Comparison of four basic models of indirect pharmacodynamic responses

Population Pharmacokinetics of Pediatric Lopinavir/Ritonavir Oral Pellets in Children Living with HIV in Africa

Antiretroviral therapy for children living with HIV (CLHIV) under 3 years of age commonly includes lopinavir/ritonavir (LPV/r). However, the original liquid LPV/r formulation has taste and cold storage difficulties. To address these challenges, LPV/r oral pellets have been developed. These pellets can be mixed with milk or food for administration and do not require refrigeration. We developed the population pharmacokinetic (PK) model and assessed drug exposure of LPV/r oral pellets administered twice daily to CLHIV per World Health Organization (WHO) weight bands. The PK analysis included Kenyan and Ugandan children participating in the LIVING studies (NCT02346487) receiving LPV/r pellets (40/10 mg) and ABC/3TC (60/30 mg) dispersible tablets. Population PK models were developed for lopinavir (LPV) and ritonavir (RTV) to evaluate the impact of RTV on the oral clearance (CL/F) of LPV. The data obtained from the study were analyzed using nonlinear mixed-effects modeling approach. Data from 514 children, comprising a total of 2,998 plasma concentrations of LPV/r were included in the analysis. The LPV and RTV concentrations were accurately represented by a one-compartment model with first-order absorption (incorporating a lag-time) and elimination. Body weight influenced LPV and RTV PK parameters. The impact of RTV concentrations on the CL/F of LPV was characterized using a maximum effect model. Simulation-predicted target LPV exposures were achieved in children with this pellet formulation across the WHO weight bands. The LPV/r pellets dosed in accordance with WHO weight bands provide adequate LPV exposures in Kenyan and Ugandan children weighing 3.0 to 24.9 kg.

Model-Based Virtual PK/PD Exploration and Machine Learning Approach to Define PK Drivers in Early Drug Discovery

While poor translatability of preclinical efficacy models can be responsible for clinical phase II failures, misdefinition of the optimal PK properties required to achieve therapeutic efficacy can also be a contributing factor. In the present work, the pharmacological dependency of PK end points in driving efficacy is demonstrated for six common pharmacological processes via model-based analysis. The analysis shows that the response is driven by multiple pharmacology-specific PK end points that change with how the response is defined. Moreover, the results demonstrate that the most important chemical structural features influencing response are specific to both target and downstream pharmacology, meaning the design and screening criteria must be defined uniquely for each target and corresponding pharmacology. The model-based virtual exploration of PK/PD relationships presented in this work offers one approach to identify target pharmacology-specific PK drivers and the associated potency-ADME space early in discovery to increase the probability of success and, ultimately, clinical attrition.

In vitro PK/PD modeling of tyrosine kinase inhibitors in non-small cell lung cancer cell lines

Tyrosine kinase inhibitors (TKIs) are routinely prescribed for the treatment of non-small cell lung cancer (NSCLC). As with all medications, patients can experience adverse events due to TKIs. Unfortunately, the relationship between many TKIs and the occurrence of certain adverse events remains unclear. There are limited in vivo studies which focus on TKIs and their effects on different regulation pathways. Many in vitro studies, however, that investigate the effects of TKIs observe additional changes, such as changes in gene activations or protein expressions. These studies could potentially help to gain greater understanding of the mechanisms for TKI induced adverse events. However, in order to utilize these pathways in a pharmacokinetic/pharmacodynamic (PK/PD) framework, an in vitro PK/PD model needs to be developed, in order to characterize the effects of TKIs in NSCLC cell lines. Through the use of ordinary differential equations, cell viability data and nonlinear mixed effects modeling, an in vitro TKI PK/PD model was developed with estimated PK and PD parameter values for the TKIs alectinib, crizotinib, erlotinib, and gefitinib. The relative standard errors for the population parameters are all less than 25%. The inclusion of random effects enabled the model to predict individual parameter values which provided a closer fit to the observed response. It is hoped that this model can be extended to include in vitro data of certain pathways that may potentially be linked with adverse events and provide a better understanding of TKI-induced adverse events.

Physiological Indirect Response Model to Omics-Powered Quantitative Systems Pharmacology Model

Over the past several decades, mathematical modeling has been applied to increasingly wider scopes of questions in drug development. Accordingly, the range of modeling tools has also been evolving, as showcased by contributions of Jusko and colleagues: from basic pharmacokinetics/pharmacodynamics (PK/PD) modeling to today's platform-based approach of quantitative systems pharmacology (QSP) modeling. Aimed at understanding the mechanism of action of investigational drugs, QSP models characterize systemic effects by incorporating information about cellular signaling networks, which is often represented by omics data. In this perspective, we share a few examples illustrating approaches for the integration of omics into mechanistic QSP modeling. We briefly overview how the evolution of PK/PD modeling into QSP has been accompanied by an increase in available data and the complexity of mathematical methods that integrate it. We discuss current gaps and challenges of integrating omics data into QSP models and propose several potential areas where integrated QSP and omics modeling may benefit drug development.

Fifty Years of Unraveling the Clinical Pharmacology of Corticosteroids

This review will highlight portions of Dr. William Jusko's and colleagues' work that affected the clinical use and study of corticosteroids in acute and chronic disease management. Selected publications related to corticosteroid pharmacokinetics and pharmacodynamics from the 1970s through today were included in this review, with a focus on the foundational human-based studies conducted in the 1970s-1990s. Dr. Jusko contributed significantly to early corticosteroid pharmacology across several domains including: 1) foundational corticosteroid pharmacokinetic methods and parameter development, 2) disease state-variation in corticosteroid pharmacokinetics, 3) drug interaction effects on corticosteroid pharmacokinetics, and 4) early corticosteroid pharmacodynamic studies. In an era where little was known about the pharmacokinetics and pharmacodynamics of corticosteroids, Dr. Jusko's work opened the eyes of researchers and clinicians to the potential for disease and drug interactions that could reduce or enhance the effects of corticosteroids. This significant body of work paved the way for alternative routes of administration that would be useful in concentrating the activity at the site of action and markedly reduced systemic drug exposure, minimizing the risk of adverse effects through application of the dose-sparing pharmacokinetic and pharmacodynamic principles.

Pharmacodynamic Age Structured Population Model For Cell Trafficking

OBJECTIVES

Cell trafficking encompasses movement of the immune system cells (e.g., granulocytes, lymphocytes) between the blood and the extravascular tissues (e.g., lymph nodes). Corticosteroids are known to suppress cell trafficking. The age-structured cell population models introduce the transit time as a structure that allows one to quantify the distribution of times the immune cells spend in the blood and the extravascular tissues. The objective of this work is to develop an age-structured cell population model describing drug effects on cell trafficking and to implement the model in pharmacometric software to enable parameter estimation and simulations.

METHODS

We adopted the well-known McKendrick age-structured population model to describe the age distributions in two cell populations: blood cells and cells in the extravascular space. The hazard of cell recirculation from the extravascular tissues was age dependent and described by the Weibull function with the shape ν and scale β parameters. The drug effect on cell trafficking was modeled as the product of the Emax function of the drug plasma concentration and the Weibull hazard. The model was implemented in NONMEM 7.5.1. The model was applied to the basophil data in 34 healthy subjects who received a single intramuscular or oral dose of 6 mg dexamethasone (DEX). A recently published pharmacokinetic model was applied to describe DEX plasma concentration. Typical values of parameter estimates were further used to simulate the DEX effect of the basophil mean transit time in the extravascular tissues.

RESULTS

Simulations of basophil time courses for varying ν demonstrated that the rebound in the blood count data following drug administration is only possible for ν >1. The estimates of model parameters were ν = 3.02, β = 0.00863 1/h, and IC50 = 7.47 ng/mL. The calculated baseline mean transit times of basophils in the blood 7.2 h and extravascular tissues 104.9 h agree with the values reported in the literature.

CONCLUSIONS

We introduced an age-structured population model to describe cell trafficking between the blood and extravascular tissues. The model was adopted to account for the inhibitory drug effect on the cell recirculation. We showed that the age structure is essential to explain the rebound observed in the blood count response to a single dose drug administration. The model was validated using the basophil responses to DEX treatment in healthy subjects.

The Physiological and Pharmacological Significance of the Circadian Timing of the HPA Axis: A Mathematical Modeling Approach

As a potent endogenous regulator of homeostasis, the circadian time-keeping system synchronizes internal physiology to periodic changes in the external environment to enhance survival. Adapting endogenous rhythms to the external time is accomplished hierarchically with the central pacemaker located in the suprachiasmatic nucleus (SCN) signaling the hypothalamus-pituitary-adrenal (HPA) axis to release hormones, notably cortisol, which help maintain the body's circadian rhythm. Given the essential role of HPA-releasing hormones in regulating physiological functions, including immune response, cell cycle, and energy metabolism, their daily variation is critical for the proper function of the circadian timing system. In this review, we focus on cortisol and key fundamental properties of the HPA axis and highlight their importance in controlling circadian dynamics. We demonstrate how systems-driven, mathematical modeling of the HPA axis complements experimental findings, enhances our understanding of complex physiological systems, helps predict potential mechanisms of action, and elucidates the consequences of circadian disruption. Finally, we outline the implications of circadian regulation in the context of personalized chronotherapy. Focusing on the chrono-pharmacology of synthetic glucocorticoids, we review the challenges and opportunities associated with moving toward personalized therapies that capitalize on circadian rhythms.

