Modelling aging

The gradual accumulation of damage and dysregulation during the aging of living organisms is readily quantified. Even so, the aging process is complex -- with multiple interacting physiological scales. Computational models that simulate realistic individual trajectories of health during aging, and that include mortality, can significantly advance our understanding of aging. To do so, they must be systems-level models that incorporate interactions between measurable aspects of age-associated changes. To incorporate individual variability in the aging process, models must be stochastic. To be useful they should also be predictive, and so must be fit or parameterized by data from large populations of aging individuals. In this perspective, we outline where we have been, where we are, and where we hope to go in computational models of aging. Our focus is on systems-level models, and on their great potential in aging research.