Feedback System Control (FSC) for HSV (Xianting Ding)
In human disease, many molecular assemblies and pathways within the cell’s signaling and regulatory network function aberrantly, resulting in a complex disease state. Therefore, the most effective way to treat such complex diseases is to use multiple approaches. For example, treating HIV infection and AIDS with a combination of multiple drugs is more effective than single drug therapy. However, determining the optimal combination of several drugs at specific dosages to reach an objective endpoint result (e.g., high efficacy and low toxicity) is a major challenge. The combination of N drugs at M dosage levels results in MN possible combinations, a testing pool size that makes complete screening cost prohibitive and infeasible. Furthermore, many high efficacy drug combinations will also exhibit high toxicity, making these inappropriate for clinical use. We addressed the challenge of identifying high efficacy/low toxicity drug combinations by introducing a feedback system control (FSC) method. With this method, we identified the optimal drug combination that inhibits all HSV-1 infection in vitro and attain limited dosage of the highly toxic drug Ribavirin. This study demonstrates this FSC platform is capable of rapidly screening a large search space using multiple parameters to identify optimal drug combinations and doses for the treatment of a viral infection.
The FSC platform technology consists of four modules. The first module is the input stimulations, namely, the drug combinations. The second module is the bio-complex system of interest, which in this case is the virus and host cell. The third module is the objective function readout, which is the goal for optimization, such as efficacy, toxicity, drug resistance, etc. The fourth module is the search algorithm, which provides the next set of stimulant dosages for directing the bio-complex system toward the desired phenotype (See figure above). For the FSC approach, we started with a set of drugs at arbitrarily chosen concentrations to stimulate the cells infected with HSV-1. The percentage of the host cells that become infected is used as the endpoint readout of the objective function in the third FSC module, and will most likely not be satisfactory in the first permutation. The fourth module of the FSC will use a search algorithm to determine a selection of drug concentrations with potentially better performance that will be used in the next iteration of the experiment and be fed back into the bio-complex system. Iterations of this feedback will continue until the optimal drug combination is reached (i.e., when the system objective function becomes satisfactory).