Pharmacodynamic Models of Indirect Effects and Irreversible Inactivation with Turnover: Applicability to Mechanism-Based Modeling of Gene Silencing and Targeted Protein Degradation

Indirect response (IDR) and turnover with inactivation (TI) comprise two arrays of mechanism-based pharmacodynamic (PD) models widely used to describe delayed drug effects. IDR Model-IV (stimulation of response loss) and TI (irreversible loss) have been described with discerning "signature" profiles; classical IDR-IV response-time profiles display slow declines where peak response shifts later with increasing dose, whereas TI profiles feature steep response declines with earlier-shifting nadirs. Herein, we demonstrate mathematical convergence of IDR-IV and TI models upon implementation with identical linear versus nonlinear pharmacologic effect terms. Time of peak response in IDR-IV can in fact shift earlier or later depending on PK or PD parameters (e.g., kel, Smax) and effect type. A generalized dynamic model linking mRNA and protein turnover is proposed. Applicability of IDR-IV and TI, with either linear or nonlinear terms acting on degradation/catabolism/loss of response, is demonstrated through model-fitting PK-PD effects of three proteolysis-targeting chimeras (PROTACs) and two ligand-conjugated small interfering RNAs (siRNA). This work clarifies mathematical properties, convergence, and expected responses of IDR-IV and TI, demonstrates their applicability for targeted gene-silencing and protein-degrading agents, and illustrates how well-designed in vivo studies covering broad dose ranges with richly sampled time-points can influence PK-PD model structure and parameter resolution.

Target Reserve and Turnover Parameters Determine Rightward Shift of Enalaprilat Potency From its Binding Affinity to the Angiotensin Converting Enzyme

Drug effects are often assumed to be directly proportional to the fraction of occupied targets. However, for a number of antagonists that exhibit target-mediated drug disposition (TMDD), such as angiotensin-converting enzyme (ACE) inhibitors, drug binding to the target at low concentrations may be significant enough to influence pharmacokinetics but insufficient to elicit a drug response (i.e., differences in drug-target binding affinity and potency). In this study, a pharmacokinetic/pharmacodynamic model for enalaprilat was developed in humans to provide a theoretical framework for assessing the relationship between ex vivo drug potency (IC50) and in vivo target-binding affinity (KD). The model includes competitive binding of angiotensin I and enalaprilat to ACE and accounts for the circulating target pool. Data were obtained from the literature, and model fitting and parameter estimation were conducted using maximum likelihood in ADAPT5. The model adequately characterized time-courses of enalaprilat concentrations and four biomarkers in the renin-angiotensin system and provided estimates for in vivo KD (0.646 nM) and system-specific parameters, such as total target density (32.0 nM) and fraction of circulating target (19.8%), which were in agreement with previous reports. Model simulations were used to predict the concentration-effect curve of enalaprilat, revealing a 6.3-fold increase in IC50 from KD. Additional simulations demonstrated that target reserve and degradation parameters are key factors determining the extent of shift of enalaprilat ex vivo potency from its in vivo binding affinity. This may be a common phenomenon for drugs exhibiting TMDD and has implications for translating binding affinity to potency in drug development.

Population pharmacokinetic-pharmacodynamic modeling of clopidogrel for dose regimen optimization based on CYP2C19 phenotypes: A proof of concept study

Clopidogrel is an antiplatelet drug used to reduce the risk of acute coronary syndrome and stroke. It is converted by CYP2C19 to its active metabolite; therefore, poor metabolizers (PMs) of CYP2C19 exhibit diminished antiplatelet effects. Herein, we conducted a proof-of-concept study for using population pharmacokinetic-pharmacodynamic (PK-PD) modeling to recommend a personalized clopidogrel dosing regimen for individuals with varying CYP2C19 phenotypes and baseline P2Y12 reaction unit (PRU) levels. Data from a prospective phase I clinical trial involving 36 healthy male participants were used to develop the population PK-PD model predicting the concentrations of clopidogrel, clopidogrel H4, and clopidogrel carboxylic acid, and linking clopidogrel H4 concentrations to changes in PRU levels. A two-compartment model effectively described the PKs of both clopidogrel and clopidogrel carboxylic acid, and a one-compartment model of those of clopidogrel H4. The CYP2C19 phenotype was identified as a significant covariate influencing the metabolic conversion of the parent drug to its metabolites. A PD submodel of clopidogrel H4 that stimulated the fractional turnover rate of PRU levels showed the best performance. Monte Carlo simulations suggested that PMs require three to four times higher doses than extensive metabolizers to reach the target PRU level. Individuals within the top 20th percentile of baseline PRU levels were shown to require 2.5-3 times higher doses than those in the bottom 20th percentile. We successfully developed a population PK-PD model for clopidogrel considering the impact of CYP2C19 phenotypes and baseline PRU levels. Further studies are necessary to confirm actual dosing recommendations for clopidogrel.

Local application of engineered insulin-like growth factor I mRNA demonstrates regenerative therapeutic potential in vivo

Insulin-like growth factor I (IGF-I) is a growth-promoting anabolic hormone that fosters cell growth and tissue homeostasis. IGF-I deficiency is associated with several diseases, including growth disorders and neurological and musculoskeletal diseases due to impaired regeneration. Despite the vast regenerative potential of IGF-I, its unfavorable pharmacokinetic profile has prevented it from being used therapeutically. In this study, we resolved these challenges by the local administration of IGF-I mRNA, which ensures desirable homeostatic kinetics and non-systemic, local dose-dependent expression of IGF-I protein. Furthermore, IGF-I mRNA constructs were sequence engineered with heterologous signal peptides, which improved in vitro protein secretion (2- to 6-fold) and accelerated in vivo functional regeneration (16-fold) over endogenous IGF-I mRNA. The regenerative potential of engineered IGF-I mRNA was validated in a mouse myotoxic muscle injury and rabbit spinal disc herniation models. Engineered IGF-I mRNA had a half-life of 17-25 h in muscle tissue and showed dose-dependent expression of IGF-I over 2-3 days. Animal models confirm that locally administered IGF-I mRNA remained at the site of injection, contributing to the safety profile of mRNA-based treatment in regenerative medicine. In summary, we demonstrate that engineered IGF-I mRNA holds therapeutic potential with high clinical translatability in different diseases.

A semimechanistic pharmacokinetic/pharmacodynamic model for alanine aminotransferase-based hepatotoxicity of methotrexate in paediatric patients with acute lymphoid leukaemia

AIMS

Methotrexate (MTX) is recognized for its potential to induce hepatotoxicity, commonly manifested by elevated alanine aminotransferase (ALT) levels. However, the quantitative relationship between the pharmacokinetics (PK) of MTX and ALT-based hepatotoxicity remains unclear. This study aimed to develop a semimechanistic PK/pharmacodynamic (PD) model to characterize the MTX-induced hepatotoxicity based on ALT in paediatric patients with acute lymphoid leukaemia.

METHODS

A retrospective study was conducted on paediatric patients who received high-dose (3-5 g/m2 ) MTX treatment. MTX concentrations were assessed at 24-h intervals until the concentration dropped below 0.1 μmol/L. ALT concentrations were measured both before and after MTX administration. A population PK model was initially developed, which was later connected to a semimechanistic hepatotoxicity model.

RESULTS

The PK model was developed using 354 MTX concentrations obtained from 51 patients, while the PD model was constructed using 379 ALT concentrations collected from 48 patients. The optimal PK model for MTX consisted of a 2-compartment structure, where body surface area served as a covariate for clearance and central volume of distribution. An indirect response model coupled to a liver injury signal transduction model was developed to describe the dynamics of ALT after MTX administration. The drug effect was adequately described by a linear model, exhibiting considerable interoccasion variability for each treatment session. No significant covariates were identified to have an impact on the PD parameters.

CONCLUSION

A semimechanistic model was developed to describe ALT-based hepatotoxicity of MTX, and it has the potential to serve as a valuable tool for characterizing drug-induced hepatotoxicity.

C-Reactive Protein as an Early Predictor of Efficacy in Advanced Non-Small-Cell Lung Cancer Patients: A Tumor Dynamics-Biomarker Modeling Framework

In oncology, longitudinal biomarkers reflecting the patient's status and disease evolution can offer reliable predictions of the patient's response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions.

Alternative routes for tranexamic acid treatment in obstetric bleeding (WOMAN-PharmacoTXA trial): a randomised trial and pharmacological study in caesarean section births

OBJECTIVE

To examine the safety, efficacy and pharmacology of intravenous (IV), intramuscular (IM) and oral tranexamic acid (TXA) use in pregnant women.

