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The new major challenge that the pharmaceutical industry is facing in the discovery and development of new drugs is to reduce costs and time needed from discovery to market, while at the same time raising standards of quality.
If the pharmaceutical industry cannot find a solution to reduce both costs and time, then its whole business model will be jeopardized. The market will hardly be able, even in the near future, to afford excessively expensive drugs, regardless of their quality.
OBJECTIVES : The use of models in the experimental cycle to reduce cost and time and improve quality.
Without models, the final purpose of an experiment was one single drug or its behavior, with the use of models, the objective of experiments will be the drug and the model at the same level.
Improving the model will help understanding the experiments on successive drugs and improving the model’s ability will help to represent reality.
CONCEPT
According to Breiman , there are two cultures in the use of statistical modeling to reach conclusions from data.
The first culture, namely, the data modeling culture, assumes that the data are generated by a given stochastic data model.
whereas the other, the algorithmic modeling culture, uses algorithmic models and treats the data mechanism as unknown.
To understand the mechanism, the use of modeling concepts is essential.
The purpose of the model is essentially for that of translating the known properties about the black box as well as some new hypotheses into a mathematical representation.
In this way, a model is a simplifying representation of the data- generating mechanism under investigation.
The identification of an appropriate model is often not easy and may require thorough investigation