Modeling corticosteroid effects in a rat model of rheumatoid arthritis I: mechanistic disease progression model for the time course of collagen-induced arthritis in Lewis rats

The relationship between gender and pharmacology

The part of sexuality in pharmacology research was not acknowledged, and it was not thought-out to be a determinant that could impact strength and disease. For decades research has mainly contained male, women and animals, leading to a lack of news about syndromes in females. Still, it is critical to guarantee equal likeness so that determine the security, influence, and resistance of healing agents for all individuals. The underrepresentation of female models in preclinical studies over various decades has surpassed to disparities in the understanding, disease, and treatment of ailments 'tween genders. The closeness of sexuality bias has happened recognized as a contributing determinant to the restricted interpretation and replicability of preclinical research. Many demands operation have stressed the significance of including sexuality as a organic changeable, and this view is acquire growing support. Regardless of important progress in incorporating more female models into preclinical studies, differences prevail contemporary. The current review focuses on the part of sexuality and common in biomedical research and, therefore, their potential function in pharmacology and analyze the potential risks guide.

Evaluation of Sex Differences in Preclinical Pharmacology Research: How Far Is Left to Go?

Until the last quarter of the 20th century, sex was not recognized as a variable in health research, nor was it believed to be a factor that could affect health and illness. Researchers preferred studying male models for a variety of reasons, such as simplicity, lower costs, hormone confounding effects, and fear of liability from perinatal exposure in case of pregnancy. Equitable representation is imperative for determining the safety, effectiveness, and tolerance of therapeutic agents for all consumers. Decades of female models' underrepresentation in preclinical studies has resulted in inequality in the understanding, diagnosis, and treatment of disease between the sexes. Sex bias has been highlighted as one of the contributing factors to the poor translation and replicability of preclinical research. There have been multiple calls for action, and the inclusion of sex as a biological variable is increasingly supported. However, although there has been substantial progress in the efforts to include more female models in preclinical studies, disparities today remain. In the present review, we consider the current standard practice of the preclinical research setting, why the sex bias exists, why there is the need to include female models, and what risks may arise from continuing this exclusion from experimental design.

Exploring the Pharmacokinetic Mysteries of the Liver: Application of Series Compartment Models of Hepatic Elimination

Among the basic hepatic clearance models, the dispersion model (DM) is the most physiologically sound compared with the well-stirred model and the parallel tube model. However, its application in physiologically-based pharmacokinetic (PBPK) modeling has been limited due to computational complexities. The series compartment models (SCM) of hepatic elimination that treats the liver as a cascade of well-stirred compartments connected by hepatic blood flow exhibits some mathematical similarities to the DM but is easier to operate. This work assesses the quantitative correlation between the SCM and DM and demonstrates the operation of the SCM in PBPK with the published single-dose blood and liver concentration-time data of six flow-limited compounds. The predicted liver concentrations and the estimated intrinsic clearance (CLint ) and PBPK-operative tissue-to-plasma partition coefficient (Kp ) values were shown to depend on the number of liver sub-compartments (n) and hepatic enzyme zonation in the SCM. The CLint and Kp decreased with increasing n, with more remarkable differences for drugs with higher hepatic extraction ratios. Given the same total CLint , the SCM yields a higher Kp when the liver perivenous region exhibits a lower CLint as compared with a high CLint at this region. Overall, the SCM nicely approximates the DM in characterizing hepatic elimination and offers an alternative flexible approach as well as providing some insights regarding sequential drug concentrations in the liver. SIGNIFICANCE STATEMENT: The SCM nicely approximates the DM when applied in PBPK for characterizing hepatic elimination. The number of liver sub-compartments and hepatic enzyme zonation are influencing factors for the SCM resulting in model-dependent predictions of total/internal liver concentrations and estimates of CLint and the PBPK-operative Kp . Such model-dependency may have an impact when the SCM is used for in vitro-to-in vivo extrapolation (IVIVE) and may also be relevant for PK/PD/toxicological effects when it is the driving force for such responses.

Development of PBPK model for intra-articular injection in human: methotrexate solution and rheumatoid arthritis case study

A physiologically based model describing the dissolution, diffusion, and transfer of drug from the intra-articular (IA) space to the plasma, was developed for GastroPlus® v9.8. The model is subdivided into compartments representing the synovial fluid, synovium, and cartilage. The synovium is broken up into two sublayers. The intimal layer acts as a diffusion barrier between the synovial fluid and the subintimal layer. The subintimal layer of the synovium has fenestrated capillaries that allow the free drug to be transported into systemic circulation. The articular cartilage is broken up into 10 diffusion sublayers as it is much thicker than the synovium. The cartilage acts as a depot tissue for the drug to diffuse into from synovial fluid. At later times, the drug will diffuse from the cartilage back into synovial fluid once a portion of the dose enters systemic circulation. In this study, a listing of all relevant details and equations for the model is presented. Methotrexate was chosen as a case study to show the application and utility of the model, based on the availability of intravenous (IV), oral (PO) and IA administration data in patients presenting rheumatoid arthritis (RA) symptoms. Systemic disposition of methotrexate in RA patients was described by compartmental pharmacokinetic (PK) model with PK parameters extracted using the PKPlus™ module in GastroPlus®. The systemic PK parameters were validated by simulating PO administration of methotrexate before being used for simulation of IA administration. For methotrexate, the concentrations of drug in the synovial fluid and plasma were well described after adjustments of physiological parameters to account for RA disease state, and with certain assumptions about binding and diffusion. The results indicate that the model can correctly describe PK profiles resulting from administration in the IA space, however, additional cases studies will be required to evaluate ability of the model to scale between species and/or doses.

Salvianolate Ameliorates Osteopenia and Improves Bone Quality in Prednisone-Treated Rheumatoid Arthritis Rats by Regulating RANKL/RANK/OPG Signaling

Rheumatoid arthritis (RA) is closely associated with periarticular osteopenia and leads to a high risk of generalized osteoporosis. Although glucocorticoid (GC) treatment ameliorates joint degradation and manages inflammation in RA, GC application may induce further bone quality deterioration in RA patients. Current treatments for RA lack relevant strategies for the prevention and treatment of osteopenia in RA. In this study, we aimed to investigate whether salvianolate treatment ameliorated osteopenia in prednisone-treated RA rats. Lewis rats with collagen-induced arthritis (CIA) were administered prednisone (PDN) or PDN plus salvianolate (PDN+Sal) treatment for 90 days. The effects of Sal were investigated in PDN-treated CIA rats. To further evaluate the effects of Sal under inflammatory conditions, we investigated the effects of Sal treatment on the TNF-α-induced inflammatory response in MC3T3-E1 osteoblasts. Bone histomorphometry, bone mineral density (BMD), bone biomechanical properties, micro-computed tomography (micro-CT), immunohistochemistry, RT-PCR and western blot analyses were performed to evaluate the effects of Sal. The results demonstrated that RA induced bone loss and bone quality deterioration, with high bone turnover in CIA rats. PDN+Sal treatment significantly increased BMD and trabecular/cortical bone mass, suppressed inflammation, and improved bone biomechanical properties compared to CIA control and PDN treatment. PDN+Sal treatment significantly suppressed bone resorption and the RANKL and RANKL/OPG ratios compared to PDN. PDN+Sal and PDN treatment significantly inhibited TNF-α by 82 and 83%, respectively, and both suppressed inflammation in CIA rats. However, there was no significant difference between PDN+Sal and PDN treatment alone in regard to bone formation parameters or the management of inflammation and arthropathy. Sal significantly increased Osterix, OPN, and Col1a1 while decreasing RANKL, TRAF6, and TRAIL gene in TNF-α-induced MC3T3-E1 osteoblasts. Sal significantly increased Osterix, OPN and RUNX2 while decreasing NF-κB, TRAF6 and IL-1β protein in TNF-α-induced MC3T3-E1 osteoblasts. The results suggested that salvianolate treatment ameliorated osteopenia and improved bone quality in prednisone-treated RA rats, and the potential mechanism may be related to the regulation of the RANKL/RANK/OPG signaling pathway, TRAIL-TRAF6-NFκB signal axis, and downregulation of inflammatory cytokines. Salvianolate could be used as a promising supplemental therapeutic strategy to ameliorate osteopenia and improve bone quality in GC-treated RA patients.