DESIGN

Randomised, open-label trial.

SETTING

Hospitals in Pakistan and Zambia.

POPULATION

Women giving birth by caesarean section.

METHODS

Women were randomised to receive 1 g IV, 1 g IM, 4 g oral TXA or no TXA. Adverse events in women and neonates were recorded. TXA concentration in whole blood was measured and the concentrations over time were examined with population pharmacokinetics. The relationship between drug exposure and D-dimer was explored. The trial registration is NCT04274335.

MAIN OUTCOME MEASURES

Concentration of TXA in maternal blood.

RESULTS

Of the 120 women included in the randomised safety study, there were no serious maternal or neonatal adverse events. TXA concentrations in 755 maternal blood and 87 cord blood samples were described by a two-compartment model with one effect compartment linked by rate transfer constants. Maximum maternal concentrations were 46.9, 21.6 and 18.1 mg/L for IV, IM and oral administration, respectively, and 9.5, 7.9 and 9.1 mg/L in the neonates. The TXA response was modelled as an inhibitory effect on the D-dimer production rate. The half-maximal inhibitory concentration (IC50 ) was 7.5 mg/L and was achieved after 2.6, 6.4 and 47 minutes with IV, IM and oral administration of TXA, respectively.

CONCLUSIONS

Both IM and oral TXA are well tolerated. Oral TXA took about 1 hour to reach minimum therapeutic concentrations and would not be suitable for emergency treatment. Intramuscular TXA inhibits fibrinolysis within 10 minutes and may be a suitable alternative to IV.

A population pharmacokinetic and pharmacokinetic-pharmacodynamic analysis of vupanorsen from phase I and phase II studies

Vupanorsen (PF-07285557) is a second-generation ligand-conjugated 2'O-methoxyethyl modified antisense oligonucleotide designed to target angiopoietin-like 3 (ANGPTL3) mRNA expressed by the liver, shown to reduce lipids and apolipoproteins in subjects with dyslipidemia. Using pooled data from two phase I studies of participants with elevated triglycerides (Western: n = 48 and Japanese: n = 12), and two phase II studies of patients with hypertriglyceridemia, diabetes, and nonalcoholic fatty liver disease (n = 105), and statin-treated patients with dyslipidemia (n = 286), we developed population pharmacokinetic (PK) and PK/pharmacodynamic (PK/PD) models. Efficacy target values were set a priori to -75%, -60%, and -35% for ANGPTL3, triglyceride (TG), and non-high-density lipoprotein-cholesterol (non-HDL-C), respectively. Covariates evaluated via a full model approach included baseline body weight, age, estimated glomerular filtration rate (eGFR), anti-drug antibody (ADA) status, sex, and race. Vupanorsen population PK was well-characterized by a two-compartment model with first-order absorption and elimination. Apparent clearance (CL/F) for ADA-positive, female, and Asian participants was estimated to be about 62% (relative standard error 12%), 18% (9%), and 30% (20%) lower than ADA-negative, male, and non-Asian participants, respectively. The associations between CL/F and Black race, age, and eGFR were negligible. The developed population PK/PD model was robust to predict the dose-response relationships. The model predicted that ANGPTL3 target reduction of 75% can be sufficiently achieved with a 320-mg monthly dose of vupanorsen, but target values for TG and non-HDL-C were not expected to be achieved at doses up to 320 mg monthly in patients with dyslipidemia.

PBTK-TD model of the phagocytosis activity in three-spined stickleback exposed to BPA

Due to the high production volume and persistence in the environment of bisphenol A (BPA) and its substitutes, realistic exposure scenarii were proposed in some species to better understand the relationship between external and internal concentrations. For example, a recent PBTK model has been developed and adapted to BPA ADME (Absorption, Distribution, Metabolization, and Excretion) processes in three-spined stickleback. These substances have an impact on organism physiology including reproductive and immune functions. In this context, physiologically-based toxicokinetic models coupled with toxicodynamics (PBTK-TD) have proven to be valuable tools to fill the knowledge gap between external exposure and effect dynamics. The aim of the current work was to explain the impact of BPA on the immune response by determining its temporality. In addition, the relationship between BPA dose and these responses was investigated using a PBTK-TD model. Two experiments were performed on stickleback to characterize their biomarker responses, (i) a short exposure (14 days) at 0, 10 and 100 µg/L, including a depuration phase (7 days), and (ii) a long exposure (21 days) at 100 µg/L to measure the immunomarker dynamic over a long period. The fish spleens were sampled to analyze immune responses of stickleback at various times of exposure and depuration: leucocyte distribution, phagocytic capacity and efficiency, lysosomal presence and leucocyte respiratory burst index. At the same date, blood, muscle, and liver were sampled to quantify BPA and their metabolites (BPA monoglucuronide and BPA monosulfate). All these data enabled the development of the indirect pharmacodynamic models (PBTK-TD) by implementing the responses of biomarkers in the existing BPA PBTK of stickleback. The results shown a high induction of phagocytosis activity by BPA in the two exposure conditions. Furthermore, the immunomarkers exhibit very different temporal dynamics. This study demonstrates the need of a thorough characterization of biomarker response for a further use in Environmental Biomonitoring.

Altered glucose-dependent secretion of glucagon and ACTH is associated with insulin resistance, assessed by population analysis

This study aimed to characterize how the dysregulation of counter-regulatory hormones can contribute to insulin resistance and potentially to diabetes. Therefore, we investigated the association between insulin sensitivity and the glucose- and insulin-dependent secretion of glucagon, adrenocorticotropic hormone (ACTH), and cortisol in non-diabetic individuals using a population model analysis. Data, from hyperinsulinemic-hypoglycemic clamps, were pooled for analysis, including 52 individuals with a wide range of insulin resistance (reflected by glucose infusion rate 20-60 min; GIR20-60min). Glucagon secretion was suppressed by glucose and, to a lesser extent, insulin. The GIR20-60min and BMI were identified as predictors of the insulin effect on glucagon. At normoglycemia (5 mmol/L), a 90% suppression of glucagon was achieved at insulin concentrations of 16.3 and 43.4 µU/mL in individuals belonging to the highest and lowest quantiles of insulin sensitivity, respectively. Insulin resistance of glucagon secretion explained the elevated fasting glucagon for individuals with a low GIR20-60min. ACTH secretion was suppressed by glucose and not affected by insulin. The GIR20-60min was superior to other measures as a predictor of glucose-dependent ACTH secretion, with 90% suppression of ACTH secretion by glucose at 3.1 and 3.5 mmol/L for insulin-sensitive and insulin-resistant individuals, respectively. This difference may appear small but shifts the suppression range into normoglycemia for individuals with insulin resistance, thus, leading to earlier and greater ACTH/cortisol response when the glucose falls. Based on modeling of pooled glucose-clamp data, insulin resistance was associated with generally elevated glucagon and a potentiated cortisol-axis response to hypoglycemia, and over time both hormonal pathways may therefore contribute to dysglycemia and possibly type 2 diabetes.

Pharmacokinetic/pharmacodynamic model of a methionine starvation based anti-cancer drug

A new therapeutic approach against cancer is developed by the firm Erytech. This approach is based on starved cancer cells of an amino acid essential to their growth (the L-methionine). The depletion of plasma methionine level can be induced by an enzyme, the methionine-γ-lyase. The new therapeutic formulation is a suspension of erythrocytes encapsulating the activated enzyme. Our work reproduces a preclinical trial of a new anti-cancer drug with a mathematical model and numerical simulations in order to replace animal experiments and to have a deeper insight on the underlying processes. With a combination of a pharmacokinetic/pharmacodynamic model for the enzyme, substrate, and co-factor with a hybrid model for tumor, we develop a "global model" that can be calibrated to simulate different human cancer cell lines. The hybrid model includes a system of ordinary differential equations for the intracellular concentrations, partial differential equations for the concentrations of nutrients and drugs in the extracellular matrix, and individual based model for cancer cells. This model describes cell motion, division, differentiation, and death determined by the intracellular concentrations. The models are developed on the basis of experiments in mice carried out by Erytech. Parameters of the pharmacokinetics model were determined by fitting a part of experimental data on the concentration of methionine in blood. Remaining experimental protocols effectuated by Erytech were used to validate the model. The validated PK model allowed the investigation of pharmacodynamics of cell populations. Numerical simulations with the global model show cell synchronization and proliferation arrest due to treatment similar to the available experiments. Thus, computer modeling confirms a possible effect of treatment based on the decrease of methionine concentration. The main goal of the study is the development of an integrated pharmacokinetic/pharmacodynamic model for encapsulated methioninase and of a mathematical model of tumor growth/regression in order to determine the kinetics of L-methionine depletion after co-administration of Erymet product and Pyridoxine.

