Safe and Effective Variability—A Criterion for Dose Individualization

Using pharmacokinetics to individualize hemophilia therapy

Prevention and treatment of bleeding in hemophilia requires that plasma clotting factor activity of the replaced factor exceeds a defined target level. Most clinical decisions in hemophilia are based on implicit or explicit application of pharmacokinetic measures. The large interindividual variability in pharmacokinetics of factor concentrates suggests that relying on the average pharmacokinetic characteristics of factor concentrates would not allow optimizing the treatment of individual patients; for example, adjusting the frequency of infusions and targeting a specific clotting factor activity level on a case-by-case basis. However, individual pharmacokinetic profiles are seldom assessed as part of routine clinical care. Population pharmacokinetics provide options for precise and convenient characterization of pharmacokinetics characteristics of factor concentrates, simplified individual pharmacokinetic profiling, and individualized dosing. Population pharmacokinetics allow for the incorporation of determinants of interpatient variability and reduces the need for extensive postinfusion plasma sampling. Barriers to the implementation of population pharmacokinetics are the need for concentrate-specific pharmacokinetic models, Bayesian calculation power, and specific expertise for production, validation, and appraisal of forecasted estimates. Population pharmacokinetics provide an important theoretical and practical contribution to tailoring the treatment of hemophilia. The need remains for prospective exploration of the clinical impact of tailoring hemophilia treatment based on individual pharmacokinetics, and for the systematic validation of existing software solutions and concentrate-specific models.

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling as tools to personalize gentamicin therapy

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling are all tools that can be applied to personalize gentamicin therapy. This review summarizes and evaluates literature knowledge on the population pharmacokinetics and pharmacodynamics of gentamicin and identifies areas where further research is required to successfully individualize gentamicin therapy using modelling and simulation techniques. Thirty-five studies have developed a population pharmacokinetic model of gentamicin and 15 studies have made dosing recommendations based on Monte Carlo simulation. Variability in gentamicin clearance was most commonly related to renal function in adults and body weight and age in paediatrics. Nine studies have related aminoglycoside exposure indices to clinical outcomes. Most commonly, efficacy has been linked to a Cmax/MIC ≥7-10 and a AUC24/MIC ≥70-100. No study to date has shown a relationship between predicted achievement of exposure targets and actual clinical success. Five studies have developed a semi-mechanistic pharmacokinetic/pharmacodynamic model to predict bacteria killing and regrowth following gentamicin exposure and one study has developed a deterministic model of aminoglycoside nephrotoxicity. More complex semi-mechanistic models are required that consider the immune response, use of multiple antibiotics, the severity of illness, and both efficacy and toxicity. As our understanding grows, dosing of gentamicin based on sound pharmacokinetic/pharmacodynamic principles should be applied more commonly in clinical practice.

Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4-5 December 2014)

Inadequate dose selection for confirmatory trials is currently still one of the most challenging issues in drug development, as illustrated by high rates of late‐stage attritions in clinical development and postmarketing commitments required by regulatory institutions. In an effort to shift the current paradigm in dose and regimen selection and highlight the availability and usefulness of well‐established and regulatory‐acceptable methods, the European Medicines Agency (EMA) in collaboration with the European Federation of Pharmaceutical Industries Association (EFPIA) hosted a multistakeholder workshop on dose finding (London 4–5 December 2014). Some methodologies that could constitute a toolkit for drug developers and regulators were presented. These methods are described in the present report: they include five advanced methods for data analysis (empirical regression models, pharmacometrics models, quantitative systems pharmacology models, MCP‐Mod, and model averaging) and three methods for study design optimization (Fisher information matrix (FIM)‐based methods, clinical trial simulations, and adaptive studies). Pairwise comparisons were also discussed during the workshop; however, mostly for historical reasons. This paper discusses the added value and limitations of these methods as well as challenges for their implementation. Some applications in different therapeutic areas are also summarized, in line with the discussions at the workshop. There was agreement at the workshop on the fact that selection of dose for phase III is an estimation problem and should not be addressed via hypothesis testing. Dose selection for phase III trials should be informed by well‐designed dose‐finding studies; however, the specific choice of method(s) will depend on several aspects and it is not possible to recommend a generalized decision tree. There are many valuable methods available, the methods are not mutually exclusive, and they should be used in conjunction to ensure a scientifically rigorous understanding of the dosing rationale.

