  Financing high-tech projects always entails a great deal of risk. The lack of
a systematic method to pinpoint the risk of such projects has been recognized
as one of the most salient barriers for evaluating them. So, in order to
develop a mechanism for evaluating high-tech projects, an Artificial Neural
Network (ANN) has been developed through this study. The structure of this
paper encompasses four parts. The first part deals with introducing paper's
whole body. The second part gives a literature review. The collection process
of risk related variables and the process of developing a Risk Assessment Index
system (RAIS) through Principal Component Analysis (PCA) are those issues that
are discussed in the third part. The fourth part particularly deals with
pharmaceutical industry. Finally, the fifth part has focused on developing an
ANN for pattern recognition of failure or success of high-tech projects.
Analysis of model's results and a final conclusion are also presented in this
part.
