It is challenging to understand complex biomedical systems that include interacting feedback and feedforward loops. What is more, the biomedical control system is only partially revealed, and it can differ dramatically between different individuals. In this talk, I will share my vision of how an integration between Quantitative Systems Pharmacology and Machine learning could utilize the strength of each method and overcome their limitation, aid us to cope with the above mentioned challenges, better understand biomedical systems, and eventually lead to the design of optimized treatments.
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