  In this paper we present a new method for deriving It\^{o} stochastic delay
differential equations (SDDEs) from delayed chemical master equations (DCMEs).
Considering alternative formulations of SDDEs that can be derived from the same
DCME, we prove that they are equivalent both in distribution, and in sample
paths they produce. This allows us to formulate an algorithmic approach to
deriving equivalent It\^{o} SDDEs with a smaller number of noise variables,
which increases the computational speed of simulating stochastic delayed
systems. The new method is illustrated on a simple model of two interacting
species, and it shows excellent agreement with the results of direct stochastic
simulations, while also demonstrating a much superior speed of performance.
