Research Article
Development of Quantitative Structure-Property Relationship Models for Self-Emulsifying Drug Delivery System of 2-Aryl Propionic Acid NSAIDs
Table 7
Experimental and predicted values of predicting set.
(a) |
| NO. | | MLR | ANN | | MLR | ANN | | MLR | ANN |
| 1a | 1.464 | 1.649 | 1.376 | 2.552 | 2.457 | 2.488 | 1.199 | 1.195 | 1.241 | 2a | 1.674 | 2.090 | 2.104 | 3.221 | 3.299 | 3.285 | 1.564 | 1.572 | 1.518 | 3a | 2.155 | 2.230 | 2.378 | 2.762 | 2.973 | 2.663 | 1.541 | 1.608 | 1.615 | 4a | 1.057 | 1.026 | 1.169 | 2.074 | 1.983 | 2.233 | 1.045 | 1.209 | 1.233 | 5a | 1.600 | 1.756 | 1.631 | 3.418 | 3.487 | 3.420 | 1.830 | 1.801 | 1.885 | 6a | 1.018 | 0.901 | 0.841 | 2.356 | 2.099 | 2.014 | 1.015 | 0.964 | 0.871 | 7a | 1.330 | 1.363 | 1.106 | 2.918 | 2.970 | 2.973 | 1.300 | 1.395 | 1.191 | 8a | 1.631 | 1.693 | 1.422 | 3.352 | 3.407 | 3.655 | 1.670 | 1.699 | 1.615 | 9a | 0.944 | 0.913 | 0.461 | 1.545 | 1.663 | 2.033 | 0.794 | 0.645 | 0.967 | 10a | 1.671 | 1.644 | 1.504 | 2.230 | 2.631 | 2.274 | 1.071 | 1.189 | 1.046 | 11a | 1.962 | 1.832 | 1.767 | 2.483 | 2.881 | 2.543 | 1.095 | 1.328 | 1.090 | 12a | 2.124 | 2.011 | 2.093 | 3.380 | 3.373 | 3.396 | 1.385 | 1.501 | 1.425 | 13a | 0.854 | 0.794 | 1.050 | 2.017 | 1.909 | 1.828 | 0.980 | 1.049 | 0.958 | 14a | 1.610 | 1.519 | 1.542 | 2.853 | 2.880 | 2.794 | 1.678 | 1.640 | 1.593 | 15a | 1.791 | 1.773 | 1.775 | 3.617 | 3.476 | 3.584 | 1.841 | 1.881 | 1.971 | 16a | 0.906 | 0.994 | 1.183 | 2.163 | 2.075 | 1.830 | 0.951 | 1.084 | 1.043 | 17a | 1.711 | 1.718 | 1.775 | 2.686 | 3.044 | 2.975 | 1.559 | 1.646 | 1.624 | 18a | 1.768 | 1.827 | 1.788 | 2.710 | 2.934 | 2.976 | 1.647 | 1.694 | 1.691 | 19 b | 1.452 | 1.047 | 1.223 | 1.801 | 1.978 | 1.947 | 1.065 | 1.173 | 1.062 | 20 b | 1.657 | 1.132 | 1.443 | 2.314 | 2.346 | 2.265 | 1.217 | 1.273 | 1.193 | 21 b | 1.614 | 1.241 | 1.476 | 2.261 | 2.748 | 2.749 | 1.369 | 1.386 | 1.315 | 22 b | 1.778 | 1.402 | 1.530 | 2.255 | 2.447 | 2.732 | 1.322 | 1.444 | 1.375 | 23 b | 1.901 | 1.486 | 1.708 | 2.516 | 2.816 | 2.842 | 1.645 | 1.544 | 1.345 | 24 b | 2.000 | 1.571 | 1.837 | 2.757 | 3.185 | 3.413 | 1.630 | 1.644 | 1.552 | 25 b | 1.887 | 1.591 | 1.680 | 2.304 | 2.699 | 2.751 | 1.342 | 1.587 | 1.596 | 26 b | 2.009 | 1.675 | 1.911 | 2.938 | 3.068 | 3.152 | 1.765 | 1.687 | 1.490 | 27 b | 2.165 | 1.735 | 1.988 | 3.140 | 3.404 | 3.810 | 1.786 | 