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Quantitative Dynamic Models of Arthritis Progression in the Rat

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Abstract

Purpose

This comparison employs mathematical disease progression models to identify a rat model of arthritis with the least inter-animal variability and features lending to better study designs.

Methods

Arthritis was induced with either collagen (CIA) or mycobacterium (AIA) in either Lewis or Dark Agouti (DA) rats. Disease progression was monitored by paw edema and body weight. Models with production, loss, and feedback components were constructed and population analysis using NONMEM software was employed to identify inter-animal variability in the various disease progression parameters.

Results

Onset time was the only parameter different within all four groups (DA–AIA 11.5 days, DA–CIA 16.5 days, Lewis–AIA 11.9 days, Lewis–CIA 13.9 days). The loss-of-edema rate constant was 20% slower in DA (0.362 h−1) than Lewis (0.466 h−1) rats. Most models exhibited peak paw edema 20 days post-induction. Edema in CIA returned to 150% of the initial value after the disease peaked. DA rats displayed more severe overall responses.

Conclusions

No statistical differences between groups were observed for inter-animal variation in disease onset, progression and severity parameters. Onset time varies and should be noted in the design of future studies. DA rats may offer a more dynamic range of edema response than Lewis rats.

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Abbreviations

AIA:

adjuvant-induced arthritis

CIA:

collagen-induced arthritis

CV:

coefficient of variation

FOCE:

first order conditional estimation

MVOF:

minimum value of the objective function

PD:

pharmacodynamics

PK:

pharmacokinetics

RA:

rheumatoid arthritis

k out :

loss of edema rate constant

k in :

production of edema rate constant

R deg :

loss of production of edema rate constant

t Onset :

disease onset time

P :

parameter

θ :

population mean of P

η :

measure of individual’s deviation from θ

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, SUNY, 565 Hochstetter Hall, Buffalo, New York, USA

    Justin C. Earp, Debra C. DuBois, Richard R. Almon & William J. Jusko

  2. Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York, 14260, USA

    Debra C. DuBois, Richard R. Almon & William J. Jusko

Authors
  1. Justin C. Earp
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  2. Debra C. DuBois
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  4. William J. Jusko
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Correspondence to William J. Jusko.

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Earp, J.C., DuBois, D.C., Almon, R.R. et al. Quantitative Dynamic Models of Arthritis Progression in the Rat. Pharm Res 26, 196–203 (2009). https://doi.org/10.1007/s11095-008-9711-3

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