  Droplets form a cornerstone of the spatiotemporal organization of
biomolecules in cells. These droplets are controlled using physical processes
like chemical reactions and imposed gradients, which are costly to simulate
using traditional approaches, like solving the Cahn-Hilliard equation. To
overcome this challenge, we here present an alternative, efficient method. The
main idea is to focus on the relevant degrees of freedom, like droplet
positions and sizes. We derive dynamical equations for these quantities using
analytical solutions to simplified situations. We verify our method against
fully-resolved simulations and show that it can describe interacting droplets
under the influence of chemical reactions and external gradients using only a
fraction of the computational costs of traditional methods. Our method can be
extended to include other processes in the future and will thus serve as a
relevant platform for understanding the dynamics of droplets in cells.
