Model-informed Precision Dosing Research Articles

AUC-based monitoring and model-informed precision dosing of vancomycin in critically ill patients: why and how?

AUC-based monitoring and model-informed precision dosing of vancomycin in critically ill patients: why and how?

Which patients benefit from model-informed precision dosing of beta-lactam antibiotics and ciprofloxacin at the ICU?

Antibiotic dosing is not optimal in the ICU. Our recent trial investigated the effect of model-informed precision dosing (MIPD) of beta-lactam antibiotics and ciprofloxacin and showed no significant differences in clinical outcomes in all patients. This study aimed to identify subgroups of patients in which the MIPD of these antibiotics could be beneficial for clinical outcomes. We analysed data from the DOLPHIN randomized controlled trial, which compared MIPD to standard dosing of beta-lactam antibiotics and ciprofloxacin in 388 ICU patients. We divided patients into subgroups based on baseline characteristics and assessed the effect of MIPD on 28-day mortality, 6-month mortality, change in sequential organ failure assessment (delta-SOFA), and ICU length of stay (LOS). We found a lower 28-day mortality in patients with a SOFA below 8 randomized to MIPD (OR 0.40; 95% CI 0.17-0.88). However, patients with a higher SOFA show an increased 28-day mortality (OR 1.94; 95% CI 1.07-3.59) in the MIPD group. ICU LOS was increased in patients receiving MIPD with a SOFA below 8 (IRR 1.36; 95% CI 1.01-1.83) and those receiving MIPD for ceftriaxone (IRR 1.76; 95% CI 1.24-2.51). Patients receiving a dose recommendation within 24 hours show a trend towards decreased ICU LOS (IRR 0.77; 95% CI 0.52-1.16) and higher delta-SOFA (estimate -1.19; 95% CI -2.98-0.60). ICU patients with a SOFA below 8 using MIPD had an increased ICU LOS but a lower 28-day mortality. Fast dose recommendations using MIPD of beta-lactam antibiotics and ciprofloxacin needs to be investigated in ICU patients.

Physiologically-based pharmacokinetic modeling for single and multiple dosing regimens of ceftriaxone in healthy and chronic kidney disease populations: a tool for model-informed precision dosing.

Introduction: Ceftriaxone is one of commonly prescribed beta-lactam antibiotics with several label and off-label clinical indications. A high fraction of administered dose of ceftriaxone is excreted renally in an unchanged form, and it may accumulate significantly in patients with impaired renal functions, which may lead to toxicity. Methods: In this study, we employed a physiologically-based pharmacokinetic (PBPK) modeling, as a tool for precision dosing, to predict the biological exposure of ceftriaxone in a virtually-constructed healthy and chronic kidney disease patient populations, with subsequent dosing optimizations. We started developing the model by integrating the physicochemical properties of the drug with biological system information in a PBPK software platform. A PBPK model in an adult healthy population was developed and evaluated visually and numerically with respect to experimental pharmacokinetic data. The model performance was evaluated based on the fold error criteria of the predicted and reported values for different pharmacokinetic parameters. Then, the model was applied to predict drug exposure in CKD patient populations with various degrees of severity. Results: The developed PBPK model was able to precisely describe the pharmacokinetic behavior of ceftriaxone in adult healthy population and in mild, moderate, and severe CKD patient populations. Decreasing the dose by approximately 25% in mild and 50% in moderate to severe renal disease provided a comparable exposure to the healthy population. Based on the simulation of multiple dosing regimens in severe CKD population, it has been found that accumulation of 2g every 24h is lower than the accumulation of 1g every 12h dosing regimen. Discussion: In this study, the observed concentration time profiles and pharmacokinetic parameters for ceftriaxone were successfully reproduced by the developed PBPK model and it has been shown that PBPK modeling can be used as a tool for precision dosing to suggest treatment regimens in population with renal impairment.

Cefepime pharmacokinetics in critically ill children and young adults undergoing continuous kidney replacement therapy.

