This study is concerned with enhanced modelbased control of a continuous direct compression pharmaceutical process. The control-loop performance is assessed in silico and results obtained will be incorporated into the pilot plant facility of the continuous direct compaction process at the NSF Engineering Research Center of Rutgers University. The models used in the study are obtained via system identification from a combination of first principlesbased dynamic models, experimental data, and/or literature data. The main objective of the paper is to formulate an effective control strategy at the basic/regulatory level, for the integrated continuous operation of the direct compaction process, and to maintain the process at the desired set-points, taking into account the multivariable process interactions and disturbances. Simulations show that that at very mild interactions, the proposed regulatory control strategy is able to maintain set-points at desired values. However, at moderate to high process interactions, oscillatory behavior of controlled variables is seen. The presence of disturbances also resulted in poor control-loop performance. Results also lend credence to the development of advanced control strategies in such scenarios and will be addressed in future work. Optimal control tuning parameters are obtained from a derivative-free optimization algorithm.