Advances in bioprocess engineering depends ultimately on the level of understanding and control of the physiological state of the cell population. Process efficiency is strongly influenced by changes in the cellular state which should be monitored, interpreted, and, if possible, properly manipulated. In most control systems this function is not explicitly considered, which hampers process development and optimization. Conventional control logic is based on direct mapping of the growth environment into process efficiency, thereby bypassing the cell state as an intermediate control objective. Today, this limitation is well realized, and explicit monitoring and control of cellular physiology are considered to be among the most challenging tasks of modern bioprocess engineering. We present here a generic methodology for the design of systems capable of performing these advanced monitoring and control functions. The term "physiological state" is quantified by a vector composed of several process variables that convey significant information about cellular state. These variables can be selected among different classes, including specific metabolic rates, metabolic rate ratios, degees of limitation, and others. The real-time monitoring of many of these is possible using commercial sensors. The definition and calculation of representative sets of physiological state variables is demonstrated with examples from several fermenter cultures : recombinant Escherichia coli for phenylalanine production, bioluminescent E. coli (harboring lux genes driven by a heat shock protein promoter) for detection of environmental pollutants, plant cell culture of Perilla frutescens for anthocyanin production, and perfusion cultures of recombinant mammalian cells (NSO and CHO) for therapeutic protein production. If the physiological state vector is on-line calculated, the fermentation process can be described by its trajectory in a space defined by the vector components. Then, the goal of the control system is to maintain the physiological state of the cell as close as possible to the trajectory, providing maximum efficiency. A control structure meant to perform this function is proposed, along with the mechanism for its design. In contrast to conventional systems which work in a closed loop in respect to the cell environment, this scheme operates in a closed loop in respect to the cell state. The discussed control concept has been successfully applied to the recombinant phenylalanine production, resulting in physiologically consistent operation, total computer control, and high process efficiency. Initial results from the application of the method to perfusion mammalian cell cultures are also presented.