Y12 inhibitors and clinical events, particularly bleeding, which significantly impeded their clinical therapeutic performance. It is therefore vital to delve into the factors that might affect the plasma concentration. The study aims to summarize population pharmacokinetics/pharmacodynamics (PopPKPD) models for commonly prescribed P2Y12 inhibitors (clopidogrel, prasugrel, and ticagrelor) and assess bleeding risk in specific individual groups.

METHODS

The PopPKPD models of P2Y12 inhibitors were collected and summarized based on predetermined inclusion and exclusion criteria. The collected models were replicated in simulations, which were used to assess factors affecting plasma concentrations of P2Y12 inhibitors. Simulation results for special populations were compared to therapeutic window based on reported exposure-effect relationships (PK/PD-related bleeding and thrombotic clinical outcomes) to predict bleeding risk in special populations with different dosing regimens and cumulative covariates.

RESULT

Finally, 12 studies were included for PK simulation, 7 of which that also included PD data were subjected to further analysis, with the majority being based on Phase I or II trials. Simulations showed that several covariates such as female gender, weight, elderly can significantly impact on exposure, with special populations reaching up to 179% of the general population. However, after dose adjustment, blood concentrations for special populations can reach approximately ±20% of general population exposure. Therefore, lowering the maintenance dose of ticagrelor from 90 to 60 mg bid was first recommended to reduce bleeding risk without significantly increasing ischemic risk, particularly in elderly, small-weight Asian females.

CONCLUSION

Lowering the maintenance dose of ticagrelor from 90 to 60 mg bid effectively reduces bleeding risk without increasing thrombotic infarction risk in elderly, small-weight Asian females.

Bridging the Worlds of Pharmacometrics and Machine Learning

Precision medicine requires individualized modeling of disease and drug dynamics, with machine learning-based computational techniques gaining increasing popularity. The complexity of either field, however, makes current pharmacological problems opaque to machine learning practitioners, and state-of-the-art machine learning methods inaccessible to pharmacometricians. To help bridge the two worlds, we provide an introduction to current problems and techniques in pharmacometrics that ranges from pharmacokinetic and pharmacodynamic modeling to pharmacometric simulations, model-informed precision dosing, and systems pharmacology, and review some of the machine learning approaches to address them. We hope this would facilitate collaboration between experts, with complementary strengths of principled pharmacometric modeling and flexibility of machine learning leading to synergistic effects in pharmacological applications.

Population pharmacokinetic analysis of lopinavir in HIV negative individuals exposed to SARS-CoV-2: a COPEP (COronavirus Post-Exposure Prophylaxis) sub-study

BACKGROUND

Lopinavir/ritonavir (LPV/r) is a drug traditionally used for the treatment of HIV that has been repurposed as a potential post-exposure prophylaxis agent against COVID-19 in the COronavirus Post-Exposure Prophylaxis (COPEP) study. The present analysis aims to evaluate LPV levels in individuals exposed to SARS-CoV-2 versus people living with HIV (PLWH) by developing a population pharmacokinetic (popPK) model, while characterizing external and patient-related factors that might affect LPV exposure along with dose-response association.

METHODS

We built a popPK model on 105 LPV concentrations measured in 105 HIV-negative COPEP individuals exposed to SARS-CoV-2, complemented with 170 LPV concentrations from 119 PLWH followed in our routine therapeutic drug-monitoring programme. Published LPV popPK models developed in PLWH and in COVID-19 patients were retrieved and validated in our study population by mean prediction error (MPE) and root mean square error (RMSE). The association between LPV model-predicted residual concentrations (Cmin) and the appearance of the COVID-19 infection in the COPEP participants was investigated.

RESULTS

A one-compartment model with linear absorption and elimination best described LPV concentrations in both our analysis and in the majority of the identified studies. Globally, similar PK parameters were found in all PK models, and provided close MPEs (from -19.4% to 8.0%, with a RMSE of 3.4% to 49.5%). No statistically significant association between Cmin and the occurrence of a COVID-19 infection could be detected.