Pharmacokinetic/Pharmacodynamic Modeling of Dexamethasone Anti-Inflammatory and Immunomodulatory Effects in LPS-Challenged Rats: A Model for Cytokine Release Syndrome

Dexamethasone (DEX) is a potent synthetic glucocorticoid used for the treatment of variety of inflammatory and immune-mediated disorders. The RECOVERY clinical trial revealed benefits of DEX therapy in COVID-19 patients. Severe SARS-CoV-2 infection leads to an excessive inflammatory reaction commonly known as a cytokine release syndrome that is associated with activation of the toll like receptor 4 (TLR4) signaling pathway. The possible mechanism of action of DEX in the treatment of COVID-19 is related to its anti-inflammatory activity arising from inhibition of cytokine production but may be also attributed to its influence on immune cell trafficking and turnover. This study, by means of pharmacokinetic/pharmacodynamic modeling, aimed at the comprehensive quantitative assessment of DEX effects in lipopolysaccharide-challenged rats and to describe interrelations among relevant signaling molecules in this animal model of cytokine release syndrome induced by activation of TLR4 pathway. DEX was administered in a range of doses from 0.005 to 2.25 mg·kg-1 in LPS-challenged rats. Serum DEX, corticosterone (CST), tumor necrosis factor α, interleukin-6, and nitric oxide as well as lymphocyte and granulocyte counts in peripheral blood were quantified at different time points. A minimal physiologically based pharmacokinetic/pharmacodynamic (mPBPK/PD) model was proposed characterizing the time courses of plasma DEX and the investigated biomarkers. A high but not complete inhibition of production of inflammatory mediators and CST was produced in vivo by DEX. The mPBPK/PD model, upon translation to humans, may help to optimize DEX therapy in patients with diseases associated with excessive production of inflammatory mediators, such as COVID-19. SIGNIFICANCE STATEMENT: A mPBPK/PD model was developed to describe concentration-time profiles of plasma DEX, mediators of inflammation, and immune cell trafficking and turnover in LPS-challenged rats. Interrelations among DEX and relevant biomarkers were reflected in the mechanistic model structure. The mPBPK/PD model enabled quantitative assessment of in vivo potency of DEX and, upon translation to humans, may help optimize dosing regimens of DEX for the treatment of immune-related conditions associated with exaggerated immune response.

Computing optimal drug dosing with OptiDose: implementation in NONMEM

Determining a drug dosing recommendation with a PKPD model can be a laborious and complex task. Recently, an optimal dosing algorithm (OptiDose) was developed to compute the optimal doses for any pharmacometrics/PKPD model for a given dosing scenario. In the present work, we reformulate the underlying optimal control problem and elaborate how to solve it with standard commands in the software NONMEM. To demonstrate the potential of the OptiDose implementation in NONMEM, four relevant but substantially different optimal dosing tasks are solved. In addition, the impact of different dosing scenarios as well as the choice of the therapeutic goal on the computed optimal doses are discussed.

Latent variable indirect response modeling of clinical efficacy endpoints with combination therapy: application to guselkumab and golimumab in patients with ulcerative colitis

Accurate characterization of longitudinal exposure-response of clinical trial endpoints is important in optimizing dose and dosing regimens in drug development. Clinical endpoints are often categorical, for which much progress has been made recently in latent variable indirect response (IDR) modeling with single drugs. However, such applications have not yet been used for trials employing multiple drugs administered concurrently. This study aims to demonstrate that the latent variable IDR approach provides a convenient longitudinal exposure-response modeling framework to assess potential interaction effects of combination therapies. This is illustrated by an application to the exposure-response modeling of guselkumab, a monoclonal antibody in clinical development that blocks the interleukin-23p19 subunit, and golimumab, a monoclonal antibody that binds with high affinity to tumor necrosis factor-alpha. A Phase 2a study was conducted in 214 patients with moderate-to severe active ulcerative colitis for which longitudinal assessments of disease severity based on patient-reported measures of rectal bleeding, stool frequency, and symptomatic remission were evaluated as categorical endpoints, and fecal calprotectin as a continuous endpoint. The modeling results suggested independent pharmacodynamic guselkumab and golimumab effects on fecal calprotectin as a continuous endpoint, as well as interaction effects on the categorical endpoints that may be explained by an additional pathway of competitive interaction.

A Mechanistic Pharmacodynamic Modeling Framework for the Assessment and Optimization of Proteolysis Targeting Chimeras (PROTACs)

The field of targeted protein degradation is growing exponentially. Yet, there is an unmet need for pharmacokinetic/pharmacodynamic models that provide mechanistic insights, while also being practically useful in a drug discovery setting. Therefore, we have developed a comprehensive modeling framework which can be applied to experimental data from routine projects to: (1) assess PROTACs based on accurate degradation metrics, (2) guide compound optimization of the most critical parameters, and (3) link degradation to downstream pharmacodynamic effects. The presented framework contains a number of first-time features: (1) a mechanistic model to fit the hook effect in the PROTAC concentration-degradation profile, (2) quantification of the role of target occupancy in the PROTAC mechanism of action and (3) deconvolution of the effects of target degradation and target inhibition by PROTACs on the overall pharmacodynamic response. To illustrate applicability and to build confidence, we have employed these three models to analyze exemplary data on various compounds from different projects and targets. The presented framework allows researchers to tailor their experimental work and to arrive at a better understanding of their results, ultimately leading to more successful PROTAC discovery. While the focus here lies on in vitro pharmacology experiments, key implications for in vivo studies are also discussed.

Clinically practical pharmacometrics computer model to evaluate and personalize pharmacotherapy in pediatric rare diseases: application to Graves' disease

Objectives

Graves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy.

Methods

Retrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis.

Results

Data from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity.

Discussion

We present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

Semimechanistic modeling of copeptin and aldosterone kinetics and dynamics in response to rehydration treatment for diabetic ketoacidosis in children

Diabetic ketoacidosis (DKA), a frequent complication of type 1 diabetes (T1D), is characterized by hyperosmolar hypovolemia. The response of water-regulating hormones arginine vasopressin (AVP; antidiuretic hormone) and aldosterone to DKA treatment in children is not well understood, although they may have potential as future diagnostic, prognostic, and/or treatment monitoring markers in diabetic patients. We aimed to characterize the dynamics of the response in copeptin (marker for AVP) and aldosterone secretion to rehydration treatment in pediatric patients with DKA. Data originated from a prospective, observational, multicenter study including 28 pediatric T1D patients treated for DKA (median age, 11.5 years; weight, 35 kg). Serial measurements of hormone levels were obtained during 72 h following rehydration start. Semimechanistic pharmacometric modeling was used to analyze the kinetic/dynamic relationship of copeptin and aldosterone secretion in response to the correction of hyperosmolality and hypovolemia, respectively. Modeling revealed different sensitivities for osmolality-dependent copeptin secretion during the first 72 h of rehydration, possibly explained by an osmotic shift introduced by hypovolemia. Response in aldosterone secretion to the correction of hypovolemia seemed to be delayed, which was well described by an extra upstream turnover compartment, possibly representing chronic upregulation of aldosterone synthase (cytochrome P450 11B2). In conclusion, semimechanistic modeling provided novel physiological insights in hormonal water regulation in pediatric patients during DKA treatment, providing rationale to further evaluate the potential of monitoring copeptin, but not aldosterone due to its delayed response, for future optimization of rehydration treatment to reduce the risk of acute complications such as cerebral edema.

Mechanistic Modeling of the Interplay Between Host Immune System, IL-7 and UCART19 Allogeneic CAR-T Cells in Adult B-cell Acute Lymphoblastic Leukemia

Chimeric antigen receptor (CAR)-T cell therapies have shown tremendous results against various hematologic cancers. Prior to cell infusion, a host preconditioning regimen is required to achieve lymphodepletion and improve CAR-T cell pharmacokinetic exposure, leading to greater chances of therapeutic success. To better understand and quantify the impact of the preconditioning regimen, we built a population-based mechanistic pharmacokinetic-pharmacodynamic model describing the complex interplay between lymphodepletion, host immune system, homeostatic cytokines, and pharmacokinetics of UCART19, an allogeneic product developed against CD19⁺ B cells. Data were collected from a phase I clinical trial in adult relapsed/refractory B-cell acute lymphoblastic leukemia and revealed three different UCART19 temporal patterns: (i) expansion and persistence, (ii) transient expansion with subsequent rapid decline, and (iii) absence of observed expansion. On the basis of translational assumptions, the final model was able to capture this variability through the incorporation of IL-7 kinetics, which are thought to be increased owing to lymphodepletion, and through an elimination of UCART19 by host T cells, which is specific to the allogeneic context. Simulations from the final model recapitulated UCART19 expansion rates in the clinical trial, confirmed the need for alemtuzumab to observe UCART19 expansion (along with fludarabine cyclophosphamide), quantified the importance of allogeneic elimination, and suggested a high impact of multipotent memory T-cell subpopulations on UCART19 expansion and persistence. In addition to supporting the role of host cytokines and lymphocytes in CAR-T cell therapy, such a model could help optimizing the preconditioning regimens in future clinical trials.

