Real Life Population Pharmacokinetics Modelling of Eight Factors VIII in Patients with Severe Haemophilia A: Is It Always Relevant to Switch to an Extended Half-Life?

A Generative and Causal Pharmacokinetic Model for Factor VIII in Hemophilia A: A Machine Learning Framework for Continuous Model Refinement

In rare diseases, such as hemophilia A, the development of accurate population pharmacokinetic (PK) models is often hindered by the limited availability of data. Most PK models are specific to a single recombinant factor VIII (rFVIII) concentrate or measurement assay, and are generally unsuited for answering counterfactual ("what-if") queries. Ideally, data from multiple hemophilia treatment centers are combined but this is generally difficult as patient data are kept private. In this work, we utilize causal inference techniques to produce a hybrid machine learning (ML) PK model that corrects for differences between rFVIII concentrates and measurement assays. Next, we augment this model with a generative model that can simulate realistic virtual patients as well as impute missing data. This model can be shared instead of actual patient data, resolving privacy issues. The hybrid ML-PK model was trained on chromogenic assay data of lonoctocog alfa and predictive performance was then evaluated on an external data set of patients who received octocog alfa with FVIII levels measured using the one-stage assay. The model presented higher accuracy compared with three previous PK models developed on data similar to the external data set (root mean squared error = 14.6 IU/dL vs. mean of 17.7 IU/dL). Finally, we show that the generative model can be used to accurately impute missing data (< 18% error). In conclusion, the proposed approach introduces interesting new possibilities for model development. In the context of rare disease, the introduction of generative models facilitates sharing of synthetic data, enabling the iterative improvement of population PK models.

A new pharmacokinetic model of urinary methotrexate to assess adherence in rheumatoid arthritis

BACKGROUND AND OBJECTIVES

Methotrexate (MTX) is the first-line therapy for rheumatoid arthritis (RA). While therapeutic adherence is essential to successful management, no objective MTX assay is currently available. Using population pharmacokinetic modelling (PopPK), our objective was to describe the urinary MTX (MTXu) kinetics in treated patients and to evaluate its abilities to assess the MTX-adherence.

METHODS

The association between urinary methotrexate level and methotrexate administration was assessed using a generalized linear model. Then, a population pharmacokinetic model was developed based on data from 59 patients using with Monolix 2021. R2. Simulations were run to establish a reference kinetic profile and evaluate the proportion of samples predicted as true positives.

RESULTS

Compared to the control group, multivariate analysis showed that MTXu was independently associated with methotrexate administration (p < 0.0001) with a sensitivity and specificity greater than 99%. The final PopPK model selected was a two-compartment model with first-order absorption and elimination. Internal and external validation of the model met all predefined criteria. When using an analytical assay with a LOQ equal to 1 nM, the proportion of samples predicted as true positives is over 90%, as a function of MTX dose (7.5-25 mg/week) and post-administration sampling days (1-7 days).

CONCLUSION

We developed a pharmacokinetic model able to describe expected patterns of urinary methotrexate. This allowed us to propose a new objective test of MTX adherence, which could help in routine practice to differentiate patients who are truly unresponsive to methotrexate from those who are unresponsive because of non-adherence.

Negative Impact of ST-Segment Elevation Myocardial Infarction and Morphine Dose on Ticagrelor Uptake and Pharmacodynamics: A Population PK/PD Analysis of Pooled Individual Participant Data

BACKGROUND

Ticagrelor is widely used in patients with stable and acute coronary artery disease. Understanding the factors that influence its pharmacokinetics (PK) and pharmacodynamics (PD) could improve therapeutic outcomes. We therefore performed a pooled population PK/PD analysis using individual patient data from two studies. We focused on the impact of morphine administration and ST-segment elevation myocardial infarction (STEMI) on the risk of high platelet reactivity (HPR) and dyspnea.

