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Clin Exp Immunol. 2010 Aug;161(2):250-67. doi: 10.1111/j.1365-2249.2010.04166.x. Epub 2010 May 18.

The Type 1 Diabetes PhysioLab Platform: a validated physiologically based mathematical model of pathogenesis in the non-obese diabetic mouse.

Author information

1
Entelos Inc., Foster City, CA 94404, USA. shoda@entelos.com

Abstract

Type 1 diabetes is an autoimmune disease whose clinical onset signifies a lifelong requirement for insulin therapy and increased risk of medical complications. To increase the efficiency and confidence with which drug candidates advance to human type 1 diabetes clinical trials, we have generated and validated a mathematical model of type 1 diabetes pathophysiology in a well-characterized animal model of spontaneous type 1 diabetes, the non-obese diabetic (NOD) mouse. The model is based on an extensive survey of the public literature and input from an independent scientific advisory board. It reproduces key disease features including activation and expansion of autoreactive lymphocytes in the pancreatic lymph nodes (PLNs), islet infiltration and beta cell loss leading to hyperglycaemia. The model uses ordinary differential and algebraic equations to represent the pancreas and PLN as well as dynamic interactions of multiple cell types (e.g. dendritic cells, macrophages, CD4+ T lymphocytes, CD8+ T lymphocytes, regulatory T cells, beta cells). The simulated features of untreated pathogenesis and disease outcomes for multiple interventions compare favourably with published experimental data. Thus, a mathematical model reproducing type 1 diabetes pathophysiology in the NOD mouse, validated based on accurate reproduction of results from multiple published interventions, is available for in silico hypothesis testing. Predictive biosimulation research evaluating therapeutic strategies and underlying biological mechanisms is intended to deprioritize hypotheses that impact disease outcome weakly and focus experimental research on hypotheses likely to provide insight into the disease and its treatment.

PMID:
20491795
PMCID:
PMC2909407
DOI:
10.1111/j.1365-2249.2010.04166.x
[Indexed for MEDLINE]
Free PMC Article
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