SIGNIFICANCE

A mathematical mechanistic pharmacokinetic/pharmacodynamic model supports and captures quantitatively the beneficial impact of lymphodepleting patients before the infusion of an allogeneic CAR-T cell product. Mediation through IL-7 increase and host T lymphocytes decrease is underlined, and the model can be further used to optimize CAR-T cell therapies lymphodepletion regimen.

A multi-model approach to predict efficacious clinical dose for an anti-TGF-β antibody (GC2008) in the treatment of osteogenesis imperfecta

Osteogenesis imperfecta (OI) is a heterogeneous group of inherited bone dysplasias characterized by reduced skeletal mass and bone fragility. Although the primary manifestation of the disease involves the skeleton, OI is a generalized connective tissue disorder that requires a multidisciplinary treatment approach. Recent studies indicate that application of a transforming growth factor beta (TGF-β) neutralizing antibody increased bone volume fraction (BVF) and strength in an OI mouse model and improved bone mineral density (BMD) in a small cohort of patients with OI. In this work, we have developed a multitiered quantitative pharmacology approach to predict human efficacious dose of a new anti-TGF-β antibody drug candidate (GC2008). This method aims to translate GC2008 pharmacokinetic/pharmacodynamic (PK/PD) relationship in patients, using a number of appropriate mathematical models and available preclinical and clinical data. Compartmental PK linked with an indirect PD effect model was used to characterize both pre-clinical and clinical PK/PD data and predict a GC2008 dose that would significantly increase BMD or BVF in patients with OI. Furthermore, a physiologically-based pharmacokinetic model incorporating GC2008 and the body's physiological properties was developed and used to predict a GC2008 dose that would decrease the TGF-β level in bone to that of healthy individuals. By using multiple models, we aim to reveal information for different aspects of OI disease that will ultimately lead to a more informed dose projection of GC2008 in humans. The different modeling efforts predicted a similar range of pharmacologically relevant doses in patients with OI providing an informed approach for an early clinical dose setting.

Delayed concentration effect models for dabigatran anticoagulation

INTRODUCTION

Dabigatran is an anticoagulant with potential use during cardiopulmonary bypass in children and adults. The pharmacokinetic-pharmacodynamic relationship for dabigatran anticoagulation effect was investigated in an intact animal model using rabbits.

METHODS

Ten male New Zealand white rabbits were given a novel preparation of intravenous dabigatran 15 mg.kg^-1 . Blood samples were collected for activated clotting time, thromboelastometric reaction time, and drug assay at 5, 15, 30, 60, 120, 180, 300, and 420 min. Plasma dabigatran concentrations and coagulation measures were analyzed using an integrated pharmacokinetic-pharmacodynamic model using nonlinear mixed effects. Effects (activated clotting and thromboelastometric reaction times) were described using a sigmoidal E_MAX model. Pharmacokinetic parameters were scaled using allometry and standardized to a 70 kg size standard. Pharmacodynamics were investigated using both an effect compartment model and an indirect response (turnover) model.

RESULTS

A two-compartment model described dabigatran pharmacokinetics with a clearance (CL 0.135 L.min^-1 .70 kg^-1 ), intercompartment clearance (Q 0.33 L.min^-1 .70 kg^-1 ), central volume of distribution (V1 12.3 L.70 kg^-1 ), and peripheral volume of distribution (V2 30.1 L.70 kg^-1 ). The effect compartment model estimates for a sigmoid E_MAX model with activated clotting time had an effect site concentration (Ce₅₀ 20.1 mg.L^-1 ) eliciting half of the maximal effect (E_MAX 899 s) and a Hill coefficient (N 0.66). The equilibration half time (T_1/2 keo) was 1.4 min. Results for the reaction time were plasma concentration (Cp₅₀ 65.3 mg.L^-1 ), E_MAX 34 min, N 0.80 with a baseline thromboelastometric reaction time of 0.4 min. The equilibration half time (T_1/2 keo) was 2.04 min.

CONCLUSIONS

Dabigatran reversibly binds to the active site on the thrombin molecule, preventing thrombin-mediated activation of coagulation factors. The effect compartment model performed slightly better than the turnover model and was able to adequately capture pharmacodynamics for both activated clotting and thromboelastometric reaction times. The equilibration half time was short (<2 min). These data can be used to inform future animal preclinical studies for those undergoing cardiopulmonary bypass. These preclinical data also demonstrate the magnitude of parameter values for a delayed effect compartment model that are applicable to humans.

Novel αO-conotoxin GeXIVA[1,2] Nonaddictive Analgesic with Pharmacokinetic Modelling-Based Mechanistic Assessment

αO-conotoxin GeXIVA[1,2] was isolated in our laboratory from Conus generalis, a snail native to the South China Sea, and is a novel, nonaddictive, intramuscularly administered analgesic targeting the α9α10 nicotinic acetylcholine receptor (nAChR) with an IC₅₀ of 4.61 nM. However, its pharmacokinetics and related mechanisms underlying the analgesic effect remain unknown. Herein, pharmacokinetics and multiscale pharmacokinetic modelling in animals were subjected systematically to mechanistic assessment for αO-conotoxin GeXIVA[1,2]. The intramuscular bioavailability in rats and dogs was 11.47% and 13.37%, respectively. The plasma exposure of GeXIVA[1,2] increased proportionally with the experimental dose. The plasma protein binding of GeXIVA[1,2] differed between the tested animal species. The one-compartment model with the first-order absorption population pharmacokinetics model predicted doses for humans with bodyweight as the covariant. The pharmacokinetics-pharmacodynamics relationships were characterized using an inhibitory loss indirect response model with an effect compartment. Model simulations have provided potential mechanistic insights into the analgesic effects of GeXIVA[1,2] by inhibiting certain endogenous substances, which may be a key biomarker. This report is the first concerning the pharmacokinetics of GeXIVA[1,2] and its potential analgesic mechanisms based on a top-down modelling approach.

Leveraging Predictive Pharmacometrics-Based Algorithms to Enhance Perinatal Care—Application to Neonatal Jaundice

The field of medicine is undergoing a fundamental change, transforming towards a modern data-driven patient-oriented approach. This paradigm shift also affects perinatal medicine as predictive algorithms and artificial intelligence are applied to enhance and individualize maternal, neonatal and perinatal care. Here, we introduce a pharmacometrics-based mathematical-statistical computer program (PMX-based algorithm) focusing on hyperbilirubinemia, a medical condition affecting half of all newborns. Independent datasets from two different centers consisting of total serum bilirubin measurements were utilized for model development (342 neonates, 1,478 bilirubin measurements) and validation (1,101 neonates, 3,081 bilirubin measurements), respectively. The mathematical-statistical structure of the PMX-based algorithm is a differential equation in the context of non-linear mixed effects modeling, together with Empirical Bayesian Estimation to predict bilirubin kinetics for a new patient. Several clinically relevant prediction scenarios were validated, i.e., prediction up to 24 h based on one bilirubin measurement, and prediction up to 48 h based on two bilirubin measurements. The PMX-based algorithm can be applied in two different clinical scenarios. First, bilirubin kinetics can be predicted up to 24 h based on one single bilirubin measurement with a median relative (absolute) prediction difference of 8.5% (median absolute prediction difference 17.4 μmol/l), and sensitivity and specificity of 95.7 and 96.3%, respectively. Second, bilirubin kinetics can be predicted up to 48 h based on two bilirubin measurements with a median relative (absolute) prediction difference of 9.2% (median absolute prediction difference 21.5 μmol/l), and sensitivity and specificity of 93.0 and 92.1%, respectively. In contrast to currently available nomogram-based static bilirubin stratification, the PMX-based algorithm presented here is a dynamic approach predicting individual bilirubin kinetics up to 48 h, an intelligent, predictive algorithm that can be incorporated in a clinical decision support tool. Such clinical decision support tools have the potential to benefit perinatal medicine facilitating personalized care of mothers and their born and unborn infants.

Pharmacokinetic/pharmacodynamic modeling of ketoprofen and flunixin at piglet castration and tail-docking

This study performed population‐pharmacokinetic/pharmacodynamic (pop‐PK/PD) modeling of ketoprofen and flunixin in piglets undergoing routine castration and tail‐docking, utilizing previously published data. Six‐day‐old male piglets (8/group) received either ketoprofen (3.0 mg/kg) or flunixin (2.2 mg/kg) intramuscularly. Two hours post‐dose, piglets were castrated and tail docked. Inhibitory indirect response models were developed utilizing plasma cortisol or interstitial fluid prostaglandin E2 (PGE2) concentration data. Plasma IC50 for ketoprofen utilizing PGE2 as a biomarker was 1.2 μg/ml, and ED50 for was 5.83 mg/kg. The ED50 calculated using cortisol was 4.36 mg/kg; however, the IC50 was high, at 2.56 μg/ml. A large degree of inter‐individual variability (124.08%) was also associated with the cortisol IC50 following ketoprofen administration. IC50 for flunixin utilizing cortisol as a biomarker was 0.06 μg/ml, and ED50 was 0.51 mg/kg. The results show that the currently marketed doses of ketoprofen (3.0 mg/kg) and flunixin (2.2 mg/kg) correspond to drug responses of 33.97% (ketoprofen‐PGE2), 40.75% (ketoprofen‐cortisol), and 81.05% (flunixin‐cortisol) of the maximal possible responses. Given this information, flunixin may be the best NSAID to use in mitigating castration and tail‐docking pain at the current label dose.