Hyaluronic acid-green tea catechin conjugates as a potential therapeutic agent for rheumatoid arthritis

Fibroblast-like synoviocytes are a key effector cell type involved in the pathogenesis of rheumatoid arthritis. The major green tea catechin, epigallocatechin-3-O-gallate (EGCG), has attracted significant interest for rheumatoid arthritis therapy because of its ability to suppress the proliferation and interleukin-6 secretion of synoviocytes. However, therapeutic efficacy of EGCG has been limited by a lack of target cell specificity. Herein we report hyaluronic acid-EGCG (HA-EGCG) conjugates as an anti-arthritic agent that is capable of targeting fibroblast-like synoviocytes via HA-CD44 interactions. These conjugates exhibited superior anti-proliferative and anti-inflammatory activities compared with EGCG under simulated physiological conditions. Near-infrared fluorescence imaging revealed preferential accumulation of the conjugates at inflamed joints in a collagen-induced arthritis rat model, and their anti-arthritic efficacy was investigated by measuring a change in the edema and histopathological scores. Our findings suggest the potential of HA-EGCG conjugates as an anti-arthritic agent for the treatment of rheumatoid arthritis.

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.

Comparative Assessment of the New PDE7 Inhibitor - GRMS-55 and Lisofylline in Animal Models of Immune-Related Disorders: A PK/PD Modeling Approach

Purpose

This study aimed to assess the activity of two phosphodiesterase (PDE) inhibitors, namely GRMS-55 and racemic lisofylline ((±)-LSF)) in vitro and in animal models of immune-mediated disorders.

Methods

Inhibition of human recombinant (hr)PDEs and TNF-alpha release from LPS-stimulated whole rat blood by the studied compounds were assessed in vitro. LPS-induced endotoxemia, concanavalin A (ConA)-induced hepatitis, and collagen-induced arthritis (CIA) animal models were used for in vivo evaluation. The potency of the investigated compounds was evaluated using PK/PD and PK/PD/disease progression modeling.

Results

GRMS-55 is a potent hrPDE7A and hrPDE1B inhibitor, while (±)-LSF most strongly inhibits hrPDE3A and hrPDE4B. GRMS-55 decreased TNF-alpha levels in vivo and CIA progression with IC₅₀ of 1.06 and 0.26 mg/L, while (±)-LSF with IC₅₀ of 5.80 and 1.06 mg/L, respectively. Moreover, GRMS-55 significantly ameliorated symptoms of ConA-induced hepatitis.

Conclusions

PDE4B but not PDE4D inhibition appears to be mainly engaged in anti-inflammatory activity of the studied compounds. GRMS-55 and (±)-LSF seem to be promising candidates for future studies on the treatment of immune-related diseases. The developed PK/PD models may be used to assess the anti-inflammatory and anti-arthritic potency of new compounds for the treatment of rheumatoid arthritis and other inflammatory disorders.

Electronic supplementary material

The online version of this article (10.1007/s11095-019-2727-z) contains supplementary material, which is available to authorized users.

Translational Quantitative Systems Pharmacology in Drug Development: from Current Landscape to Good Practices

Systems pharmacology approaches have the capability of quantitatively linking the key biological molecules relevant to a drug candidate's mechanism of action (drug-induced signaling pathways) to the clinical biomarkers associated with the proposed target disease, thereby quantitatively facilitating its development and life cycle management. In this review, the model attributes of published quantitative systems pharmacology (QSP) modeling for lowering cholesterol, treating salt-sensitive hypertension, and treating rare diseases as well as describing bone homeostasis and related pharmacological effects are critically reviewed with respect to model quality, calibration, validation, and performance. We further reviewed the common practices in optimizing QSP modeling and prediction. Notably, leveraging genetics and genomic studies for model calibration and validation is common. Statistical and quantitative assessment of QSP prediction and handling of model uncertainty are, however, mostly lacking as are the quantitative and statistical criteria for assessing QSP predictions and the covariance matrix of coefficients between the parameters in a validated virtual population. To accelerate advances and application of QSP with consistent quality, a list of key questions is proposed to be addressed when assessing the quality of a QSP model in hopes of stimulating the scientific community to set common expectations. The common expectations as to what constitutes the best QSP modeling practices, which the scientific community supports, will advance QSP modeling in the realm of informed drug development. In the long run, good practices will extend the life cycles of QSP models beyond the life cycles of individual drugs.

Anti-arthritic effect of pentosan polysulfate in rats with collagen-induced arthritis

Pentosan polysulfate (PPS) is currently under investigation as a potential disease-modifying antiarthritic agent. In the present study the effects of PPS on arthritic profiles based on clinical score, ankle size, histological changes, and activity of inflammatory mediators using collagen-induced arthritic rat are reported. Model of arthritis was developed in Sprague Dawley rats by intradermal injection of bovine type II collagen emulsified with incomplete Freund's adjuvant. The rats were randomly divided into four groups: normal control, arthritic control, arthritic rats treated with PPS (at dose level 20 μg/g) and arthritic rats treated with meloxicam (2 μg/g). The treatment was continued daily until the day 30. Arthritic biomarkers (cartilage oligomeric matrix protein and tartrate-resistant acid phosphatase 5b) in synovial fluid, expression of inflammatory mediators (interleukin-1β, and tumor necrosis factor-α) and osteoclast marker genes (cathepsin K, tartrate-resistant acid phosphatase) in synovial membrane were measured. Daily administration of PPS to the arthritic rats significantly decreased the severity of arthritis by effectively suppressing the symptoms of arthritis and improving the functional recovery based on clinical score and histopathological evidence. Intriguingly, identical downregulation pattern of arthritis profiles, biological markers as well as relative mRNA levels of osteoclast markers and cytokines were monitored in arthritic rats treated with PPS. In conclusion, PPS exerted protective effects against collagen-induced arthritis in rats. The results suggest that PPS acts as an anti-inflammatory and anti-arthritic agent in decreasing the arthritic effects in collagen-induced arthritic rats.

