In
microscopic systems formed by living cells, the small numbers of some
reactant molecules can result in dynamical behavior that is discrete and
stochastic rather than continuous and deterministic. An analysis tool
that respects these dynamical characteristics is the stochastic
simulation algorithm (SSA). Despite recent improvements, as a procedure
that simulates every reaction event, the SSA is necessarily inefficient
for most realistic problems. There are two main reasons for this, both
arising from the multiscale nature of the underlying problem: (1) the
presence of multiple timescales (both fast and slow reactions); and (2)
the need to include in the simulation both chemical species that are
present in relatively small quantities and should be modeled by a
discrete stochastic process, and species that are present in larger
quantities and are more efficiently modeled by a deterministic
differential equation. We will describe several recently developed
techniques for multiscale simulation of biochemical systems, along with
some biological applications and a new software toolkit.