This brief proposes a novel data-driven feedforward control mechanism to regulate micro/nanoscale systems subject to insufficient measurements. The theoretical framework integrates data-driven planning and formulates a feedforward controller, which is successfully applied to an electroporation mediated gene delivery problem in gene therapy. Nonlinear dynamics modeling and analysis of the biological cell electroporation process, especially hysteresis and nonlinear jump phenomenon, are discussed. Simulation results demonstrate that the proposed control outperforms existing methods in the open literature.