Methods for modeling hepatic inflammation

Abstract

Provided herein are in silico methods of modeling hepatic inflammation, fibrosis/cirrhosis, and cancer. The models are computer-implemented agent-based models and are useful in determining patient prognoses in hepatic conditions, including viral infections, damage, inflammation, and cancer. The modeling system also is useful in modeling the effects of active agents on normal hepatic tissue or hepatic tissue perturbed by inflammation, infection, damage, fibrosis/cirrhosis, and cancer.

We claim: 
     
         1 . A system for modeling progression of at least one hepatic condition, comprising:
 on at least one computer with a computer readable medium having programming instructions stored thereon, which, when executed by a processor of the at least one computer, cause the processor to:
 receive or define at least one of the following: agent data, global data, initialization process data, or any combination thereof, the agent data comprising at least one of the following: definition data, behavior data, class data, internal state data, function data, link data, space data, or any combination thereof; 
 model the at least one hepatic condition associated with at least one agent based at least in part upon at least a portion of the agent data corresponding to the at least one agent; and 
 generate modeling output data representative of at least one of the following: hepatic tissue structure, hepatic inflammation state, inflammation-induced hepatic damage, hepatic viral load, virally-induced hepatic damage, hepatic tumor presence, hepatic tumor size, hepatic cancer presence, hepatic metastasis size, hepatic metastasis extent, hepatic fibrosis state, or any combination thereof. 
   
     
     
         2 . The system of  claim 1 , wherein the at least one hepatic condition is modeled multiple times to generate a stochastic range of multiple different modeling output data. 
     
     
         3 . The system of  claim 2 , wherein the agent data, global data, initialization process data, or any combination thereof is altered and the at least one hepatic condition is modeled multiple times to generate a stochastic range of multiple different modeling output data. 
     
     
         4 . The system of  claim 1 , wherein the output data comprises a simulation of liver tissue on a grid for a plurality of time points. 
     
     
         5 . The system of  claim 4 , wherein the output data comprises a plurality of image representations of the grid for the plurality of time points. 
     
     
         6 . The system of  claim 5 , wherein the at least one hepatic condition is modeled multiple times to generate a stochastic range of multiple different modeling output data comprising a plurality of image representations of the grid for the plurality of time points, and the image representations of the multiple simulation outputs are stored on a computer readable medium. 
     
     
         7 . The system of  claim 6 , wherein a sample image of a liver biopsy of a patient is compared to the image representations on the computer-readable media and determining a best match with the sample image; and producing an output that includes a patient prognosis based upon output data produced by the modeling of the at least one hepatic condition that generated the best match image representation. 
     
     
         8 . The system of  claim 6 , further comprising agent data, global data, initialization process data, or any combination thereof and modeling the at least one hepatic condition multiple times to generate a stochastic range of multiple different modeling output data comprising a plurality of image representations of the grid for the plurality of time points, and storing the image representations of the multiple simulation outputs on a computer readable medium. 
     
     
         9 . The system of  claim 8 , further comprising a sample image of a liver biopsy of a patient with the image representations of the multiple simulation outputs on the computer readable medium and determining a best match with the sample image; and producing an output that includes a patient prognosis based upon output data produced by the modeling of the at least one hepatic condition that generated the best match image representation. 
     
     
         10 . The system of  claim 1 , wherein the receiving or defining of at least one of agent data, global data, initialization process data, or any combination thereof comprises inputting test data obtained from a patient and generating modeling output data as a representation of a prognosis for the patient. 
     
     
         11 . The system of  claim 1 , wherein the receiving or defining of at least one of agent data, global data, initialization process data, or any combination thereof comprises data representative of the effect of an active agent; and generating the output data as a representation of the effect of the active agent on hepatic inflammation, fibrosis and cancer. 
     
     
         12 . The system of  claim 1 , in which the agent data, global data, initialization process data, or any combination thereof comprises agent data, global data, initialization process data, or any combination thereof representing hepatocytes, macrophages, stellate cells, cancer cells, TNF-α, TGF-β1, and HMGB1. 
     
     
         13 . The system of  claim 1 , in which the agent data, global data, initialization process data, or any combination thereof comprises agent data, global data, initialization process data, or any combination thereof representing one or both of a hepatic lobule and a portal triad. 
     
     
         14 . The system of  claim 1 , in which the agent data, global data, initialization process data, or any combination thereof comprises agent data, global data, initialization process data, or any combination thereof representing one or more of septa, myofibroblasts and collagen. 
     
     
         15 . The system of  claim 1 , in which the agent data, global data, initialization process data, or any combination thereof comprises agent data, global data, initialization process data, or any combination thereof representing hepatic septa, myofibroblasts and collagen. 
     
     
         16 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof is data obtained from a patient. 
     
     
         17 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof includes data representing the effect of an active agent on one or more of the elements. 
     
     
         18 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof is data representing simulating surgical removal of a simulated tumor with attendant tissue damage that stimulates further inflammation. 
     
     
         19 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof is data representing simulating a chemotherapeutic cytotoxic drug, such that the simulated death of both tumor cells and hepatocytes occurs. 
     
     
         20 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof is data representing simulating an antiviral drug, such that both viral killing and inflammatory damage to the simulated liver tissue are simulated. 
     
     
         21 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof is data representing simulating an anti-inflammatory drug, such that reduction in inflammation and subsequent inflammatory damage to the simulated liver tissue, immunosuppresion and virus growth-stimulating effects, are simulated. 
     
     
         22 . The system of  claim 1 , wherein the agent data, global data, initialization process data, or any combination thereof is data representing simulating an anti-fibrotic drug, such that both reduction in fibrosis and subsequent inflammatory damage to the simulated liver tissue, as well as suppression of tissue healing, are simulated. 
     
     
         23 . A computer-implemented method of modeling progression of at least one hepatic condition, comprising, receiving or defining at least one of the agent data, global data, initialization process data, or any combination thereof; modeling the at least one hepatic condition; and generating output data from the modeling step representative of at least one of the following: hepatic tissue structure, hepatic inflammation state, inflammation-induced hepatic damage, hepatic viral load, virally-induced hepatic damage, hepatic tumor presence, hepatic tumor size, hepatic cancer presence, hepatic metastasis size, hepatic metastasis extent, hepatic fibrosis state, or any combination thereof.