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Serum creatinine in neonates follows complex dynamics due to maturation processes, most pronounced in the first few weeks of life. The development of a mechanism-based model describing complex dynamics requires high expertise in pharmacometric (PMX) modeling and substantial model development time. A recently published machine learning (ML) approach of low-dimensional neural ordinary differential equations (NODEs) is capable of modeling such data from newborns automatically. However, this efficient data-driven approach in itself does not result in a clinically interpretable model. In this work, an approach to deriving an interpretable model with reasonable PMX-type functions is presented. This "translation" was applied to derive a PMX model for serum creatinine in neonates considering maturation processes and covariates. The developed model was compared to a previously published mechanism-based PMX model whereas both models had similar mechanistic structures. The developed model was then utilized to simulate serum creatinine concentrations in the first few weeks of life considering different covariate values for gestational age and birth weight. The reference serum creatinine values derived from these simulations are consistent with observed serum creatinine values and previously published reference values. Thus, the presented NODE-based ML approach to model complex serum creatinine dynamics in newborns and derive interpretable, mathematical-statistical components similar to those in a conventional PMX model demonstrates a novel, viable approach to facilitate the modeling of complex dynamics in clinical settings and pediatric drug development., (© 2024 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

Understanding pharmacokinetics (PK) in children is a prerequisite to determine optimal pediatric dosing. As plasma sampling in children is challenging, alternative PK sampling strategies are needed. In this case study we evaluated the suitability of saliva as alternative PK matrix to simplify studies in infants, investigating metamizole, an analgesic used off-label in infants. Six plasma and 6 saliva PK sample collections were scheduled after a single intravenous dose of 10 mg/kg metamizole. Plasma/saliva pharmacometric (PMX) modeling of the active metabolites 4-methylaminoantipyrine (4-MAA) and 4-aminoantipyrine (4-AA) was performed. Various reduced plasma sampling scenarios were evaluated by PMX simulations. Saliva and plasma samples from 25 children were included (age range, 5-70 months; weight range, 8.7-24.8 kg). Distribution of metamizole metabolites between plasma and saliva was without delay. Estimated mean (individual range) saliva/plasma fractions of 4-MAA and 4-AA were 0.32 (0.05-0.57) and 0.57 (0.25-0.70), respectively. Residual variability of 4-MAA (4-AA) in saliva was 47% (28%) versus 17% (11%) in plasma. A simplified sampling scenario with up to 6 saliva samples combined with 1 plasma sample was associated with similar PK parameter estimates as the full plasma sampling scenario. This case study with metamizole shows increased PK variability in saliva compared to plasma, compromising its suitability as single matrix for PK studies in infants. Nonetheless, rich saliva sampling can reduce the number of plasma samples required for PK characterization, thereby facilitating the conduct of PK studies to optimize dosing in pediatric patients., (© 2024 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

Machine Learning (ML) is a fast-evolving field, integrated in many of today's scientific disciplines. With the recent development of neural ordinary differential equations (NODEs), ML provides a new tool to model dynamical systems in the field of pharmacology and pharmacometrics, such as pharmacokinetics (PK) or pharmacodynamics. The novel and conceptionally different approach of NODEs compared to classical PK modeling creates challenges but also provides opportunities for its application. In this manuscript, we introduce the functionality of NODEs and develop specific low-dimensional NODE structures based on PK principles. We discuss two challenges of NODEs, overfitting and extrapolation to unseen data, and provide practical solutions to these problems. We illustrate concept and application of our proposed low-dimensional NODE approach with several PK modeling examples, including multi-compartmental, target-mediated drug disposition, and delayed absorption behavior. In all investigated scenarios, the NODEs were able to describe the data well and simulate data for new subjects within the observed dosing range. Finally, we briefly demonstrate how NODEs can be combined with mechanistic models. This research work enhances understanding of how NODEs can be applied in PK analyses and illustrates the potential for NODEs in the field of pharmacology and pharmacometrics., (© 2023. The Author(s).)

