Pharmacodynamics of glucose regulation by methylprednisolone. I. Adrenalectomized rats

Transitioning from Basic toward Systems Pharmacodynamic Models: Lessons from Corticosteroids

Technology in bioanalysis, -omics, and computation have evolved over the past half century to allow for comprehensive assessments of the molecular to whole body pharmacology of diverse corticosteroids. Such studies have advanced pharmacokinetic and pharmacodynamic (PK/PD) concepts and models that often generalize across various classes of drugs. These models encompass the "pillars" of pharmacology, namely PK and target drug exposure, the mass-law interactions of drugs with receptors/targets, and the consequent turnover and homeostatic control of genes, biomarkers, physiologic responses, and disease symptoms. Pharmacokinetic methodology utilizes noncompartmental, compartmental, reversible, physiologic [full physiologically based pharmacokinetic (PBPK) and minimal PBPK], and target-mediated drug disposition models using a growing array of pharmacometric considerations and software. Basic PK/PD models have emerged (simple direct, biophase, slow receptor binding, indirect response, irreversible, turnover with inactivation, and transduction models) that place emphasis on parsimony, are mechanistic in nature, and serve as highly useful "top-down" methods of quantitating the actions of diverse drugs. These are often components of more complex quantitative systems pharmacology (QSP) models that explain the array of responses to various drugs, including corticosteroids. Progressively deeper mechanistic appreciation of PBPK, drug-target interactions, and systems physiology from the molecular (genomic, proteomic, metabolomic) to cellular to whole body levels provides the foundation for enhanced PK/PD to comprehensive QSP models. Our research based on cell, animal, clinical, and theoretical studies with corticosteroids have provided ideas and quantitative methods that have broadly advanced the fields of PK/PD and QSP modeling and illustrates the transition toward a global, systems understanding of actions of diverse drugs. SIGNIFICANCE STATEMENT: Over the past half century, pharmacokinetics (PK) and pharmacokinetics/pharmacodynamics (PK/PD) have evolved to provide an array of mechanism-based models that help quantitate the disposition and actions of most drugs. We describe how many basic PK and PK/PD model components were identified and often applied to the diverse properties of corticosteroids (CS). The CS have complications in disposition and a wide array of simple receptor-to complex gene-mediated actions in multiple organs. Continued assessments of such complexities have offered opportunities to develop models ranging from simple PK to enhanced PK/PD to quantitative systems pharmacology (QSP) that help explain therapeutic and adverse CS effects. Concurrent development of state-of-the-art PK, PK/PD, and QSP models are described alongside experimental studies that revealed diverse CS actions.

Receptor/gene/protein-mediated signaling connects methylprednisolone exposure to metabolic and immune-related pharmacodynamic actions in liver

A multiscale pharmacodynamic model was developed to characterize the receptor-mediated, transcriptomic, and proteomic determinants of corticosteroid (CS) effects on clinically relevant hepatic processes following a single dose of methylprednisolone (MPL) given to adrenalectomized (ADX) rats. The enhancement of tyrosine aminotransferase (TAT) mRNA, protein, and enzyme activity were simultaneously described. Mechanisms related to the effects of MPL on glucose homeostasis, including the regulation of CCAAT-enhancer binding protein-beta (C/EBPβ) and phosphoenolpyruvate carboxykinase (PEPCK) as well as insulin dynamics were evaluated. The MPL-induced suppression of circulating lymphocytes was modeled by coupling its effect on cell trafficking with pharmacogenomic effects on cell apoptosis via the hepatic (STAT3-regulated) acute phase response. Transcriptomic and proteomic time-course profiles measured in steroid-treated rat liver were utilized to model the dynamics of mechanistically relevant gene products, which were linked to associated systemic end-points. While time-courses of TAT mRNA, protein, and activity were well described by transcription-mediated changes, additional post-transcriptional processes were included to explain the lack of correlation between PEPCK mRNA and protein. The immune response model quantitatively discerned the relative roles of cell trafficking versus gene-mediated lymphocyte apoptosis by MPL. This systems pharmacodynamic model provides insights into the contributions of selected molecular events occurring in liver and explores mechanistic hypotheses for the multi-factorial control of clinically relevant pharmacodynamic outcomes.

