{
  "abstract": "Background Chimeric antigen receptor (CAR)-T cell therapy represents an innovative and potentially revolutionary modality in cancer treatment. Despite their great success in treating blood cancers, CAR-T therapies exhibit significantly lower effectiveness in treating solid tumors. Moreover, the preclinical-to-clinical translation of CAR-T therapies targeting solid tumors is still a challenging task because of their unique “live cell” nature and the substantial variability in patients’ pathophysiology.Methods We have developed a multiscale quantitative systems pharmacology (QSP) model to facilitate the clinical translation of CAR-T therapies in solid tumors. Our mechanistic modeling framework integrates the essential biological features that impact CAR-T cell fate and antitumor cytotoxicity, from cell-level CAR-antigen interaction and activation, to in vivo CAR-T biodistribution, proliferation and phenotype transition, and finally to clinical-level patient tumor heterogeneity and response variability. This modeling framework has been calibrated and validated by multimodal experimental data including published preclinical and clinical data of various CAR-T products and original preclinical data of a novel claudin18.2-targeted CAR-T product LB1908.Results We demonstrated the general utility of this framework in facilitating clinical translation and characterizing the paired cellular kinetics-cytotoxicity response of different antigen-targeting solid tumor CAR-T cell therapies. As an example, we generated model-based virtual patients and prospectively simulated the response to claudin18.2-targeted CAR-T therapies under different dosing strategies, including step-fractionated dosing and convenient flat dose-based regimens, to inform future clinical trial implementation.Conclusions Our translational QSP platform offers an innovative pathway to integrate multiscale knowledge and inform clinical decision-making of novel solid tumor-targeting CAR-T therapies.",
  "authors": [
    {
      "affiliations": [
        "School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Siyuan Yang"
    },
    {
      "affiliations": [
        "Department of Clinical Pharmacology, Legend Biotech, Nanjing, Jiangsu, China"
      ],
      "name": "Wenjie Wang"
    },
    {
      "affiliations": [
        "School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Qi Rao"
    },
    {
      "affiliations": [
        "School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Yiyang Xu"
    },
    {
      "affiliations": [
        "School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Sujie Zhang"
    },
    {
      "affiliations": [
        "School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Yuchen Qu"
    },
    {
      "affiliations": [
        "Department of Discovery Research, Legend Biotech, Nanjing, Jiangsu, China"
      ],
      "name": "Qiuchuan Zhuang"
    },
    {
      "affiliations": [
        "Department of Discovery Research, Legend Biotech, Nanjing, Jiangsu, China"
      ],
      "name": "Jie Mao"
    },
    {
      "affiliations": [
        "Department of Discovery Research, Legend Biotech, Nanjing, Jiangsu, China"
      ],
      "name": "Laura Sun"
    },
    {
      "affiliations": [
        "Early-Stage Drug Development Department, Legend Biotech USA Inc, Piscataway Township, New Jersey, USA"
      ],
      "name": "Dong Geng"
    },
    {
      "affiliations": [
        "Department of Clinical Pharmacology, Legend Biotech, Nanjing, Jiangsu, China"
      ],
      "name": "Da Xu"
    },
    {
      "affiliations": [
        "School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, China",
        "Department of Oncology, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Chen Zhao"
    }
  ],
  "title": "Mechanistic data-informed multiscale quantitative systems pharmacology modeling framework enables the clinical translation and efficacy assessment of CAR-T therapy in solid tumors",
  "uid": "55ff551c-c043-5c14-bca9-94f0389fad58"
}