ARTIFICIAL INTELLIGENCE EVALUATION OF RELEASE PROPERTIES OF TABLET FORMULATION CONTAINING FLURBIPROFEN

Abstract

Objective: The aim of this study was to examine the behavior of two different modified release polymers at different concentrations in terms of their similarity to a commercial product in the market, and to perform optimization studies with these polymers using artificial intelligence to find the most suitable formulation. Materials and Methods: Hydroxypropyl methyl cellulose K100M and sodium alginate polymers were compressed at three different concentrations with the same pressing force. Tests for tablet weights, tablet hardness, diameter/ thickness values and dissolution rate were conducted. The results were evaluated with Minitab19 TM. Results: Tablet weights were found to be between 0.2142 mg±0.039 mg and 0.2974 mg±0.001 mg. Tablet thickness varied between 3.80 mm±0.00 mm and 5.00 mm±0.00 mm. Hardness values of formulations containing the 20 mg polymer could not be measured. For other polymer concentrations, they were between 22.6 N±10.11 N and 111.4 N±9.50 N. The dissolution results of formulations prepared with HPMC were lower than those of sodium alginate at the same concentration. The obtained data was evaluated with Minitab19 TM, which suggested a 41% sodium alginate concentration as the closest formulation to the reference product. Conclusion: The advantages of artificial intelligence applications are not to be underestimated, and researchers are able to find and obtain results of experiments that they might not be able to conduct. In the light of all these findings, it would not be wrong to say that artificial intelligence will become even more preferable in the coming years.

Keywords

• Flurbiprofen
• modified release
• artificial intelligence
• Minitab
• optimization

FLURBİPROFEN İÇEREN TABLET FORMÜLASYONUNUN SALIM ÖZELLİKLERİNİN YAPAY ZEKÂ İLE DEĞERLENDİRİLMESİ

Abstract

Amaç: Çalışmada iki farklı uzatılmış salım polimerinin farklı konsantrasyonlarda ki davranışının piyasada bulunan bir ticari ürüne benzerliği yönünden incelenmesi ve yapay zeka uygulaması olan Minitab19 TM kullanılarak bu polimerlerle optimizasyon çalışması yapılması ve en uygun formülasyonun bulunması amaçlanmıştır. Gereç ve Yöntem: Hidroksipropil metil selüloz K100 M ve sodyum aljinat polimerleri üç farklı konsantrasyonda, her tablette 20 mg, 60 mg ve 100 mg polimer içerecek şekilde aynı baskı kuvveti, 1000 psi’da basılmıştır ve basılan tabletlerin tablet ağırlıkları, sertlik testleri, çap/yükseklik değerleri ve çözünme hızı testleri gerçekleştirilmiştir. Orijinal ürüne benzer bir salım profili gösterecek bir formülasyon yapay zeka programı olan Minitab19 TM ile sonuçlar değerlendirilmiş ve optimizasyon çalışması yapılmıştır. Bulgular: Hazırlanan tabletlerin tablet ağırlıkları 0,2142 mg±0,039 mg ile 0,2974 mg±0,001 mg arasında bulunmuştur. Tablet çapları 3,80mm±0,00mm ile 5,00 mm±0,00 mm arasında değişkenlik göstermektedir. 20 mg polimer içeren formülasyonların tablet sertlik değerleri ölçülememişken, diğer polimer konsantrasyonları için 22,6 N±10,11 N ile 111,4 N±9,50 N arasında bulunmuştur. HPMC K100M ile hazırlanan formülasyonların çözünme hızı testi sonuçları aynı konsantrasyonda ki sodyum Aljinat sonuçlarına göre daha düşük bulunmuştur. Yapılan çalışmalar sonucunda elde edilen veriler Minitab19 TM ile değerlendirilmiş ve yapay zeka programı %41 oranında sodyum aljinat konsantrasyonunu referans ürüne en yakın formülasyon olarak önermiştir. Sonuç: Yapay zeka uygulamalarının sağladıkları avantajlar azımsanamayacak düzeydedir ve bilim insanlarının belki de deneme şansı olamayacak sonuçları datalar arasından bulup çıkartabilmektedirler. Tüm bu veriler ışığında önümüzdeki süreçlerde daha da tercih edilir hale geleceğini söylemek yanlış olmayacaktır.

Keywords

• Flurbiprofen
• modifiye salım
• yapay zeka
• Minitab
• optimizasyon

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