The two main objectives of this analysis were to (i) characterize the relationship between immunoglobulin (Ig) exposure and chronic inflammatory demyelinating polyneuropathy (CIDP) disease severity using data from 171 patients with CIDP who received either subcutaneous Ig (IgPro20; Hizentra ® ) or placebo (PATH study), and to (ii) simulate and compare exposure coverage with various dosing approaches considering weekly dosing to be the reference dose. IgG pharmacokinetic (PK) parameters, including those from a previous population PK model, were used to predict individual IgG profile and exposure metrics. Treatment-related changes in Inflammatory Neuropathy Cause and Treatment (INCAT) scores were best described by a maximum effect (E max ) model as a function of ΔIgG (total serum IgG at INCAT score assessment minus baseline IgG levels before intravenous Ig restabilization). Simulations indicate that flexible dosing from daily to biweekly (every other week) provide an exposure coverage equivalent to that of a weekly Ig dose., (© 2021 CSL Behring. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

There is no consensus regarding optimal dosing of vancomycin in term or preterm neonates. Various available dosing recommendations are based on age, kidney function and/or body weight to define a starting dose. Our objectives were (i) to develop a comprehensive population PK model of vancomycin in a large cohort of neonates and (ii) to evaluate and compare the performances of current dosing approaches with respect to target attainment, using simulations based on our model. This will serve the purpose to recommend the best dosing approaches among existing regimens in the early and later phases after treatment initiation as a complementary approach to therapeutic drug monitoring (TDM). A total 405 neonates provided 1831 vancomycin concentrations measured during routine TDM. A one-compartment model with linear elimination incorporating covariates such as age, kidney function and body weight was developed (NONMEM®). The final model was applied to simulate in our population vancomycin exposure resulting from 20 dosing guidelines identified in the literature. Proportions of patients within and above target exposure were used as a performance measure. Target attainment meant area under the curve/minimal inhibitory concentration (AUC 24 /MIC) ratio of 400-700 h and trough concentration of 10-20 mg/L, both on days 1 and 7. Most current vancomycin dosing regimens fail to ensure target attainment in a majority of neonates. Insufficiently dosed regimens should be avoided, especially in centers with widespread coagulase negative Staphylococci. Adding a loading dose to simple regimens is best recommended to increase the proportion of early target attainment. Complex regimens seem to marginally improve exposure. Optimisation of efficacy while minimizing toxicity of vancomycin in neonates is needed. The application of a simple dosing regimens like NNF7 or the Neofax Hi-Dose regimens, with a 25 mg/kg loading dose for severe infections, or the SmPC regimen should be recommended to ensure the highest proportion of target attainment after 24 h. TDM should then be carried out, to account for residual unexplained variability in vancomycin elimination., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Urea dialyzer clearance (KD) has been suggested to be underpredicted from blood flow (QB), dialysate flow (QD), and in vitro mass transfer-area coefficient of urea (KoA) in pediatric hemodialysis (HD) patients using a widely accepted mechanistic equation. We characterize factors that could explain this, assuming that it results from a bias between reported in vitro and actual in vivo KoA. An adult urea kinetic model was scaled to 923 patients aged 1-29 years based on pediatric physiologic knowledge (intercompartmental clearance, volumes of distribution). Using data from 2,676 HD sessions of those patients (pre-/post-HD urea concentrations and HD treatment parameters), mixed effect modeling was applied to estimate individual KoA correction factors (fKoA) required for unbiased KD and post-HD urea concentration predictions in vivo. QD/QB ratio was most strongly associated with individual fKoA estimates (P < 0.001; fKoA = -1%, 18%, and 110% at QD/QB ratios of 1.5, 2, and 5). Additional factors included in the model were filter flux (-12% lower fKoA for low- vs high-flux filters), ultra-filtration rate, and true QB (lower than nominal QB ≥200 ml/min). Of note, high QD/QB ratios used in children ≤6 years were associated with significant underprediction of KD in vivo, with post-HD urea concentrations being 23% lower than expected. In conclusion, dialyzers should be characterized under pediatric conditions where high QD/QB ratios are used. Our model can be used to prevent underestimation of urea clearance, allowing shorter dialysis sessions, higher quality of life, and individualized treatment prescription in children on maintenance HD.

Purpose: The prodrug metamizole is prescribed intravenously for postoperative pain in children, including off-label use in infants < 1 year. We aimed to assess the pharmacokinetics of the main metabolites of metamizole in children aged 3-72 months., Methods: A single dose of 10 mg/kg metamizole was administered intravenously for postoperative analgesia. Pharmacokinetic samples were drawn at predefined time points. Pharmacokinetics of the main active metabolite 4-methylaminoantipyrine and three other metabolites was characterized by both non-compartmental and population pharmacokinetic analysis. AUC 0-inf of 4-methylaminoantipyrine was calculated by non-compartmental analysis for two age cohorts (3-23 months, 2-6 years) and compared with the 80-125% range of adult dose-adjusted reference exposure (AUC ref ). Population pharmacokinetic analysis investigated age and weight dependency of the pharmacokinetics and optimal dosing strategies to achieve equivalent adult exposure., Results: A total of 25 children aged 5 months-5.8 years (7.8-24.8 kg) with at least one concentration sample were included; 19 children had ≥ 5 predefined samples up to 10 h after metamizole dose administration. AUC 0-inf of 4-methylaminoantipyrine in children 2-6 years was 29.9 mg/L/h (95% CI 23.4-38.2), significantly lower than AUC ref (80-125% range 39.2-61.2 mg/L/h). AUC 0-inf of 4-methylaminoantipyrine in infants < 2 years was 43.6 mg/L/h (95% CI 15.8-119.0), comparable with AUC ref , while infants < 12 months showed increased exposure. Observed variability could be partially explained by covariates weight and age., Conclusions: Age-related changes in pharmacokinetics of 4-methylaminoantipyrine requires reduced weight-based IV dosing in infants < 1 year compared with infants and children up to 6 years (5 versus 10-20 mg/kg) to achieve equivalent adult exposure., Trial Registration: ClinicalTrials.gov identifier: NCT02660177 .

Aims: A dramatic increase in newborn infants with neonatal abstinence syndrome has been observed and these neonates are frequently treated with complex methadone dosing schemes to control their withdrawal symptoms. Despite its abundant use, hardly any data on the pharmacokinetics (PK) of methadone is available in preterm neonates. Therefore we investigated developmental PK of methadone and evaluated current dosing strategies and possible simplification in this vulnerable population., Methods: A single-centre open-label prospective study was performed to collect PK data after a single oral dose of methadone in preterm neonates. A population PK model was built to characterize developmental PK of (R)- and (S)-methadone. Model-based simulations were performed to identify a simplified dosing strategy to reach and maintain target methadone exposure., Results: A total of 121 methadone concentrations were collected from 31 preterm neonates. A one-compartment model with first order absorption and elimination kinetics best described PK data for (R)- and (S)-methadone. Clearance increases with advancing gestational age and differs between R- and S-enantiomer, being slightly higher for the former (0.244 vs 0.167 L/h). Preterm neonates reached target exposure after 48 hours with currently used dosing schedules. Output from simulations revealed that target exposures can be achieved with a simplified dosing strategy during the first 4 days of treatment., Conclusion: Methadone clearance in preterm neonates increases with advancing gestational age and its disposition is influenced by its chirality. Simulations that account for developmental PK changes indicate a shorter methadone dosing strategy can maintain target exposure to control withdrawal symptoms., (© 2019 The British Pharmacological Society.)

Ceftazidime is a parenteral cephalosporin frequently used in pregnant women for treatment of urinary tract or intrauterine infections. Despite its regular use in pregnant women, ceftazidime disposition in both mother and fetus is not well understood, and a pharmacokinetic (PK) model that allows characterization and simulation of both maternal and preterm neonatal ceftazidime disposition is not available. In this study, 10 pregnant women with suspected or proven intrauterine infections in the late second and early third trimester were treated with 1 g of ceftazidime intravenously every 6 hours. During ceftazidime treatment, one maternal and umbilical cord blood sample was taken at delivery to quantify ceftazidime concentrations in the mother and preterm neonate. Data showed that ceftazidime concentrations in the mother were comparable to those observed in the neonate. Based on these data, a PK model was developed to describe maternal disposition, ceftazidime distribution over the placenta, and elimination in the neonate. The maternal substructure of the model was parameterized according to a previously reported ceftazidime model with minor adjustments to account for pregnancy-related effects on renal elimination of ceftazidime. The expanded population PK model with an additional neonatal compartment was fitted to measured drug concentrations in the neonate. The neonatal elimination rate constant at delivery was close to that estimated for the mother. The presented results show that ceftazidime readily crosses the placenta and indicate that perinatal PK behavior of ceftazidime in preterm neonates can be expected to be similar to those observed in their mothers., (© 2018, The American College of Clinical Pharmacology.)

Introduction: In addition to tailored clinical trials in patients on chronic hemodialysis (HD) during drug development, clinician-initiated post-marketing studies and case reports on individual pharmacokinetic (PK) assessments provide an important source of information about drug dialysability and individualized dose recommendations in this vulnerable population. Areas covered: First, factors that may alter drug exposure in HD patients are explained. Second, available regulatory and methodological guidelines for PK assessments in this population are summarized. Third, a 4-step approach is proposed to develop individual dose recommendations for HD patients receiving drugs without data from a PK study: (1) literature search, (2) model-based dosage decisions, (3) validation and refinement through concentration monitoring, and (4) publication of relevant observations. Fourth, clinician-initiated PK assessments and case reports to evaluate and individualize use of drugs in HD patients are reviewed, and recommendations to enhance their quality are discussed. Expert commentary: Guidance on collecting and reporting PK information in individual HD patients is warranted to ensure completeness and consistency of such PK studies. A checklist and template for easy-to-implement PK calculations and pharmacometric modeling is provided to facilitate evaluation and individualization of dosing strategies in these patients.

The effects of altered gastric emptying on glucose absorption and kinetics are not well understood in nondiabetic obese adults. The aim of this work was to develop a physiology-based model that can characterize and compare interactions among gastric emptying, glucose absorption, and glycemic control in nondiabetic obese and lean healthy adults. Dynamic glucose, insulin, and gastric emptying (measured with breath test) data from 12 nondiabetic obese and 12 lean healthy adults were available until 180 min after an oral glucose tolerance test (OGTT) with 10, 25, and 75 g of glucose. A physiology-based model was developed to characterize glucose kinetics applying nonlinear mixed-effects modeling with NONMEM7.3. Glucose kinetics after OGTT was described by a one-compartment model with an effect compartment to describe delayed insulin effects on glucose clearance. After the interactions between individual gastric emptying and glucose absorption profiles were accounted for, the glucose absorption rate was found to be similar in nondiabetic obese and lean controls. Baseline glucose concentration was estimated to be only marginally higher in nondiabetic obese subjects (4.9 vs. 5.2 mmol/l), whereas insulin-dependent glucose clearance in nondiabetic obese subjects was found to be cut in half compared with lean controls (0.052 vs. 0.029 l/min) and the insulin concentration associated with 50% of insulin-dependent glucose elimination rate was approximately twofold higher in nondiabetic obese subjects compared with lean controls (7.1 vs. 15.3 μU/ml). Physiology-based models can characterize and compare the dynamic interaction among gastric emptying, glucose absorption and glycemic control in populations of interest such as lean healthy and nondiabetic obese adults., (Copyright © 2017 the American Physiological Society.)

The draft United States Food and Drug Administration guidance recommends a dedicated pharmacokinetic (PK) study for most drugs intended for use in patients with chronic kidney disease (CKD), including stage V patients requiring hemodialysis (HD) treatment. However, clinical studies conducted in CKD patients are challenged by difficulties in recruiting stage IV and V patients not yet on dialysis, and in balancing patient characteristics among each studied CKD group. Furthermore, study design for dialysis patients often involves a single dose administered before an HD session. The design may not necessarily represent usual patient care in current clinical practice, in which multiple doses are more likely to be administered at varying times between HD sessions. Using exposure modeling of saxagliptin and its active metabolite, 5-hydroxy saxagliptin, as an example, this work illustrates how these challenges can be alleviated by modeling the impact of HD on drug exposure in clinical studies and simulating the expected exposure level in patient care. The modeled PK profiles in dialysis patients were used to understand PK profiles in patients with various CKD stages. The applied pharmacometric approach increased the efficiency of knowledge generation from existing data.

Atazanavir (Reyataz; ATV) is a well-tolerated protease inhibitor (PI) that is indicated as a once-daily treatment for HIV infections. These features of ATV, combined with its virologic potency, make it particularly desirable for the treatment of HIV-infected pediatric patients. The objective of this study was to use a model-based approach to recommend body weight-based ATV capsule doses for pediatric patients. ATV concentration-time data from three adult studies and one pediatric study were described by a C(0)-delinked one-compartment model to guard against introducing bias in pharmacokinetic (PK) parameter estimates due to the potential nonadherence in outpatient studies. The apparent clearance (CL/F) and apparent volume of distribution (V/F) were determined to increase with body weight, and CL/F was 40.9% lower in patients receiving ATV comedication with ritonavir (RTV). The relative bioavailability (F(rel)) of ATV was 132% higher with RTV comedication and was 35.5% lower for the ATV powder formulation than the capsule formulation. Model-based simulations were used to recommend weight-based ATV capsule doses of 150 to 300 mg boosted with 100 mg RTV for pediatric patients weighing ≥15 kg, such that the exposures in these patients are similar to those obtained in HIV-infected adults treated with the recommended ATV/RTV dose of 300/100 mg.

Systematic implementation of model-based drug development (MBDD) to drug discovery and development has the potential to significantly increase the rate of medical breakthroughs and make available new and better treatments to patients. An analysis of the strengths, weaknesses, opportunities, and threats (ie, SWOT) was conducted through focus group discussions that included 24 members representing 8 pharmaceutical companies to systematically assess the challenges to implementing MBDD into the drug development decision-making process. The application of the SWOT analysis to the successful implementation of MBDD yielded 19 strengths, 27 weaknesses, 34 opportunities, and 22 threats, which support the following conclusions. The shift from empirical drug development to MBDD requires a question-based mentality; early, proactive planning; dynamic access to multisource data; quantitative knowledge integration; multidisciplinary collaboration; effective communication and leadership skills; and innovative, impactful application of pharmacometrics focused on enhancing quantitative decision making. The ultimate goal of MBDD is to streamline discovery and development of innovative medicines to benefit patients.

During the past decade, the pharmaceutical industry has seen the increasing application of pharmacometrics approaches in drug development. However, the full potential of incorporating model-based approaches in drug development and its impact on decision making has not been fully realized to date. In 2009, a survey on model-based drug development (MBDD) was conducted (1) to further understand the current state of MBDD in the pharmaceutical industry and (2) to identify opportunities to realize the full potential of MBDD. Ten large and mid-sized pharmaceutical companies provided responses to this survey. The results indicate that MBDD is achieving broad application in early and late development and is positively affecting both internal and regulatory decisions. Senior leadership (vice president and higher) within the companies indicated widely accepted utility for dose selection and gaining acceptance for study design and regulatory interactions but limited acceptance in discovery and commercial/pipeline decisions. Mounting appreciation for the impact of MBDD on internal and regulatory decision-making bodes well for the future of the pharmacometric discipline and the growth of opportunities to realize the full potential of MBDD.

Characterizing the key determinants of variability in the exposure of orally administered drugs may be important in understanding the implications of exposure variability on clinical responses. In particular, partitioning overall variability into interoccasion variability (IOV) and interindividual variability (IIV) allows a better assessment of the clinical importance of exposure variability. The IOV characterizes the dose-to-dose variability in exposure within a subject and is likely to be less clinically relevant than IIV for chronically administered drugs as the effect of IOV averages out over repeated dosing. The main aims of this model-based analysis were (1) to characterize the IOV and IIV of dasatinib, a novel, orally administered, multitargeted kinase inhibitor of BCR-ABL and SRC family kinases that is indicated for the treatment of chronic myeloid leukemia and Philadelphia-positive acute lymphoblastic leukemia and (2) to demonstrate using simulated data that it is possible to estimate IIV and IOV in relative bioavailability (F(R)) of an orally administered drug, given an adequate sampling scheme. Variability in dasatinib exposure was estimated to be mainly due to IOV in F(R) (44% coefficient of variation [CV]) and, to a lesser extent, due to IIV in F(R) and IIV in clearance (32% and 25% CV, respectively). The IIV is expected to be more clinically relevant than IOV for chronically administered oral drugs such as dasatinib, as the overall variability in cumulative exposure will be mainly due to IIV. The analysis of simulated data demonstrated that models ignoring either IIV or IOV in F(R) resulted in upwardly biased estimates of interindividual or residual variability. Thus, it may be important to account for both IIV and IOV in F(R), particularly for orally administered agents that exhibit absorption-related variability in exposure.

Abatacept is a recombinant soluble fusion protein that inhibits the CD80/CD86:CD28 costimulatory signal required for T cell activation and has demonstrated efficacy in the treatment of rheumatoid arthritis. The objectives of this analysis were to provide support for a body weight-tiered dosing regimen approximating 10 mg/kg by (1) quantifying the effect of body weight on exposure and (2) characterizing the relationship between exposure and serum interleukin (IL)-6 concentration. The abatacept exposure and exposure-response models were developed with 2148 abatacept serum concentrations (from 388 subjects) and 1894 IL-6 serum concentrations (from 799 subjects), respectively, followed by simulation with these models to address the above objectives. Abatacept exposure was characterized by a linear 2-compartmental model, in which clearance was linearly related to body weight. The IL-6 response was characterized by an indirect-response model, in which the IL-6 production rate increased with baseline C-reactive protein levels. Model-based simulations demonstrated that body weight-tiered dosing was desirable to ensure consistent steady-state abatacept trough concentrations across a range of body weights; doses approximating 10 mg/kg (500, 750, 1000 mg for subjects weighing <60, 60-100, and >100 kg, respectively) provided consistent exposure across the body weight groups. In addition, doses >10 mg/kg did not result in further increases in IL-6 suppression. These modeling and simulation results indicate that the body weight-tiered abatacept therapeutic doses approximating 10 mg/kg will ensure consistent abatacept exposure and optimal IL-6 suppression.