Effect of prednisone treatment for 30 and 90 days on bone metabolism in collagen-induced arthritis (CIA) rats

Glucocorticoids (GCs) are often prescribed to treat rheumatoid arthritis (RA) in the long term, but there is still controversy in the administration of GCs, mainly because of the adverse reactions such as osteoporosis. Numerous studies have demonstrated that osteoporosis could be induced by GCs in normal rats. However, few experiments have focused on whether osteoporosis could be induced or aggravated by GCs in collagen induced arthritis (CIA) rats. We have investigated bone changes in CIA rats treated with prednisone at 4.5 mg/kg/day for 30 and 90 days by bone histomorphometry, bone mineral density (BMD), micro-CT, biomechanical test, and enzyme-linked immunosorbant assay. We found that high bone turnover osteoporosis was shown in CIA rats. Prednisone treatment for 30 and 90 days improved articular structure and decelerated the degeneration of the femur in CIA rats, but did not improve BMD and bone biomechanics. We conclude that osteoporosis was not aggravated in CIA rats treated with prednisone for 30 and 90 days. On the contrary, prednisone treatment for 30 and 90 days could prevent bone loss of the femur in CIA rats. There was a negative effect on bone metabolism in CIA rats treated with prednisone for 90 days.

Modeling Sex Differences in Anti-inflammatory Effects of Dexamethasone in Arthritic Rats

PURPOSE

Collagen-induced arthritic (CIA) rats are used commonly for preclinical pharmacologic research into rheumatoid arthritis (RA). Dexamethasone (DEX), a potent corticosteroid (CS), remains an important component in combination therapy for RA. Although sex differences in RA and CS pharmacokinetics/pharmacodynamics (PK/PD) have been documented in humans, there has been no such comprehensive evaluation of sex differences in CIA rats.

METHODS

Paw size measurements were obtained for males and females from four groups of animals: healthy controls, non-drug treated arthritic animals, and both 0.225 and 2.25 mg/kg DEX-treated arthritic animals. A turnover model for disease progression, minimal PBPK model for drug concentrations, and inhibitory indirect response model were applied using population PK/PD modeling.

RESULTS

The clearances of DEX were 43% greater in males, but other PK parameters were similar. The temporal profiles of paw swelling exhibited earlier progression, peak edema times, and disease remission in females. DEX suppressed paw edema well in both males and females with similar capacity (I_max) values (=1.0), but DEX potency was less in females with higher IC₅₀ values (0.101 versus 0.015 ng/mL).

CONCLUSIONS

The pharmacology of DEX was well characterized in CIA rats. This study addresses knowledge gaps about sex differences and can be a guide for more mechanistic assessment of sex, drug, and disease differences in RA.

Ectopic RASGRP2 (CalDAG-GEFI) expression in rheumatoid synovium contributes to the development of destructive arthritis

OBJECTIVES

Rheumatoid arthritis (RA) is an autoimmune polyarthritis, in which fibroblast-like synoviocytes (FLS) play a key role in cartilage and bone destruction through tumour-like proliferation and invasiveness. Considering still unsatisfactory remission rate in RA even under treatment with biological disease-modifying antirheumatic drugs, novel therapeutic strategy for treatment-resistant RA is still awaited. In this study, we analysed the expression and function of Ras guanine nucleotide-releasing proteins (RASGRPs), guanine exchange factors for small GTPase Ras, in FLS as a potential therapeutic target for RA.

METHODS

The expression of RASGRPs mRNA was quantified by a real-time PCR assay in FLS isolated from synovial tissue samples. RASGRP2 protein was also evaluated immunohistochemically. Then, we transiently transfected FLS with RASGRP2 expression vector and assessed their proliferation, adhesion, migration and invasion by cellular functional assays and downstream signalling activation using immunoblot. Finally, the therapeutic effect of RASGRP2 silencing was evaluated in type-II collagen-induced arthritis rats.

RESULTS

RASGRP2 was abundantly expressed in FLS from RA synovium, whereas scarcely found in those from osteoarthritis. Expression of RASGRP2 in RA-FLS was enhanced by transforming growth factor-beta. RASGRP2 activated RAP-1, subsequently affecting nuclear factor kappa-light-chain-enhancer of activated B cells pathway and actin dynamics in FLS. RASGRP2-overexpressed FLS had increased abilities of adhesion, migration and interleukin (IL)-6 production. Silencing of RASGRP2 using the intra-articular injection of Rasgrp2-specific siRNAs dampened experimental arthritis in rats by inhibiting pannus formation.

CONCLUSIONS

RASGRP2 was identified to be involved in the pathogenesis of RA by promoting adhesion, migration and IL-6 production from FLS, proposed as a potential novel non-immunosuppressive therapeutic target for RA.

Local cryotherapy improves adjuvant-induced arthritis through down-regulation of IL-6 / IL-17 pathway but independently of TNFα

OBJECTIVES

Local cryotherapy is widely and empirically used in the adjuvant setting in rheumatoid arthritis treatment, however its own therapeutic and anti-inflammatory effects are poorly characterized. We aimed to evaluate the effects of local cryotherapy on local and systemic inflammation in Adjuvant-induced arthritis, a murine model of rheumatoid arthritis.

METHODS

The effects of mild hypothermia (30°C for 2 hours) on cytokine protein levels (Multiplex/ELISA) were evaluated in vitro in cultured rat adjuvant-induced arthritis patellae. In vivo, local cryotherapy was applied twice a day for 14 days in arthritic rats (ice: n = 10, cold gas: n = 9, non-treated: n = 10). At day 24 after the induction of arthritis, cytokine expression levels were measured in grinded hind paws (Q-RT-PCR) and in the plasma (Multiplex/ELISA).

RESULTS

In vitro, punctual mild hypothermia down-regulated IL-6 protein expression. In vivo, ice showed a better efficacy profile on the arthritis score and joint swelling and was better tolerated, while cold gas induced a biphasic response profile with initial, transient arthritis worsening. Local cryotherapy also exerted local and systemic anti-inflammatory effects, both at the gene and the protein levels: IL-6, IL-17A and IL-1β gene expression levels were significantly down-regulated in hind paws. Both techniques decreased plasma IL-17A while ice decreased plasma IL-6 protein levels. By contrast, we observed no effect on local/systemic TNF-α pathway.

CONCLUSIONS

We demonstrated for the first time that sub-chronically applied local cryotherapy (ice and cold gas) is an effective and well-tolerated treatment in adjuvant-induced arthritis. Furthermore, we provided novel insights into the cytokine pathways involved in Local cryotherapy's local and systemic anti-inflammatory effects, which were mainly IL-6/IL-17A-driven and TNF-α independent in this model.

