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1.  Population pharmacokinetic–pharmacodynamic–disease progression model for effects of anakinra in Lewis rats with collagen-induced arthritis 
A population pharmacokinetic–pharmacodynamic–disease progression (PK/PD/DIS) model was developed to characterize the effects of anakinra in collagen-induced arthritic (CIA) rats and explore the role of interleukin-1β (IL-1β) in rheumatoid arthritis. The CIA rats received either vehicle, or anakinra at 100 mg/kg for about 33 h, 100 mg/kg for about 188 h, or 10 mg/kg for about 188 h by subcutaneous infusion. Plasma concentrations of anakinra were assayed by enzyme-linked immunosorbent assay. Swelling of rat hind paws was measured. Population PK/PD/DIS parameters were computed for the various groups using non-linear mixed-effects modeling software (NONMEM® Version VI). The final model was assessed using visual predictive checks and nonparameter stratified bootstrapping. A two-compartment PK model with two sequential absorption processes and linear elimination was used to capture PK profiles of anakinra. A transduction-based feedback model incorporating logistic growth rate captured disease progression and indirect response model I captured drug effects. The PK and paw swelling versus time profiles in CIA rats were fitted well. Anakinra has modest effects (Imax = 0.28) on paw edema in CIA rats. The profiles are well-described by our PK/PD/DIS model which provides a basis for future mechanism-based assessment of anakinra dynamics in rheumatoid arthritis.
doi:10.1007/s10928-011-9219-z
PMCID: PMC3407879  PMID: 22002845
Anakinra; Pharmacokinetics; Pharmacodynamics; Rheumatoid arthritis; Population model
2.  Differential Muscle Gene Expression as a Function of Disease Progression in Goto-Kakizaki Diabetic Rats 
The Goto-Kakizaki (GK) rat, a polygenic non-obese model of type 2 diabetes, is a useful surrogate for study of diabetes-related changes independent of obesity. GK rats and appropriate controls were killed at 4, 8, 12, 16 and 20 weeks post-weaning and differential muscle gene expression along with body and muscle weights, plasma hormones and lipids, and blood cell measurements were carried out. Gene expression analysis identified 204 genes showing 2-fold or greater differences between GK and controls in at least 3 ages. Array results suggested increased oxidative capacity in GK muscles, as well as differential gene expression related to insulin resistance, which was also indicated by HOMA-IR measurements. In addition, potential new biomarkers in muscle gene expression were identified that could be either a cause or consequence of T2DM. Furthermore, we demonstrate here the presence of chronic inflammation evident both systemically and in the musculature, despite the absence of obesity.
doi:10.1016/j.mce.2011.02.016
PMCID: PMC3093670  PMID: 21356272
type 2 diabetes; skeletal muscle; inflammation; microarrays; gene expression
3.  Assessment of Pharmacologic Area Under the Curve When Baselines are Variable 
Pharmaceutical research  2011;28(5):1081-1089.
Purpose
The area under the curve (AUC) is commonly used to assess the extent of exposure of a drug. The same concept can be applied to generally assess pharmacodynamic responses and the deviation of a signal from its baseline value. When the initial condition for the response of interest is not zero, there is uncertainty in the true value of the baseline measurement. This necessitates the consideration of the AUC relative to baseline to account for this inherent uncertainty and variability in baseline measurements.
Methods
An algorithm to calculate the AUC with respect to a variable baseline is developed by comparing the AUC of the response curve with the AUC of the baseline while taking into account uncertainty in both measurements. Furthermore, positive and negative components of AUC (above and below baseline) are calculated separately to allow for the identification of biphasic responses.
Results
This algorithm is applied to gene expression data to illustrate its ability to capture transcriptional responses to a drug that deviate from baseline and to synthetic data to quantitatively test its performance.
