A Systematic Review of the Efforts and Hindrances of Modeling and Simulation of CAR T-cell Therapy

Chimeric antigen receptor (CAR) T-cell therapy is an immunotherapy that has recently become highly instrumental in the fight against life-threatening diseases. A variety of modeling and computational simulation efforts have addressed different aspects CAR therapy, including activation, T- malignant cell population dynamics, therapeutic cost-effectiveness strategies, patient survival. In this article, we present a systematic review those efforts, mathematical, statistical, stochastic models employing wide range algorithms, from differential equations to machine learning. To best our knowledge, first all such studying therapy. review, provide detailed summary strengths, limitations, methodology, data used, gap currently published models. This information may help designing building better for enhanced prediction assessment benefit-risk balance associated with novel therapies, as well need