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Modeling and design of challenge tests: Inflammatory and metabolic biomarker study examples

Given the complexity of pharmacological challenge experiments, it is perhaps not surprising that design and analysis, and in turn interpretation and communication of results from a quantitative point of view, is often suboptimal. Here we report an inventory of common designs sampled from anti-inflammatory, respiratory and metabolic disease drug discovery studies, all of which are based on animal models of disease involving pharmacological and/or patho/physiological interaction challenges. The corresponding data are modeled and analyzed quantitatively, the merits of the respective approach discussed and inferences made with respect to future design improvements. Although our analysis is limited to these disease model examples, the challenge approach is generally applicable to the vast majority of pharmacological intervention studies. In the present five Case Studies results from pharmacodynamic effect models from different therapeutic areas were explored and analyzed according to five typical designs. Plasma exposures of test compounds were assayed by either liquid chromatography/mass spectrometry or ligand binding assays. To describe how drug intervention can regulate diverse processes, turnover models of test compound-challenger interaction, transduction processes, and biophase time courses were applied for biomarker response in eosinophil count, IL6 response, paw-swelling, TNFα response and glucose turnover in vivo. Case Study 1 shows results from intratracheal administration of Sephadex, which is a glucocorticoid-sensitive model of airway inflammation in rats. Eosinophils in bronchoalveolar fluid were obtained at different time points via destructive sampling and then regressed by the mixed-effects modeling. A biophase function of the Sephadex time course was inferred from the modeled eosinophil time courses. In Case Study 2, a mouse model showed that the time course of cytokine-induced IL1β challenge was altered with or without drug intervention. Anakinra reversed the IL1β induced cytokine IL6 response in a dose-dependent manner. This Case Study contained time courses of test compound (drug), challenger (IL1β) and cytokine response (IL6), which resulted in high parameter precision. Case Study 3 illustrates collagen-induced arthritis progression in the rat. Swelling scores (based on severity of hind paw swelling) were used to describe arthritis progression after the challenge and the inhibitory effect of two doses of an orally administered test compound. In Case Study 4, a cynomolgus monkey model for lipopolysaccharide LPS-induced TNFα synthesis and/or release was investigated. This model provides integrated information on pharmacokinetics and in vivo potency of the test compounds. Case Study 5 contains data from an oral glucose tolerance test in rats, where the challenger is the same as the pharmacodynamic response biomarker (glucose). It is therefore convenient to model the extra input of glucose simultaneously with baseline data and during intervention of a glucose-lowering compound at different dose levels. Typically time-series analyses of challenger- and biomarker-time data are necessary if an accurate and precise estimate of the pharmacodynamic properties of a test compound is sought. Erosion of data, resulting in the single-point assessment of drug action after a challenge test, should generally be avoided. This is particularly relevant for situations where one expects time-curve shifts, tolerance/rebound, impact of disease, or hormetic concentration-response relationships to occur.

Meta-modeling of methylprednisolone effects on glucose regulation in rats

A retrospective meta-modeling analysis was performed to integrate previously reported data of glucocorticoid (GC) effects on glucose regulation following a single intramuscular dose (50 mg/kg), single intravenous doses (10, 50 mg/kg), and intravenous infusions (0.1, 0.2, 0.3 and 0.4 mg/kg/h) of methylprednisolone (MPL) in normal and adrenalectomized (ADX) male Wistar rats. A mechanistic pharmacodynamic (PD) model was developed based on the receptor/gene/protein-mediated GC effects on glucose regulation. Three major target organs (liver, white adipose tissue and skeletal muscle) together with some selected intermediate controlling factors were designated as important regulators involved in the pathogenesis of GC-induced glucose dysregulation. Assessed were dynamic changes of food intake and systemic factors (plasma glucose, insulin, free fatty acids (FFA) and leptin) and tissue-specific biomarkers (cAMP, phosphoenolpyruvate carboxykinase (PEPCK) mRNA and enzyme activity, leptin mRNA, interleukin 6 receptor type 1 (IL6R1) mRNA and Insulin receptor substrate-1 (IRS-1) mRNA) after acute and chronic dosing with MPL along with the GC receptor (GR) dynamics in each target organ. Upon binding to GR in liver, MPL dosing caused increased glucose production by stimulating hepatic cAMP and PEPCK activity. In adipose tissue, the rise in leptin mRNA and plasma leptin caused reduction of food intake, the exogenous source of glucose input. Down-regulation of IRS-1 mRNA expression in skeletal muscle inhibited the stimulatory effect of insulin on glucose utilization further contributing to hyperglycemia. The nuclear drug-receptor complex served as the driving force for stimulation or inhibition of downstream target gene expression within different tissues. Incorporating information such as receptor dynamics, as well as the gene and protein induction, allowed us to describe the receptor-mediated effects of MPL on glucose regulation in each important tissue. This advanced mechanistic model provides unique insights into the contributions of major tissues and quantitative hypotheses for the multi-factor control of a complex metabolic system.

