{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T01:16:02Z","timestamp":1760577362546,"version":"3.37.3"},"reference-count":34,"publisher":"Wiley","license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>The purpose of this work was to develop a mathematical model of the drug dissolution (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi>Q<\/mml:mi><\/mml:mrow><\/mml:math>) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>Q<\/mml:mi><\/mml:mrow><\/mml:math>versus extrudate diameter (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M3\"><mml:mrow><mml:mi>d<\/mml:mi><\/mml:mrow><\/mml:math>) and the time variable (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M4\"><mml:mrow><mml:mi>t<\/mml:mi><\/mml:mrow><\/mml:math>) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations\u2019 parameters. Two inputs were found important for the drug dissolution:<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M5\"><mml:mrow><mml:mi>d<\/mml:mi><\/mml:mrow><\/mml:math>and<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M6\"><mml:mrow><mml:mi>t<\/mml:mi><\/mml:mrow><\/mml:math>. The extrudates length (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M7\"><mml:mrow><mml:mi>L<\/mml:mi><\/mml:mrow><\/mml:math>) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M8\"><mml:mrow><mml:mi>Q<\/mml:mi><\/mml:mrow><\/mml:math>versus<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M9\"><mml:mrow><mml:mi>d<\/mml:mi><\/mml:mrow><\/mml:math>and<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M10\"><mml:mrow><mml:mi>t<\/mml:mi><\/mml:mrow><\/mml:math>resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs\u2019 black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies.<\/jats:p>","DOI":"10.1155\/2015\/863874","type":"journal-article","created":{"date-parts":[[2015,5,27]],"date-time":"2015-05-27T02:35:30Z","timestamp":1432694130000},"page":"1-9","source":"Crossref","is-referenced-by-count":18,"title":["From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming"],"prefix":"10.1155","volume":"2015","author":[{"given":"Aleksander","family":"Mendyk","sequence":"first","affiliation":[{"name":"Department of Pharmaceutical Technology and Biopharmaceutics, Jagiellonian University Medical College, Medyczna 9 Street, 30-688 Krakow, Poland"}]},{"given":"Sinan","family":"G\u00fcres","sequence":"additional","affiliation":[{"name":"Institute of Pharmaceutics and Biopharmaceutics, Heinrich-Heine University of D\u00fcsseldorf, Universit\u00e4tsstra\u00dfe 1, 40225 Duesseldorf, 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