A quantitative mechanistic PK/PD model directly connects Btk target engagement and in vivo efficacy

Correlating target engagement with in vivo drug activity remains a central challenge in efforts to improve the efficiency of drug discovery. Previously we described a mechanistic pharmacokinetic-pharmacodynamic (PK/PD) model that used drug-target binding kinetics to successfully predict the in vivo efficacy of antibacterial compounds in models of Pseudomonas aeruginosa and Staphylococcus aureus infection. In the present work we extend this model to quantitatively correlate the engagement of Bruton's tyrosine kinase (Btk) by the covalent inhibitor CC-292 with the ability of this compound to reduce ankle swelling in an animal model of arthritis. The modeling studies include the rate of Btk turnover and reveal the vulnerability of Btk to engagement by CC-292.

Modeling Combined Immunosuppressive and Anti-inflammatory Effects of Dexamethasone and Naproxen in Rats Predicts the Steroid-Sparing Potential of Naproxen

Dexamethasone (DEX), a widely prescribed corticosteroid, has long been the cornerstone of the treatment of inflammation and immunologic dysfunctions in rheumatoid arthritis. Corticosteroids are frequently used in combination with other antirheumatic agents such as nonsteroidal anti-inflammatory drugs (NSAIDs) and disease-modifying antirheumatic drugs to mitigate disease symptoms and minimize unwanted effects. We explored the steroid dose-sparing potential of the NSAID naproxen (NPX) with in vitro and in vivo studies. The single and joint suppressive effects of DEX and NPX on the in vitro mitogen-induced proliferation of T lymphocytes in blood and their anti-inflammatory actions on paw edema were investigated in female and male Lewis rats with collagen-induced arthritis (CIA). As expected, DEX was far more potent than NPX in these systems. Mathematical models incorporating an interaction term ψ were applied to quantitatively assess the nature and intensity of pharmacodynamic interactions between DEX and NPX. Modest synergistic effects of the two drugs were found in suppressing the mitogenic response of T lymphocytes. A pharmacokinetic/pharmacodynamic/disease progression model integrating dual drug inhibition quantitatively described the pharmacokinetics, time-course of single and joint anti-inflammatory effects (paw edema), and sex differences in CIA rats, and indicated additive effects of DEX and NPX. Further model simulations demonstrated the promising steroid-sparing potential of NPX in CIA rats, with the beneficial effects of the combination therapy more likely in males than females.

Effect of Disease-Related Changes in Plasma Albumin on the Pharmacokinetics of Naproxen in Male and Female Arthritic Rats

Naproxen (NPX) is used in the treatment of rheumatoid arthritis (RA) for alleviation of pain and inflammation. In view of the extensive albumin binding of NPX, this study investigates whether chronic inflammation and sex influence the physiologic albumin concentrations, plasma protein binding, and pharmacokinetics (PK) of NPX. The PK of NPX was evaluated in a rat model of RA [collagen-induced arthritis (CIA) in Lewis rats] and in healthy controls. These PK studies included 1) NPX in female and male CIA rats that received 10, 25, or 50 mg/kg NPX i.p.; and 2) NPX in healthy female and male rats after i.p. dosing of NPX at 50 mg/kg. Plasma albumin concentrations were quantified by enzyme-linked immunosorbent assay, and protein binding was assessed using ultrafiltration. The NPX concentrations in plasma and filtrates were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Plasma concentration-time data of NPX were first assessed by noncompartmental analysis (NCA). Nonlinear PK as indicated by dose-dependent NCA clearances and distribution volumes was observed. A two-compartment model with a first-order absorption process incorporating nonlinear protein binding in plasma and tissues jointly described the PK data of all groups. Saturable albumin binding accounts for the nonlinearity of NPX PK in all rats as well as part of the PK differences in arthritic rats. The CIA rats exhibited reduced albumin concentrations, reduced overall protein binding, and reduced clearances of unbound NPX, consistent with expectations during inflammation. The net effect of chronic inflammation was an elevation of the C_max and area under the plasma concentration-time curve (AUC) of unbound drug.

Modeling Sex Differences in Pharmacokinetics, Pharmacodynamics, and Disease Progression Effects of Naproxen in Rats with Collagen-Induced Arthritis

Naproxen (NPX) is a frequently used nonsteroidal anti-inflammatory drug for rheumatoid arthritis (RA). Lack of quantitative information about the drug exposure-response relationship has resulted in empirical dosage regimens for use of NPX in RA. Few studies to date have included sex as a factor, although RA predominates in women. A pharmacokinetic, pharmacodynamic, and disease progression model described the anti-inflammatory effects of NPX in collagen-induced arthritic (CIA) male and female rats. Three groups of rats were included for each sex: healthy animals, CIA controls, and CIA rats given a single 50-mg/kg dose of NPX intraperitoneally. Paw volumes of healthy rats indicated natural growth, and disease status was measured by paw edema. An innovative minimal physiologically based pharmacokinetic (mPBPK) model incorporating nonlinear albumin binding of NPX in both plasma and interstitial fluid (ISF) was applied. Arthritic rats exhibited lower plasma and ISF albumin concentrations and reduced clearances of unbound drug to explain pharmacokinetic profiles. The unbound ISF NPX concentrations predicted by the mPBPK model were used as the driving force for pharmacological effects of NPX. A logistic growth function accounting for natural paw growth and an indirect response model for paw edema and drug effects (inhibition of k_in) was applied. Female rats showed a higher incidence of CIA, earlier disease onset, and more severe symptoms. NPX had stronger effects in males, owing to higher unbound ISF NPX concentrations and lower IC₅₀ values. The model described the pharmacokinetics, unbound NPX in ISF, time course of anti-inflammatory effects, and sex differences in CIA rats.

Model-Informed Development and Registration of a Once-Daily Regimen of Extended-Release Tofacitinib

Extended‐release (XR) formulations enable less frequent dosing vs. conventional (e.g., immediate release (IR)) formulations. Regulatory registration of such formulations typically requires pharmacokinetic (PK) and clinical efficacy data. Here we illustrate a model‐informed, exposure–response (E‐R) approach to translate controlled trial data from one formulation to another without a phase III trial, using a tofacitinib case study. Tofacitinib is an oral Janus kinase (JAK) inhibitor for the treatment of rheumatoid arthritis (RA). E‐R analyses were conducted using validated clinical endpoints from phase II dose–response and nonclinical dose fractionation studies of the IR formulation. Consistent with the delay in clinical response dynamics relative to PK, average concentration was established as the relevant PK parameter for tofacitinib efficacy and supported pharmacodynamic similarity. These evaluations, alongside demonstrated equivalence in total systemic exposure between IR and XR formulations, provided the basis for the regulatory approval of tofacitinib XR once daily by the US Food and Drug Administration.

Early detection of rheumatoid arthritis in rats and humans with 99mTc-3PRGD2 scintigraphy: imaging synovial neoangiogenesis

OBJECTIVES

To validate 99mTc-labeled arginylglycylaspartic acid (99mTc-3PRGD2) scintigraphy as a means to image synovial neoangiogenesis in joints afflicted by rheumatoid arthritis and to investigate its potential in the early detection and management of rheumatoid arthritis.

