| Acceptance rate | 46% |
|---|---|
| Time to first decision | 6 months* |
| Time to decision with review | 50 days* |
*Approximate number of days
**The days mentioned above are averages and do not indicate exact durations. The process may vary for each article.
ACTA Pharmaceutica Sciencia
2009 , Vol 51 , Num 3
QUANTITATIVE STRUCTURE PHARMACOKINETIC RELATIONSHIP (QSPKR) OF COX-2 INHIBITORS USING ARTIFICIAL NEURAL NETWORK
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The purpose of this study was to develop Quantitative Structure Pharmacokinetic Relationship (QSPkR) for selected Cox-2 inhibitors. Artificial neural network (ANN) was used for data pruning (leave one out strategy) and prediction of pharmacokinetic and construct the QSPkR model from molecular descriptors that were generated using the TSAR, Codessa and Dragon computer programme. The final equation estimating Cl, Vd, t1/2, AUC and Tmax, all show good correlation but Vd,Cl and t1/2 shows significant correlation (r: 0.9-0.7). This investigation will help in rationalizing the design of new molecule and allow more rapid progression of potential drug candidates to the markets.
Keywords :
QUANTITATIVE STRUCTURE PHARMACOKINETIC RELATIONSHIP (QSPKR), ARTIFICIAL NEURAL NETWORK, PHARMACOKINETICS, MOLECULAR MODELING, DESCRIPTORS