Table 1.

Description of model parameters to describe resistance dynamics. Descriptions of the parameters either from measured data (data), fit of the model to the N(t) (fit from N(t)) or ϕ(t) (fit from ϕ(t)), the model assumptions (fixed), or predicted from the parameter estimation from the fitted model (predicted). We fit for six free parameters in the calibration scheme, as listed by the first four rows of the table.

Parameter	Description	Units	Determination
N(t)	Total cell number over time, and predicted by the model	Number of cells	Directly measured measured directly
ϕ(t)	Phenotypic composition: the fraction of sensitive cells over time, estimated from scRNA-seq data and predicted by the model	Cell fraction	Estimated from classifier output from scRNA-seq data
rS, rR	Growth rate of sensitive and resistant cell subpopulations	h−1	Fit from N(t) & ϕ(t) data
α	Drug-induced rate of transition from sensitive to resistant state	nM−1 hour−1	Fit from N(t) & ϕ(t) data
dS, dR	Death rate of sensitive and resistant dR < dS cell populations due to drug,	nM−1 hour−1	Fit from N(t) & ϕ(t) data
ϕ0	Initial proportion of sensitive cells	Number of cells	Fit from N(t) & ϕ(t) data
KN	Carrying capacity for the longitudinal treatment to experiment performed in a 96 well plate measure N(t)	Number of cells	Fit from N(t) untreated control
Kϕ	Carrying capacity of the scRNA-seq experiment t performed in a 10 cm dish to measure ϕ(t)	Number of cells	Fixed
k1	Scaling factor to non-dimensionalize concentration in nM of doxorubicin	nM−1	Fixed
k2	Estimated rate of decay of effect of doxorubicin after pulse-treatment	hour−1	Fixed