METHODS

Rheumatoid arthritis and osteoarthritis were generated in Sprague Dawley rats by type II collagen immunization and papain injection, respectively. Rats were imaged with 99mTc-3PRGD2 and 99mTc- methyl diphosphonate (99mTc MDP). X-ray images were also obtained and assessed by a radiologist. Immunohistochemistry of αvβ3 and CD31confirmed the onset of synovial neoangiogenesis. The effect of bevacizumab on rheumatoid arthritis was followed with 99mTc-3PRGD2 scintigraphy. A patient with rheumatoid arthritis and a healthy volunteer were scanned with 99mTc-3PRGD2.

RESULTS

Two weeks after immunization, a significant increase in 99mTc-3PRGD2 was observed in the joints of the rheumatoid arthritis model though uptake in osteoarthritis model and untreated controls was low. 99mTc-MDP whole body scans failed to distinguish early rheumatoid arthritis joints from healthy controls. The expression of αvβ3 and CD31was significantly higher in the joints of rheumatoid arthritis rats compared to normal controls. In serial 99mTc-3PRGD2 scintigraphy studies, 99mTc-3PRGD2 uptake increased in parallel with disease progression. Bevacizumab anti-angiogenetic therapy both improved the symptoms of the rheumatoid arthritis rats and significantly decreased 99mTc-3PRGD2 uptake. Significantly higher 99mTc-3PRGD2 accumulation was also observed in rheumatoid arthritis joints in the patient.

CONCLUSIONS

Our findings indicate that 99mTc-3PRGD2 scintigraphy could detect early rheumatoid arthritis by imaging the associated synovial neoangiogenesis, and may be useful in disease management.

Mathematical modeling of the circadian dynamics of the neuroendocrine-immune network in experimentally induced arthritis

The circadian dynamics of important neuroendocrine-immune mediators have been implicated in progression of rheumatoid arthritis pathophysiology, both clinically as well as in animal models. We present a mathematical model that describes the circadian interactions between mediators of the hypothalamic-pituitary-adrenal (HPA) axis and the proinflammatory cytokines. Model predictions demonstrate that chronically elevated cytokine expression results in the development of adrenal insufficiency and circadian variability in paw edema. Notably, our model also predicts that an increase in mean secretion of corticosterone (CST) after the induction of the disease is accompanied by a decrease in the amplitude of the CST oscillation. Furthermore, alterations in the phase of circadian oscillation of both cytokines and HPA axis mediators are observed. Therefore, by incorporating the circadian interactions between the neuroendocrine-immune mediators, our model is able to simulate important features of rheumatoid arthritis pathophysiology.

Application of a Systems Pharmacology-Based Placebo Population Model to Analyze Long-Term Data of Postmenopausal Osteoporosis

Osteoporosis is a progressive bone disease characterized by decreased bone mass resulting in increased fracture risk. The objective of this investigation was to test whether a recently developed disease systems analysis model for osteoporosis could describe disease progression in a placebo-treated population from the Early Postmenopausal Intervention Cohort (EPIC) study. First, we qualified the model using a subset from the placebo arm of the EPIC study of 222 women who had similar demographic characteristics as the 149 women from the placebo arm of the original population. Second, we applied the model to all 470 women. Bone mineral density (BMD) dynamics were changed to an indirect response model to describe lumbar spine and total hip BMD in this second population. This updated disease systems analysis placebo model describes the dynamics of all biomarkers in the corresponding datasets to a very good approximation; a good description of an individual placebo response will be valuable for evaluating treatments for osteoporosis.

Modeling effects of dexamethasone on disease progression of bone mineral density in collagen-induced arthritic rats

A mechanism-based model was developed to characterize the crosstalk between proinflammatory cytokines, bone remodeling biomarkers, and bone mineral density (BMD) in collagen-induced arthritic (CIA) rats. Male Lewis rats were divided into five groups: healthy control, CIA control, CIA receiving single 0.225 mg kg⁻¹ subcutaneous (SC) dexamethasone (DEX), CIA receiving single 2.25 mg kg⁻¹ SC DEX, and CIA receiving chronic 0.225 mg kg⁻¹ SC DEX. The CIA rats underwent collagen induction at day 0 and DEX was injected at day 21 post-induction. Disease activity was monitored throughout the study and rats were sacrificed at different time points for blood and paw collection. Protein concentrations of interleukin (IL)-1β, IL-6, receptor activator of nuclear factor kappa-B ligand (RANKL), osteoprotegerin (OPG), and tartrate-resistant acid phosphatase 5b (TRACP-5b) in paws were measured by enzyme-linked immunosorbent assays (ELISA). Disease progression and DEX pharmacodynamic profiles of IL-1β, IL-6, RANKL, and OPG were fitted simultaneously and parameters were sequentially applied to fit the TRACP-5b and BMD data. The model was built according to the mechanisms reported in the literature and modeling was performed using ADAPT 5 software with naïve pooling. Time profiles of IL-1β and IL-6 protein concentrations correlated with their mRNAs. The RANKL and OPG profiles matched previous findings in CIA rats. DEX inhibited the expressions of IL-1β, IL-6, and RANKL, but did not alter OPG. TRACP-5b was also inhibited by DEX. Model predictions suggested that anti-IL-1β therapy and anti-RANKL therapy would result in similar efficacy for prevention of bone loss among the cytokine antagonists.

Ras guanine nucleotide-releasing protein 4 is aberrantly expressed in the fibroblast-like synoviocytes of patients with rheumatoid arthritis and controls their proliferation

OBJECTIVE

Ras guanine nucleotide-releasing protein 4 (RasGRP-4) is a calcium-regulated guanine nucleotide exchange factor and diacylglycerol/phorbol ester receptor not normally expressed in fibroblasts. While RasGRP-4-null mice are resistant to arthritis induced by anti-glucose-6-phosphate isomerase autoantibodies, the relevance of these findings to humans is unknown. We undertook this study to evaluate the importance of RasGRP-4 in the pathogenesis of human and rat arthritis.

METHODS

Synovial tissue from patients with rheumatoid arthritis (RA) and osteoarthritis (OA) were evaluated immunohistochemically for the presence of RasGRP-4 protein. Fibroblast-like synoviocytes (FLS) were isolated from synovial samples, and expression of RasGRP-4 was evaluated by real-time quantitative reverse transcription-polymerase chain reaction analyses. The proliferation potency of FLS was evaluated by exposing the cells to a RasGRP-4-specific small interfering RNA (siRNA). Finally, the ability of RasGRP-4-specific siRNAs to hinder type II collagen-induced arthritis in rats was evaluated to confirm the importance of the signaling protein in the disease.

RESULTS

Unexpectedly, RasGRP-4 protein was detected in the synovial hyperplastic lining, where proliferating FLS preferentially reside. FLS isolated from tissues obtained from a subpopulation of RA patients expressed much more RasGRP-4 than did FLS from examined OA patients. Moreover, the level of RasGRP-4 transcript was correlated with the FLS proliferation rate. The ability of cultured FLS to divide was diminished when they were treated with RasGRP-4-specific siRNAs. The intraarticular injection of RasGRP-4-specific siRNAs also dampened experimental arthritis in rats.

CONCLUSION

RasGRP-4 is aberrantly expressed in FLS and helps regulate their growth. This intracellular signaling protein is therefore a candidate target for dampening proliferative synovitis and joint destruction.

