Gopkumar P

Present work is about the development of bioanalytical method of estimation for an atypical antipsychotic drug Olanzapine from endogenous matrix. Olanzapine is an atypical antipsychotic drug that chemically belongs to thieno benzodiazepine derivative. Bioanalytical estimation of antipsychotic drugs has clinical significance because of probable drug accumulation in body tissues because of long term treatment regime. Olanzapine has been recommended as the first-line drug for the treatment of schizophrenia. It is considered an atypical neuroleptic agent with fewer extrapyramidal side effects than classical neuroleptic agents. In the study initially an alternative bioanalytical estimation method, with the added advantages of decreased run time and minimization of endogenous matrix interferences was developed, which is indicated by high degree of specificity. Developed method was validated for quantization of drug Olanzapine. Developed method was finally cross validated for the estimation of Olanzapine after multiple dosing of drug in experimental animal. Result of study revealed linear detector response from 100 –500 ng/ml, with the correlation coefficient (r2 =0.989). The limit of detection and limit of quantification of the assay were 27.76 ng/ml and 79.96 and 78.55% ng/ml respectively. The recoveries of Olanzapine from plasma and brain tissue were found to be 79.96 % w/v and 78.55% w/v respectively. The applicability of the assay was confirmed for multiple dose drug determination in blood plasma and brain tissue of Olanzapine in wistar rats after i.p. administration for 10 consecutive days. This method is suitable for studying Olanzapine pharmacokinetics and toxico-kinetics in single or multiple-dose studies. Key words: Olanzapine, Bioanalytical, High Performance Liquid Chromatography.

Spleen Tyrosine Kinase (SYK) is known to play vital role in many signal transduction pathways and hence is considered as a potent target for various disorders like inflammatory, cancer and many auto immune disorders. QSAR study of Napthyridines as SYK Kinase inhibitors was performed using accelrrys discovery studio client (DSV - Version 3.0) as the modelling tool. A total of 53 selected molecules were considered for the development of QSAR model. The study was performed using the most stable confirmer fitting best to SYK Kinase enzyme binding site. The study resulted in development of cross validated QSAR models using different set of descriptors.  Partial least square model of the data generated exhibited a very good linear relation between the training set of compounds with that of the reported activity as well as the test set of compounds with the predicted activity. The 4 statistical analysis performed revealed following observations; Training data set r2= 0.848, q2 (Cross validated r2) = 0.581 validated by internal validation with correlation of coefficient (r2) of 0.941 and cross validated r2 (q2) of 0.617 and external set of compounds with a predictive correlation of coefficient of 0.918.  A total of 11 descriptors pruned on the study explained the structural correlation of Napthyridines with SYK Kinase enzyme. The mode developed can be used to predict bio-efficacy of unknown molecules 7-methoxy-6-[3-morpholinopropoxy]-quinazoline as SYK Kinase inhibitors. The study calls for the development of the molecules predicted as bio efficacious in this model and a quantitative inhibitory analysis of SYK Kinase. Key words: Napthyridines, QSAR, SYK.

Epidermal Growth Factor Receptor (EGFR) is known to play vital role in many cellular signalling pathways and hence is considered as a potent target for cancer. Inhibition of this enzyme has been reported to be beneficial by various workers. QSAR study of Quinazolines as EGFR was performed using accelrys discovery studio client (DSV-Version 3.0) as the modelling tool. A total of 67 selected molecules were considered for the development of QSAR model. Partial least square model of the data generated exhibited a very good linear relation between the training set of compounds with that of the reported activity as well as the test set of compounds with the predicted activity. The 4 statistical analysis performed revealed following observations; Training data set r2= 0.701, q2 (Cross validated r2) = 0.616 validated by internal validation with correlation of coefficient (r2) of 0.848 and cross validated r2 (q2) of 0.573 and external set of compounds with a predictive correlation of coefficient of 0.900.  A total of 9 descripters pruned on the study explained the structural correlation of quinazolines with EGFR. The model developed can be used to predict bioefficacy of unknown molecules 4-[1,3-benzothiazol-2-yl]-N-[(1E)-(4-nitrophenyl)methylene]aniline as EGFR inhibitors. Further a hypothetical model to describe the interaction between the predicted molecules with EGFR is proposed and this hypothetical model explains the possibility of Met769 and Gln767 as the possible binding sites. The activity is observed in the preliminary cytotoxic activity (MTT assay). The study calls for the development of the molecules predicted as bio efficacious in this model and a quantitative inhibitory analysis of EGFR. Key word: EGFR, QSAR, r2, q2