Current Pharmaceutical Analysis, 2008, 4, 231-237 231 1573-4129/08 $55.00+.00 © 2008 Bentham Science Publishers Ltd. Development and Validation of a Rapid Chemometrics-Assisted Spectro- photometry and Liquid Chromatography Methods for the Simultaneous Determination of the Phenylalanine, Tryptophan and Tyrosine in the Pharmaceutical Products Siavash Riahi a,b, *, Mohammad R. Ganjali b , Eslam Pourbasheer b , Faten Divsar c , Parviz Norouzi b and Marzieh Chaloosi c a Institute of Petroleum Engineering, Faculty of Engineering, University of Tehran, P. O. Box 11365-4563, Tehran, Iran b Center of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P. O. Box 14155-6455, Tehran, Iran c Factually of Chemistry, University of Tarbiat Moalem, Tehran, Iran Abstract: The simultaneous multicomponent analysis is usually carried out using multivariate calibration models, such as the partial least squares (PLS). The genetic algorithm (GA) is a suitable method for the wavelength selection for the PLS calibration of the mixtures with almost identical spectra and without loss of the predictive ability, using the spectropho- tometric method. In this work, a simple and precise method for rapid and accurate simultaneous determination of phenyla- lanine, tryptophan and tyrosine is proposed with the employment of the PLS regression together with GA for the variable selection. The method was successfully applied to the quantitation of these amino acids in aminoplasmal serum, providing results in agreement with those obtained by high performance liquid chromatography (HPLC). Keywords: Spectrophotometric, Amino acids, Chemometrics, Genetic Algorithm, Aminoplasmal serum. 1. INTRODUCTION The identification and determination of amino acids are important in studying human diseases and are routinely per- formed especially in clinical and biomedical laboratories [1, 2]. Many types of samples, such as biological fluids, serum albumin, food and protein hydrolysates, contain these amino acids. Within the nutrition field, essential amino acids play an important role and are considered as industrially interest- ing metabolites [3]. Tryptophan (Try) interposes in brain functioning [4], phenylalanine (Phe) is the diagnostic marker for phenylke- tonuria (PKU) and tyrosine (Tyr) for tyrosinemia in the screening of IEM (Inborn Errors Metabolism) [5-7]. It has also been reported that patients with schizophrenia have al- tered brain levels of the essential amino acid, tyrosine, the precursor for the synthesis of dopamine [8]. Commercially available amino acid analyzers are often used for the determination of amino acids. In the recent years, a number of clinical institutes that have introduced HPLC methods for the IEM screening have increased. Sev- eral specific instruments for the analysis of amino acids are based on liquid chromatography [9], HPLC [10], thin layer chromatography, GC-MS spectrometry analysis [11] and capillary electrophoresis [12-14]. It should be mentioned that although chromatographic techniques provide accurate re- *Address correspondence to this author at the Institute of Petroleum Engi- neering, Faculty of Engineering, University of Tehran, Iran; Tel: +98-21- 88333058; Fax: +98-21-88632975; E-mail: riahisv@khayam.ut.ac.ir sults, they may be unsuitable for the analysis of large sets of samples, because the separation step is time-consuming. Nowadays, simpler and faster procedures are needed to sat- isfy the great demand of amino acid determinations in fields such as food processing, biochemistry, pharmaceuticals and clinical analysis. Phe, Try and Tyr show typical absorbance bands in the ultraviolet region, between 190 and 235 nm. The simultane- ous spectrophotometric determination of these amino acids shows that some difficulties occur, due to the high overlap- ping between their spectra. Multivariate calibration methods are being applied successfully to the multicomponent deter- mination to overcome some of the drawbacks of the classical methods. The application of quantitative chemometrics methods, particularly partial least squares (PLS), to multivariate chemical data is becoming more widespread, owing to the availability of the digitized spectroscopic data and commer- cial software for laboratory computers [13-15]. The advan- tage of multicomponent analysis along with partial least squares in mixtures is the demonstration of fast separation steps. The theory and application of partial least squares (PLS) in spectrometry have previously been discussed by several workers [16, 17]. Genetic algorithm (GA) is a very useful technique in the variable selection problems, because the relationship be- tween the presence/absence of the variables in a calibration model and the prediction ability of the model, specifically for the PLS models, is very complex and the mathematical