1.773 | 1.625 | 28 b | 2.056 | 1.710 | 1.774 | 2.377 | 2.856 | 2.754 | 1.477 | 1.675 | 1.661 | 29 b | 2.062 | 1.770 | 1.991 | 2.944 | 3.192 | 3.273 | 1.687 | 1.761 | 1.582 | 30 b | 2.206 | 1.830 | 2.071 | 3.603 | 3.528 | 3.916 | 1.632 | 1.848 | 1.654 | 31 b | 1.534 | 1.092 | 1.080 | 1.933 | 2.053 | 2.149 | 1.171 | 1.162 | 1.062 | 32 b | 1.653 | 1.177 | 1.144 | 2.142 | 2.422 | 2.205 | 1.339 | 1.262 | 1.194 | 33 b | 1.622 | 1.286 | 1.068 | 2.195 | 2.824 | 2.822 | 1.435 | 1.376 | 1.233 | 34 b | 1.812 | 1.457 | 1.344 | 2.327 | 2.542 | 2.753 | 1.574 | 1.464 | 1.381 | 35 b | 1.802 | 1.541 | 1.521 | 2.347 | 2.911 | 3.096 | 1.770 | 1.564 | 1.415 | 36 b | 1.721 | 1.626 | 1.471 | 2.833 | 3.280 | 3.551 | 1.787 | 1.664 | 1.483 | 37 b | 1.852 | 1.651 | 1.494 | 2.247 | 2.803 | 3.085 | 1.685 | 1.621 | 1.657 | 38 b | 1.796 | 1.736 | 1.698 | 2.165 | 3.172 | 3.504 | 1.690 | 1.721 | 1.586 | 39 b | 1.820 | 1.796 | 1.733 | 2.865 | 3.508 | 3.771 | 1.877 | 1.808 | 1.662 | 40 b | 1.916 | 1.773 | 1.604 | 2.129 | 2.967 | 3.157 | 1.767 | 1.718 | 1.796 | 41 b | 2.133 | 1.833 | 1.779 | 2.529 | 3.303 | 3.627 | 1.855 | 1.805 | 1.691 | 42 b | 1.884 | 1.893 | 1.885 | 3.116 | 3.639 | 3.948 | 1.884 | 1.891 | 1.778 |
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(b) |
| NO. | | MLR | ANN | | MLR | ANN | | MLR | ANN |
| 1a | 0.426 | 0.438 | 0.441 | 2.144 | 2.104 | 2.175 | 1.146 | 1.227 | 1.193 | 2a | 0.552 | 0.534 | 0.531 | 2.457 | 2.465 | 2.462 | 1.689 | 1.641 | 1.680 | 3a | 0.596 | 0.612 | 0.606 | 2.355 | 2.549 | 2.201 | 1.842 | 1.913 | 1.698 | 4a | 0.450 | 0.505 | 0.479 | 1.904 | 1.728 | 1.884 | 1.475 | 1.357 | 1.378 | 5a | 0.696 | 0.651 | 0.672 | 2.229 | 2.347 | 2.260 | 2.009 | 2.132 | 2.082 | 6a | 0.437 | 0.435 | 0.403 | 1.653 | 1.742 | 1.505 | 1.405 | 1.449 | 1.505 | 7a | 0.497 | 0.553 | 0.518 | 2.100 | 2.112 | 2.127 | 1.939 | 1.939 | 1.884 | 8a | 0.624 | 0.661 | 0.631 | 2.339 | 2.360 | 2.300 | 2.366 | 2.359 | 2.326 | 9a | 0.342 | 0.312 | 0.315 | 1.585 | 1.520 | 1.620 | 0.818 | 0.769 | 1.006 | 10a | 0.444 | 0.473 | 0.491 | 2.081 | 2.100 | 2.099 | 1.553 | 1.495 | 1.606 | 11a | 0.455 | 0.514 | 0.485 | 2.133 | 2.250 | 2.313 | 1.725 | 1.681 | 1.808 | 12a | 0.503 | 0.536 | 0.488 | 2.419 | 2.404 | 2.455 | 1.892 | 1.805 | 1.879 | 13a | 0.440 | 0.456 | 0.435 | 1.649 | 1.666 | 1.574 | 1.208 | 1.175 | 1.346 | 14a | 0.678 | 0.650 | 0.661 | 2.286 | 2.233 | 2.339 | 2.010 | 2.065 | 2.313 | 15a | 0.694 | 0.697 | 0.708 | 2.435 | 2.445 | 2.379 | 2.300 | 2.305 | 2.361 | 16a | 0.371 | 0.402 | 0.389 | 1.665 | 1.706 | 1.514 | 1.320 | 1.501 | 1.505 | 17a | 0.631 | 0.618 | 0.621 | 2.069 | 2.279 | 2.258 | 2.258 | 2.338 | 2.381 | 18a | 0.668 | 0.673 | 0.651 | 2.295 | 2.352 | 2.336 | 2.500 | 2.529 | 2.624 | 19b | 0.403 | 0.536 | 0.528 | 1.774 | 1.858 | 1.825 | 1.318 | 1.362 | 1.239 | 20b | 0.480 | 0.537 | 0.528 | 1.660 | 1.938 | 1.904 | 1.409 | 1.390 | 1.489 | 21b | 0.501 | 0.543 | 0.512 | 1.601 | 2.039 | 2.220 | 1.358 | 1.440 | 1.709 | 22b | 0.544 | 0.628 | 0.650 | 2.054 | 2.138 | 2.046 | 1.632 | 1.730 | 1.677 | 23b | 0.514 | 0.629 | 0.633 | 2.333 | 2.218 | 2.346 | 1.776 | 1.759 | 1.957 | 24b | 0.537 | 0.631 | 0.611 | 2.223 | 2.298 | 2.463 | 1.753 | 1.787 | 2.133 | 25b | 0.593 | 0.677 | 0.692 | 2.250 | 2.288 | 2.163 | 1.788 | 1.925 | 1.804 | 26b | 0.734 | 0.678 | 0.673 | 2.405 | 2.368 | 2.516 | 2.008 | 1.954 | 2.063 | 27b | 0.602 | 0.674 | 0.659 | 2.309 | 2.428 | 2.544 | 2.050 | 1.961 | 2.160 | 28b | 0.630 | 0.707 | 0.716 | 2.418 | 2.382 | 2.242 | 2.060 | 2.046 | 1.890 | 29b | 0.724 | 0.703 | 0.693 | 2.493 | 2.442 | 2.585 | 2.163 | 2.054 | 2.116 | 30b | 0.682 | 0.700 | 0.686 | 2.417 | 2.501 | 2.588 | 2.230 | 2.061 | 2.167 | 31b | 0.686 | 0.499 | 0.546 | 1.944 | 1.846 | 1.681 | 1.627 | 1.478 | 1.430 | 32b | 0.852 | 0.500 | 0.525 | 1.933 | 1.926 | 1.862 | 1.731 | 1.507 | 1.544 | 33b | 0.742 | 0.506 | 0.482 | 2.037 | 2.027 | 2.195 | 1.725 | 1.556 | 1.746 | 34b | 0.489 | 0.599 | 0.675 | 2.274 | 2.131 | 2.076 | 1.966 | 1.940 | 1.945 | 35b | 0.529 | 0.600 | 0.641 | 2.313 | 2.211 | 2.357 | 2.077 | 1.969 | 2.028 | 36b | 0.499 | 0.601 | 0.619 | 2.363 | 2.291 | 2.426 | 2.012 | 1.998 | 2.097 | 37b | 0.595 | 0.651 | 0.729 | 2.449 | 2.283 | 2.263 | 2.271 | 2.182 | 2.172 | 38b | 0.586 | 0.652 | 0.705 | 2.493 | 2.363 | 2.490 | 2.003 | 2.211 | 2.219 | 39b | 0.579 | 0.648 | 0.689 | 2.437 | 2.423 | 2.527 | 2.268 | 2.218 | 2.244 | 40b | 0.761 | 0.683 | 0.778 | 2.265 | 2.379 | 2.363 | 2.474 | 2.331 | 2.325 | 41b | 0.732 | 0.680 | 0.751 | 2.446 | 2.438 | 2.539 | 2.356 | 2.339 | 2.375 | 42b | 0.791 | 0.676 | 0.732 | 2.500 | 2.498 | 2.603 | 2.544 | 2.347 | 2.383 |
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aInternal validation set.
bExternal prediction set.
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