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

A mathematical model of white blood cell dynamics during maintenance therapy of childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia is the most common malignancy in childhood and requires prolonged oral maintenance chemotherapy to prevent disease relapse after remission induction with intensive intravenous chemotherapy. In maintenance therapy, drug doses of 6-mercaptopurine (6-MP) and methotrexate (MTX) are adjusted to achieve sustained antileukemic activity without excessive myelosuppression. However, uncertainty exists regarding timing and extent of drug dose responses and optimal dose adaptation strategies. We propose a novel comprehensive mathematical model for 6-MP and MTX pharmacokinetics, pharmacodynamics and myelosuppression in acute lymphoblastic maintenance therapy. We personalize and cross-validate the mathematical model using clinical data and propose a real-time algorithm to predict chemotherapy responses with a clinical decision support system as a potential future application.

Association of NUDT15*3 and FPGS 2572C>T Variants with the Risk of Early Hematologic Toxicity During 6-MP and Low-Dose Methotrexate-Based Maintenance Therapy in Indian Patients with Acute Lymphoblastic Leukemia

Genetic variants influencing the pharmacokinetics and/or pharmacodynamics of the chemotherapeutic drugs used in Acute Lymphoblastic Leukemia (ALL) therapy often contribute to the occurrence of treatment related toxicity (TRT). In this study, we explored the association of candidate genetic variants with early hematological TRT (grade 3–4) occurring within the first 100 days of low-dose methotrexate and 6-mercaptopurine based maintenance therapy (n = 73). Fourteen variants in the following candidate genes were genotyped using allele discrimination assay by real-time PCR: ABCB1, DHFR, GGH, FPGS, MTHFR, RFC1, SLCO1B1, TPMT, and NUDT15. Methotrexate polyglutamate (MTXPG3-5) levels in red blood cells were measured by LC-MS/MS. Early hematological TRT (grade 3–4) was seen in 54.9% of patients. The NUDT15c.415T allele was associated with early TRT occurrence [HR: 3.04 (95% CI: 1.5–6.1); p = 0.007]. Sensitivity of early TRT prediction improved (from 30.7% to 89.7%) by considering FPGS variant (rs1544105’T’) carrier status along with NUDT15c.415T allele [HR = 2.7 (1.5–4.7, p = 0.008)]. None of the considered genetic variants were associated with MTXPG3-5 levels, which in turn were not associated with early TRT. NUDT15c.415T allele carrier status could be used as a stratifying marker for Indian ALL patients to distinguish patients at high or low risk of developing early hematological TRT.

A methodological framework for drug development in rare diseases. The CRESim program: Epilogue and perspectives

Based on the 'European Child-Rare-Euro-Simulation' (CRESim) project, this article proposes a generalizable strategy utilizing datasets analysis in combination with modeling and simulation, in order to optimize the clinical drug development applied in the field of rare diseases. The global process includes: (i) the simulation of a realistic virtual population of patients (modeled from a real dataset of patients), (ii) the modeling of disease pathophysiological components and of pharmacokinetic-pharmacodynamic relations of the drug(s) of interest, (iii) the modeling of several randomized controlled clinical trials (RCTs) designs and (iv) the analysis of the results (multi-dimensional approach for RCTs durations and precision of the estimation of the treatment effect). However, whereas modeling and numerical simulation may provide supplementary tools for drug development, they cannot be considered as a substitute for RCTs performed in 'real' patients.

Mathematical model of T-cell lymphoblastic lymphoma: disease, treatment, cure or relapse of a virtual cohort of patients

T lymphoblastic lymphoma (T-LBL) is a rare type of lymphoma with a good prognosis with a remission rate of 85%. Patients can be completely cured or can relapse during or after a 2-year treatment. Relapses usually occur early after the remission of the acute phase. The median time of relapse is equal to 1 year, after the occurrence of complete remission (range 0.2-5.9 years) (Uyttebroeck et al., 2008). It can be assumed that patients may be treated longer than necessary with undue toxicity.The aim of our model was to investigate whether the duration of the maintenance therapy could be reduced without increasing the risk of relapses and to determine the minimum treatment duration that could be tested in a future clinical trial.We developed a mathematical model of virtual patients with T-LBL in order to obtain a proportion of virtual relapses close to the one observed in the real population of patients from the EuroLB database. Our simulations reproduced a 2-year follow-up required to study the onset of the disease, the treatment of the acute phase and the maintenance treatment phase.

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

Almost half of recent pediatric trials failed to achieve labeling indications, in large part because of inadequate study design. Therefore, innovative study methods are crucial to optimizing trial design while also reducing the potential harms inherent with drug investigation. Several methods exist to optimize the amount of pharmacokinetic data collected from the smallest possible volume and with the fewest number of procedures, including the use of opportunistic and sparse sampling, alternative and noninvasive matrices, and microvolume assays. In addition, large research networks using master protocols promote collaboration, reduce regulatory burden, and increase trial efficiency for both early- and late-phase trials. Large pragmatic trials that leverage electronic health records can capitalize on central management strategies to reduce costs, enroll patients with rare diseases on a large scale, and augment study generalizability. Further, trial efficiency and safety can be optimized through Bayesian adaptive techniques that permit planned protocol changes based on analyses of prior and accumulated data. In addition to these trial design features, advances in modeling and simulation have paved the way for systems-based and physiologically based models that individualize pediatric dosing recommendations and support drug approval. Last, given the low prevalence of many pediatric diseases, collecting deidentified genetic and clinical data on a large scale is a potentially transformative way to augment clinical pharmacology research in children.

Ordinary differential equations and Boolean networks in application to modelling of 6-mercaptopurine metabolism

We consider two approaches to modelling the cell metabolism of 6-mercaptopurine, one of the important chemotherapy drugs used for treating acute lymphocytic leukaemia: kinetic ordinary differential equations, and Boolean networks supplied with one controlling node, which takes continual values. We analyse their interplay with respect to taking into account ATP concentration as a key parameter of switching between different pathways. It is shown that the Boolean networks, which allow avoiding the complexity of general kinetic modelling, preserve the possibility of reproducing the principal switching mechanism.

Mathematical modeling and simulation in animal health. Part I: Moving beyond pharmacokinetics

The application of mathematical modeling to problems in animal health has a rich history in the form of pharmacokinetic modeling applied to problems in veterinary medicine. Advances in modeling and simulation beyond pharmacokinetics have the potential to streamline and speed-up drug research and development programs. To foster these goals, a series of manuscripts will be published with the following goals: (i) expand the application of modeling and simulation to issues in veterinary pharmacology; (ii) bridge the gap between the level of modeling and simulation practiced in human and veterinary pharmacology; (iii) explore how modeling and simulation concepts can be used to improve our understanding of common issues not readily addressed in human pharmacology (e.g. breed differences, tissue residue depletion, vast weight ranges among adults within a single species, interspecies differences, small animal species research where data collection is limited to sparse sampling, availability of different sampling matrices); and (iv) describe how quantitative pharmacology approaches could help understanding key pharmacokinetic and pharmacodynamic characteristics of a drug candidate, with the goal of providing explicit, reproducible, and predictive evidence for optimizing drug development plans, enabling critical decision making, and eventually bringing safe and effective medicines to patients. This study introduces these concepts and introduces new approaches to modeling and simulation as well as clearly articulate basic assumptions and good practices. The driving force behind these activities is to create predictive models that are based on solid physiological and pharmacological principles as well as adhering to the limitations that are fundamental to applying mathematical and statistical models to biological systems.

Optimizing pharmacokinetic bridging studies in paediatric oncology using physiologically-based pharmacokinetic modelling: application to docetaxel

AIM

Applying physiologically-based pharmacokinetic (PBPK) modelling in paediatric cancer drug development is still challenging. We aimed to demonstrate how PBPK modelling can be applied to optimize dose and sampling times for a paediatric pharmacokinetic (PK) bridging study in oncology and to compare with the allometric scaling population PK (AS-popPK) approach, using docetaxel as an example.

