  Locally optimal designs for generalized linear models are derived at certain
values of the regression parameters. In the present paper a general setup of
the generalized linear model is considered. Analytic solutions for optimal
designs are developed under Kiefer $\Phi_k$-criteria highlighting the D- and
A-optimal designs. By means of The General Equivalence Theorem necessary and
sufficient conditions in term of intensity values are obtained to characterize
the locally optimal designs. In this context, linear predictors are assumed
constituting first order models with and without intercept on appropriate
experimental regions.