Conclusions
The variable nature of the baseline is an important aspect to consider when calculating the AUC.
doi:10.1007/s11095-010-0363-8
PMCID: PMC3152796  PMID: 21234658
AUC; baseline; bioinformatics; microarrays; pharmacogenomics
4.  Adipose Tissue Deficiency and Chronic Inflammation in Diabetic Goto-Kakizaki Rats 
PLoS ONE  2011;6(2):e17386.
Type 2 diabetes (T2DM) is a heterogeneous group of diseases that is progressive and involves multiple tissues. Goto-Kakizaki (GK) rats are a polygenic model with elevated blood glucose, peripheral insulin resistance, a non-obese phenotype, and exhibit many degenerative changes observed in human T2DM. As part of a systems analysis of disease progression in this animal model, this study characterized the contribution of adipose tissue to pathophysiology of the disease. We sacrificed subgroups of GK rats and appropriate controls at 4, 8, 12, 16 and 20 weeks of age and carried out a gene array analysis of white adipose tissue. We expanded our physiological analysis of the animals that accompanied our initial gene array study on the livers from these animals. The expanded analysis included adipose tissue weights, HbA1c, additional hormonal profiles, lipid profiles, differential blood cell counts, and food consumption. HbA1c progressively increased in the GK animals. Altered corticosterone, leptin, and adiponectin profiles were also documented in GK animals. Gene array analysis identified 412 genes that were differentially expressed in adipose tissue of GKs relative to controls. The GK animals exhibited an age-specific failure to accumulate body fat despite their relatively higher calorie consumption which was well supported by the altered expression of genes involved in adipogenesis and lipogenesis in the white adipose tissue of these animals, including Fasn, Acly, Kklf9, and Stat3. Systemic inflammation was reflected by chronically elevated white blood cell counts. Furthermore, chronic inflammation in adipose tissue was evident from the differential expression of genes involved in inflammatory responses and activation of natural immunity, including two interferon regulated genes, Ifit and Iipg, as well as MHC class II genes. This study demonstrates an age specific failure to accumulate adipose tissue in the GK rat and the presence of chronic inflammation in adipose tissue from these animals.
doi:10.1371/journal.pone.0017386
PMCID: PMC3045458  PMID: 21364767
5.  Pharmacokinetic-Pharmacodynamic Disease Progression Model for Effect of Etanercept in Lewis Rats with Collagen-Induced Arthritis 
Pharmaceutical research  2011;28(7):1622-1630.
Purpose
To develop a pharmacokinetic-pharmacodynamic disease progression (PK/PD/DIS) model to characterize the effect of etanercept in collagen-induced arthritis (CIA) rats on rheumatoid arthritis (RA) progression.
Methods
The CIA rats received either 5 mg/kg intravenous (IV), 1 mg/kg IV, or 5 mg/kg subcutaneous (SC) etanercept at day 21 post-disease induction. Effect on disease progression was measured by paw swelling. Plasma concentrations of etanercept were assayed by enzyme-linked immunosorbent assay (ELISA). PK profiles were fitted first; parameter estimates were applied to fit paw edema data for PD and DIS-related parameter estimation using ADAPT 5 software.
Results
The model contained a two-compartment PK model with Michaelis-Menten elimination. For SC administration, two additional mathematical functions for absorption were added. The disease progression component was an indirect response model with a time-dependent change in paw edema production rate constant (kin) assumed to be inhibited by etanercept.
Conclusions
Etanercept has modest effects on paw swelling in CIA rats. The PK and PD profiles were well described by the developed PK/PD/DIS model, which may be used for other anti-cytokine biologic agents for RA.
doi:10.1007/s11095-011-0396-7
PMCID: PMC3726066  PMID: 21360252
arthritis; etanercept; model; pharmacodynamics; pharmacokinetics
6.  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. Hyper-insulinemia 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.
doi:10.1007/s10928-011-9194-4
PMCID: PMC3407886  PMID: 21394487
Glucocorticoids; Methylprednisolone; Pharmacodynamics; Food intake; Body weight; Glucose; Insulin; Free fatty acids

Results 1-6 (6)