Batch and continuous reactors both enable exploration of a chemical design space. The former rely on transient experiments, thus experiencing a wide variety of operating conditions over time, whereas the latter are usually operated at steady state and are representative of only one set of conditions. Operating a continuous reactor under dynamic conditions allows more efficient exploration of the underlying reaction space for extraction of kinetics and optimization of performance. We present a methodology to efficiently explore a design space using a tubular flow reactor installed on an automatic platform (equipped with FTIR and HPLC analysis) operated in a transient regime using sinusoidal variations of the parameters. This data-dense method proves to be quicker with respect to steady-state operations because of the larger amount of information collected during a single experiment. A computational analysis provides a simple criterion for the design of dynamic experiments in order for them to be representative of steady-state conditions. The methodology is applied experimentally to the synthesis of a pharmaceutical intermediate via an esterification reaction in the presence of base. In the experiments, up to three parameters (reaction time, base equivalents, and temperature) are changed simultaneously. Proper design of the trajectories in the design space allows verification of the consistency of the results by exploiting the self-crossings within each trajectory and crossings between different trajectories. The experiments further validate the developed criterion for dynamic operations.