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Principles of feedback control have been shown to naturally arise inbiological systems and successfully applied to build synthetic circuits. Inthis work we consider Biochemical Reaction Networks (CRNs) as a paradigm formodelling biochemical systems and provide the first implementation of aderivative component in CRNs. That is, given an input signal represented by theconcentration level of some species, we build a CRN that produces as output theconcentration of two species whose difference is the derivative of the inputsignal. By relying on this component, we present a CRN implementation of afeedback control loop with Proportional-Integral-Derivative (PID) controllerand apply the resulting control architecture to regulate the protein expressionin a microRNA regulated gene expression model.

PID Control of Biochemical Reaction Networks