A key advantage of Merrimack’s validated Biochemical Network Models is the ability to rapidly consider all of the potential targets in the pathway in silico, and inexpensively model and compare the variety of therapeutic strategies that can be applied to those targets.

As an example, when considering targeting a receptor or receptor system, several therapeutic strategies are possible, and many of them have been proven in the clinic. One simple strategy is a ligand sink, which binds and/or inactivates free ligand. Another strategy might employ receptor antagonists that bind to the receptor and physically prevent ligand from binding. More recent strategies include the use of antibodies to modulate receptor internalization or prevent receptor dimerization. An alternative strategy could focus on the intracellular tyrosine kinase domain of the receptor, inhibiting activation with a highly specific small molecule. Rarely are these approaches equally potent and, surprisingly, the best approach varies dramatically from network to network.

Increasingly, investigators are interested in another alternative approach – combining more than one targeted therapeutic. Our models provide a unique and elegant tool to evaluate the effect of combination therapies. We can rapidly identify potential synergistic (or antagonistic) effects of combining therapeutics that target multiple “nodes” in the pathway or even two separate pathways.

The expression of network proteins varies among different organ and tissue types and between diseased and normal tissue. This variation, as well as genetic variation among patients, is also considered by our models. As a result, we can easily consider another important drug-development issue: target-specific toxicity in non-target tissues, e.g. the heart and liver, by adapting the model with expression data on network components in these tissues.

[ back to top ]