Modeling disease progression and rosiglitazone intervention in type 2 diabetic Goto-Kakizaki rats

The pharmacokinetics (PK) and pharmacodynamics (PD) of rosiglitazone were studied in type 2 diabetic (T2D) Goto-Kakizaki (GK) rats that received daily doses of 0, 5, or 10 mg/kg for 23 days followed by 60 days of washout. Blood glucose, plasma insulin, and hemoglobin A1c were determined over time. Oral glucose tolerance tests were performed before and at the end of treatment and after 20 days of washout to determine insulin sensitivity and β-cell function. Rosiglitazone effectively lowered glucose by inhibiting hepatic glucose production and enhancing insulin sensitivity. The glucose-insulin inter-regulation was characterized by a feedback model: glucose and insulin have their own production (k(in)) and elimination (k(out)) rate constants, whereas glucose stimulates insulin production (k(inI)) and insulin, in turn, promotes glucose utilization (k(outG)). Animal handling and placebo treatment affected glucose turnover with k(pl) = 0.388 kg/mg/day. The PK of rosiglitazone was fitted with a one-compartment model with first-order absorption. The effect of rosiglitazone was described as inhibition of k(inG) with I(max) = 0.296 and IC(50) = 1.97 μg/ml. Rosiglitazone also stimulated glucose utilization by improving insulin sensitivity with a linear factor S(R) = 0.0796 kg/mg. In GK rats, 23 days of treatment increased body weight but did not cause hemodilution. Weight gain was characterized with body weight input (k(s)(w)) and output (k(d)(w)), and rosiglitazone inhibited k(d)(w) with ID(50) = 96.8 mg/kg. The mechanistic PK/PD model quantitatively described the glucose-insulin system and body weights under chronic rosiglitazone treatment in T2D rats.

Mechanistic modeling of the effects of glucocorticoids and circadian rhythms on adipokine expression

A mechanism-based model was developed to describe the effects of methylprednisolone (MPL), circadian rhythms, and the glucose/free fatty acid (FFA)/insulin system on leptin and adiponectin expression in white adipose tissue in rats. Fifty-four normal Wistar rats received 50 mg/kg MPL intramuscularly and were sacrificed at various times. An additional set of 54 normal Wistar rats were sacrificed at 18 time points across the 24-h light/dark cycle and served as controls. Measurements included plasma MPL, glucocorticoid receptor (GR) mRNA, leptin mRNA, adiponectin mRNA, plasma leptin, adiponectin, glucose, FFA, and insulin. MPL pharmacokinetics was described by a two-compartment model with two absorption components. All measured plasma markers and mRNA expression exhibited circadian patterns except for adiponectin and were described by Fourier harmonic functions. MPL caused significant down-regulation in GR mRNA with the nadir occurring at 5 h. MPL disrupted the circadian patterns in plasma glucose and FFA by stimulating their production. Plasma glucose and FFA subsequently caused an increase in plasma insulin. Furthermore, MPL disrupted the circadian patterns in leptin mRNA expression by stimulating its production. This rise was closely followed by an increase in plasma leptin. Both leptin mRNA and plasma leptin peaked at 12 h after MPL and eventually returned back to their circadian baselines. MPL and insulin had opposing effects on adiponectin mRNA expression and plasma adiponectin, which resulted in biphasic pharmacodynamic profiles. This small systems model quantitatively describes, integrates, and provides additional insights into various factors controlling adipokine gene expression.