What is the role for population pharmacokinetics in hemophilia?

Prevention of bleeding in hemophilia requires that plasma levels of the deficient factor exceed the desired minimum target level. Large interindividual variability suggests that knowledge of individual pharmacokinetic (PK) would help to achieve this goal, simultaneously minimizing infusion frequency and the amount of concentrate used. Population PK (PopPK) allows for the incorporation of determinants of interpatient variability and eliminates the need for extensive postinfusion plasma sampling. Barriers to implementation of PopPK are the need for concentrate specific models, Bayesian calculation power, specific expertise for validation and appraisal of forecasted estimates. The Web Accessible Population Pharmacokinetic Service – Hemophilia ( www.wapps-hemo.org ), developed by an international research network of hemophilia centers will test if PK-guided dose individualization can improve patient important outcomes in hemophilia.

Data Analysis Protocol for the Development and Evaluation of Population Pharmacokinetic Models for Incorporation Into the Web-Accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo)

BACKGROUND

Hemophilia is an inherited bleeding disorder caused by a deficiency in a specific clotting factor. This results in spontaneous bleeding episodes and eventual arthropathy. The mainstay of hemophilia treatment is prophylactic replacement of the missing factor, but an optimal regimen remains to be determined. Rather, individualized prophylaxis has been suggested to improve both patient safety and resource utilization. However, uptake of this approach has been hampered by the demanding sampling schedules and complex calculations required to obtain individual estimates of pharmacokinetic (PK) parameters. The use of population pharmacokinetics (PopPK) can alleviate this burden by reducing the number of plasma samples required for accurate estimation, but few tools incorporating this approach are readily available to clinicians.

OBJECTIVE

The Web-accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo) project aims to bridge this gap by providing a Web-accessible service for the reliable estimation of individual PK parameters from only a few patient samples. This service is predicated on the development of validated brand-specific PopPK models.

METHODS

We describe the data analysis plan for the development and evaluation of each PopPK model to be incorporated into the WAPPS-Hemo platform. The data sources and structure of the dataset are discussed first, followed by the procedures for handling both data below limit of quantification (BLQ) and absence of such BLQ data. Next, we outline the strategies for building the appropriate structural and covariate models, including the possible need for a process algorithm when PK behavior varies between subjects or significant covariates are not provided. Prior to use in a prospective manner, the models will undergo extensive evaluation using a variety of techniques such as diagnostic plots, bootstrap analysis and cross-validation. Finally, we describe the incorporation of a validated PopPK model into the Bayesian post hoc model to produce individualized estimates of PK parameters.

RESULTS

Dense PK data has been collected for more than 20 brands of factor concentrate from both industry-sponsored and investigator-driven studies. The model development process is underway for the majority of molecules, with refinement and validation to be completed in 2017. Further, the WAPPS-Hemo co-investigator network has contributed more than 300 PK assessments for use in model development and evaluation. This constitutes the largest repository of this type of PK data globally.

CONCLUSIONS

The WAPPS-Hemo service aims to eliminate barriers to the uptake of individualized PK-tailored hemophilia treatment. By incorporating this tool into routine practice, clinicians can implement a personalized dosing strategy without performing rigorous sampling or complex calculations. This service is centred on validated models developed according to the robust approach to PopPK modeling described herein.

CLINICALTRIAL

ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRIXJh55).

