- Tytuł:
- Computational intelligence for predicting biological effects of drug absorption in lungs
- Autorzy:
-
Pacławski, Adam
Szlęk, Jakub
Mendyk, Aleksander - Powiązania:
- https://bibliotekanauki.pl/articles/305803.pdf
- Data publikacji:
- 2019
- Wydawca:
- Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
- Tematy:
-
empirical model
absorption enhancers
pulmonary drugs
genetic programming
symbolic regression
computational intelligence - Opis:
- Recently, the lungs have been extensively examined as a route for delivering drugs (active pharmaceutical ingredients, APIs) into the bloodstream; this is mainly due to the possibility of the noninvasive administration of macromolecules such as proteins and peptides. The absorption mechanisms of chemical compounds in the lungs are still not fully understood, which makes pulmonary formulation composition development challenging. This manuscript presents the development of an empirical model capable of predicting the excipients’ influence on the absorption of drugs in the lungs. Due to the complexity of the problem and the not-fully-understood mechanisms of absorption, computational intelligence tools were applied. As a result, a mathematical formula was established and analyzed. The normalized root-mean-squared error (NRMSE) and R2 of the model were 4.57%, and 0.83, respectively. The presented approach is beneficial both practically by developing an in silico predictive model and theoretically by gaining knowledge of the influence of APIs and excipient structure on absorption in the lungs.
- Źródło:
-
Computer Science; 2019, 20 (1); 99-121
1508-2806
2300-7036 - Pojawia się w:
- Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł