CAR T cells are engineered to bind and destroy tumor cells by targeting overexpressed surface antigens. However, healthy cells expressing lower abundances of these antigens can also be lysed by CAR T cells. Various CAR T cell designs increase tumor cell elimination, whereas reducing damage to healthy cells. However, these efforts are costly and labor-intensive, constraining systematic exploration of potential hypotheses. We develop a protein abundance structured population dynamic model for CAR T cells (PASCAR), a framework that combines multiscale population dynamic models and multi-objective optimization approaches with data from cytometry and cytotoxicity assays to systematically explore the design space of constitutive and tunable CAR T cells. PASCAR can quantitatively describe in vitro and in vivo results for constitutive and inducible CAR T cells and can successfully predict experiments outside the training data. Our exploration of the CAR design space reveals that optimal CAR affinities in the intermediate range of dissociation constants effectively reduce healthy cell lysis, whereas maintaining high tumor cell-killing rates. Furthermore, our modeling offers guidance for optimizing CAR expressions in synthetic notch CAR T cells. PASCAR can be extended to other CAR immune cells.
Using a system of time-dynamical equations, we investigate how daily mobility indices, such as the homestay percentage above the pre-COVID normal ($$H\%$$ H % ; or H-forcing), and the vaccinated percentage ($$V_c\%$$ V c % ; or V-forcing) impact the net reproductive rate (R0) of COVID-19 in ten island nations as a prototype, and then, extending it to 124 countries worldwide. Our H- and V-forcing model of R0 can explain the new trends in 106 countries. The disease transmission can be controlled by forcing down $$R0(H,V_c) < 1$$ R 0 ( H , V c ) < 1 with an enforcement of continuous $$H > 40\%$$ H > 40 % in $$93\%$$ 93 % of countries with $$0\%$$ 0 % vaccinated plus recovered, $$V_p$$ V p . The required critical $$H\%$$ H % decreases with increasing $$V_p\%$$ V p % , dropping it down to $$20\%$$ 20 % with $$25\% V_p$$ 25 % V p , and further down to $$8\%$$ 8 % with $$50\% V_p$$ 50 % V p . However, the regulations on $$H\%$$ H % are context-dependent and country-specific. Our model gives insights into forecasting and controlling the disease’s transmission behaviour when the effectiveness of the vaccines is a concern due to new variants, and/or there are delays in vaccination rollout programs.
Engineered chimeric antigen receptor (CAR)-T cells are designed to bind to antigens overexpressed on the surface of tumor cells and induce tumor cell lysis. However, healthy cells can express these antigens at lower abundances and can get lysed by CAR-T cells. A wide variety of CAR-T cells have been designed that increase tumor cell elimination while decreasing destruction of healthy cells. However, given the cost and labor-intensive nature of such efforts, a systematic exploration of potential hypotheses becomes limited. To this end, we develop a framework (PASCAR) by combining multiscale population dynamic models and multi-objective optimization approaches with data obtained from published cytometry and cytotoxicity assays to systematically explore design space of constitutive and tunable CAR-T cells. We demonstrate PASCAR can quantitatively describe in vitro and in vivo results for constitutive and inducible CAR-T cells and can successfully predict experiments outside the training data. Our exploration of the CAR design space reveals that CAR affinities in an intermediate range of dissociation constants (KD) in constitutive and tunable CAR-T cells can dramatically decrease healthy cell lysis but sustain a high rate of tumor cell killing. In addition, our modeling provides guidance towards optimal tuning of CAR expressions in synNotch CAR T cells. The proposed framework can be extended for other CAR immune cells.
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