This article analyzes and assumes the construction of laboratory platforms in response to the specific requirements for intelligent management of pharmaceutical experiments and the experimental teaching requirements of pharmaceutical concepts. Then, the influencing factors and main constraints in the course scheduling problem are systematically discussed, a mathematical model of the course scheduling process is provided, and an overall framework for the solution method is also proposed. On this basis, the improvements are proposed to the algorithm, which mixed simulated annealing algorithm to improve the accuracy and convergence speed of the algorithm. Finally, the improved adaptive genetic algorithm is applied to the intelligent course scheduling system in universities, and the usability of the system is tested through empirical analysis. The comparison and analysis results between the improved genetic algorithm and the classical genetic algorithm indicate that our strategy can achieve good global optimal solution search ability, which provides better service for teaching management system of pharmaceutical laboratories.