Cefepime is an antibiotic commonly used to treat sepsis and is cleared by renal excretion. Cefepime dosing requires adjustment in patients with decreased kidney function and in those receiving continuous kidney replacement therapy (CKRT). We aimed to characterize cefepime PK in a diverse cohort of critically ill paediatric patients on CKRT. Patients were identified from an ongoing pharmacokinetic/pharmacodynamic (PK/PD) study of beta-lactam antibiotics, and were included if they had received at least two cefepime doses in the ICU and were on CKRT for at least 24 h. PK parameters were estimated using MwPharm++ with Bayesian estimation and a paediatric population PK model. Target attainment was assessed as time of free cefepime concentrations above minimum inhibitory concentration (fT > 1× or 4 × MIC). Seven patients were included in the study (ages 2 to 20 years). CKRT indications included liver failure (n = 1), renal failure (n = 4) and fluid overload (n = 2). Total effluent flow rates ranged from 1833 to 3115 (mean 2603) mL/1.73 m2/h, while clearance was 2.11-3.70 (mean 3.0) L/h/70 kg. Effluent flows were lower, but clearance and fT > MIC were similar to paediatric data published previously. Using Pseudomonas aeruginosa MIC breakpoints, all patients had 100% of dosing interval above MIC, but only one had 100% of dosing interval above 4× MIC. Since most patients failed to attain stringent targets of 100% fT > 4× MIC, model-informed precision dosing may benefit such patients.

Daptomycin Exposure as a Risk Factor for Daptomycin-Induced Eosinophilic Pneumonia and Muscular Toxicity.

High-dose daptomycin is increasingly used in patients with bone and joint infection (BJI). This raises concerns about a higher risk of adverse events (AEs), including daptomycin-induced eosinophilic pneumonia (DIEP) and myotoxicity. We aimed to examine pharmacokinetic and other potential determinants of DIEP and myotoxicity in patients with BJI receiving daptomycin. All patients receiving daptomycin for BJI were identified in a prospective cohort study. Cases were matched at a 1:3 ratio, with controls randomly selected from the same cohort. Bayesian estimation of the daptomycin daily area under the concentration-time curve over 24 hours (AUC24h) was performed with the Monolix software based on therapeutic drug monitoring (TDM) data. Demographic and biological data were also collected. Risk factors of AEs were analyzed using Cox proportional hazards model. From 1130 patients followed over 7 years, 9 with DIEP, 26 with myotoxicity, and 106 controls were included in the final analysis. Daptomycin AUC24h, C-reactive protein, and serum protein levels were associated with the risk of AEs. The adjusted hazard ratio of DIEP or myotoxicity was 3.1 (95% confidence interval [CI], 1.48-6.5; P < .001) for daptomycin AUC24h > 939 mg/h/L, 9.8 (95% CI, 3.94-24.5; P < .001) for C-reactive protein > 21.6 mg/L, and 2.4 (95% CI, 1.02-5.65; P = .04) for serum protein <72 g/L. We identified common determinants of DIEP and myotoxicity in patients with BJI. Because the risk of AEs was associated with daptomycin exposure, daptomycin TDM and model-informed precision dosing may help optimize the efficacy and safety of daptomycin treatment in this setting. A target AUC24h range of 666 to 939 mg/h/L is suggested.

Towards model-informed precision dosing of piperacillin: multicenter systematic external evaluation of pharmacokinetic models in critically ill adults with a focus on Bayesian forecasting

PurposeInadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models.MethodsA multicenter dataset of 561 ICU patients (11 centers/3654 concentrations) was used for the evaluation of 24 identified models. Model performance was investigated for a priori (A) predictions, i.e., considering dosing records and patient characteristics only, and for Bayesian forecasting, i.e., additionally including the first (B1) or first and second (B2) therapeutic drug monitoring (TDM) samples per patient. Median relative prediction error (MPE) [%] and median absolute relative prediction error (MAPE) [%] were calculated to quantify accuracy and precision.ResultsThe evaluation revealed a large inter-model variability (A: MPE − 135.6–78.3% and MAPE 35.7–135.6%). Integration of TDM data improved all model predictions (B1/B2 relative improvement vs. A: |MPE|median_all_models 45.1/67.5%; MAPEmedian_all_models 29/39%). The model by Kim et al. was identified to be most appropriate for the total dataset (A/B1/B2: MPE − 9.8/− 5.9/− 0.9%; MAPE 37/27.3/23.7%), Udy et al. performed best in patients receiving intermittent infusion, and Klastrup et al. best predicted patients receiving continuous infusion. Additional evaluations stratified by sex and renal replacement therapy revealed further promising models.ConclusionThe predictive performance of published PIP models in ICU patients varied considerably, highlighting the relevance of appropriate model selection for MIPD. Our differentiated external evaluation identified specific models suitable for clinical use, especially in combination with TDM.

Model-informed precision dosing of antimicrobial drugs in pediatrics: experiences from a pilot scale program.

Antibiotics are among the most utilized drugs in pediatrics. Nonetheless, there is a lack in pharmacokinetics information for this population, and dosing criteria may vary between healthcare centers. Physiological variability associated with maturation in pediatrics makes it challenging to reach a consensus on adequate dosing, which is further accentuated in more vulnerable groups, such as critically ill or oncology patients. Model-informed precision dosing is a useful practice that allows dose optimization and attainment of antibiotic-specific pharmacokinetic/pharmacodynamic targets. The aim of this study was to evaluate the needs of model-informed precision dosing of antibiotics in a pediatrics unit, at a pilot scale. Pediatric patients under antibiotic treatment were monitored with either a pharmacokinetic/pharmacodynamic optimized sampling scheme or through opportunistic sampling. Clindamycin, fluconazole, linezolid, meropenem, metronidazole, piperacillin, and vancomycin plasma concentrations were quantified through a liquid chromatography coupled to mass spectrometry method. Pharmacokinetic parameters were estimated using a Bayesian approach to verify pharmacokinetic/pharmacodynamic target attainment. A total of 23 pediatric patients aged 2 to 16years were included, and 43 dosing regimens were evaluated; 27 (63%) of them required adjustments as follows: 14 patients were underdosed, 4 were overdosed, and 9 patients needed infusion rate adjustments. Infusion rate adjustments were mostly recommended for piperacillin and meropenem; daily doses were augmented for vancomycin and metronidazole, meanwhile linezolid was adjusted for under- and overdosing. Clindamycin and fluconazole regimens were not adjusted at all. Conclusion: Results showcase a lack of antibiotic pharmacokinetic/pharmacodynamic target attainment (particularly for linezolid, vancomycin, meropenem, and piperacillin), and the need for model-informed precision dosing in pediatrics. This study provides pharmacokinetic evidence which can further improve antibiotic dosing practices. What is Known: • Model-informed precision dosing is performed in pediatrics to optimize the treatment of antimicrobial drugs such as vancomycin and aminoglycosides, while its usefulness is debated for other groups (beta-lactams, macrolides, etc.). What is New: • Vulnerable pediatric subpopulations, such as critically ill or oncology patients, can benefit the most from model-informed precision dosing of antibiotics. • Model-informed precision dosing of linezolid, meropenem, piperacillin, and vancomycin is particularly useful in pediatrics, and further research mayimprove dosing practices altogether.

Impact of model-informed precision dosing on achievement of vancomycin exposure targets in pediatric patients with cystic fibrosis.

Vancomycin is commonly used to treat acute pulmonary exacerbations in pediatric patients with cystic fibrosis (CF) and a history of methicillin-resistant Staphylococcus aureus. Optimizing vancomycin exposure during therapy is essential and area under-the-curve (AUC)-guided dosing is now recommended. Model-informed precision dosing (MIPD) utilizing Bayesian forecasting is a powerful approach that can support AUC-guided dose individualization. The objective of the current study was to examine the impact of implementing an AUC-guided dose individualization approach supported via a MIPD clinical decision support (CDS) tool on vancomycin exposure, target attainment rate, and safety in pediatric patients with CF treated with vancomycin during clinical care. A retrospective chart review was performed in patients with CF at a single children's hospital comparing pre- and post-implementation of a MIPD approach for vancomycin supported by a cloud-based, CDS tool integrated into the electronic health record (EHR). In the pre-MIPD period, vancomycin starting doses of 60 mg/kg/day (<13 years) or 45 mg/kg/day (≥13 years) were used. Dose adjustment was guided by therapeutic drug monitoring (TDM) with a target trough 10-20 mg/L. In the post-MIPD period, starting dose and dose adjustment were based on the MIPD CDS tool predictions with a target 24 h AUC (AUC24 ) 400-600 mg*h/L. Exposure and target achievement rates were retrospectively calculated and compared. Rates of acute kidney injury (AKI) were also compared. Overall, 23 patient courses were included in the pre-MIPD period and 21 patient courses in the post-MIPD period. In the post-MIPD period, an individualized MIPD starting dose resulted in 71% of patients achieving target AUC24 compared to 39% in the pre-MIPD period (p < 0.05). After the first TDM and dose adjustment, target AUC24 achievement was also higher post-MIPD versus pre-MIPD (86% vs. 57%; p < 0.05). AKI rates were low and similar between periods (pre-MIPD 8.7% vs. post-MIPD 9.5%; p = 0.9). An MIPD approach implemented within a cloud-based, EHR-integrated CDS tool safely supported vancomycin AUC-guided dosing and resulted in high rates of target achievement.

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review.

Pharmacokinetic nomograms, equations, and software are considered the main tools available for Therapeutic Drug Monitoring (TDM). Model-informed precision dosing (MIPD) is an advanced discipline of TDM that allows dose individualization, and requires a software for knowledge integration and statistical calculations. Due to its precision and extensive applicability, the use of these software is widespread in clinical practice. However, the currently available evidence on these tools remains scarce. To review and summarize the available evidence on MIPD software tools to facilitate its identification, evaluation, and selection by users. An electronic literature search was conducted in MEDLINE, EMBASE, OpenAIRE, and BASE before July 2022. The PRISMA-ScR was applied. The main inclusion criteria were studies focused on developing software for use in clinical practice, research, or modelling. Twenty-eight software were classified as MIPD software. Ten are currently unavailable. The remaining 18 software were described in depth. It is noteworthy that all MIPD software used Bayesian statistical methods to estimate drug exposure and all provided a population model by default, except NONMEN. Pharmacokinetic software have become relevant tools for TDM. MIPD software have been compared, facilitating its selection for use in clinical practice. However, it would be interesting to standardize the quality and validate the software tools.

Acute Kidney Injury Incidence With Bayesian Dosing Software Versus 2-Level First-Order Area Under the Curve-Based Dosing of Vancomycin With Piperacillin-Tazobactam.

Background: Two methods of area under the curve (AUC) dosing are recommended in vancomycin consensus guidelines: first-order calculations utilizing 2 vancomycin concentrations or a Bayesian approach. It is unknown if there is a difference in acute kidney injury (AKI) between the 2 dosing strategies for patients receiving concomitant piperacillin-tazobactam and vancomycin (VPT). Objective: The objective of this study was to compare incidence of AKI in patients being administered VPT with first-order calculations versus model-informed precision dosing (MIPD)/Bayesian dosing. Methods: This was a single-center, retrospective, observational study at a community hospital. Patients who received VPT therapy for at least 48 hours were included. The primary outcome was overall incidence of AKI. Secondary outcomes included percentage target attainment with initial regimen, average serum creatinine increase, time to AKI, usable vancomycin levels, and need for temporary dialysis or intensive care unit admission. Results: There were 100 patients included (50 in the first-order group and 50 in the MIPD/Bayesian group). The overall incidence of AKI was lower in the MIPD/Bayesian group (12% vs 28%, P = 0.046). There was no difference in average serum creatinine increase, time to AKI, need for temporary dialysis, or intensive care unit admission. Patients in the MIPD/Bayesian group had a higher percentage of target attainment (46% vs 18%, P = 0.003) and usable vancomycin levels (98% vs 60%, P < 0.001). Conclusion and Relevance: In patients receiving VPT, model-informed precision dosing with Bayesian modeling resulted in a lower rate of AKI, higher target attainment, and more usable vancomycin levels compared with first-order AUC dosing. The small sample and retrospective nature of this study reinforces the need for additional data.

Model-Informed Precision Dosing Guidance of Ethosuximide Developed from a Randomized Controlled Clinical Trial of Childhood Absence Epilepsy.

Ethosuximide was identified as the optimal option for new-onset childhood absence epilepsy (CAE) in a randomized, two-phase dose escalation comparative effectiveness trial of ethosuximide, lamotrigine, and valproic acid. However, 47% of ethosuximide initial monotherapy participants experienced short-term treatment failure. This study aimed to characterize the initial monotherapy ethosuximide exposure-response relationship and to propose model-informed precision dosing guidance. Dose titration occurred over a 16-20-week period until patients experienced seizure freedom or intolerable side effects. Subjects with initial monotherapy failure were randomized to one of the other two medications and dose escalation was repeated. A population pharmacokinetic model was created using plasma concentration data (n = 1,320), collected at 4-week intervals from 211 unique participants during both the initial and second monotherapy phases. A logistic regression analysis was performed on the initial monotherapy cohort (n = 103) with complete exposure-response data. Eighty-four participants achieved seizure freedom with a wide range of ethosuximide area under the curves (AUC) ranging from 420 to 2,420 μg·h/mL. AUC exposure estimates for achieving a 50% and 75% probability of seizure freedom were 1,027 and 1,489 μg·h/mL, respectively, whereas the corresponding cumulative frequency of intolerable adverse events was 11% and 16%. Monte Carlo Simulation indicated a daily dose of 40 and 55 mg/kg to achieve 50% and 75% probability of seizure freedom in the overall population, respectively. We identified the need for adjusted mg/kg dosing in different body weight cohorts. This ethosuximide proposed model-informed precision dosing guidance to achieve seizure freedom carries promise to optimize initial monotherapy success for patients with CAE.

Establishment and Evaluation of a Parametric Population Pharmacokinetic Model Repository for Ganciclovir and Valganciclovir.

Ganciclovir and valganciclovir are used for prophylaxis and treatment of cytomegalovirus infection. However, there is great interindividual variability in ganciclovir's pharmacokinetics (PK), highlighting the importance of individualized dosing. To facilitate model-informed precision dosing (MIPD), this study aimed to establish a parametric model repository of ganciclovir and valganciclovir by summarizing existing population pharmacokinetic information and analyzing the sources of variability. (2) Methods: A total of four databases were searched for published population PK models. We replicated these models, evaluated the impact of covariates on clearance, calculated the probability of target attainment for each model based on a predetermined dosing regimen, and developed an area under the concentration-time curve (AUC) calculator using maximum a posteriori Bayesian estimation. (3) Results: A total of 16 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area) and renal function. The results show that 5 mg/kg/12 h of ganciclovir could make the AUC0-24h within 40-80 mg·h/L for 50.03% pediatrics but cause AUC0-24h exceeding the exposure thresholds for toxicity (120 mg·h/L) in 51.24% adults. (4) Conclusions: Dosing regimens of ganciclovir and valganciclovir should be adjusted according to body size and renal function. This model repository has a broad range of potential applications in MIPD.

Bayesian model-guided antimicrobial therapy in pediatrics.

Antimicrobials have transformed the practice of medicine, making life-threatening infections treatable, but determining optimal dosing, particularly in pediatric patients, remains a challenge. The lack of pediatric data can largely be traced back to pharmaceutical companies, which, until recently, were not required to perform clinical testing in pediatrics. As a result, most antimicrobial use in pediatrics is off-label. In recent years, a concerted effort (e.g., Pediatric Research Equality Act) has been made to fill these knowledge gaps, but progress is slow and better strategies are needed. Model-based techniques have been used by pharmaceutical companies and regulatory agencies for decades to derive rational individualized dosing guidelines. Historically, these techniques have been unavailable in a clinical setting, but the advent of Bayesian-model-driven, integrated clinical decision support platforms has made model-informed precision dosing more accessible. Unfortunately, the rollout of these systems remains slow despite their increasingly well documented contributions to patient-centered care. The primary goals of this work are to 1) provide a succinct, easy-to-follow description of the challenges associated with designing and implementing dose-optimization strategies; and 2) provide supporting evidence that Bayesian-model informed precision dosing can meet those challenges. There are numerous stakeholders in a hospital setting, and our intention is for this work to serve as a starting point for clinicians who recognize that these techniques are the future of modern pharmacotherapy and wish to become champions of that movement.

Dose optimisation of linezolid in critically ill patients based on a population pharmacokinetic model: A two-centre prospective interventional study

ObjectivesThis study evaluated the intervention effect of clinical pharmacist-mediated optimisation of a linezolid regimen using a population pharmacokinetic (PPK) model. MethodsPatients treated with linezolid in two medical centres from January 2020 to June 2021 were retrospectively included in the control group; those treated from July 2021 to June 2022 were prospectively enrolled in the intervention group. Clinical pharmacists optimised the dosage regimen according to a published linezolid PPK model in the intervention group. An interrupted times series approach was used to analyse the data. The incidence of linezolid-induced thrombocytopenia (LIT), target attainment of pharmacokinetic/pharmacodynamic parameters and other adverse drug reactions (ADRs) were compared between the two groups. ResultsIn total, 77 and 103 patients were enrolled in the control and intervention groups, respectively. The intervention group had a lower incidence of LIT and other ADRs than the control group (10.7% vs. 23.4%, P = 0.002; 1.0% vs. 7.8%, P = 0.027). The intervention group exhibited a considerably lower trough concentration (Cmin) and area under the concentration–time curve/MIC ratio (AUC24/MIC) (P = 0.001 and P < 0.001). Cmin and AUC24/MIC rates within the target range were substantially higher in the intervention group (49.6% vs. 20.0%, adjusted P < 0.05; 48.1% vs. 25.6%, adjusted P < 0.05). ConclusionInterventions by clinical pharmacists reduced the incidence of LIT and other ADRs. Implementation of model-informed precision dosing (MIPD) for linezolid markedly increased the Cmin and AUC24/MIC rates within the target range. We recommend MIPD-guided linezolid dose reduction for patients with renal impairment.

Population Pharmacokinetics of Total Rabbit Anti-thymocyte Globulin in Non-obese Adult Patients Undergoing Hematopoietic Cell Transplantation for Hematologic Malignancy.

Rabbit anti-thymocyte globulin (rATG), a therapeutic polyclonal antibody against human T cells, is commonly used in conditioning therapy prior to allogeneic hematopoietic cell transplantation (HCT). Previous studies successfully developed an individualized rATG dosing regimen based on "active" rATG population PK (popPK) analysis, while "total" rATG can be a more logistically favorable alternative for early HCT outcomes. We conducted a novel popPK analysis of total rATG. Total rATG concentration was measured in adult human-leukocyte antigen (HLA) mismatched HCT patients who received a low-dose rATG regimen (total 2.5-3mg/kg) within 3days prior to HCT. PopPK modeling and simulation was performed using nonlinear mixed effect modeling approach. A total of 504 rATG concentrations were available from 105 non-obese patients with hematologic malignancy (median age 47years) treated in Japan. The majority had acute leukemia or malignant lymphoma (94%). Total rATG PK was described by a two-compartment linear model. Influential covariate relations include ideal body weight [positively on both clearance (CL) and central volume of distribution], baseline serum albumin (negatively on CL), CD4+ T cell dose (positively on CL), and baseline serum IgG (positively on CL). Simulated covariate effects predicted that early total rATG exposures were affected by ideal body weight. This novel popPK model described the PK of total rATG in the adult HCT patients who received a low-dose rATG conditioning regimen. This model can be used for model-informed precision dosing in the settings with minimal baseline rATG targets (T cells), and early clinical outcomes are of interest.

External validation of population pharmacokinetic models of gentamicin in paediatric population from preterm newborns to adolescents.

The aim of this study was to externally validate the predictive performance of published population pharmacokinetic models of gentamicin in all paediatric age groups, from preterm newborns to adolescents. We first selected published population pharmacokinetic models of gentamicin developed in the paediatric population with a wide age range. The parameters of the literature models were then re-estimated using the PRIOR subroutine in NONMEM®. The predictive ability of the literature and the tweaked models was evaluated. Retrospectively collected data from a routine clinical practice (512 concentrations from 308 patients) were used for validation. The models with covariates characterising developmental changes in clearance and volume of distribution had better predictive performance, which improved further after re-estimation. The tweaked model by Wang 2019 performed best, with suitable accuracy and precision across the complete paediatric population. For patients treated in the intensive care unit, a lower proportion of patients would be expected to reach the target trough concentration at standard dosing. The selected model could be used for model-informed precision dosing in clinical settings where the entire paediatric population is treated. However, for use in clinical practice, the next step should include additional analysis of the impact of intensive care treatment on gentamicin pharmacokinetics, followed by prospective validation.

Failure to predict amikacin elimination in critically ill patients with cancer based on the estimated glomerular filtration rate: applying PBPK approach in a therapeutic drug monitoring study.