METHODS

A parent-metabolite population PK/PD model was developed based on data from 63 STEMI, 50 non-STEMI, and 25 chronic coronary syndrome (CCS) patients. Simulations were then run to evaluate the risk of non-response and adverse events associated with the identified variability factors.

RESULTS

The final PK model consisted of first-order absorption with transit compartments, distribution with two compartments for ticagrelor and one compartment for AR-C124910XX (active metabolite of ticagrelor), and linear elimination for both drugs. The final PK/PD model was an indirect turnover model with production inhibition. Morphine dose and STEMI, independently, had a significant negative effect on the absorption rate (reduction of log([Formula: see text]) by 0.21×morphine dose (mg) and by 2.37 in STEMI patients, both p < 0.001), and the presence of STEMI significantly impacted both efficacy and potency (both p < 0.001). The simulations run with the validated model showed a high rate of non-response in patients with those covariates (RR 1.19 for morphine, 4.11 for STEMI and 5.73 for morphine and STEMI, all three p < 0.001). By increasing ticagrelor dosage, the negative morphine effect was reversible in patients without STEMI and just limited in patients with STEMI.

CONCLUSION

The developed population PK/PD model confirmed the negative impact of morphine administration and presence of STEMI on ticagrelor PK and antiplatelet effect. Increasing ticagrelor doses seems effective in morphine users without STEMI, whereas the STEMI effect is not entirely reversible.

Population Pharmacokinetics of Isavuconazole in Critical Care Patients with COVID-19-Associated Pulmonary Aspergillosis and Monte Carlo Simulations of High Off-Label Doses

Isavuconazole is a triazole antifungal agent recently recommended as first-line therapy for invasive pulmonary aspergillosis. With the COVID-19 pandemic, cases of COVID-19-associated pulmonary aspergillosis (CAPA) have been described with a prevalence ranging from 5 to 30%. We developed and validated a population pharmacokinetic (PKpop) model of isavuconazole plasma concentrations in intensive care unit patients with CAPA. Nonlinear mixed-effect modeling Monolix software were used for PK analysis of 65 plasma trough concentrations from 18 patients. PK parameters were best estimated with a one-compartment model. The mean of ISA plasma concentrations was 1.87 [1.29-2.25] mg/L despite prolonged loading dose (72 h for one-third) and a mean maintenance dose of 300 mg per day. Pharmacokinetics (PK) modeling showed that renal replacement therapy (RRT) was significantly associated with under exposure, explaining a part of clearance variability. The Monte Carlo simulations suggested that the recommended dosing regimen did not achieve the trough target of 2 mg/L in a timely manner (72 h). This is the first isavuconazole PKpop model developed for CAPA critical care patients underlying the need of therapeutic drug monitoring, especially for patients under RRT.

Design of a Prospective Study on Pharmacokinetic-Guided Dosing of Prophylactic Factor Replacement in Hemophilia A and B (OPTI-CLOT TARGET Study)

In resource-rich countries, almost all severe hemophilia patients receive prophylactic replacement therapy with factor concentrates to prevent spontaneous bleeding in joints and muscles to decrease the development of arthropathy and risk of long-term disability. Pharmacokinetic (PK)-guided dosing can be applied to individualize factor replacement therapy, as interindividual differences in PK parameters influence factor VIII (FVIII) and FIX activity levels. PK-guided dosing may therefore lead to more optimal safeguarding of FVIII/FIX levels during prophylaxis and on demand treatment. The OPTI-CLOT TARGET study is a multicenter, nonrandomized, prospective cohort study that aims to investigate the reliability and feasibility of PK-guided prophylactic dosing of factor concentrates in hemophilia-A and -B patients in daily clinical practice. At least 50 patients of all ages on prophylactic treatment using standard half-life (SHL) and extended half-life (EHL) factor concentrates will be included during 9 months and will receive PK-guided treatment. As primary endpoint, a minimum of four FVIII/FIX levels will be compared with FVIII/FIX levels as predicted by Bayesian forecasting. Secondary endpoints are the association of FVIII and FIX levels with bleeding episodes and physical activity, expectations and experiences, economic analyses, and optimization of population PK models. This study will lead to more insight in the reliability and feasibility of PK-guided dosing in hemophilia patients. Moreover, it will contribute to personalization of treatment by greater knowledge of dosing regimens needed to prevent and treat bleeding in the individual patient and provide evidence to more clearly associate factor activity levels with bleeding risk.