Biodistribution of etanercept to tissues and sites of inflammation in arthritic rats

Many monoclonal antibodies (mAbs) and other protein drugs have targets usually residing within tissues, making tissue concentrations of mAbs relevant to their pharmacologic effects. Therefore, knowledge of tissue distribution kinetics is important to better understand their pharmacokinetics and pharmacodynamics. The tissue distribution of mAbs is affected by many physiologic factors that may be altered in disease status. In the present work, we studied the tissue distribution kinetics of the fusion protein etanercept in inflamed joint tissues and examined the impact of inflammation on the tissue distribution of etanercept. Etanercept concentration profiles in plasma, blister fluid, and different tissues were obtained from healthy and collagen-induced arthritic (CIA) rats by use of a fluorescence quantification method via IRDye800CW labeling. Stepwise minimal and full physiologically based pharmacokinetic (PBPK) approaches were applied to characterize the distribution kinetics of etanercept in tissues in healthy and diseased animals. Etanercept exhibited modest tissue access (tissue/plasma area under the concentration curve [AUC] ratios 0.03-0.15 and estimated tissue reflection coefficients [σ] of 0.6-1.0), but with good penetration into arthritic paws (tissue/plasma AUC ratio 0.23 and σ 0.36). Etanercept exposure in the inflamed paws of CIA rats was approximately 3-fold higher than in normal paws taken from either CIA or healthy rats (tissue/plasma AUC ratios 0.23 versus 0.07 and σ 0.36 versus 0.71). The tissue distribution kinetics of etanercept in arthritic paws were well characterized with PBPK modeling approaches. Etanercept shows good penetration to arthritic paws in CIA rats. Our study indicates that inflammation produced increased tissue distribution of etanercept in CIA rats.

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.

Modeling pharmacokinetics/pharmacodynamics of abatacept and disease progression in collagen-induced arthritic rats: a population approach

The PK/PD of abatacept, a selective T cell co-stimulation modulator, was examined in rats with collagen-induced arthritis (CIA) using a nonlinear mixed effect modeling approach. Male Lewis rats underwent collagen induction to produce rheumatoid arthritis. Two single-dose groups received either 10 mg/kg intravenous (IV) or 20 mg/kg subcutaneous (SC) abatacept, and one multiple-dose group received one 20 mg/kg SC abatacept dose and four additional 10 mg/kg SC doses. Effects on disease progression (DIS) were measured by paw swelling. Plasma concentrations of abatacept were assayed by enzyme-linked immunosorbent assay. The PK/PD data were sequentially fitted using NONMEM VI. Goodness-of-fit was assessed by objective functions and visual inspection of diagnostic plots. The PK of abatacept followed a two-compartment model with linear elimination. For SC doses, short-term zero-order absorption was assumed with F = 59.2 %. The disease progression component was an indirect response model with a time-dependent change in paw edema production rate constant (k in ) that was inhibited by abatacept. Variation in the PK data could be explained by inter-individual variability in clearance and central compartment volume (V 1 ), while the large variability of the PD data may be the result of paw edema production (k in 0 ) and loss rate constant (k out ). Abatacept has modest effects on paw swelling in CIA rats. The PK/PD profiles were well described by the proposed model and allowed evaluation of inter-individual variability on drug- and DIS-related parameters.

Radiodensitometric and DXA analyses for the measurement of bone mineral density after systemic alendronate therapy

Precise techniques for the measurement of maxillary bone mineral density (BMD) are useful for the early diagnosis of systemic diseases. The aim of this study was to compare in vivo the efficacy of dual-energy x-ray absorptiometry (DXA) and radiographic densitometry for the measurement of BMD after systemic administration of sodium alendronate. Wistar rats were randomly allocated to a control group (n = 5), which received distilled water, and a sodium alendronate group (n = 8), which received two doses of chemically pure sodium alendronate (1 mg/kg) per week. After 8 weeks, the animals were euthanized, the tibias were removed, and the BMD of the proximal tibial metaphysis was analyzed radiographically and by DXA. The data were subjected to statistical analysis by the Kruskal-Wallis test at a significance level of 5%. Both of the techniques revealed that the alendronate-treated group had a significantly higher BMD (p < 0.05) than the control group after 8 weeks of treatment. Comparing the groups with and without alendronate therapy revealed increases of 14.9% and 29.6% in BMD, as detected radiographically and by DXA, respectively. In conclusion, both of the methods were able to detect an increase in BMD of the proximal tibial metaphysis after alendronate therapy.

Network-based approaches in drug discovery and early development

Identification of novel targets is a critical first step in the drug discovery and development process. Most diseases such as cancer, metabolic disorders, and neurological disorders are complex, and their pathogenesis involves multiple genetic and environmental factors. Finding a viable drug target-drug combination with high potential for yielding clinical success within the efficacy-toxicity spectrum is extremely challenging. Many examples are now available in which network-based approaches show potential for the identification of novel targets and for the repositioning of established targets. The objective of this article is to highlight network approaches for identifying novel targets with greater chances of gaining approved drugs with maximal efficacy and minimal side effects. Further enhancement of these approaches may emerge from effectively integrating computational systems biology with pharmacodynamic systems analysis. Coupling genomics, proteomics, and metabolomics databases with systems pharmacology modeling may aid in the development of disease-specific networks that can be further used to build confidence in target identification.

Moving from basic toward systems pharmacodynamic models

Building upon many classical foundations of pharmacology, a diverse array of mechanistic pharmacokinetic-pharmacodynamic (PK/PD) models have emerged based on mechanisms of drug action and primary rate-limiting or turnover processes in physiology. An array of basic models can be extended to handle various complexities including tolerance and can readily be employed as building blocks in assembling enhanced PK/PD or small systems models. Our corticosteroid models demonstrate these concepts as well as elements of horizontal and vertical integration of molecular to whole-body processes. The potential advantages and challenges in moving PK/PD toward systems models are described.

Pharmacokinetics, pharmacodynamics and toxicities of methotrexate in healthy and collagen-induced arthritic rats

Methotrexate (MTX) is an anchor drug used to treat rheumatoid arthritis (RA), but responsiveness is variable in effectiveness and toxicity. Methotrexate and its polyglutamate conjugates (MTXPG(n)) in red blood cells (RBC) have been associated with patient response. In the current study, 13 collagen-induced arthritic (CIA) rats and 12 healthy rats were given subcutaneous doses of either saline or 0.3 or 1.5 mg/kg per 2 days of MTX from day 21 to 43 post-induction. Blood samples were obtained at various times to measure MTX in plasma, and MTX and MTXPG(n) in RBC. Effects on disease progression were indicated by body weight and paw size. After multiple-doses, RBC MTX reached steady-state (82.4 nm) within 4 days. The MTXPG(2) and MTXPG(3) in RBC kept increasing until the end of the study, attaining 12.5 and 17.7 nm. Significant weight loss was observed after dosing with 1.5 mg/kg/2 days, whereas moderate effectiveness was observed after dosing with 0.3 mg/kg/2 days. A pharmacokinetic/pharmacodynamic/disease (PK/PD/DIS) model with indirect mechanisms and transduction components incorporating plasma MTX, RBC MTX and RBC MTXPG(n) concentrations, and paw size was developed using naïve data pooling and ADAPT 5. The PK/PD in CIA rats dosed at 0.3 mg/kg/2 days were captured well by our proposed model. Methotrexate showed modest (I(maxd) = 0.16) but sensitive (IC(50d) = 0.712 nm) effectiveness on paw edema. The higher dose produced toxicity. The proposed model offers improved understanding of the effects of methotrexate on rheumatoid arthritis.