CONCLUSION

Our analysis indicated that LPV circulating concentrations were similar between COPEP participants and PLWH, and that published popPK models described our data in a comparable way.

Population Pharmacokinetic Analysis of Perampanel in Portuguese Patients Diagnosed with Refractory Epilepsy

Perampanel is a promising antiepileptic drug (AED) for refractory epilepsy treatment due to its innovative mechanism of action. This study aimed to develop a population pharmacokinetic (PopPK) model to be further used in initial dose optimization of perampanel in patients diagnosed with refractory epilepsy. A total of seventy-two plasma concentrations of perampanel obtained from forty-four patients were analyzed through a population pharmacokinetic approach by means of nonlinear mixed effects modeling (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic profiles of perampanel. Interpatient variability (IPV) was entered on clearance (CL), while the residual error (RE) was modeled as proportional. The presence of enzyme-inducing AEDs (EIAEDs) and body mass index (BMI) were found as significant covariates for CL and volume of distribution (V), respectively. The mean (relative standard error) estimates for CL and V of the final model were 0.419 L/h (5.56%) and 29.50 (6.41%), respectively. IPV was 30.84% and the proportional RE was 6.44%. Internal validation demonstrated an acceptable predictive performance of the final model. A reliable population pharmacokinetic model was successfully developed, and it is the first enrolling real-life adults diagnosed with refractory epilepsy.

Safety of medicines during breastfeeding - from case report to modeling : A contribution from the ConcePTION project

INTRODUCTION

Despite many research efforts, current data on the safety of medicines during breastfeeding are either fragmented or lacking, resulting in restrictive labeling of most medicines. In the absence of pharmacoepidemiologic safety studies, risk estimation for breastfed infants is mainly derived from pharmacokinetic (PK) information on the medicine. This manuscript provides a description and a comparison of the different methodological approaches that can yield reliable information on medicine transfer into human milk and the resulting infant exposure.

AREA COVERED

Currently, most information on medicine transfer in human milk relies on case reports or traditional PK studies, which generate data that can hardly be generalized to the population. Some methodological approaches, such as population PK (popPK) and physiologically-based PK (PBPK) modeling, can be used to provide a more complete characterization of infant medicine exposure through human milk and simulate the most extreme situations, while decreasing the burden of sampling in breastfeeding women.

EXPERT OPINION

PBPK and popPK modeling are promising approaches to fill the gap of knowledge in medicine safety in breastfeeding, as illustrated with our escitalopram example.

Population pharmacokinetic modelling to characterize the effect of chronic kidney disease on tenofovir exposure after tenofovir alafenamide administration

BACKGROUND

Tenofovir alafenamide is gradually replacing tenofovir disoproxil fumarate, both prodrugs of tenofovir, in HIV prevention and treatment. There is thus an interest in describing tenofovir pharmacokinetics (PK) and its variability in people living with HIV (PLWH) under tenofovir alafenamide in a real-life setting.

OBJECTIVES

To characterize the usual range of tenofovir exposure in PLWH receiving tenofovir alafenamide, while assessing the impact of chronic kidney disease (CKD).

METHODS

We conducted a population PK analysis (NONMEM®) on 877 tenofovir and 100 tenofovir alafenamide concentrations measured in 569 PLWH. Model-based simulations allowed prediction of tenofovir trough concentrations (Cmin) in patients having various levels of renal function.

RESULTS

Tenofovir PK was best described using a one-compartment model with linear absorption and elimination. Creatinine clearance (CLCR, estimated according to Cockcroft and Gault), age, ethnicity and potent P-glycoprotein inhibitors were statistically significantly associated with tenofovir clearance. However, only CLCR appeared clinically relevant. Model-based simulations revealed 294% and 515% increases of median tenofovir Cmin in patients with CLCR of 15-29 mL/min (CKD stage 3), and less than 15 mL/min (stage 4), respectively, compared with normal renal function (CLCR = 90-149 mL/min). Conversely, patients with augmented renal function (CLCR > 149 mL/min) had a 36% decrease of median tenofovir Cmin.

CONCLUSIONS

Kidney function markedly affects circulating tenofovir exposure after tenofovir alafenamide administration in PLWH. However, considering its rapid uptake into target cells, we suggest only a cautious increase of tenofovir alafenamide dosage intervals to 2 or 3 days only in case of moderate or severe CKD, respectively.

Precision Oncology by Point-of-Care Therapeutic Drug Monitoring and Dosage Adjustment of Conventional Cytotoxic Chemotherapies: A Perspective

Therapeutic drug monitoring (TDM) of conventional cytotoxic chemotherapies is strongly supported yet poorly implemented in daily practice in hospitals. Analytical methods for the quantification of cytotoxic drugs are instead widely presented in the scientific literature, while the use of these therapeutics is expected to keep going for longer. There are two main issues hindering the implementation of TDM: turnaround time, which is incompatible with the dosage profiles of these drugs, and exposure surrogate marker, namely total area under the curve (AUC). Therefore, this perspective article aims to define the adjustment needed from current to efficient TDM practice for cytotoxics, namely point-of-care (POC) TDM. For real-time dose adjustment, which is required for chemotherapies, such POC TDM is only achievable with analytical methods that match the sensitivity and selectivity of current methods, such as chromatography, as well as model-informed precision dosing platforms to assist the oncologist with dose fine-tuning based on quantification results and targeted intervals.

Individualized Patient Care Through Model-Informed Precision Dosing: Reflections on Training Future Practitioners

Prior to his passing, Dr. Roger Jelliffe, expressed the need for educating future physicians and clinical pharmacists on the availability of computer-based tools to support dose optimization in patients in stable or unstable physiological states. His perspectives were to be captured in a commentary for the AAPS J with a focus on incorporating population pharmacokinetic (PK)/pharmacodynamic (PD) models that are designed to hit the therapeutic target with maximal precision. Unfortunately, knowing that he would be unable to complete this project, Dr. Jelliffe requested that a manuscript conveying his concerns be completed upon his passing. With this in mind, this final installment of the AAPS J theme issue titled "Alternative Perspectives for Evaluating Drug Exposure Characteristics in a Population - Avoiding Analysis Pitfalls and Pigeonholes" is an effort to honor Dr. Jelliffe's request, conveying his concerns and the need to incorporate modeling and simulation into the training of physicians and clinical pharmacists. Accordingly, Dr. Jelliffe's perspectives have been integrated with those of the other three co-authors on the following topics: the clinical utility of population PK models; the role of multiple model (MM) dosage regimens to identify an optimal dose for an individual; tools for determining dosing regimens in renal dialysis patients (or undergoing other therapies that modulate renal clearance); methods to analyze and track drug PK in acutely ill patients presenting with high inter-occasion variability; implementation of a 2-cycle approach to minimize the duration between blood samples taken to estimate the changing PK in an acutely ill patient and for the generation of therapeutic decisions in advance for each dosing cycle based on an analysis of the previous cycle; and the importance of expressing therapeutic drug monitoring results as 1/variance rather than as the coefficient of variation. Examples showcase why, irrespective of the overall approach, the combination of therapeutic drug monitoring and computer-informed precision dosing is indispensable for maximizing the likelihood of achieving the target drug concentrations in the individual patient.

Implementation and Cross-Validation of a Pharmacokinetic Model for Precision Dosing of Busulfan in Hematopoietic Stem Cell Transplanted Children

Busulfan, a drug used in conditioning prior to hematopoietic stem cell transplantation (HSCT) in children, has a narrow therapeutic margin. The model-informed precision dosing (MIPD) of busulfan is desirable, but there is a lack of validated tools. The objective of this study was to implement and cross-validate a population pharmacokinetic (PK) model in the Tucuxi software for busulfan MIPD in HSCT children. A search of the literature was performed to identify candidate population PK models. The goodness of fit of three selected models was assessed in a dataset of 178 children by computing the mean error (ME) and root-mean-squared error of prediction (RMSE). The best model was implemented in Tucuxi. The individual predicted concentrations, the area under the concentration-time curve (AUC), and dosage requirements were compared between the Tucuxi model and a reference model available in the BestDose software in a subset of 61 children. The model from Paci et al. best fitted the data in the full dataset. In a subset of 61 patients, the predictive performance of Tucuxi and BestDose models was comparable with ME values of 6.4% and -2.5% and RMSE values of 11.4% and 13.6%, respectively. The agreement between the estimated AUC and the predicted dose was good, with 6.6% and 4.9% of the values being out of the 95% limits of agreement, respectively. To conclude, a PK model for busulfan MIPD was cross-validated and is now available in the Tucuxi software.