Hemophilia A Gene Therapy: Current and Next-Generation Approaches

INTRODUCTION

: Hemophilia comprises a group of X-linked hemorrhagic disorders that result from a deficiency of coagulation factors. The disorder affects mainly males and leads to chronic pain, joint deformity, reduced mobility, and increased mortality. Current therapies require frequent administration of replacement clotting factors, but the emergence of alloantibodies (inhibitors) diminishes their efficacy. New therapies are being developed to produce the deficient clotting factors and prevent the emergence of inhibitors.

AREAS COVERED

: This article provides an update on the characteristics and disease pathophysiology of hemophilia A, as well as current treatments, with a special focus on ongoing clinical trials related to gene replacement therapies.

EXPERT OPINION

: Gene replacement therapies provide safe, durable, and stable transgene expression while avoiding the challenges of clotting factor replacement therapies in patients with hemophilia. Improving the specificity of the viral construct and decreasing the therapeutic dose are critical toward minimizing cellular stress, induction of the unfolded protein response, and the resulting loss of protein production in liver cells. Next-generation gene therapies incorporating chimeric DNA sequences in the transgene can increase clotting factor synthesis and secretion, and advance the efficacy, safety, and durability of gene replacement therapy for hemophilia A as well as other blood clotting disorders.

Population pharmacokinetic modeling of factor concentrates in hemophilia: an overview and evaluation of best practice

The accuracy of pharmacokinetic (PK)-guided dosing depends on the clinical and laboratory data used to construct a population PK model, as well as the patient’s individual PK profile. This review provides a detailed overview of data used for published population PK models for factor VIII (FVIII) and factor IX (FIX) concentrates, to support physicians in their choices of which model best suits each patient. Furthermore, to enhance detailed data collection and documentation, we do suggestions for best practice. A literature search was performed; publications describing prophylactic population PK models for FVIII and FIX concentrates based on original patient data and constructed using nonlinear mixed-effect modeling were included. The following data were collected: detailed demographics, type of product, assessed and included covariates, laboratory specifications, and validation of models. Included models were scored according to our recommendations for best practice, specifically scoring the quality of data documentation as reported. Respectively, 20 models for FVIII and 7 for FIX concentrates were retrieved. Although most models (22/27) included pediatric patients, only 4 reported detailed demographics. The wide range of body weights suggested that overweight and obese adults were represented. Twenty-six models reported the assay applied to measure factor levels, whereas only 16 models named reagents used. Eight models were internally validated using a data subset. This overview presents detailed information on clinical and laboratory data used for published population PK models. We provide recommendations on data collection and documentation to increase the reliability of PK-guided prophylactic dosing of factor concentrates in hemophilia A and B.

External Evaluation of Population Pharmacokinetic Models and Bayes-Based Dosing of Infliximab

Despite the well-demonstrated efficacy of infliximab in inflammatory diseases, treatment failure remains frequent. Dose adjustment using Bayesian methods has shown in silico its interest in achieving target plasma concentrations. However, most of the published models have not been fully validated in accordance with the recommendations. This study aimed to submit these models to an external evaluation and verify their predictive capabilities. Eight models were selected for external evaluation, carried out on an independent database (409 concentrations from 157 patients). Each model was evaluated based on the following parameters: goodness-of-fit (comparison of predictions to observations), residual error model (population weighted residuals (PWRES), individual weighted residuals (IWRES), and normalized prediction distribution errors (NPDE)), and predictive performances (prediction-corrected visual predictive checks (pcVPC) and Bayesian simulations). The performances observed during this external evaluation varied greatly from one model to another. The eight evaluated models showed a significant bias in population predictions (from -7.19 to 7.38 mg/L). Individual predictions showed acceptable bias and precision for six of the eight models (mean error of -0.74 to -0.29 mg/L and mean percent error of -16.6 to -0.4%). Analysis of NPDE and pcVPC confirmed these results and revealed a problem with the inclusion of several covariates (weight, concomitant immunomodulatory treatment, presence of anti-drug antibodies). This external evaluation showed satisfactory results for some models, notably models A and B, and highlighted several prospects for improving the pharmacokinetic models of infliximab for clinical-biological application.