The use of pharmacokinetics in dose individualization of factor VIII in the treatment of hemophilia A

INTRODUCTION

Hemophilia A is a bleeding disorder resulting from a lack of clotting factor VIII (FVIII), and treatment typically consists of prophylactic replacement of the deficient factor. However, high between subject variability precludes the development of a 'one size fits all' dosing strategy and necessitates an individualized approach. We sought to summarize the data on the pharmacokinetics of FVIII available as a basis for the development of population pharmacokinetic models to be used in dose tailoring. Areas covered: We reviewed the pharmacokinetics of FVIII as used for the treatment of hemophilia A, with a focus on the variability observed between patients and the application of pharmacokinetic methods to dose individualization. We also explored the covariates affecting pharmacokinetic parameters, the differences between plasma-derived and recombinant FVIII and the development of extended half-life products. Expert opinion: The pharmacokinetics of factor VIII in patients with hemophilia shows a high interpatient variability, and is affected by age, weight, level of von Willebrand factor, and blood group. A population approach to estimating individual pharmacokinetics is likely to provide the most successful strategy to tailor factor concentrate dosing to the individual needs and to ensure optimal patient outcomes, while also improving the cost-effectiveness of prophylactic replacement therapy.

Population pharmacokinetics of vancomycin in adult Chinese patients with post-craniotomy meningitis and its application in individualised dosage regimens

PURPOSE

Vancomycin (VCM) is a first-line antibacterial drug used to treat post-craniotomy meningitis (PCM). VCM pharmacokinetic parameters are altered in PCM patients, compared to those in other patients. Although VCM population pharmacokinetics (PPK) has been reported, changes in VCM PPK in adult Chinese PCM patients remain unknown. We developed a VCM PPK model in adult Chinese PCM patients and proposed a new strategy for individualising VCM administration using this model.

METHODS

Data was obtained from a prospective study of 100 adult PCM patients in the Neurosurgery Department of the First Affiliated Hospital of Fujian Medical University. The trough concentrations at steady state were determined by enzyme multiplied immunoassay. Nonlinear mixed-effect model software was employed to develop the PPK model. The final model was evaluated using the bootstrap method and normalised prediction error distribution and through the testing of 20 independent adult PCM patients.

RESULTS

VCM clearance in PCM patients was higher than that observed in other patients. Creatinine clearance affected VCM clearance, whereas no co-administered drugs influenced VCM pharmacokinetics. Trough concentrations were accurately predicted by the final model, while the prediction errors were less than ±32 %. Moreover, a new strategy for individualising VCM regimens using the PPK model was proposed and validated.

CONCLUSIONS

A PPK model was developed to estimate the individual clearance in inpatients receiving intravenously infused VCM and could be used to develop individualised dosing of adult Chinese PCM patients.

Considerations when using pharmacokinetic/pharmacodynamic modeling to determine the effectiveness of simple analgesics in children

INTRODUCTION

Assessment of analgesic drugs includes comparative studies to other analgesics and local anesthesia blockade, number needed to treat estimates and opioid sparing descriptions. An additional methodology is to define the concentration-response relationship using pharmacokinetic/pharmacodynamic (PK/PD) modeling.

AREAS COVERED

A concentration-response relationship allows analgesic effect comparison between drugs for different acute pain types. Covariates such as size, age and organ function impact greatly on PK in children. The cumulative effect of confounding factors (e.g., pharmacogenetics, placebo and changes in baseline pain over time) complicates PD. Other factors (outcome measures, method of measurement, failure to account for study attrition) impact on outcome. Population PK/PD modeling approaches allow us to account for these various factors to some extent.

EXPERT OPINION

Nonlinear mixed effects models help interpret analgesic data and their use is increasing. The PK is relatively well understood. The next investigative step will involve investigation into covariate effects for PD. Mathematical functions for both placebo models and dropout models are well described and should be incorporated into analgesic effectiveness studies that investigate a range of doses. Improvements in pain assessment tools and a greater understanding of pharmacogenomics factors will help individualize analgesic therapy.

Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling

Aims

The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models.

Methods

Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting.

Results

Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h⁻¹ [95% CI 12.6, 18.0 l h⁻¹]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An E_max model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of −1.2% (95% CI −3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range.

Conclusion

A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.

