A robust control algorithm which uses partial state feedback is designed for a class of biochemical processes in the presence of modeling uncertainties. To design the controller, the model uncertainty and the nonmeasurable state are combined into a new state variable. A sliding mode state observer is used to obtain on-line estimates of this new state. A practical stabilizer is obtained by combining the observer with an input-output linearizing controller. The practical convergence of the observer and the controller are proved. The performance of the sliding mode observer and the closed-loop behavior is illustrated through numerical simulations.