Protective effect of curcumin on experimentally induced arthritic rats: detailed histopathological study of the joints and white blood cell count

Curcuma longa (turmeric) rhizomes contains curcumin, an active compound which possesses anti-inflammatory effects. Collagen-induced arthritis (CIA) is an accepted experimental animal model of rheumatoid arthritis. The present study aimed to observe the histological changes in the joints of experimental arthritic rats treated with curcumin. Twenty four male Sprague-Dawley (approximately 7 weeks-old) rats were randomly divided into four groups. Three groups were immunized with 150 µg collagen. All rats with established CIA, with arthritis scores exceeding 1, were orally treated with betamethasone (0.5 mg/ml/kg body weight), curcumin (110 mg/ml/kg body weight) or olive oil (1.0 ml/kg body weight) daily, for two weeks. One remaining group was kept as normal control. Treatment with 110 mg/ml/kg curcumin showed significant mean differences in the average white blood cell (WBC) count (p<0.05), cell infiltration, bone and cartilage erosion scores (p<0.05) compared to the olive oil treated group. Pannus formation scores showed that curcumin supplementation successfully suppressed the pannus formation process that occurred in the articular cartilage of the CIA joints. The mean difference for histological scores for the curcumin group was insignificant compared to the betamethasone treated group. It is concluded that supplementation of curcumin has protective effect on the histopathological and degenerative changes in the joints of CIA rats which was at par with betamethasone.

Pharmacokinetic/pharmacodynamic modeling in inflammation

Inflammation is an array of immune responses to infection and injury. It results from a complex immune cascade and is the basis of many chronic diseases such as arthritis, diabetes, and cancer. Numerous mathematical models have been developed to describe the disease progression and effects of anti-inflammatory drugs. This review illustrates the state of the art in modeling the effects of diverse drugs for treating inflammation, describes relevant biomarkers amenable to modeling, and summarizes major advantages and limitations of the published pharmacokinetic/ pharmacodynamic (PK/PD) models. Simple direct inhibitory models are often used to describe in vitro effects of anti-inflammatory drugs. Indirect response models are more mechanism based and have been widely applied to the turnover of symptoms and biomarkers. These, along with target-mediated and transduction models, have been successfully applied to capture the PK/PD of many anti-inflammatory drugs and describe disease progression of inflammation. Biologics have offered opportunities to address specific mechanisms of action, and evolve small systems models to quantitatively capture the underlying physiological processes. More advanced mechanistic models should allow evaluation of the roles of some key mediators in disease progression, assess drug interactions, and better translate drug properties from in vitro and animal data to patients.

Multi-response model for rheumatoid arthritis based on delay differential equations in collagen-induced arthritic mice treated with an anti-GM-CSF antibody

Collagen-induced arthritis (CIA) in mice is an experimental model for rheumatoid arthritis, a human chronic inflammatory destructive disease. The therapeutic effect of neutralizing the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) by an antibody was examined in the mouse disease in a view of deriving a pharmacokinetic/pharmacodynamic (PKPD) model. In CIA mice the development of disease is measured by a total arthritic score (TAS) and an ankylosis score (AKS). We present a multi-response PKPD model which describes the time course of the unperturbed and perturbed TAS and AKS. The antibody acts directly on GM-CSF by binding to it. Therefore, a compartment for the cytokine GM-CSF is an essential component of the mathematical model. This compartment drives the disease development in the PKPD model. Different known properties of arthritis development in the CIA model are included in the PKPD model. Firstly, the inflammation, driven by GM-CSF, dominates at the beginning of the disease and decreases after some time. Secondly, a destructive (ankylosis) part evolves in the TAS that is delayed in time. In order to model these two properties a delay differential equation was used. The PKPD model was applied to different experiments with doses ranging from 0.1 to 100 mg/kg. The influence of the drug was modeled by a non-linear approach. The final mathematical model consists of three differential equations representing the compartments for GM-CSF, inflammation and destruction. Our mathematical model described well all available dosing schedules by a simultaneous fit. We also present an equivalent and easy reformulation as ordinary differential equation which grants the use of standard PKPD software.

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 (I ( max ) = 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.

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the estrogen-like effect of ginsenoside Rb1 on neural 5-HT in ovariectomized mice

We sought to develop a mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) model to characterize the effects of ginsenoside Rb1 (Rb1) and estradiol (E(2)) on neural 5-hydroxytryptamine (5-HT) concentration in ovariectomized mice. PK data of Rb1 and E(2) were obtained in plasma and brain. Brain levels of 5-HT, tryptophan (TRP), 5-hydroxytryptophan (5-HTP), and 5-hydroxyindoleacetic acid (5-HIAA) were determined after a single intravenous injection of Rb1 (20mg/kg) and E(2) (0.2mg/kg) in ovariectomized mice. The activities of tryptophan hydroxylase (TPH), aromatic amino acid decarboxylase (AAAD), and monoamine oxidase (MAO) were also evaluated. Rb1 and E(2) elevated neural 5-HT levels via TPH activation and MAO inhibition, respectively. Effects were well described by the mechanism-based PK-PD model. The net effect of increased 5-HT induced by MAO inhibition is greater than TPH activation. The increased brain levels of 5-HT induced by Rb1 and E(2) were well described by the present PK-PD model, suggesting the use and further development of this mechanism-based model for the effects of ginsenoside on brain 5-HT levels.

Antiarthritis effect of a novel Bruton's tyrosine kinase (BTK) inhibitor in rat collagen-induced arthritis and mechanism-based pharmacokinetic/pharmacodynamic modeling: relationships between inhibition of BTK phosphorylation and efficacy

Bruton's tyrosine kinase (BTK) plays a critical role in the development, differentiation, and proliferation of B-lineage cells, making it an attractive target for the treatment of rheumatoid arthritis. The objective of this study was to evaluate the antiarthritis effect of GDC-0834 [R-N-(3-(6-(4-(1,4-dimethyl-3-oxopiperazin-2-yl)phenylamino)-4-methyl-5-oxo-4,5-dihydropyrazin-2-yl)-2-methylphenyl)-4,5,6,7-tetrahydrobenzo[b]thiophene-2-carboxamide], a potent and selective BTK inhibitor, and characterize the relationship between inhibition of BTK phosphorylation (pBTK) and efficacy. GDC-0834 inhibited BTK with an in vitro IC(50) of 5.9 and 6.4 nM in biochemical and cellular assays, respectively, and in vivo IC(50) of 1.1 and 5.6 μM in mouse and rat, respectively. Administration of GDC-0834 (30-100 mg/kg) in a rat collagen-induced arthritis (CIA) model resulted in a dose-dependent decrease of ankle swelling and reduction of morphologic pathology. An integrated disease progression pharmacokinetic/pharmacodynamic model where efficacy is driven by pBTK inhibition was fit to ankle-diameter time-course data. This model incorporated a transit model to characterize nondrug-related decreases in ankle swelling occurring at later stages of disease progression in CIA rats. The time course of ankle swelling in vehicle animals was described well by the base model. Simultaneous fitting of data from vehicle- and GDC-0834-treated groups showed that overall 73% inhibition of pBTK was needed to decrease the rate constant describing the ankle swelling increase (k(in)) by half. These findings suggest a high degree of pBTK inhibition is required for maximal activity of the pathway on inflammatory arthritis in rats.

