Nelson, Perelson, 1995

Model Status

This CellML model has been built from the differential expressions in Nelson and Perelson's 1995 paper for the initial model without DIV interference (equations 1-10). This file is known to run in OpenCell and COR, and uses the parameters values in Tables 1, 2, and 3 of the paper. One of the units (for the variable theta) has been changed from micro_L (in the paper), to per_micro_L, to be dimensionally consistent. Parameters in years are represented in day equivalents. The CellML model simulation will replicate the graph traces in figure 2 of the paper. Note that in the paper, some figures are scaled logarithmically.

Model Structure

ABSTRACT: The administration of a genetically engineered defective interfering virus (DIV) that interferes with HIV-1 replication has been proposed as a therapy for HIV-1 infection and AIDS. The proposed interfering virus, which is designed to superinfect HIV-1 infected cells, carries ribozymes that cleave conserved regions in HIV-1 RNA that code for the viral envelope protein. Thus DIV infection of HIV-1 infected cells should reduce or eliminate viral production by these cells. The success of this therapeutic strategy will depend both on the intercellular interaction of DIV and HIV-1, and on the overall dynamics of virus and T cells in the body. To study these dynamical issues, we have constructed a mathematical model of the interaction of HIV-1, DIV, and CD4+ cells in vivo. The results of both mathematical analysis and numerical simulation indicate that survival of the engineered DIV purely on a peripheral blood HIV-1 infection is unlikely. However, analytical results indicate that DIV might well survive on HIV-1 infected CD4+ cells in lymphoid organs such as lymph nodes and spleen, or on other HIV-1 infected cells in these organs.

Schematic illustration of the main features of the model.

The original paper reference is cited below:

Modeling defective interfering virus therapy for AIDS: conditions for DIV survival, Nelson G, Perelson A, 1995, Mathematical Biosciences, 125, 127-153. PubMed ID: 7881191