There are many diseases and conditions that can be studied using a cro
ss-over clinical trial, where the subjects receive sequences of treatm
ents. The treatments are then compared using the repeated measurements
taken 'within' subjects. The actual plan or design of the trial is us
ually obtained by consulting a published table of designs or by applyi
ng relatively simple rules such as using all possible permutations of
the treatments. However, there is a danger is this approach because th
e model assumed for the data when the tables or rules were constructed
may not be appropriate for the new trial being planned. Also, there m
ay be restrictions in the new trial on the number of treatment sequenc
es that can be used or on the number of periods of treatment particula
r subjects can be given. Such restrictions may mean that a published d
esign of the ideal size cannot be found unless compromises are made. A
better approach is to make the design satisfy the objectives of the t
rial rather than vice versa. In this paper we describe an approach to
constructing such tailor-made designs which we hope will lead to ill-f
itting 'off the peg' designs being a thing of the past. We use a compu
ter algorithm to search for optimal designs and illustrate it using a
number of examples. The criterion of optimality used in this paper is
A-optimality but our approach is not restricted to one particular crit
erion. The model used in the search for the optimal design is chosen t
o suit the nature of the trial at hand and as an example a variety of
models for three treatments are considered. We also illustrate the con
struction of designs for the comparison of two active treatments and a
placebo where it can be assumed that the carry-over effects of the ac
tive treatments are similar. Finally, we illustrate an augmentation of
a design that could arise when the objectives of a trial change.