A Bayesian population PK–PD model for ispinesib/docetaxel combination-induced myelosuppression

Flexible and efficient Bayesian pharmacometrics modeling using Stan and Torsten, Part I

Stan is an open-source probabilistic programing language, primarily designed to do Bayesian data analysis. Its main inference algorithm is an adaptive Hamiltonian Monte Carlo sampler, supported by state-of-the-art gradient computation. Stan's strengths include efficient computation, an expressive language that offers a great deal of flexibility, and numerous diagnostics that allow modelers to check whether the inference is reliable. Torsten extends Stan with a suite of functions that facilitate the specification of pharmacokinetic and pharmacodynamic models and makes it straightforward to specify a clinical event schedule. Part I of this tutorial demonstrates how to build, fit, and criticize standard pharmacokinetic and pharmacodynamic models using Stan and Torsten.

Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity

Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).

Impact of granulocyte colony-stimulating factor on FOLFIRINOX-induced neutropenia prevention: A population pharmacokinetic/pharmacodynamic approach

AIMS

Granulocyte colony-stimulating factor (G-CSF) is frequently prescribed to prevent chemotherapy-induced neutropenia, but the administration schedule remains empirical in case of bimonthly chemotherapy such as FOLFIRINOX regimen. This pharmacokinetic/pharmacodynamic (PK/PD) study was performed to determine the effect of different G-CSF regimens on the incidence and duration of neutropenia following FOLFIRINOX administration in order to propose an optimal G-CSF dosing schedule.

METHODS

A population PK/PD model was developed to describe individual neutrophil time course from absolute neutrophil counts (ANC) obtained in 40 advanced cancer patients receiving FOLFIRINOX regimen. The structural model considered ANC dynamics, neutropenic effect of cytotoxics and the stimulating effect of G-CSF on neutrophils. Final model estimates were used to simulate different G-CSF dosing schedules for 1000 virtual subjects. The incidence and duration of neutropenia were then calculated for different G-CSF dosing schedules.

RESULTS

The final model successfully described the myelosuppressive effect induced by the 3 cytotoxics for all patients. Simulations showed that pegfilgrastim administration reduced the risk of severe neutropenia by 22.9% for subjects with low ANC at the start of chemotherapy. Median duration in this group was also shortened by 3.1 days when compared to absence of G-CSF. Delayed G-CSF administration was responsible for higher incidence and longer duration of neutropenia compared to absence of administration.

CONCLUSION

The PK/PD model well described our population's ANC data. Simulations showed that pegylated-G-CSF administration 24 hours after the end of chemotherapy seems to be the optimal schedule to reduce FOLFIRINOX-induced neutropenia. We also underline the potential negative effect of G-CSF maladministration.

Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working group

Explicitly modeling underlying relationships between a survival endpoint and processes that generate longitudinal measured or reported outcomes potentially could improve the efficiency of clinical trials and provide greater insight into the various dimensions of the clinical effect of interventions included in the trials. Various strategies have been proposed for using longitudinal findings to elucidate intervention effects on clinical outcomes such as survival. The application of specifically Bayesian approaches for constructing models that address longitudinal and survival outcomes explicitly has been recently addressed in the literature. We review currently available methods for carrying out joint analyses, including issues of implementation and interpretation, identify software tools that can be used to carry out the necessary calculations, and review applications of the methodology.

Evaluation of 4β-Hydroxycholesterol as a Clinical Biomarker of CYP3A4 Drug Interactions Using a Bayesian Mechanism-Based Pharmacometric Model

A Bayesian mechanism–based pharmacokinetic/pharmacodynamic model of cytochrome P450 3A4 (CYP3A4) activity was developed based on a clinical study of the effects of ketoconazole and rifampin on midazolam exposure and plasma 4β-hydroxycholesterol (4βHC) concentrations. Simulations from the model demonstrated that the dynamic range of 4βHC as a biomarker of CYP3A4 induction or inhibition was narrower than that of midazolam; an inhibitor that increases midazolam area under the curve by 20-fold may only result in a 20% decrease in 4βHC after 14 days of dosing. Likewise, an inducer that elevates CYP3A4 activity by 1.2-fold would reduce the area under the curve of midazolam by 50% but would only increase 4βHC levels by 20% after 14 days of dosing. Elevation in 4βHC could be reliably detected with a twofold induction in CYP3A4 activity with study sample sizes (N ~ 6–20) typically used in early clinical development. Only a strong CYP3A4 inhibitor (e.g., ketoconazole) could be detected with similar sample sizes.

Population pharmacokinetic–pharmacodynamic modelling and simulation of neutropenia induced by TP300, a novel topoisomerase I inhibitor

Objectives

TP300 is a novel topoisomerase I inhibitor with neutropenia as a significant toxicity. We developed and evaluated a pharmacokinetic–pharmacodynamic (PK-PD) model, using data from Phase I and II trials to predict neutrophil decrease in patients treated with TP300.

Methods

Plasma drug concentrations of TP300, its active form TP3076 and active metabolite TP3011 and absolute neutrophil counts (ANCs) from a Phase I trial were analysed as a training dataset. A two-plus-two-compartment model was applied to the pharmacokinetics of TP3076 and TP3011. A semi-mechanistic model was used to describe the PK-PD relationship between the plasma concentration of TP3076 and TP3011, and changes in ANC.

Key findings

 The model fitted well to plasma concentrations of TP3076 and TP3011. Model appropriateness was confirmed in a Phase II trial validation dataset. Body weight and liver biochemistry values were identified as covariates. A semi-mechanistic PK-PD model was applied and the longitudinal decrease in ANC was simulated. Neutrophil counts reached their nadir approximately 2 weeks after administration of TP300, and the proportion of subjects affected increased with dose.

Conclusions

This PK-PD model to predict neutropenia following treatment with TP300 fitted well the decrease in ANC with total concentration of TP3076 and TP3011.

Synthesis and characterization of tritylthioethanamine derivatives with potent KSP inhibitory activity

Assembly of a bipolar mitotic spindle requires the action of class 5 kinesins, and inhibition or depletion of this motor results in mitotic arrest and apoptosis. S-Trityl-l-cysteine is an allosteric inhibitor of vertebrate Kinesin Spindle Protein (KSP) that has generated considerable interest due to its anti-cancer properties, however, poor pharmacological properties have limited the use of this compound. We have modified the triphenylmethyl and cysteine groups, guided by biochemical and cell-based assays, to yield new cysteinol and cysteamine derivatives with increased inhibitory activity, greater efficacy in model systems, and significantly enhanced potency against the NCI60 tumor panel. These results reveal a promising new class of conformationally-flexible small molecules as allosteric KSP inhibitors for use as research tools, with activities that provide impetus for further development as anti-tumor agents.

Prediction of neutropenia-related effects of a new combination therapy with the anticancer drugs BI 2536 (a Plk1 inhibitor) and pemetrexed

This study investigated the feasibility of predicting the neutropenia-related effects of a therapy that combines the investigational drug BI 2536 (inhibitor of Polo-like kinase 1) and pemetrexed, an approved anticancer drug. Predictions were arrived at using the pharmacokinetic/pharmacodynamic (PK/PD) parameters of each of the drugs obtained from monotherapy studies and assuming that the neutropenic effect is additive when the drugs are administered as a combination therapy. Subsequently, a PK/PD model was developed to determine whether this assumption of additive effect was reasonable in relation to these two drugs. All analyses and simulations were performed using the population approach in NONMEM, version VI.