Effect of autoinduction and food on the pharmacokinetics of furmonertinib and its active metabolite characterized by a population pharmacokinetic model

Furmonertinib (AST2818) is a novel third-generation irreversible EGFR TKI and recently has been approved in China for the treatment of non-small cell lung cancer (NSCLC) with EGFR-sensitizing and T790M resistance mutations. In the current study, we developed a semi-mechanistic population pharmacokinetic model to characterize the nonstationary pharmacokinetics (PK) of the furmonertinib and its active metabolite AST5902 simultaneously. The PK data of furmonertinib and AST5902 were obtained from 38 NSCLC patients and 16 healthy volunteers receiving 20-240 mg furmonertinib in three clinical trials. A nonlinear mixed-effects modeling approach was used to describe the PK data. The absorption process of furmonertinib was described by a transit compartment model. The disposition of both furmonertinib and AST5902 was described by a two-compartment model. An indirect response model accounted for the autoinduction of furmonertinib metabolism mediated by CYP3A4. The model-based simulation suggested that furmonertinib clearance was increased in one cycle of treatment (orally once daily for 21 days) compared to baseline, ranging from 1.1 to 1.8 fold corresponding to the dose range of 20-240 mg. The concentration of furmonertinib was decreased over time whereas that of AST5902 was increased. Interestingly, the concentration of the total active compounds (furmonertinib and AST5902) appeared to be stable. The food intake, serum alkaline phosphatase and body weight were identified as statistically significant covariates. The mechanism of food effect on PK was investigated, where the food intake might increase the bioavailability of furmonertinib via increasing the splanchnic blood flow. Overall, a population PK model was successfully developed to characterize the nonstationary PK of furmonertinib and AST5902 simultaneously. The concentrations of total active compounds were less affected by the autoinduction of furmonertinib metabolism.

Pharmacokinetic/Pharmacodynamic Evaluation of a New Purine-2,6-Dione Derivative in Rodents with Experimental Autoimmune Diseases

Current treatment strategies of autoimmune diseases (ADs) display a limited efficacy and cause numerous adverse effects. Phosphodiesterase (PDE)4 and PDE7 inhibitors have been studied recently as a potential treatment of a variety of ADs. In this study, a PK/PD disease progression modeling approach was employed to evaluate effects of a new theophylline derivative, compound 34, being a strong PDE4 and PDE7 inhibitor. Activity of the studied compound against PDE1 and PDE3 in vitro was investigated. Animal models of multiple sclerosis (MS), rheumatoid arthritis (RA), and autoimmune hepatitis were utilized to assess the efficacy of this compound, and its pharmacokinetics was investigated in mice and rats. A new PK/PD disease progression model of compound 34 was developed that satisfactorily predicted the clinical score-time courses in mice with experimental encephalomyelitis that is an animal model of MS. Compound 34 displayed a high efficacy in all three animal models of ADs. Simultaneous inhibition of PDE types located in immune cells may constitute an alternative treatment strategy of ADs. The PK/PD encephalomyelitis and arthritis progression models presented in this study may be used in future preclinical research, and, upon modifications, may enable translation of the results of preclinical investigations into the clinical settings.

Pharmacokinetic/Pharmacodynamic Assessment of Selective Phosphodiesterase Inhibitors in a Mouse Model of Autoimmune Hepatitis

Autoimmune hepatitis (AIH) is a life-threatening disorder currently treated with nonspecific immunosuppressive drugs. It is postulated that phosphodiesterase (PDE) inhibitors, as agents exerting anti-inflammatory and immunomodulatory activities, may constitute a possible treatment of autoimmune disorders. This study develops a pharmacokinetic/pharmacodynamic (PK/PD) model to assess the effects of PDE-selective inhibitors, namely, cilostazol (PDE3), rolipram (PDE4), and BRL-50481 (PDE7), in a mouse model of AIH. The pharmacokinetics of the PDE inhibitors (PDEi) were assessed in male BALB/c mice after intraperitoneal administration. In pharmacodynamic studies, mice received PDEi and AIH was induced in these animals by intravenous injection of concanavalin A (ConA). Serum drug concentrations, tumor necrosis factor α (TNFα), interleukin 17 (IL-17), and aminotransferase activities were quantified. The PK/PD analysis was performed using ADAPT5 software. The PK/PD model assumes inhibition of cAMP hydrolysis in T cells by PDEi, ConA-triggered formation of TNFα and IL-17, suppression of TNFα and IL-17 production by cAMP, and stimulatory effects of TNFα and IL-17 on the hepatic release of aminotransferases. Selective blockage of PDE4 leads to the highest inhibition of cAMP degradation in T cells and amelioration of disease outcomes. However, inhibition of both PDE3 and PDE7 also contribute to this effect. The proposed PK/PD model may be used to assess and predict the activities of novel PDEi and their combinations in ConA-induced hepatitis. A balanced suppression of different types of PDE appears to be a promising treatment option for AIH; however, this hypothesis warrants testing in humans based on translation of the PK/PD model into clinical settings. SIGNIFICANCE STATEMENT: A novel PK/PD model of PDE inhibitor effects in mice with ConA-induced autoimmune hepatitis was developed involving a mechanistic component describing changes in cAMP concentrations in mouse T cells. According to model predictions, inhibition of PDE4 in T cells causes the highest cAMP elevation in T cells, but suppression of PDE3 and PDE7 also contribute to this effect. A balanced inhibition of PDE3, PDE4, and PDE7 appears to be a promising treatment strategy for AIH.

A semimechanistic population pharmacokinetic and pharmacodynamic model incorporating autoinduction for the dose justification of TAS-114

TAS-114 is a dual deoxyuridine triphosphatase (dUTPase) and dihydropyrimidine dehydrogenase (DPD) inhibitor expected to widen the therapeutic index of capecitabine. Its maximum tolerated dose (MTD) was determined from a safety perspective in a combination study with capecitabine; however, its inhibitory effects on DPD activity were not assessed in the study. The dose justification to select its MTD as the recommended dose in terms of DPD inhibition has been required, but the autoinduction profile of TAS-114 made it difficult. To this end, an approach using a population pharmacokinetic (PPK)/pharmacodynamic (PD) model incorporating autoinduction was planned; however, the utility of this approach in the dose justification has not been reported. Thus, the aim of this study was to demonstrate the utility of a PPK/PD model incorporating autoinduction in the dose justification via a case study of TAS-114. Plasma concentrations of TAS-114 from 185 subjects and those of the endogenous DPD substrate uracil from 24 subjects were used. A two-compartment model with first-order absorption with lag time and an enzyme turnover model were selected for the pharmacokinetic (PK) model. Moreover, an indirect response model was selected for the PD model to capture the changes in plasma uracil concentrations. Model-based simulations provided the dose justification that DPD inhibition by TAS-114 reached a plateau level at the MTD, whereas exposures of TAS-114 increased dose dependently. Thus, the utility of a PPK/PD model incorporating autoinduction in the dose justification was demonstrated via this case study of TAS-114.

Time-Dissociated Pharmacokinetic Pharmacodynamic Model of Cyclosporine Among Malaysian Renal Transplant Recipients

BACKGROUND

Cyclosporine is an essential component of many immunosuppressive regimens. However, its pharmacokinetic and pharmacodynamic (PKPD) modeling has not been widely investigated. This study aims to develop a time-dissociated PKPD model of cyclosporine in renal transplant patients.

METHODS

Medical records of renal transplant patients at Penang General Hospital were retrospectively analyzed. A time-dissociated PKPD model with covariate effects was developed using NONMEM to evaluate renal graft function response, quantified as estimated glomerular filtration rate (eGFR), toward the cyclosporine cumulative exposure (area under the concentration-time curve). The final model was integrated into a tool to predict the potential outcome. Individual eGFR predictions were evaluated based on the clinical response recorded as acute rejection/nephrotoxicity events.

RESULTS

A total of 1256 eGFR readings with 2473 drug concentrations were obtained from 107 renal transplant patients receiving cyclosporine. An Emax drug effect with a linear drug toxicity model best described the data. The baseline renal graft level (E0), maximum effect (Emax), area under the concentration-time curve achieving 50% of the maximum effect, and nephrotoxicity slope were estimated as 12.9 mL·min-1·1.73 m-2, 50.7 mL·min-1·1.73 m-2, 1740 ng·h·mL-1, and 0.00033, respectively. The hemoglobin level was identified as a significant covariate affecting the E0. The model discerned acute rejection from nephrotoxicity in 19/24 cases.

