The objective was to evaluate the effect of supplementation or not of 10 ppm of ractopamine in diets for swine females in the final stage of finishing, on carcass characteristics and meat quality, 54 animals were used, with an initial average weight of 98 kg (± 0 , 9 kg), distributed in a completely randomized design composed of two treatments, 27 repetitions and one animal per experimental unit. The treatments used were diets without or with supplementation of 10 ppm of ractopamine, for 21 days. The supplementation of ractopamine in diets for female pigs in the final finishing phase influenced the parameters of carcass characteristics and meat quality of the animals. Significant effects were observed (P <0.05) for all evaluated carcass characteristics, except for carcass yield and meat quality: hot and cooled straight carcass, loss of carcass on cooling, lean meat in the carcass, water loss by dripping, shear force on day 7 and water loss by cooking on day 14, there was no effect (P> 0.05) for water loss by cooking on days 1 and 7 and shear force on day 14. With the addition of 10 ppm of ractopamine in the diet of the finishing female pigs for 21 days, it obtained influence on the meat quality, providing better parameters of carcass characteristics, with higher yield of lean meat in the carcass.

In silico pharmacokinetics studies can aid the search for molecules with potential ability to be drug candidates. In this paper, a number of quinazoline candidates for epidermal growth factor receptor inhibitors-EGFR, important targets for the treatment of cancer, are computationally analyzed. The literature described that 69 quinazoline molecules were synthesized and the respective half maximum inhibitory concentrations (IC50) were obtained. A bilinear parabolic model was built to investigate the druglikeness by correlating the corresponding lipophilicities, which can be represented by the ideal Log P, with the optimal biological activity in terms of pIC50 values. Structural characteristics leading to improved pharmacokinetics parameters were then analyzed. Compound 56 exhibited the lowest IC50 and, therefore, it had the highest ability to inhibit the EGFR. In the present work, the most potent inhibitor 56 is not calculated to be the most promising drug candidate, since it's out of the parabolic model obtained due to a Log P above 5, which is not within the expected optimum range. Finally, this work is an example of computational prediction that an experimentally, highly active EGFR inhibitor can be unsuccessful as drug candidate because of pitfalls in pharmacokinetics parameters.