Automatic extraction of chemical names has a great importance in biomedical and life science research field. In the proposed system, accuracy in training data generation is improved by generating large amount of regular expressions. Regular expressions are generated from systematic chemical names collected from PubChem Database. Due to large amount of regular expressions, accuracy in chemical name extraction is also improved. In the work carried out, an efficient chemical name extraction system is designed. It is deployed by processing the algorithm in following steps. First stop words are removed. After removal of stop words trivial name extraction is performed by dictionary matching approach. Then CAS/Registry numbers are extracted by regular expression. For systematic name extraction, sample systematic names from various categories are given as an input for training. Normalization type 1 and type 2 is performed on these sample systematic names which is followed by tokenization. Finally regular expressions are generated from training data. Input document is then matched with the regular expressions to extract systematic chemical names.