External evaluation of published population pharmacokinetic models of posaconazole

Population pharmacokinetic (PopPK) models of posaconazole have been established to promote the precision dosing. However, the performance of these models extrapolated to other centers has not been evaluated. This study aimed to conduct an external evaluation of published posaconazole PopPK models to evaluate their predictive performance. Posaconazole PopPK models screened from the PubMed and MEDLINE databases were evaluated using an external dataset of 213 trough concentration samples collected from 97 patients. Their predictive performance was evaluated by prediction-based diagnosis (prediction error), simulation-based diagnosis (visual predictive check), and Bayesian forecasting. In addition, external cohorts with and without proton pump inhibitor were used to evaluate the models respectively. Ten models suitable for the external dataset were finally included into the study. In prediction-based diagnostics, none of the models met pre-determined criteria for predictive indexes. Only M4, M6, and M10 demonstrated favorable simulations in visual predictive check. The prediction performance of M5, M7, M8, and M9 evaluated using the cohort without proton pump inhibitor showed a significant improvement compared to that evaluated using the whole cohort. Consistent with our expectations, Bayesian forecasting significantly improved the predictive per-formance of the models with two or three prior observations. In general, the applicability of these published posaconazole PopPK models extrapolated to our center was unsatisfactory. Prospective studies combined with therapeutic drug monitoring are needed to establish a PopPK model for posaconazole in the Chinese population to promote individualized dosing.

Population pharmacokinetics identifies rapid gastrointestinal absorption and plasma clearance of oral chlorambucil administered to cats with indolent lymphoproliferative malignancies

OBJECTIVE

To establish the pharmacokinetics of a single 2-mg oral dose of chlorambucil in cats with indolent lymphoproliferative malignancies.

ANIMALS

24 client-owned cats.

PROCEDURES

Cats were assigned to 1 of 4 groups, with each group having a total of 3 sample collection time points over 12 hours after receiving a single 2-mg oral dose of chlorambucil. Each time point combined to generate 6 full patient plasma chlorambucil concentration-time curves from the 24 cats. Chlorambucil treatment was continued every other day and a single, variably timed sample collection was obtained on day 14. Population parameter estimates were obtained by nonlinear mixed-effects modeling. Covariates investigated included age, sex, baseline serum cobalamin, study location, weight, and body condition score.

RESULTS

Chlorambucil administered orally to cats was found to have a peak plasma concentration of approximately 170 ng/mL (SE, 31.1 ng/mL), percent coefficient of variation (%CV) of 18.4% within 15 minutes, and a terminal half-life of 1.8 hours (SE, 0.21 hour; %CV, 12.4). At the 4-hour mark, a smaller secondary peak in plasma chlorambucil was found. Day 14 samples were similar to those of the initial dose. No covariates showed a significant effect in the population model.

CLINICAL RELEVANCE

In these cats, chlorambucil at a 2-mg dose administered every other day undergoes rapid gastrointestinal absorption and plasma clearance with no drug accumulation between doses. These data are critical to inform future work investigating the association of chlorambucil drug exposure with adverse events and outcome of cats with lymphoproliferative diseases.

Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: a systematic review of population pharmacokinetic models

Purpose

Significant pharmacokinetic variabilities have been reported for isoniazid across various populations. We aimed to summarize population pharmacokinetic studies of isoniazid in tuberculosis (TB) patients with a specific focus on the influence of N-acetyltransferase 2 (NAT2) genotype/single-nucleotide polymorphism (SNP) on clearance of isoniazid.

Methods

A systematic search was conducted in PubMed and Embase for articles published in the English language from inception till February 2022 to identify population pharmacokinetic (PopPK) studies of isoniazid. Studies were included if patient population had TB and received isoniazid therapy, non-linear mixed effects modelling, and parametric approach was used for building isoniazid PopPK model and NAT2 genotype/SNP was tested as a covariate for model development.

Results

A total of 12 articles were identified from PubMed, Embase, and hand searching of articles. Isoniazid disposition was described using a two-compartment model with first-order absorption and linear elimination in most of the studies. Significant covariates influencing the pharmacokinetics of isoniazid were NAT2 genotype, body weight, lean body weight, body mass index, fat-free mass, efavirenz, formulation, CD4 cell count, and gender. Majority of studies conducted in adult TB population have reported a twofold or threefold increase in isoniazid clearance for NAT2 rapid acetylators compared to slow acetylators.

Conclusion

The variability in disposition of isoniazid can be majorly attributed to NAT2 genotype. This results in a trimodal clearance pattern with a multi-fold increase in clearance of NAT2 rapid acetylators compared to slow acetylators. Further studies exploring the generalizability/adaptability of developed PopPK models in different clinical settings are required.

Population Pharmacokinetic Models for Direct Oral Anticoagulants: A Systematic Review and Clinical Appraisal Using Exposure Simulation

Available data have shown an association between direct oral anticoagulant (DOAC) plasma concentration and clinical, particularly bleeding, events. Factors that may influence DOAC plasma concentration are therefore the focus of particular attention. Population pharmacokinetic (PopPK) analyses can help in identifying such factors while providing predictive models. The main aim of the present study was to identify all the PopPK models to date for the four most frequently used DOACs (dabigatran, apixaban, rivaroxaban, and edoxaban). The secondary aim was to use these models to simulate different DOAC plasma concentration–time profiles in relevant clinical scenarios. The results of our model‐based simulations confirm the clinical relevance of the known major factors influencing DOAC exposure and support the current approved dose adaptation, at least for atrial fibrillation. They also highlight how the accumulation of covariates, not currently considered for dose adaptation due to their seemingly minor influence on DOAC exposure, lead to supratherapeutic blood concentrations and could thus enhance the risk of major bleeding. The present results therefore question DOAC dose adaptation in the presence of these covariates, such as drug–drug interaction or genotypes, alongside the known existing covariates. As the overall effect of accumulation of several covariates could be difficult to apprehend for the clinicians, PopPK modeling could represent an interesting approach for informed precision dosing and to improve personalized prescription of DOACs.

Population Pharmacokinetics and Dosing Regimen Optimization of Latamoxef in Chinese Children

The present study aimed to establish population pharmacokinetic models of latamoxef, as well as its R- and S-epimers, and generate findings to guide the individualized administration of latamoxef in pediatric patients. A total of 145 in-hospital children aged 0.08-10.58 years old were included in this study. Three population pharmacokinetic models of latamoxef and its R- and S-epimers were established. The stability and predictive ability of the final models were evaluated by utilizing goodness-of-fit plots, nonparametric bootstrapping, and normalized prediction distribution errors. The final model of total latamoxef was considered as a basis for the dosing regimen. A two-compartment model with first-order elimination best described the pharmacokinetics of total latamoxef. The population typical values of total latamoxef were as follows: central compartment distribution volume (V1) of 4.84 L, peripheral compartment distribution volume (V2) of 16.18 L, clearance (CL) of 1.00 L/h, and inter-compartmental clearance (Q) of 0.97 L/h. Moreover, R-epimer has a higher apparent volume of distribution and lower clearance than S-epimer. Body surface area (BSA) was identified as the most significant covariate to V, CL, and Q. Specific recommendations are given for dosage adjustment in pediatric patients based on BSA. This study highlights that a BSA-normalized dose of latamoxef was required when treating different bacteria to reach the therapeutic target more effectively.

PBPK Modeling and Simulation and Therapeutic Drug Monitoring: Possible Ways for Antibiotic Dose Adjustment

Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.

From Therapeutic Drug Monitoring to Model-Informed Precision Dosing for Antibiotics

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended.