Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy.

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Radiation in Combination with Immune Checkpoint Blockade and DNA Damage Response Inhibitors in Mice: Dosage Optimization in MC38 Syngeneic Tumors via Modelling and Simulation.

Clinical trials assessing the impact of radiotherapy (RT) in combination with DNA damage response pathway inhibitors (DDRis) and/or immune checkpoint blockade are currently ongoing. However, current methods for optimizing dosage and schedule are limited. A mathematical model was developed to capture the impacts of RT in combination with DDRi and/or anti-PD-L1 [immune checkpoint inhibitor (ICI)] on tumor immune interactions in the MC38 syngeneic tumor model. The model was fitted to datasets that assessed the impact of RT in combination with the DNA protein kinase inhibitor (DNAPKi) AZD7648. The model was further fitted to datasets from studies that were used to assess both RT/ICI combinations as well as RT/ICI combinations followed by concurrent administration of the poly ADP ribose polymerase inhibitor (PARPi) olaparib. Nonlinear mixed-effects modeling was performed followed by internal validation with visual predictive checks (VPC). Simulations of alternative dosage regimens and scheduling were performed to identify optimal candidate dosage regimens of RT/DNAPKi and RT/PARPi/ICI. Model fits and VPCs confirmed a successful internal validation for both datasets and demonstrated very small differences in the median, lower, and upper percentile values of tumor diameters between RT/ICI and RT/PARPi/ICI, which indicated that the triple combination of RT/PARPi/ICI at the given dosage and schedule does not provide additional benefit compared with ICI in combination with RT. Simulation of alternative dosage regimens indicated that lowering the dosage of ICI to between 2 and 4 mg/kg could induce similar benefits to the full dosage regimen, which could be of translational benefit. SIGNIFICANCE STATEMENT: This work provides a mixed-effects model framework to quantify the effects of combination radiotherapy/DNA damage response pathway inhibitors/immune checkpoint inhibitors in preclinical tumor models and identify optimal dosage regimens, which could be of translational benefit.

Exploring the Boundaries for In Vitro-In Vivo Extrapolation: Use of Isolated Rat Hepatocytes in Co-culture and Impact of Albumin Binding Properties in the Prediction of Clearance of Various Drug Types.

Prediction of hepatic clearance of drugs (via uptake or metabolism) from in vitro systems continues to be problematic, particularly when plasma protein binding is high. The following work explores simultaneous assessment of both clearance processes, focusing on a commercial hepatocyte-fibroblast co-culture system (HµREL) over a 24-hour period using six probe drugs (ranging in metabolic and transporter clearance and low-to-high plasma protein binding). A rat hepatocyte co-culture assay was established using drug depletion (measuring both medium and total concentrations) and cell uptake kinetic analysis, both in the presence and absence of plasma protein (1% bovine serum albumin). Secretion of endogenous albumin was monitored as a marker of viability, and this reached 0.004% in incubations (at a rate similar to in vivo synthesis). Binding to stromal cells was substantial and required appropriate correction factors. Drug concentration-time courses were analyzed both by conventional methods and a mechanistic cell model prior to in vivo extrapolation. Clearance assayed by drug depletion in conventional suspended rat hepatocytes provided a benchmark to evaluate co-culture value. Addition of albumin appeared to improve predictions for some compounds (where fraction unbound in the medium is less than 0.1); however, for high-binding drugs, albumin significantly limited quantification and thus predictions. Overall, these results highlight ongoing challenges concerning in vitro hepatocyte system complexity and limitations of practical expediency. Considering this, more reliable measurement of hepatically cleared compounds seems possible through judicious use of available hepatocyte systems, including co-culture systems, as described herein; this would include those compounds with low metabolic turnover but high active uptake clearance. SIGNIFICANCE STATEMENT: Co-culture systems offer a more advanced tool than standard hepatocytes, with the ability to be cultured for longer periods of time, yet their potential as an in vitro tool has not been extensively assessed. We evaluate the strengths and limitations of the HµREL system using six drugs representing various metabolic and transporter-mediated clearance pathways with various degrees of albumin binding. Studies in the presence/absence of albumin allow in vitro-in vivo extrapolation and a framework to maximize their utility.

Evaluation of area under the concentration curve adjusted by the terminal-phase as a metric to reduce the impact of variability in bioequivalence testing.

AIM: To quantify the utility of a terminal-phase adjusted area under the concentration curve method in increasing the probability of a correct and conclusive outcome of a bioequivalence (BE) trial for highly variable drugs when clearance (CL) varies more than the volume of distribution (V). METHODS: Data from a large population of subjects were generated with variability in CL and V, and used to simulate a two-period, two-sequence crossover BE trial. The 90% confidence interval for formulation comparison was determined following BE assessment using the area under the concentration curve (AUC) ratio test, and the proposed terminal-phase adjusted AUC ratio test. An outcome of bioequivalent, nonbioequivalent or inconclusive was then assigned according to predefined BE limits. RESULTS: When CL varied more than V, the proposed approach enhanced the probability of correctly assigning bioequivalent or nonbioequivalent and reduced the risk of an inconclusive trial. For a hypothetical drug with between-subject variability of 35% for CL and 10% for V, when the true test-reference ratio of bioavailability was 1.15, a crossover study of n = 14 subjects analysed by the proposed method would have 80% or 20% probability of claiming bioequivalent or nonbioequivalent, compared to 22%, 46% or 32% probability of claiming bioequivalent, nonbioequivalent or inconclusive using the standard AUC ratio test. CONCLUSIONS: The terminal-phase adjusted AUC ratio test represents a simple and readily applicable approach to enhance the BE assessment of drug products when CL varies more than V.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats.

Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug-drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro-in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis-Menten constant (Km,u) of gadoxetate was 106 µM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK-IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE-MRI profiles and elimination from the liver. Therefore, in vivo rat DCE-MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE-MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.

Dose individualisation in oncology using chemotherapy-induced neutropenia: Example of docetaxel in non-small cell lung cancer patients.

AIMS: Chemotherapy-induced neutropenia has been associated with an increase in overall survival in non-small cell lung cancer patients. Therefore, neutrophil counts could be an interesting biomarker for drug efficacy as well as linked directly to toxicity. For drugs where neutropenia is dose limiting, neutrophil counts might be used for monitoring drug effect and for dosing optimisation. METHODS: The relationship between drug effect on the first cycle neutrophil counts and patient survival was explored in a Phase III clinical trial where patients with non-small cell lung cancer were treated with docetaxel. Once the association has been established, dosing optimisation was performed for patients with severe toxicities (neutropenia) without compromising drug efficacy (overall survival). RESULTS: After taking into account baseline prognostic factors, such as Eastern Cooperative Oncology Group performance status, smoking status, liver metastasis, tumour burden, neutrophil counts and albumin levels, a model-predicted drug effect on the first cycle neutrophil counts was strongly associated with patient survival (P = .005). Utilising this relationship in a dose optimisation algorithm, 194 out of 366 patients would have benefited from a dose reduction after the first cycle of docetaxel. The simulated 1-year survival probabilities associated with the original dose and the individualised dose were not different. CONCLUSION: The strong relationship between drug effect on the first cycle neutrophil counts and patient survival suggests that this variable could be used to individualise dosing, possibly without needing pharmacokinetic samples. The algorithm highlights that doses could be reduced in case of severe haematological toxicities without compromising drug efficacy.

Comprehensive Evaluation of the Utility of 20 Endogenous Molecules as Biomarkers of OATP1B Inhibition Compared with Rosuvastatin and Coproporphyrin I.

Endogenous biomarkers can be clinically relevant tools for the assessment of transporter function in vivo and corresponding drug-drug interactions (DDIs). The aim of this study was to perform systematic evaluation of plasma data obtained for 20 endogenous molecules in the same healthy subjects (n = 8-12) in the absence and presence of organic anion transporting polypeptide (OATP) inhibitor rifampicin (600 mg, single dose). The extent of rifampicin DDI magnitude [the ratio of the plasma concentration-time area under the curve (AUCR)], estimated fraction transported (fT), and baseline variability was compared across the biomarkers and relative to rosuvastatin and coproporphyrin I (CPI). Out of the 20 biomarkers investigated tetradecanedioate (TDA), hexadecanedioate (HDA), glycocholic acid, glycodeoxycholic acid (GDCA), taurodeoxycholic acid (TDCA), and coproporphyrin III (CPIII) showed the high AUCR (2.1-8.5) and fT (0.5-0.76) values, indicative of substantial OATP1B-mediated transport. A significant positive correlation was observed between the individual GDCA and TDCA AUCRs and the magnitude of rosuvastatin-rifampicin interaction. The CPI and CPIII AUCRs were significantly correlated, but no clear trend was established with the rosuvastatin AUCR. Moderate interindividual variability (15%-62%) in baseline exposure and AUCR was observed for TDA, HDA, and CPIII. In contrast, bile acids demonstrated high interindividual variability (69%-113%) and significant decreases in baseline plasma concentrations during the first 4 hours. This comprehensive analysis in the same individuals confirms that none of the biomarkers supersede CPI in the evaluation of OATP1B-mediated DDI risk. Monitoring of CPI and GDCA/TDCA may be beneficial for dual OATP1B/sodium-taurocholate cotransporting polypeptide inhibitors with consideration of challenges associated with large inter- and intraindividual variability observed for bile acids. Benefit of monitoring combined biomarkers (CPI, one bile acid and one fatty acid) needs to be confirmed with larger data sets and against multiple OATP1B clinical probes and perpetrators.

Development and validation of a methotrexate adherence assay.

BACKGROUND: The first-line therapy for rheumatoid arthritis (RA) is weekly oral methotrexate (MTX) at low dosages (7.5-25 mg/week). However, ~40% of patients are non-adherent which may explain why some do not respond and need to start more expensive biological therapies. To monitor adherence more accurately and develop strategies to improve it, a validated objective MTX adherence test is required. OBJECTIVE: To develop and validate the diagnostic accuracy of a novel MTX adherence assay using high-performance liquid chromatography-selected reaction monitoring- mass spectrometry (HPLC-SRM-MS) based biochemical analysis of drug levels. METHODS: 20 patients with RA underwent MTX pharmacokinetic assessment using HPLC-SRM-MS MTX plasma concentration analysis over a 6-day period. Directly observed therapy was the reference standard. Pharmacokinetic model validation was performed using independent plasma samples from real-world patients (n=50) with self-reported times of drug administration. Following assay optimisation, the sensitivity of the assay to detect adherence was established using samples from an observational cohort study (n=138). RESULTS: A two-compartment pharmacokinetic model was developed and validated. Simulations described the sensitivity required for MTX detection over 7 days; subsequent assay optimisation and retesting of samples confirmed that all patients were correctly identified as MTX adherers. Using real-world samples, the assays sensitivity was 95%. CONCLUSION: Non-adherence to MTX is common and can have a significant effect on disease activity. HPLC-SRM-MS plasma analysis accurately detects MTX adherence. The validated objective test could easily be used in clinic to identify patients requiring adherence support.

A population pharmacokinetic model for simvastatin and its metabolites in children and adolescents.

PURPOSE: Poor adherence to dietary/behaviour modifications as interventions for hypercholesterolemia in paediatric patients often necessitates the initiation of statin therapy. The aim of this study was to develop a joint population pharmacokinetic model for simvastatin and four metabolites in children and adolescents to investigate sources of variability in simvastatin acid exposure in this patient population, in addition to SLCO1B1 genotype status. METHODS: Plasma concentrations of simvastatin and its four metabolites, demographic and polymorphism data for OATP1B1 and CYP3A5 were analysed utilising a population pharmacokinetic modelling approach from an existing single oral dose (10 mg < 17 years and 20 mg ≥ 18 years) pharmacokinetic dataset of 32 children and adolescents. RESULTS: The population PK model included a one compartment disposition model for simvastatin with irregular oral absorption described by two parallel absorption processes each consisting of sequential zero and first-order processes. The data for each metabolite were described by a one-compartment disposition model with the formation and elimination apparent parameters estimated. The model confirmed the statistically significant effect of c.521T>C (rs4149056) on the pharmacokinetics of the active metabolite simvastatin acid in children/adolescents, consistent with adult data. In addition, age was identified as a covariate affecting elimination clearances of 6-hydroxymethyl simvastatin acid and 3, 5 dihydrodiol simvastatin metabolites. CONCLUSION: The model developed describes the pharmacokinetics of simvastatin and its metabolites in children/adolescents capturing the effects of both c.521T>C and age on variability in exposure in this patient population. This joint simvastatin metabolite model is envisaged to facilitate optimisation of simvastatin dosing in children/adolescents.

A study of the dosage and duration for levobupivacaine infusion by the caudal-epidural route in infants aged 3-6 months.

BACKGROUND: The local anesthetic, levobupivacaine, is the safer enantiomer of racemic bupivacaine. Present protocols for levobupivacaine are based on studies and pharmacokinetic modeling with racemic bupivacaine. AIMS: The aim is to investigate total serum levobupivacaine concentrations after a caudalepidural loading dose followed by a maintenance infusion over 48 hours in infants aged 3-6 months. METHODS: The clinical trial was conducted in eight infants aged 3-6 months, undergoing bladder exstrophy repair. Pharmacokinetic modeling allowed optimization of clinical sampling to measure total levobupivacaine and α1 -acid glycoprotein and prediction of the effect of α1 -acid glycoprotein on levobupivacaine plasma protein binding. RESULTS: The observed median total levobupivacaine serum concentration was 0.30 mg/L (range: 0.20-0.70 mg/L) at 1 hour after the loading dose of 2 mg/kg. The median total levobupivacaine concentration after 47 hours of infusion, at 0.2 mg/kg/h, was 1.21 mg/L (0.07-1.85 mg/L). Concentrations of α1 -acid glycoprotein were found to rise throughout the study period. Pharmacokinetic modeling suggested that unbound levobupivacaine quickly reached steady state at a concentration of approximately 0.03 mg/L. CONCLUSION: The study allows the development of a pharmacokinetic model, combining levobupivacaine and α1 -acid glycoprotein data. Modeling indicates that unbound levobupivacaine quickly reaches steady state once the infusion is started. Simulations suggest that it may be possible to continue the infusion beyond 48 hours.

Capsaicin-evoked cough responses in asthmatic patients: Evidence for airway neuronal dysfunction.

BACKGROUND: Cough in asthmatic patients is a common and troublesome symptom. It is generally assumed coughing occurs as a consequence of bronchial hyperresponsiveness and inflammation, but the possibility that airway nerves are dysfunctional has not been fully explored. OBJECTIVES: We sought to investigate capsaicin-evoked cough responses in a group of patients with well-characterized mild-to-moderate asthma compared with healthy volunteers and assess the influences of sex, atopy, lung physiology, inflammation, and asthma control on these responses. METHODS: Capsaicin inhalational challenge was performed, and cough responses were analyzed by using nonlinear mixed-effects modeling to estimate the maximum cough response evoked by any concentration of capsaicin (Emax) and the capsaicin dose inducing half-maximal response (ED50). RESULTS: Ninety-seven patients with stable asthma (median age, 23 years [interquartile range, 21-27 years]; 60% female) and 47 healthy volunteers (median age, 38 years [interquartile range, 29-47 years]; 64% female) were recruited. Asthmatic patients had higher Emax and lower ED50 values than healthy volunteers. Emax values were 27% higher in female subjects (P = .006) and 46% higher in patients with nonatopic asthma (P = .003) compared with healthy volunteers. Also, patients with atopic asthma had a 21% lower Emax value than nonatopic asthmatic patients (P = .04). The ED50 value was 65% lower in female patients (P = .0001) and 71% lower in all asthmatic patients (P = .0008). ED50 values were also influenced by asthma control and serum IgE levels, whereas Emax values were related to 24-hour cough frequency. Age, body mass index, FEV1, PC20, fraction of exhaled nitric oxide, blood eosinophil counts, and inhaled steroid treatment did not influence cough parameters. CONCLUSION: Patients with stable asthma exhibited exaggerated capsaicin-evoked cough responses consistent with neuronal dysfunction. Nonatopic asthmatic patients had the highest cough responses, suggesting this mechanism might be most important in type 2-low asthma phenotypes.

Study design and population pharmacokinetic analysis of a phase II dose-ranging study of interleukin-1 receptor antagonist.

Interleukin-1 receptor antagonist, a naturally-occurring antagonist to the pro-inflammatory cytokine Interleukin-1, is already in clinical use. In experimental models of stroke, Interleukin-1 receptor antagonist in cerebrospinal fluid has been associated with cerebral neuroprotection and in a phase I clinical trial in patients with subarachnoid haemorrhage it crosses the blood-cerebrospinal fluid barrier. The aims of the current work were to design a dose-ranging clinical study in patients and to analyse the plasma and cerebrospinal fluid data obtained using a population pharmacokinetic modelling approach. The study was designed using prior information: a published population pharmacokinetic model and associated parameter estimates. Simulations were carried out to identify combinations of intravenous bolus and 4 h infusion doses that could achieve a concentration of 100 ng/ml in cerebrospinal fluid within approximately 30 min. The most informative time points for plasma and cerebrospinal fluid were obtained prospectively; optimisation identified five sampling time points that were included in the 15 time points in the present study design. All plasma and cerebrospinal fluid concentration data from previous and current studies were combined for updated analysis. The result of the simulations showed that a dosage regimen of 500 mg intravenous bolus and 10 mg/kg/h could achieve the target concentration, however four other regimens that represent a stepwise increase in maximum concentration were also selected. Analysis of the updated data showed improvement in parameter accuracy and predictive performance of the model; the percentage relative standard errors for fixed and random-effects parameters were <15 and 35% respectively. A dose-ranging study was successfully designed using modelling and simulation.

Physiologically based pharmacokinetic model for 6-mercpatopurine: exploring the role of genetic polymorphism in TPMT enzyme activity.

AIMS: To extend the physiologically based pharmacokinetic (PBPK) model developed for 6-mercaptopurine to account for intracellular metabolism and to explore the role of genetic polymorphism in the TPMT enzyme on the pharmacokinetics of 6-mercaptopurine. METHODS: The developed PBPK model was extended for 6-mercaptopurine to account for intracellular metabolism and genetic polymorphism in TPMT activity. System and drug specific parameters were obtained from the literature or estimated using plasma or intracellular red blood cell concentrations of 6-mercaptopurine and its metabolites. Age-dependent changes in parameters were implemented for scaling, and variability was also introduced for simulation. The model was validated using published data. RESULTS: The model was extended successfully. Parameter estimation and model predictions were satisfactory. Prediction of intracellular red blood cell concentrations of 6-thioguanine nucleotide for different TPMT phenotypes (in a clinical study that compared conventional and individualized dosing) showed results that were consistent with observed values and reported incidence of haematopoietic toxicity. Following conventional dosing, the predicted mean concentrations for homozygous and heterozygous variants, respectively, were about 10 times and two times the levels for wild-type. However, following individualized dosing, the mean concentration was around the same level for the three phenotypes despite different doses. CONCLUSIONS: The developed PBPK model has been extended for 6-mercaptopurine and can be used to predict plasma 6-mercaptopurine and tissue concentration of 6-mercaptopurine, 6-thioguanine nucleotide and 6-methylmercaptopurine ribonucleotide in adults and children. Predictions of reported data from clinical studies showed satisfactory results. The model may help to improve 6-mercaptopurine dosing, achieve better clinical outcome and reduce toxicity.

A physiologically based pharmacokinetic model for clobazam and stiripentol in adults and children.

PURPOSE: To develop a physiologically based pharmacokinetic model in adults and children for clobazam, its active metabolite norclobazam and stiripentol and to account for significant clinical interaction that has been reported when clobazam and stiripentol are co-administered. METHODS: A PBPK model with ten compartments was developed. An in vitro-in vivo extrapolation technique was used to scale clearance in children for clobazam and norclobazam and clearance parameters for stiripentol were obtained from fitting. Other drug and system parameters were obtained from the literature. RESULTS: The tissue/blood partition coefficients adequately predict observed volume of distribution for clobazam and stiripentol. In a clinical study in children where clobazam was administered alone and co-administered with stiripentol, the predicted and observed minimum concentration at steady state (mean and 95% confidence interval) during clobazam monotherapy were 0.19 (0.05-0.49 mg/L) and 0.20 (0.17-0.23 mg/L), respectively, and predicted and observed norclobazam concentrations were 0.49 (0.16-1.38 mg/L) and 0.95 (0.91-0.99 mg/L), respectively. From an interaction study with stiripentol the predicted stiripentol concentration was 10.12 (2.51-39.36 mg/L) and the observed concentration was 10.0 (8.3-11.7 mg/L); the predicted clobazam concentration was 0.29 (0.07-1.05 mg/L) and the observed concentration was 0.31 (0.24-0.38 mg/L); and the predicted norclobazam concentration was 2.30 (0.45-5.53 mg/L) and the observed concentration was 4.32 (3.77-4.87 mg/L). CONCLUSIONS: The PBPK model adequately described observed data and the extent of interaction between clobazam/norclobazam and stiripentol.

Model-based evaluation of the impact of formulation and food intake on the complex oral absorption of mavoglurant in healthy subjects.

PURPOSE: To compare the pharmacokinetics of intravenous (IV), oral immediate-release (IR) and oral modified-release (MR) formulations of mavoglurant in healthy subjects, and to assess the food effect on the MR formulation's input characteristics. METHODS: Plasma concentration-time data from two clinical studies in healthy volunteers were pooled and analysed using NONMEM®. Drug entry into the systemic circulation was modelled using a sum of inverse Gaussian (IG) functions as an input rate function, which was estimated specifically for each formulation and food state. RESULTS: Mavoglurant pharmacokinetics was best described by a two-compartment model with a sum of either two or three IG functions as input function. The mean absolute bioavailability from the MR formulation (0.387) was less than from the IR formulation (0.436). The MR formulation pharmacokinetics were significantly impacted by food: bioavailability was higher (0.508) and the input process was shorter (complete in approximately 36 versus 12 h for the fasted and fed states, respectively). CONCLUSIONS: Modelling and simulation of mavoglurant pharmacokinetics indicate that the MR formulation might provide a slightly lower steady-state concentration range with lower peaks (possibly better drug tolerance) than the IR formulation, and that the MR formulation's input properties strongly depend on the food conditions at drug administration.

Application of a Bayesian approach to physiological modelling of mavoglurant population pharmacokinetics.

Mavoglurant (MVG) is an antagonist at the metabotropic glutamate receptor-5 currently under clinical development at Novartis Pharma AG for the treatment of central nervous system diseases. The aim of this study was to develop and optimise a population whole-body physiologically-based pharmacokinetic (WBPBPK) model for MVG, to predict the impact of drug-drug interaction (DDI) and age on its pharmacokinetics. In a first step, the model was fitted to intravenous (IV) data from a clinical study in adults using a Bayesian approach. In a second step, the optimised model was used together with a mechanistic absorption model for exploratory Monte Carlo simulations. The ability of the model to predict MVG pharmacokinetics when orally co-administered with ketoconazole in adults or administered alone in 3-11 year-old children was evaluated using data from three other clinical studies. The population model provided a good description of both the median trend and variability in MVG plasma pharmacokinetics following IV administration in adults. The Bayesian approach offered a continuous flow of information from pre-clinical to clinical studies. Prediction of the DDI with ketoconazole was consistent with the results of a non-compartmental analysis of the clinical data (threefold increase in systemic exposure). Scaling of the WBPBPK model allowed reasonable extrapolation of MVG pharmacokinetics from adults to children. The model can be used to predict plasma and brain (target site) concentration-time profiles following oral administration of various immediate-release formulations of MVG alone or when co-administered with other drugs, in adults as well as in children.

Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children. Part 1: methotrexate.

Methotrexate is an antimetabolite and antifolate drug that is widely used in the treatment of malignancies and auto-immune disorders. In childhood acute lymphoblastic leukaemia, methotrexate is often combined with 6-mercaptopurine and both of them have been shown to be very effective for maintenance of remission. Large variability in the pharmacokinetics of methotrexate has led to increasing use of therapeutic drug monitoring in its clinical use to identify patients with high risk of toxicity and optimise clinical outcome. A physiologically based pharmacokinetic model was developed for methotrexate for oral and intravenous dosing and adults and paediatric use. The model has compartments for stomach, gut lumen, enterocyte, gut tissue, spleen, liver vascular, liver tissue, gall bladder, systemic plasma, red blood cells, kidney vascular, kidney tissue, skin, bone marrow, thymus, muscle and rest of body. A mechanistic model was also developed for the kidney to account for renal clearance of methotrexate via filtration and secretion. Variability on system and drug specific parameters was incorporated in the model to reflect observed clinical data and assuming the same pathways in adults and children, age-dependent changes in body size, organ volumes and plasma flows, the model was scaled to children. The model was developed successfully for adults and parameters such as net secretion clearance, biliary transit time and red blood cell distribution and binding parameters were estimated from published adult profiles. A relationship between fraction absorbed and dose using reported mean bioavailability data in the literature was also established. The model also incorporates non-linear binding in some tissues that has been described in the literature. Predictions using this model provide adequate description of observed plasma concentration data in adults and children. The model can be used to predict plasma and tissue concentrations of methotrexate following intravenous and oral dosing in adults and children and therefore help to improve clinical outcome.

Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children. Part 2: 6-mercaptopurine and its interaction with methotrexate.

6-mercaptopurine (6-MP) is a purine antimetabolite and prodrug that undergoes extensive intracellular metabolism to produce thionucleotides, active metabolites which have cytotoxic and immunosuppressive properties. Combination therapies involving 6-MP and methotrexate have shown remarkable results in the cure of childhood acute lymphoblastic leukaemia (ALL) in the last 30 years. 6-MP undergoes very extensive intestinal and hepatic metabolism following oral dosing due to the activity of xanthine oxidase leading to very low and highly variable bioavailability and methotrexate has been demonstrated as an inhibitor of xanthine oxidase. Despite the success recorded in the use of 6-MP in ALL, there is still lack of effect and life threatening toxicity in some patients due to variability in the pharmacokinetics of 6-MP. Also, dose adjustment during treatment is still based on toxicity. The aim of the current work was to develop a mechanistic model that can be used to simulate trial outcomes and help to improve dose individualisation and dosage regimen optimisation. A physiological based pharmacokinetic model was proposed for 6-MP, this model has compartments for stomach, gut lumen, enterocyte, gut tissue, spleen, liver vascular, liver tissue, kidney vascular, kidney tissue, skin, bone marrow, thymus, muscle, rest of body and red blood cells. The model was based on the assumption of the same elimination pathways in adults and children. Parameters of the model include physiological parameters and drug-specific parameter which were obtained from the literature or estimated using plasma and red blood cell concentration data. Age-dependent changes in parameters were implemented for scaling and variability was also introduced on the parameters for prediction. Inhibition of 6-MP first-pass effect by methotrexate was implemented to predict observed clinical interaction between the two drugs. The model was developed successfully and plasma and red blood cell concentrations were adequately predicted both in terms of mean prediction and variability. The predicted interaction between 6-MP and methotrexate was slightly lower than the reported clinical interaction between the two drugs. The model can be used to predict plasma and tissue concentration in adults and children following oral and intravenous dosing and may ultimately help to improve treatment outcome in childhood ALL patients.

Hierarchical cluster analysis and nonlinear mixed-effects modelling for candidate biomarker detection in preclinical models of cancer.

BACKGROUND: Preclinical models of cancer can be of translational benefit when assessing how different biomarkers are regulated in response to particular treatments. Detection of molecular biomarkers in preclinical models of cancer is difficult due inter-animal variability in responses, combined with limited accessibility of longitudinal data. METHODS: Nonlinear mixed-effects modelling (NLME) was used to analyse tumour growth data based on expected tumour growth rates observed 7 days after initial doses (DD7) of Radiotherapy (RT) and Combination of RT with DNA Damage Response Inhibitors (DDRi). Cox regression was performed to confirm an association between DD7 and survival. Hierarchical Cluster Analysis (HCA) was then used to identify candidate biomarkers impacting responses to RT and RT/DDRi and these were validated using NLME. RESULTS: Cox regression confirmed significant associations between DD7 and survival. HCA of RT treated samples, combined with NLME confirmed significant associations between DD7 and Cluster specific CD8+ Ki67 MFI, as well as DD7 and cluster specific Natural Killer cell density in RT treated mice. CONCLUSION: Application of NLME, as well as HCA of candidate biomarkers may provide additional avenues to assess the effect of RT in MC38 syngeneic tumour models. Additional studies would need to be conducted to confirm association between DD7 and biomarkers in RT/DDRi treated mice.

Covariates in population pharmacokinetic studies of critically ill adults receiving ß-lactam antimicrobials: a systematic review and narrative synthesis.

Introduction: Population pharmacokinetic studies of ß-lactam antimicrobials in critically ill patients derive models that inform their dosing. In non-linear mixed-effects modelling, covariates are often used to improve model fit and explain variability. We aimed to investigate which covariates are most commonly assessed and which are found to be significant, along with global patterns of publication. Methods: We conducted a systematic review, searching MEDLINE, Embase, CENTRAL and Web of Science on 01 March 2023, including studies of critically ill adults receiving ß-lactam antimicrobials who underwent blood sampling for population pharmacokinetic studies. We extracted and categorized all reported covariates and assessed reporting quality using the ClinPK checklist. Results: Our search identified 151 studies with 6018 participants. Most studies reported observational cohorts (120 studies, 80%), with the majority conducted in high-income settings (136 studies, 90%). Of the 1083 identified covariate instances, 237 were unique; the most common categories were patient characteristics (n = 404), biomarkers (n = 206) and physiological parameters (n = 163). Only seven distinct commonly reported covariates (CLCR, weight, glomerular filtration rate, diuresis, need for renal replacement, serum albumin and C-reactive protein) were significant more than 20% of the time. Conclusions: Covariates are most commonly chosen based on biological plausibility, with patient characteristics and biomarkers the most frequently investigated. We developed an openly accessible database of reported covariates to aid investigators with covariate selection when designing population pharmacokinetic studies. Novel covariates, such as sepsis subphenotypes, have not been explored yet, leaving a research gap for future work.