CONCLUSIONS

A time-dissociated PKPD model successfully described a large number of observations and was used to develop an online tool to predict renal graft response. This may help discern early rejection from nephrotoxicity, especially for patients unwilling to undergo a biopsy or those waiting for biopsy results.

Impact of Pharmacokinetic and Pharmacodynamic Properties of Monoclonal Antibodies in the Management of Psoriasis

The treatment of psoriasis has been revolutionized by the emergence of biological therapies. Monoclonal antibodies (mAb) generally have complex pharmacokinetic (PK) properties with nonlinear distribution and elimination. In recent years, several population pharmacokinetic/pharmacodynamic (PK/PD) models capable of describing different types of mAb have been published. This study aims to summarize the findings of a literature search about population PK/PD modeling and therapeutic drug monitoring (TDM) of mAb in psoriasis. A total of 22 articles corresponding to population PK/PD models of tumor necrosis factor (TNF)-α inhibitors (adalimumab and golimumab), interleukin (IL)-23 inhibitors (guselkumab, tildrakizumab, and risankizumab), IL-23/IL-12 inhibitor (ustekinumab), and IL-17 inhibitors (secukinumab, ixekizumab, and brodalumab) were collected. A summary of the clinical trials conducted so far in psoriasis was included, together with the current structural population PK and PD models. The most significant and clinical covariates were body weight (BW) and the presence of immunogenicity on clearance (CL). The lack of consensus on PK/PD relationships has prevented establishing an adequate dosage and, therefore, accentuates the need for TDM in psoriasis.

Etavopivat, a Pyruvate Kinase Activator in Red Blood Cells, for the Treatment of Sickle Cell Disease

Etavopivat is an investigational, oral, small molecule activator of erythrocyte pyruvate kinase (PKR) in development for the treatment of sickle cell disease (SCD) and other hemoglobinopathies. PKR activation is proposed to ameliorate the sickling of SCD red blood cells (RBC) through multiple mechanisms, including reduction of 2,3-diphosphoglycerate (2,3-DPG), which consequently increases hemoglobin (Hb)-oxygen affinity; increased binding of oxygen reduces HbS polymerization and sickling. In addition, PKR activation increases adenosine triphosphate (ATP) produced via glycolytic flux, which helps preserve membrane integrity and RBC deformability. We evaluated the pharmacodynamic response to etavopivat in non-human primates (NHP) and in healthy human subjects, and the effects in RBC from patients with SCD after ex vivo treatment with etavopivat. A single dose of etavopivat decreased 2,3-DPG in NHP and healthy subjects. Hb-oxygen affinity was significantly increased in healthy subjects after 24 hours. Following daily dosing of etavopivat over 5 consecutive days in NHP, ATP was increased by 38% from baseline. Etavopivat increased Hb-oxygen affinity and reduced sickling in RBC collected from SCD patients with either HbSS or HbSC disease. Collectively, these results demonstrate the ability of etavopivat to decrease 2,3-DPG and increase ATP, resulting in increased Hb-oxygen affinity and improved sickle RBC function. Etavopivat is currently being evaluated in clinical trials for the treatment of SCD. ClinicalTrials.gov identifier: NCT03815695 Significance Statement Etavopivat-a small molecule activator of the glycolytic enzyme erythrocyte pyruvate kinase -decreased 2,3-diphosphoglycerate in red blood cells (RBC) from non-human primates and healthy subjects and significantly increased hemoglobin (Hb)-oxygen affinity in healthy subjects. Using ex vivo RBC from donors with sickle cell disease (SCD) (HbSS or HbSC genotype), etavopivat increased Hb-oxygen affinity and reduced sickling under deoxygenation. Etavopivat shows promise as a treatment for SCD, that potentially might reduce vaso-occlusion and improve anemia.

Synthesis and Pharmacological Characterization of Visabron, a Backbone Cyclic Peptide Dual Antagonist of α4β1 (VLA-4)/α9β1 Integrin for Therapy of Multiple Sclerosis

Integrins α4β1/ α9β1 are important in the pathogenesis and progression of inflammatory and autoimmune diseases by their roles in leukocyte activation and trafficking. Natalizumab, a monoclonal antibody selectively targeting α4β1 integrin and blocking leukocyte trafficking to the central nervous system, is an immunotherapy for multiple sclerosis (MS). However, due to its adverse effects associated with chronic treatment, alternative strategies using small peptide mimetic inhibitors are being sought. In the present study, we synthesized and characterized visabron c (4-4), a backbone cyclic octapeptide based on the sequence TMLD, a non-RGD unique α4β1 integrin recognition sequence motif derived from visabres, a proteinous disintegrin from the viper venom. Visabron c (4-4) was selected from a minilibrary with conformational diversity based on its potency and selectivity in functional adhesion cellular assays. Visabron c (4-4)'s serum stability, pharmacokinetics, and therapeutic effects following ip injection were assessed in an experimental autoimmune encephalomyelitis (EAE) animal model. Furthermore, visabron c (4-4)'s lack of toxic effects in mice was verified by blood analysis, tissue pathology, immunogenicity, and "off-target" effects, indicating its significant tolerability and lack of immunogenicity. Visabron c (4-4) can be delivered systemically. The in vitro and in vivo data justify visabron c (4-4) as a safe alternative peptidomimetic lead compound/drug to monoclonal anti-α4 integrin antibodies, steroids, and other immunosuppressant drugs. Moreover, visabron c (4-4) design may pave the way for developing new therapies for a variety of other inflammatory and/or autoimmune diseases.

Effect of Anti-VEGF Therapy on the Disease Progression of Neovascular Age-Related Macular Degeneration: A Systematic Review and Model-Based Meta-Analysis

Anti–vascular endothelial growth factor (VEGF) therapy is used to slow the disease progression of neovascular age‐related macular degeneration. Due to the treatment burden of frequent intravitreal injections, anti‐VEGFs are often used on treat and extend protocols rather than the labeled frequency. The current goal of anti‐VEGF drug development is to minimize treatment burden by reducing the number of intravitreal injections. The purpose of this systemic review and model‐based meta‐analysis (MBMA) was to (1) perform modeling to describe the disease progression of neovascular age‐related macular degeneration in the absence of treatment, as well as in the presence of abicipar, aflibercept, brolucizumab, or ranibizumab intervention; (2) and to simulate virtual head‐to‐head comparisons among the drugs with an extended dose schedule of once every 12 weeks (Q12). Data sources were PubMed, internal Allergan data, www.clinicaltrials.gov, and www.clinicaltrialsregister.eu. Eligibility assessment was performed by 2 independent review authors. Randomized, controlled trials that had at least 1 arm with an anti‐VEGF (aflibercept, abicipar, bevacizumab, brolucizumab, pegaptanib, or ranibizumab), a control arm of placebo or anti‐VEGF, a treatment duration of at least 4 months, reported best‐corrected visual acuity data, and at least 20 patients were included. A total of 22 trials, consisting of 55 arms, from across 9500+ subjects and 500+ best‐corrected visual acuity observations were used to develop the model. Consistent with reported data, results from the model showed that abicipar Q12 underperformed ranibizumab (every 4 weeks), aflibercept (every 4 weeks), and brolucizumab (every 8 weeks/Q12) labeled dosing schedules. However, when all drugs were virtually tested using the extended schedule, abicipar outperformed ranibizumab and aflibercept and produced a similar week 52 change from baseline as brolucizumab. Predicted week 52 changes from baseline were 5.92 ± 1.02, 3.04 ± 1.61, 6.61 ± 0.284, and 3.02 ± 2.35 best‐corrected visual acuity letters for abicipar, aflibercept, brolucizumab, and ranibizumab, respectively, using the Q12 schedule. Results demonstrate the feasibility of Q12 dosing with clinically meaningful letter gains for abicipar and brolucizumab. The model developed under this MBMA has utility for exploring different regimens for existing or novel anti‐VEGF agents.

Translation of Pharmacodynamic Biomarkers of Antibiotic Efficacy in Specific Populations to Optimize Doses

Antibiotic efficacy determination in clinical trials often relies on non-inferiority designs because they afford smaller study sample sizes. These efficacy studies tend to exclude patients within specific populations or include too few patients to discern potential differences in their clinical outcomes. As a result, dosing guidance in patients with abnormal liver and kidney function, age across the lifespan, and other specific populations relies on drug exposure-matching. The underlying assumption for exposure-matching is that the disease course and the response to the antibiotic are similar in patients with and without the specific condition. While this may not be the case, clinical efficacy studies are underpowered to ensure this is true. The current paper provides an integrative review of the current approach to dose selection in specific populations. We review existing clinical trial endpoints that could be measured on a more continuous rather than a discrete scale to better inform exposure-response relationships. The inclusion of newer systemic biomarkers of efficacy can help overcome the current limitations. We use a modeling and simulation exercise to illustrate how an efficacy biomarker can inform dose selection better. Studies that inform response-matching rather than exposure-matching only are needed to improve dose selection in specific populations.

