  Dynamic treatment regimes (DTR) are a statistical paradigm in precision
medicine which aim to optimize patient outcomes by individualizing treatments.
At its simplest, a DTR may require only a single decision to be made; this
special case is called an individualized treatment rule (ITR) and is often used
to maximize short-term rewards. Generalized dynamic weighted ordinary least
squares (G-dWOLS), a DTR estimation method that offers theoretical advantages
such as double robustness of parameter estimators in the decision rules, has
been recently extended to now accommodate categorical treatments. In this work,
G-dWOLS is applied to longitudinal data to estimate an optimal ITR, which is
demonstrated in simulations. This novel method is then applied to a population
affected by HIV whereby an ITR for the administration of Interleukin 7 (IL-7)
is devised to maximize the duration where the CD4 load is above a healthy
threshold (500 cells/$\mu$L) while preventing the administration of unnecessary
injections.
