Date of Award


Degree Type


Degree Name

Master of Science in Biological and Environmental Sciences (MSBES)


Cell and Molecular Biology


Cell & Molecular Biology

First Advisor

Gongqin Sun


Protein kinase inhibitors have been an effective treatment for cancers driven by an identifiable predominant protein kinase that drives cancer development. Most cancers, however, are supported by multiple independent drivers and cannot be effectively treated by targeted therapies that inhibits only a single driver. Instead, a combination targeted therapy with multiple targeted drugs to block all drivers is required. Developing combination targeted therapies for such cancers requires identification of the individual drivers and pharmacological understanding of the complex interactions between the drugs and the cancer targets. The current pharmacological models, based on the Hill equation, only describe the interaction between a drug and a single target in a biological system. Thereby, any observed effect is ascribed to the interaction with one target only. In practice, such drugs often inhibit multiple kinase targets, both on and off-target, and the resulting inhibition will be a compound of the effectiveness against all affected targets. Yet when such drugs are used for cancer therapy, only the target-specific inhibition is likely responsible for efficacy, while the off-target inhibition is likely the cause of toxicity. This perspective article discusses a recently developed biphasic pharmacological model for characterizing such complex interactions, assessing the contribution of individual drug targets, and predicting synergistic drug combinations for multi-driver cancers. This approach can produce mechanism-based and synergistic drug combinations against multi-driver cancers.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License



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