Semimechanistic models to relate noxious stimulation, movement, and pupillary dilation responses in the presence of opioids

Intraoperative targeting of the analgesic effect still lacks an optimal solution. Opioids are currently the main drug used to achieve antinociception, and although underdosing can lead to an increased stress response, overdose can also lead to undesirable adverse effects. To better understand how to achieve the optimal analgesic effect of opioids, we studied the influence of remifentanil on the pupillary reflex dilation (PRD) and its relationship with the reflex movement response to a standardized noxious stimulus. The main objective was to generate population pharmacodynamic models relating remifentanil predicted concentrations to movement and to pupillary dilation during general anesthesia. A total of 78 patients undergoing gynecological surgery under general anesthesia were recruited for the study. PRD and movement response to a tetanic stimulus were measured multiple times before and after surgery. We used nonlinear mixed effects modeling to generate a population pharmacodynamic model to describe both the time profiles of PRD and movement responses to noxious stimulation. Our model demonstrated that movement and PRD are equally depressed by remifentanil. Using the developed model, we changed the intensity of stimulation and simulated remifentanil predicted concentrations maximizing the probability of absence of movement response. An estimated effect site concentration of 2 ng/ml of remifentanil was found to inhibit movement to a tetanic stimulation with a probability of 81%.

Pharmacokinetic/Pharmacodynamic Modeling of a Cell-Penetrating Peptide Phosphorodiamidate Morpholino Oligomer in mdx Mice

PURPOSE

Peptide-conjugated phosphorodiamidate morpholino oligomers (PPMOs) have shown promise in treating Duchenne muscular dystrophy (DMD). We evaluated a semi-mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) model to capture the relationship between plasma and muscle tissue exposure/response in mdx mice treated by mouse surrogate PPMO.

METHODS

A single or repeated (every 4 weeks for 20 weeks) intravenous PPMO dose was administered to mdx mice (n = 6/timepoint). A PK/PD model was built to characterize data via sequential modeling. A 2-compartment model was used to describe plasma PK. A simultaneous tissue PK/PD model was subsequently developed: 2-compartment model to describe muscle PK; linked to an indirect response model describing stimulation of synthesis of skipped transcript, which was in turn linked to stimulation of synthesis of dystrophin protein expression.

RESULTS

Model performance assessment via goodness-of-fit plots, visual predictive checks, and accurate parameter estimation indicated robust fits of plasma PK and muscle PK/PD data. The model estimated a PPMO tissue half-life of 5 days-a useful parameter in determining the longevity of PPMOs in tissue and their limited accumulation after multiple doses. Additionally, the model successfully described dystrophin expression after single dosing and associated protein accumulation after multiple dosing (increasing ~ twofold accumulation from the first to last dose).

CONCLUSIONS

This first PK/PD model of a PPMO in a DMD disease model will help characterize and predict the time course of PK/PD biomarkers in mdx mice. Furthermore, the model framework can be used to develop clinical PK/PD models and can be extended to other exon-skipping therapies and species.

Population pharmacokinetics and exposure-response modeling for evinacumab in homozygous familial hypercholesterolemia

Evinacumab, an angiopoietin‐like protein 3 (ANGPTL3) inhibitor, has been shown to significantly reduce low‐density lipoprotein cholesterol (LDL‐C) in patients with homozygous familial hypercholesterolemia (HoFH). This work characterized the population pharmacokinetics (PK)/pharmacodynamics (PD) of evinacumab using pooled phase III clinical data. Total evinacumab PK were described by a two‐compartment model with combined linear and saturable (Michaelis–Menten) elimination, and first‐order absorption. At clinically relevant concentrations, plasma drug concentrations were mainly influenced by the linear clearance pathway. Although the maximum target‐mediated rate of elimination (V_max) parameter for the saturable pathway was found to be positively related to baseline ANGPLTL3, variability in body weight contributed more to the variability in evinacumab exposure than variability in ANGPTL3. An effect of HoFH versus healthy volunteers on V_max was also identified. Weight‐based dosing regimens resulted in consistent evinacumab exposure across weight ranges. An indirect exposure–response model adequately described the relationship between evinacumab and LDL‐C, where drug concentration is assumed to inhibit LDL‐C production. The final population PK/PD model included two nonclinically significant covariates (race and baseline body weight) on the maximum drug‐induced inhibitory effect (I_max) and one (baseline LDL‐C) on the evinacumab concentration inducing 50% of I_max (IC₅₀). A smaller IC₅₀ was observed in patients with higher baseline LDL‐C, suggesting greater sensitivity to treatment. Population exposure–response analysis permitted estimation of derived PD parameters and individual LDL‐C levels over time for patients with HoFH. The model accurately predicted the proportion of patients with HoFH achieving prespecified LDL‐C goals with evinacumab during the ELIPSE HoFH study, further supporting a dosing strategy.

Population Modelling of Dexmedetomidine Pharmacokinetics and Haemodynamic Effects After Intravenous and Subcutaneous Administration

Background and Objective

Dexmedetomidine is a potent agonist of α₂-adrenoceptors causing dose-dependent sedation in humans. Intravenous dexmedetomidine is commonly used perioperatively, but an extravascular route of administration would be favoured in palliative care. Subcutaneous infusions provide desired therapeutic plasma concentrations with fewer unwanted effects as compared with intravenous dosing. We aimed to develop semi-mechanistic population models for predicting pharmacokinetic and pharmacodynamic profiles of dexmedetomidine after intravenous and subcutaneous dosing.

Methods

Non-linear mixed-effects modelling was performed using previously collected concentration and haemodynamic effects data from ten (eight in the intravenous phase) healthy human subjects, aged 19–27 years, receiving 1 µg/kg of intravenous or subcutaneous dexmedetomidine during a 10-min infusion.

Results

The absorption of dexmedetomidine from the subcutaneous injection site, and distribution to local subcutaneous fat tissue was modelled using a semi-physiological approach consisting of a depot and fat compartment, while a two-compartment mammillary model explained further disposition. Dexmedetomidine-induced reductions in plasma norepinephrine concentrations were accurately described by an indirect response model. For blood pressure models, the net effect was specified as hyper- and hypotensive effects of dexmedetomidine due to vasoconstriction on peripheral arteries and sympatholysis mediated via the central nervous system, respectively. A heart rate model combined the dexmedetomidine-induced sympatholytic effect, and input from the central nervous system, predicted from arterial blood pressure levels. Internal evaluation confirmed the predictive performance of the final models, as well as the accuracy of the parameter estimates with narrow confidence intervals.

Conclusions

Our final model precisely describes dexmedetomidine pharmacokinetics and accurately predicts dexmedetomidine-induced sympatholysis and other pharmacodynamic effects. After subcutaneous dosing, dexmedetomidine is taken up into subcutaneous fat tissue, but our simulations indicate that accumulation of dexmedetomidine in this compartment is insignificant.

ClinicalTrials.org

NCT02724098 and EudraCT 2015-004698-34

Electronic supplementary material

The online version of this article (10.1007/s40262-020-00900-3) contains supplementary material, which is available to authorized users.

Analyze impact of tumor-associated kinetics on antibody delivery in solid tumors with a physiologically based pharmacokinetics/pharmacodynamics model

Monoclonal antibody (mAb)-based drugs are critical anti-cancer therapies. Unfortunately, therapeutic efficacy can be compromised by spatially heterogeneous intratumoral Ab deposition. Binding-site barriers arising from Ab and tumor-associated kinetics often underlie this phenomenon. Quantitative insight into these issues may lead to more efficient drug delivery. Difficulties in addressing this issue include (1) lack of techniques to quantify critical kinetic events, (2) lack of a pharmacokinetic/pharmacodynamic (PK/PD) model to assess important parameters for specific tumor types, and (3) uncertainty or variability of critical kinetic factors even within a single tumor type. This study developed a mechanism-based PK/PD model to profile heterogeneous distribution of Ab within tumors and tested this model using real-life experimental data. Model simulations incorporating several uncertainties were used to determine how mAb and tumor-associated kinetics influence receptor occupancy. Simulations were also used to predict the potential impact of these findings in preclinical tumor models and human tumors. We found significant differences in tumor-associated kinetics between groups in which mAb therapy was effective versus groups in which it was ineffective. These kinetic differences included rates of tumor-associated antigen (TAA) degradation, TAA expression, apparent flow rates of interstitial fluid, and ratios of Ab-TAA complex internalization to TAA degradation. We found less significant differences in mAb kinetics, including rates of clearance or affinity for target antigens. In conclusion, our mechanism-based PK/PD model suggests that TAA-associated kinetic factors participate more significantly than those associated with the Ab in generating barriers to mAb delivery and distribution in tumors.