Dynamic modeling of methylprednisolone effects on body weight and glucose regulation in rats

Influences of methylprednisolone (MPL) and food consumption on body weight (BW), and the effects of MPL on glycemic control including food consumption and the dynamic interactions among glucose, insulin, and free fatty acids (FFA) were evaluated in normal male Wistar rats. Six groups of animals received either saline or MPL via subcutaneous infusions at the rate of 0.03, 0.1, 0.2, 0.3 and 0.4 mg/kg/h for different treatment periods. BW and food consumption were measured twice a week. Plasma concentrations of MPL and corticosterone (CST) were determined at animal sacrifice. Plasma glucose, insulin, and FFA were measured at various times after infusion. Plasma MPL concentrations were simulated by a two-compartment model and used as the driving force in the pharmacodynamic (PD) analysis. All data were modeled using ADAPT 5. The MPL treatments caused reduction of food consumption and body weights in all dosing groups. The steroid also caused changes in plasma glucose, insulin, and FFA concentrations. Hyperinsulinemia was achieved rapidly at the first sampling time of 6 h; significant elevations of FFA were observed in all drug treatment groups; whereas only modest increases in plasma glucose were observed in the low dosing groups (0.03 and 0.1 mg/kg/h). Body weight changes were modeled by dual actions of MPL: inhibition of food consumption and stimulation of weight loss, with food consumption accounting for the input of energy for body weight. Dynamic models of glucose and insulin feedback interactions were extended to capture the major metabolic effects of FFA: stimulation of insulin secretion and inhibition of insulin-stimulated glucose utilization. These models of body weight and glucose regulation adequately captured the experimental data and reflect significant physiological interactions among glucose, insulin, and FFA. These mechanism-based PD models provide further insights into the multi-factor control of this essential metabolic system.

Mechanism-based disease progression modeling of type 2 diabetes in Goto-Kakizaki rats

The dynamics of aging and type 2 diabetes (T2D) disease progression were investigated in normal [Wistar-Kyoto (WKY)] and diabetic [Goto-Kakizaki (GK)] rats and a mechanistic disease progression model was developed for glucose, insulin, and glycosylated hemoglobin (HbA1c) changes over time. The study included 30 WKY and 30 GK rats. Plasma glucose and insulin, blood glucose and HbA1c concentrations and hematological measurements were taken at ages 4, 8, 12, 16 and 20 weeks. A mathematical model described the development of insulin resistance (IR) and β-cell function with age/growth and diabetes progression. The model utilized transit compartments and an indirect response model to quantitate biomarker changes over time. Glucose, insulin and HbA1c concentrations in WKY rats increased to a steady-state at 8 weeks due to developmental changes. Glucose concentrations at 4 weeks in GK rats were almost twice those of controls, and increased to a steady-state after 8 weeks. Insulin concentrations at 4 weeks in GK rats were similar to controls, and then hyperinsulinemia occurred until 12-16 weeks of age indicating IR. Subsequently, insulin concentrations in GK rats declined to slightly below WKY controls due to β-cell failure. HbA1c showed a delayed increase relative to glucose. Modeling of HbA1c was complicated by age-related changes in hematology in rats. The diabetes model quantitatively described the glucose/insulin inter-regulation and HbA1c production and reflected the underlying pathogenic factors of T2D--IR and β-cell dysfunction. The model could be extended to incorporate other biomarkers and effects of various anti-diabetic drugs.

Pharmacodynamics of glucose regulation by methylprednisolone. II. normal rats

A physiologic pharmacodynamic model was developed to jointly describe the effects of methylprednisolone (MPL) on adrenal suppression and glycemic control in normal rats. Six groups of animals were given MPL intravenously at 0, 10 and 50 mg/kg, or by subcutaneous 7 day infusion at rates of 0, 0.1 and 0.3 mg/kg/h. Plasma concentrations of MPL, corticosterone (CST), glucose and insulin were determined at various times up to 72 h after injection and 336 h after infusion. The pharmacokinetics of MPL was described by a two-compartment model. A circadian rhythm for CST was found in untreated rats with a stress-altered baseline caused by handling, which was captured by a circadian harmonic secretion rate with an increasing mesor. All drug treatments caused CST suppression. Injection of MPL caused temporary increases in glucose over 4 h. Insulin secretion was thereby stimulated yielding a later peak around 6 h. In turn, insulin can normalize glucose. However, long-term dosing caused continuous hyperglycemia during and after infusion. Hyperinsulinemia was achieved during infusion, but diminished immediately after dosing despite the high glucose concentration. The effects of CST and MPL on glucose production were described with a competitive stimulation function. A disease progression model incorporating reduced endogenous glucose uptake/utilization was used to describe glucose metabolism under different treatments. The results exemplify the roles of endogenous and exogenous hormones in mediating glucose dynamics. The pharmacokinetic/pharmacodynamic model is valuable for quantitating diabetogenic effects of corticosteroid treatments and provides mechanistic insights into the hormonal control of the metabolic system.