The integration of allometry and virtual populations to predict clearance and clearance variability in pediatric populations over the age of 6 years

BACKGROUND AND OBJECTIVES

Pharmacokinetics play an integral role in the pediatric drug development process. The determination of pharmacokinetic parameters, particularly clearance, in different age groups directly informs dosing strategies for subsequent efficacy trials. Allometric scaling for prediction of pediatric clearance from the observed clearance in adults has been used in this effort. Clinical trial simulation, a powerful tool used to inform clinical trial design, requires both an estimate of clearance along with an estimate of the expected pharmacokinetic variability. The standard deviations (SD) of individual clearance values for adults are typically used and may lead to inaccurate predictions by not taking into account the more widespread distribution of factors such as body weight in the pediatric population. The objective of this study was to assess the accuracy of allometric prediction of drug clearance as well as methods for predicting clearance variability in children 6 years of age and older.

METHODS

US Food and Drug Administration (FDA) clinical pharmacology reviews of pediatric studies conducted from 2002 onwards were reviewed to collate adult and pediatric clearance and clearance variability for studies including children 6 years of age and older. A set of 1,000 virtual adults {A} and a set of 5,000 virtual children (aged 2-17) {P} were generated on the basis of the White American NHANES database. Pediatric clearances were predicted in method 1 by using the geometric mean adult clearance from the in vivo study and calculating pediatric clearance for each virtual child within a subset {P'} of {P} that contained only those children that were within the age range of the in vivo pediatric study. In method 2, adult clearance values were randomly generated from the geometric mean adult clearance and standard deviation and assigned to each virtual adult in {A}. For each adult, allometric clearance scaling was completed with each virtual child within {P'}. The prediction error for the predicted and observed clearance and the clearance variability metric, coefficient of variation (CV), was calculated. The prediction accuracy as a function of the lowest age range (2 years and older) included in the study was also assessed.

RESULTS

Thirty-nine unique drugs were included in the study. For both method 1 and method 2, 100 % of predicted pediatric mean clearances were within 2-fold of the observed values and approximately 82 % were within a 30 % prediction error. There was a significant increase in the prediction accuracy of CV using method 2 vs. method 1. There was a major bias towards underprediction of pediatric CV in method 1 whereas method 2 was precise and not biased. Clearance and CV prediction accuracy were not a function of the age range included in the in vivo studies. The observed CV between the adult and pediatric study groups was not significantly different although, on average, the observed pediatric CV was 32 % greater than that from adult studies.

CONCLUSIONS

Allometric scaling may be a useful tool during pediatric drug development to predict drug clearance and dosing requirements in children 6 years of age and older. A novel methodology is reported that employs virtual adult and pediatric populations and adult pharmacokinetic data to accurately predict clearance variability in specific pediatric subpopulations. This approach has important implications for both clinical trial simulations and sample size determination for pediatric pharmacokinetic studies.

Busulfan in infant to adult hematopoietic cell transplant recipients: a population pharmacokinetic model for initial and Bayesian dose personalization

PURPOSE

Personalizing intravenous busulfan doses to a target plasma concentration at steady state (Css) is an essential component of hematopoietic cell transplantation (HCT). We sought to develop a population pharmacokinetic model to predict i.v. busulfan doses over a wide age spectrum (0.1-66 years) that accounts for differences in age and body size.

EXPERIMENTAL DESIGN

A population pharmacokinetic model based on normal fat mass and maturation based on postmenstrual age was built from 12,380 busulfan concentration time points obtained after i.v. busulfan administration in 1,610 HCT recipients. Subsequently, simulation results of the initial dose necessary to achieve a target Css with this model were compared with pediatric-only models.

RESULTS

A two-compartment model with first-order elimination best fit the data. The population busulfan clearance was 12.4 L/h for an adult male with 62 kg normal fat mass (equivalent to 70 kg total body weight). Busulfan clearance, scaled to body size-specifically normal fat mass, is predicted to be 95% of the adult clearance at 2.5 years postnatal age. With a target Css of 770 ng/mL, a higher proportion of initial doses achieved the therapeutic window with this age- and size--dependent model (72%) compared with dosing recommended by the U.S. Food and Drug Administration (57%) or the European Medicines Agency (70%).

CONCLUSION

This is the first population pharmacokinetic model developed to predict initial i.v. busulfan doses and personalize to a target Css over a wide age spectrum, ranging from infants to adults.