An Algorithm for Nonparametric Estimation of a Multivariate Mixing Distribution with Applications to Population Pharmacokinetics

Population pharmacokinetic (PK) modeling has become a cornerstone of drug development and optimal patient dosing. This approach offers great benefits for datasets with sparse sampling, such as in pediatric patients, and can describe between-patient variability. While most current algorithms assume normal or log-normal distributions for PK parameters, we present a mathematically consistent nonparametric maximum likelihood (NPML) method for estimating multivariate mixing distributions without any assumption about the shape of the distribution. This approach can handle distributions with any shape for all PK parameters. It is shown in convexity theory that the NPML estimator is discrete, meaning that it has finite number of points with nonzero probability. In fact, there are at most N points where N is the number of observed subjects. The original infinite NPML problem then becomes the finite dimensional problem of finding the location and probability of the support points. In the simplest case, each point essentially represents the set of PK parameters for one patient. The probability of the points is found by a primal-dual interior-point method; the location of the support points is found by an adaptive grid method. Our method is able to handle high-dimensional and complex multivariate mixture models. An important application is discussed for the problem of population pharmacokinetics and a nontrivial example is treated. Our algorithm has been successfully applied in hundreds of published pharmacometric studies. In addition to population pharmacokinetics, this research also applies to empirical Bayes estimation and many other areas of applied mathematics. Thereby, this approach presents an important addition to the pharmacometric toolbox for drug development and optimal patient dosing.

Population Pharmacokinetics of Clotting Factor Concentrates and Desmopressin in Hemophilia

Hemophilia A and B are bleeding disorders caused by a deficiency of clotting factor VIII and IX, respectively. Patients with severe hemophilia (< 0.01 IU mL⁻¹) and some patients with moderate hemophilia (0.01–0.05 IU mL⁻¹) administer clotting factor concentrates prophylactically. Desmopressin (d-amino d-arginine vasopressin) can be applied in patients with non-severe hemophilia A. The aim of administration of factor concentrates or desmopressin is the prevention or cessation of bleeding. Despite weight-based dosing, it has been demonstrated that factor concentrates still exhibit considerable pharmacokinetic variability. Population pharmacokinetic analyses, in which this variability is quantified and explained, are increasingly performed in hemophilia research. These analyses can assist in the identification of important patient characteristics and can be applied to perform patient-tailored dosing. This review aims to present and discuss the population pharmacokinetic analyses that have been conducted to develop population pharmacokinetic models describing factor levels after administration of factor VIII or factor IX concentrates or d-amino d-arginine vasopressin. In total, 33 publications were retrieved from the literature. Two approaches were applied to perform population pharmacokinetic analyses, the standard two-stage approach and non-linear mixed-effect modeling. Using the standard two-stage approach, four population pharmacokinetic models were established describing factor VIII levels. In the remaining 29 analyses, the non-linear mixed-effect modeling approach was applied. NONMEM was the preferred software to establish population pharmacokinetic models. In total, 18 population pharmacokinetic analyses were conducted on the basis of data from a single product. From all available population pharmacokinetic analyses, 27 studies also included data from pediatric patients. In the majority of the population pharmacokinetic models, the population pharmacokinetic parameters were allometrically scaled using actual body weight. In this review, the available methods used for constructing the models, key features of these models, patient population characteristics, and established covariate relationships are described in detail.