Performance and robustness of the Monte Carlo importance sampling algorithm using parallelized S-ADAPT for basic and complex mechanistic models

The Monte Carlo Parametric Expectation Maximization (MC-PEM) algorithm can approximate the true log-likelihood as precisely as needed and is efficiently parallelizable. Our objectives were to evaluate an importance sampling version of the MC-PEM algorithm for mechanistic models and to qualify the default estimation settings in SADAPT-TRAN. We assessed bias, imprecision and robustness of this algorithm in S-ADAPT for mechanistic models with up to 45 simultaneously estimated structural parameters, 14 differential equations, and 10 dependent variables (one drug concentration and nine pharmacodynamic effects). Simpler models comprising 15 parameters were estimated using three of the ten dependent variables. We set initial estimates to 0.1 or 10 times the true value and evaluated 30 bootstrap replicates with frequent or sparse sampling. Datasets comprised three dose levels with 16 subjects each. For simultaneous estimation of the full model, the ratio of estimated to true values for structural model parameters (median [5-95% percentile] over 45 parameters) was 1.01 [0.94-1.13] for means and 0.99 [0.68-1.39] for between-subject variances for frequent sampling and 1.02 [0.81-1.47] for means and 1.02 [0.47-2.56] for variances for sparse sampling. Imprecision was ≤25% for 43 of 45 means for frequent sampling. Bias and imprecision was well comparable for the full and simpler models. Parallelized estimation was 23-fold (6.9-fold) faster using 48 threads (eight threads) relative to one thread. The MC-PEM algorithm was robust and provided unbiased and adequately precise means and variances during simultaneous estimation of complex, mechanistic models in a 45 dimensional parameter space with rich or sparse data using poor initial estimates.

Development of a new pre- and post-processing tool (SADAPT-TRAN) for nonlinear mixed-effects modeling in S-ADAPT

Mechanistic modeling greatly benefits from automated pre- and post-processing of model code and modeling results. While S-ADAPT provides many state-of-the-art parametric population estimation methods, its pre- and post-processing capabilities are limited. Our objective was to develop a fully automated, open-source pre- and post-processor for nonlinear mixed-effects modeling in S-ADAPT. We developed a new translator tool (SADAPT-TRAN) based on Perl scripts. These scripts (a) automatically translate the core model components into robust Fortran code, (b) perform extensive mutual error checks across all input files and the raw dataset, (c) extend the options of the Monte Carlo Parametric Expectation Maximization (MC-PEM) algorithm, and (d) improve the numerical robustness of the model code. The post-processing scripts automatically summarize the results of one or multiple models as tables and, by generating problem specific R scripts, provide an extended series of standard and covariate-stratified diagnostic plots. The SADAPT-TRAN package substantially improved the efficiency to specify, debug, and evaluate models and enhanced the flexibility of using the MC-PEM algorithm for parallelized estimation in S-ADAPT. The parameter variability model can take any combination of normally, log-normally, or logistically distributed parameters and the SADAPT-TRAN package can automatically generate the Fortran code required to specify between occasion variability. Extended estimation features are available to avoid local minima, estimate means with negligible variances, and estimate variances for fixed means. The SADAPT-TRAN package significantly facilitated model development in S-ADAPT, reduced model specification errors, and provided useful error messages for beginner and advanced users. This benefit was greatest for complex mechanistic models.

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.

Local metabolism of glucocorticoids and its role in rat adjuvant arthritis

11beta-Hydroxysteroid dehydrogenase 1 (11HSD1) regulates local glucocorticoid activity and plays an important role in various diseases. Here, we studied whether arthritis modulates 11HSD1, what is the role of pro-inflammatory cytokines in this process and whether altered local metabolism of glucocorticoids may contribute to the feedback regulation of inflammation. Adjuvant arthritis increased synovial 11HSD1 mRNA and 11-reductase activity but treatments with tumor necrosis factor alpha (TNF-alpha) and interleukin 1beta (IL-1beta) antagonists etanercept and anakinra reduced 11HSD1 upregulation. Treatment with carbenoxolone, an 11HSD inhibitor, increased expression of TNF-alpha, cyclooxygenase 2, and osteopontin mRNA without any changes in the plasma levels of corticosterone. Similar changes were observed when arthritic rats were treated with RU486, an antagonist of GR. This study suggests that arthritis upregulates synovial 11HSD1, this upregulation is controlled by TNF-alpha and IL-1beta and that the increased supply of local corticosterone might contribute to feedback regulation of inflammation.

Therapeutic options for rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, systemic inflammatory disorder primarily targeting the synovium. Unchecked disease activity is associated with significant morbidity and an increased mortality. Recent advances in the understanding of the pathogenesis of RA and the capability of biologically engineered treatments for RA have expanded the armamentarium of antirheumatic agents.

METHODS

A systematic literature review was conducted through PubMed.

RESULTS/CONCLUSIONS

At present, a common strategy for the treatment of RA uses methotrexate either as monotherapy or in combination with a variety of conventional and/or biologic disease-modifying antirheumatic drugs (DMARDs), with the goal of inducing remission of active disease. The choice of which agent(s) to use is based upon patient-specific criteria (activity of disease, comorbidities, patient preferences, costs etc.). Emerging therapies that target specific cytokines and growth factors in the inflammatory cascade of RA offer a potent new means of modifying disease activity, but many questions regarding their use remain unanswered.

Scaling pharmacodynamics from in vitro and preclinical animal studies to humans

An important feature of mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) models is the identification of drug- and system-specific factors that determine the intensity and time-course of pharmacological effects. This provides an opportunity to integrate information obtained from in vitro bioassays and preclinical pharmacological studies in animals to anticipate the clinical and adverse responses to drugs in humans. The fact that contemporary PK/PD modeling continues to evolve and seeks to emulate systems level properties should provide enhanced capabilities to scale-up pharmacodynamic data. Critical steps in drug discovery and development, such as lead compound and first in human dose selection, may become more efficient with the implementation and further refinement of translational PK/PD modeling. In this review, we highlight fundamental principles in pharmacodynamics and the basic expectations for in vitro bioassays and traditional allometric scaling in PK/PD modeling. Discussion of PK/PD modeling efforts for recombinant human erythropoietin is also included as a case study showing the potential for advanced systems analysis to facilitate extrapolations and improve understanding of inter-species differences in drug responses.