The reproducibility and optimal operation of mammalian cell cultures depends on various environmental and physiological factors. High variability in the mammalian cell metabolism towards the growth medium, biological oscillations, metabolism shifts in case of thermal, mechanical or chemical shocks makes these processes worse in control prospective as identification of these phenomena itself offers a great challenge. In this work, those predominant physiological phenomena that determine the intrinsic state of mammalian cells are modeled in an effort to unify them to estimate the onset of metabolism shift from the available on-line and off-line measurements which may be noisy. Multi-level modeling will be adapted to characterize the intra-cellular and inter-cellular processes in mammalian cell cultures. A hybrid (structured-unstructured) single cell model is developed to quantify cell growth, death, lysis, nutrient uptake, metabolite and protein production and their dependency on various environmental and physiological factors. Population balance model is combined with this hybrid model to characterize various phases in the cell cycle and in turn account for the heterogeneity in the cell populations. This model is validated against the experimental data obtained in the culture of genetically modified Chinese hamster ovary (CHO) cells producing recombinant tissue type plasminogen activator (r-tPA). Experimental design based on parametric sensitivity is performed to capture accurate information on cell metabolism dynamics.