Our second ISL tracing paper has been published online as a JPET FastForward Article Tracing Multiscale Mechanisms of Drug Disposition in Normal and Diseased Livers.
I’ll repeat the brief blurb on my agent based modeling website.
This paper talks in relative detail about how hypothesis formulation and falsification (failed validation) can be done at a fine grain when only coarse grained validation data is available. Because our in silico liver (ISL) is an analog built in software, we can trace its internals. And because the internals of the analog were designed to map to the internal structure and dynamics of its referent (wet-lab liver perfusion experiments), traces of the ISL become detailed hypotheses about the internals of the liver. However, those detailed hypotheses are not falsifiable, except to the extent that they fail to reproduce the coarse validation data. Nothing can be done about that until we design wet-lab experiments to perform on real livers. In the meantime, though, we can alter the ISL mechanisms so that the coarse grained data matches that taken from wet-lab experiments under different conditions. In this case, we build 3 ISLs that generate the outflow profiles for drug and a sucrose marker for: 1) normal healthy livers, 2) alcohol damaged livers, and 3) carbon tetrachloride damaged livers. With the traces for each of the 3 ISLs, based upon the validated (i.e. not proven true, of course, but proven true enough) mechanisms of the ISL, we can formulate ‘proto-theories’ for the translation of an experimental liver from a healthy to a diseased (cirrhotic) state.
Note that the particulars of the ‘proto-theories’ suggested by these traces are not as sophisticated as those that might be generated by an expert hepatologist. In fact, these ‘proto-theories’ may even seem bizarre or patently false to such an expert (though I believe they don’t seem so to the experts). Indeed, as Box’s aphorism says,
… all models are wrong; the practical question is how wrong do they have to be to not be useful.
The point is not to build computer programs that attempt to compete with the hypothesis formulation of experts. This is not an AI project. The point is to build devices, with whatever tools are available including computers, that make the experts more efficient and effective. By formulating these ‘proto-theories’ about the translation of healthy livers to diseased livers (and vice versa), models like the ISLs provide a foil or sounding board to help sharpen the theories developed by the experts.