METHODS

A PBPK model for docetaxel was first developed for adult cancer patients using Simcyp® and subsequently used to predict its PK profiles in children by accounting for age-dependent physiological differences. Dose (mg m(-2) ) requirements for children aged 0-18 years were calculated to achieve targeted exposure in adults. Simulated data were then analyzed using population PK modelling with MONOLIX® in order to perform design optimization with the population Fisher information matrix (PFIM). In parallel, the AS-popPK approach was performed for the comparison.

RESULTS

The PBPK model developed for docetaxel adequately predicted its PK profiles in both adult and paediatric cancer patients (predicted clearance and volume of distribution within 1.5 fold of observed data). The revised dose of docetaxel for a child over 1.5 years old was higher than the adult dose. Considering clinical constraints, the optimal design contained two groups of 15 patients, having three or four sampling times and had good predicted relative standard errors (RSE<30%) for almost all parameters. The AS-popPK approach performed reasonably well but could not predict for very young children.

CONCLUSION

This research shows the clinical utility of PBPK modelling in combination with population PK modelling and optimal design to support paediatric oncology development.

Modeling and simulation in pediatric drug therapy: Application of pharmacometrics to define the right dose for children

During the past decades significant progress has been made in our understanding of the importance of age-appropriate development of new drug therapies in children. Importantly, several regulatory initiatives in Europe and the US have provided a framework for a rationale. In the US, most notably the enactment of the Best Pharmaceuticals for Children Act (BPCA) and Product Research and Equity Act (PREA) has facilitated the studying of on-patent and off-patent drugs in children. The biggest challenge in pediatric studies is defining a safe and effective dose or dose range in a patient population that can span from premature neonates to adolescents. From a mechanism-based perspective, advances in the science of quantitative pharmacology and pharmacometrics have resulted in the development of model-based approaches to better describe and understand important age-related factors influencing drug disposition and response in pediatric patients. The application of modeling and simulation has been shown to result in better estimates of pediatric doses as evidenced by several studies, although the optimal approach is still being debated. The extrapolation of efficacy findings from adults to the pediatric population has streamlined the development process especially for studies in older children. However, a focus on developmental changes in neonates and infants as well as further developing a paradigm for conducting pharmacodynamic studies in neonates, infants, and children remain important unmet needs. In this overview we will review current approaches for age-appropriate dose selection and highlight ongoing efforts to define exposure-response and clinical outcome relationships across the pediatric age spectrum.

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.

Montelukast potentiates the anticonvulsant effect of phenobarbital in mice: an isobolographic analysis

Although leukotrienes have been implicated in seizures, no study has systematically investigated whether the blockade of CysLT1 receptors synergistically increases the anticonvulsant action of classic antiepileptics. In this study, behavioral and electroencephalographic methods, as well as isobolographic analysis, are used to show that the CysLT1 inverse agonist montelukast synergistically increases the anticonvulsant action of phenobarbital against pentylenetetrazole-induced seizures. Moreover, it is shown that LTD4 reverses the effect of montelukast. The experimentally derived ED50mix value for a fixed-ratio combination (1:1 proportion) of montelukast plus phenobarbital was 0.06±0.02 μmol, whereas the additively calculated ED50add value was 0.49±0.03 μmol. The calculated interaction index was 0.12, indicating a synergistic interaction. The association of montelukast significantly decreased the antiseizure ED50 for phenobarbital (0.74 and 0.04 μmol in the absence and presence of montelukast, respectively) and, consequently, phenobarbital-induced sedation at equieffective doses. The demonstration of a strong synergism between montelukast and phenobarbital is particularly relevant because both drugs are already used in the clinics, foreseeing an immediate translational application for epileptic patients who have drug-resistant seizures.