Generating QSP-based Digital Twins for TCR-engineered T cell Therapies

There remain challenges in understanding and predicting the kinetics of adoptive T cell therapy, particularly for TCR-engineered T cells in solid tumor indications. In this work, we develop a novel quantitative systems pharmacology (QSP) model that describes the kinetics of endogenous and TCR-engineered T cells across various memory subsets post infusion. Following known biology, these T cells undergo diverse processes including proliferation, trafficking differentiation and apoptosis across physiologically relevant compartments. Using the QSP model, we created digital twins that mirror the individual patient cellular kinetics reported in a clinical trial of TCR-engineered T cells targeting E7 in patients with HPV-associated epithelial cancers. Our in silico clinical trials and analysis suggest that Tscm cells can be deciding factors for both expansion and persistence and we predict the impact of altering dose composition with our digital twins. This investigation offers valuable insights into the essential role of T scm biology on T cell kinetics and provides a quantitative framework to evaluate cellular kinetics for the future development and clinical application of TCR-engineered T cell therapies.