Simulation-Based Optimization Of Car T-Cell Therapy Supply Chain And Manufacturing

CAR-T cell therapy presents significant logistical and cost challenges due to its complex manufacturing and supply chain requirements. This study applies a simheuristic approach that integrates metaheuristic optimization with stochastic simulation to address these uncertainties. The proposed framework optimizes transportation, manufacturing scheduling, and patient prioritization, ensuring cost efficiency while maintaining timely delivery. Experimental results demonstrate that Simulated Annealing (SA) outperforms traditional scheduling heuristics, particularly as problem complexity increases. This research highlights the potential of simulation-driven optimization for improving decision-making in personalized medicine logistics.