Cell Population Dynamics Informed by Cell-Cycle Regulation: A Deterministic Modeling Toolkit.

Cell populations grow, shrink, and reshuffle their composition as individual cells divide, arrest, and die. Because cell division is paced by progression through the cell cycle, cell-cycle control is the fundamental axis linking intracellular regulation to population-level dynamics. Quantitatively capturing how cell-cycle regulation affects population dynamics is thus central to understanding tissue homeostasis, tumor expansion, immune responses, and the performance of cell-based bioprocesses-from tissue engineering and regenerative applications to the manufacturing of vaccines and recombinant therapeutics. In this view, a broad spectrum of mathematical models has been proposed to describe cell population dynamics, ranging from phenomenological growth laws that treat net proliferation as a black box to structured descriptions that resolve single-cell heterogeneity and link population change to cell-cycle progression. In this review, we survey deterministic frameworks for modeling cell-cycle-informed population dynamics, highlighting how modeling choices map onto accessible experimental readouts and biomedical and biotechnological questions. In doing so, we aim to provide a theoretical roadmap for readers new to the field who seek to translate intracellular cell-cycle regulation into empirically grounded population-level models. We organize models along 2 conceptual dimensions: the representation of cell-to-cell heterogeneity through increasing levels of population structure and the level of mechanistic specification of cell division through cell-cycle regulation. In particular, we discuss practical approaches to couple cell-cycle regulation to population-level dynamics-from coarse-grained to explicit multiscale couplings-and how external perturbations enter such couplings. We conclude by outlining open challenges toward cell-cycle-aware population models that match mechanistic resolution with experimental identifiability.