| dc.description.abstract | Medicinal herbs constitute an important source of raw materials for both the traditional and the conventional medicine. Due to their availability all over the world,
they play a key role in world health as complement if not substitute to conventional
medicine mainly due to lack of suitable, effective, cheap and reliable drugs at the
time they are required and in many cases in the remotest places of the world.
Over reliance on herbal drugs whose active ingredients have not been quantified
resulting to different herbalist prescribing different concoctions depending on the
flora availability, may lead to resistance development, overdose or under dose
which may lead to negative repercussion.
For these reasons there is need to standardize commonly used herbal drugs,
by formulating a mathematical model that can be used to determine the best combination of herbs and best preparation practices in order to achieve the optimal
response. By so doing, useful results and conclusions can be drawn by planned
and designed experiment.
Response surface methodology as a statistical technique is useful in modeling
and analysis of problems in which response of interest is influenced by several
variables where the objective is to optimize the response. This is equivalent to
locating feasible treatment combinations for which the mean response is optimized.
This excursion yields interesting patterns of the response surface where ridges
are mapped with a view to identifying combinations which give optimal response.
It is of interest to note how to discriminate amongst the various points on the
response surface which the yield is the same for different combinations of the
predictor variables and to isolate the ones which are identified as parsimoniously
feasible.
This research employs response surface methodology to investigate effectiveness of herbal medicine in reducing the blood sugar level of a diabetic to a level
that is acceptable. In this setup, observations are made to investigate effectiveness
for particular dosage at reducing the blood sugar level with time.
The variance function comes in handy as a tool for discrimination between two
points on the identified response surface. The most feasible of all the identified
points of equal yield is the one in which the variance function is minimal. In this
research we use the variance function of the difference as well as the difference of
the variance functions between two points to provide reliable advice on the range
around which the dosage is desirable and time required to effectively reduce the
blood sugar level to acceptable range.
Key words: Response surface; Rotatable design; Variance function ; diabetic;
Herbal-Medicine; treatment. | en_US |