The aim of this work was to integrate the Therapeutic Drug Monitoring (TDM) with the model-informed precision dosing (MIPD) approach, using Physiologically-based Pharmacokinetic/Pharmacodynamic (PBPK/PD) modelling and simulation, to explore the relationship between amikacin exposure and estimated glomerular filtration rate (GFR) in critically ill patients with cancer. In the TDM study, samples from 51 critically-ill patients with cancer treated with amikacin were analysed. Patients were stratified according to renal function based on GFR status. A full-body PBPK model with 12 organs model was developed using Simcyp V. 21, including steady-state volume of distribution of 0.21 L/kg and renal clearance of 6.9 L/h in healthy adults. PK parameters evaluated were within the 2-fold error range. During the validation step, predicted vs observed amikacin clearance values after single infusion dose in patients with normal renal function, mild and moderate renal impairment were 7.6 vs 8.1 L/h (7.5mg/kg dose); 3.8 vs 4.5 L/h (1500mg dose) and 2.2 vs 3.1 L/h (25mg/kg dose), respectively. However, predicted vs observed amikacin clearance after a single dose infusion of 1400mg in critically-ill patients with cancer were 1.46 vs 1.63 (P = 0.6406) L/h (severe), 2.83 vs 1.08 (P < 0.05) L/h (moderate), 4.23 vs 2.49 (P = 0.0625) L/h (mild) and 7.41 vs 3.36 (P < 0.05) L/h (normal renal function). This study demonstrated that estimated GFR did not predict amikacin elimination in critically-ill patients with cancer. Further studies are necessary to find amikacin PK covariates to optimize the pharmacotherapy in this population. Therefore, TDM of amikacin is imperative in cancer patients.

Therapeutic Drug Monitoring Consulting Cannot be Ruled out by Model-Informed Precision Dosing.

Launay, Manon PharmD, PhD*; Correia, Patricia MD†; Thiery, Guillaume MD, PhD‡; Ragey, Sophie Perinel MD, PhD§ Author Information

Model-Informed Precision Dosing of Vancomycin in Adult Patients Undergoing Hemodialysis.

Model-informed precision dosing (MIPD) maximizes the probability of successful dosing in patients undergoing hemodialysis. In these patients, area under the concentration-time curve (AUC)-guided dosing is recommended for vancomycin. However, this model is yet to be developed. The purpose of this study was to address this issue. The overall mass transfer-area coefficient (KoA) was used for the estimation of vancomycin hemodialysis clearance. A population pharmacokinetic (popPK) model was developed, resulting in a fixed-effect parameter for nonhemodialysis clearance of 0.316 liters/h. This popPK model was externally evaluated, with a resulting mean absolute error of 13.4% and mean prediction error of -0.17%. KoA-predicted hemodialysis clearance was prospectively evaluated for vancomycin (n = 10) and meropenem (n = 10), with a correlation equation being obtained (slope of 1.099, intercept of 1.642; r = 0.927, P < 0.001). An experimental evaluation using an in vitro hemodialysis circuit validated the developed model of KoA-predicted hemodialysis clearance using vancomycin, meropenem, vitamin B6, and inulin in 12 hemodialysis settings. This popPK model indicated a maximum a priori dosing for vancomycin-a loading dose of 30 mg/kg, which achieves the target AUC for 24 h after first dose with a probability of 93.0%, ensured by a predialysis concentration of >15 μg/mL. Maintenance doses of 12 mg/kg after every hemodialysis session could achieve the required exposure, with a probability of 80.6%. In conclusion, this study demonstrated that KoA-predicted hemodialysis clearance may lead to an upgrade from conventional dosing to MIPD for vancomycin in patients undergoing hemodialysis.

Immunosuppressant adherence in adult outpatient hematopoietic cell transplant recipients.

Medication nonadherence continues to be challenging for allogeneic hematopoietic cell transplant (HCT) recipients. The risk and severity of chronic graft-versus-host disease (GVHD) are associated with low immunosuppressant concentrations (which can be improved with model-informed precision dosing (MIPD)) and with immunosuppressant nonadherence (which can be improved with acceptable interventions). With the goals of improving adherence and achieving therapeutic concentrations of immunosuppressants to eliminate GVHD, we characterized the feasibility of using the Medication Event Monitoring (MEMS®) Cap in adult HCT recipients. Of the 27 participants offered the MEMS® Cap at the time of hospital discharge, 7 (25.9%) used it, which is below our a priori threshold of 70%. These data suggest the MEMS® Cap is not feasible for HCT recipients. The MEMS® Cap data were available for a median of 35 days per participant per medication (range: 7-109 days). The average daily adherence per participant ranged from 0 to 100%; four participants had an average daily adherence of over 80%. MIPD may be supported by MEMS® technology to provide the precise time of immunosuppressant self-administration. The MEMS® Cap was used by only a small percentage (25.9%) of HCT recipients in this pilot study. In accordance with larger studies using less accurate tools to evaluate adherence, immunosuppressant adherence varied from 0% to 100%. Future studies should establish the feasibility and clinical benefit of combining MIPD with newer technology, specifically the MEMS® Button, which can inform the oncology pharmacist of the time of immunosuppressant self-administration.