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FLURBİPROFEN İÇEREN TABLET FORMÜLASYONUNUN SALIM ÖZELLİKLERİNİN YAPAY ZEKÂ İLE DEĞERLENDİRİLMESİ

Yıl 2023, Cilt: 6 Sayı: 3, 332 - 336, 24.10.2023
https://doi.org/10.26650/JARHS2023-1325701

Öz

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.

Proje Numarası

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Kaynakça

  • Hedaya MA, El-Masry SM, Helmy SA. Physiologically relevant model to establish the in vivo-in vitro correlation for etamsylate controlled release matrix tablets. J Drug Deliv Sci Technol 2021;1(66):102864. google scholar
  • Moussa E, Siepmann F, Flament MP, Benzine Y, Penz F, Siepmann J, et al. Controlled release tablets based on HPMC: lactose blends. J Drug Deliv Sci Technol 2019;1(52):607-17. google scholar
  • Paolini MS, Fenton OS, Bhattacharya C, Andresen JL, Langer R. Polymers for extended-release administration. Biomed Microdevices 2019;21(2):45. google scholar
  • Cascone S, Lamberti G, Titomanlio G, d’Amore M, Barba AA. Measurements of non-uniform water content in hydroxypropylmethyl- cellulose based matrices via texture analysis. Carbohydr Polym 2014;103:348-54. google scholar
  • Rogers TL, Hewlett KO, Theuerkauf J, Balwinski KM. Assessing how the physical properties of enhanced powder flow of HPMC affect process control during direct compression of matrix tablets. Tablets Capsule (October) 2013;14-22. google scholar
  • Mandal S, Basu SK, Sa B. Sustained release of a water-soluble drug from alginate matrix tablets prepared by wet granulation method. AAPS PharmSciTech 2009;10(4):1348-56. google scholar
  • Geraili A, Xing M, Mequanint K. Design and fabrication of drug‐delivery systems toward adjustable release profiles for personalized treatment. View 2021;2(5):20200126. google scholar
  • Shaheen N, Shahiq uz Zaman. Development of fast dissolving tablets of flurbiprofen by sublimation method and its in vitro evaluation. Braz J Pharm Sci 2018;54(4):e17061. google scholar
  • RxMedia, 2023, Majezik 200 mg SR Kapsül, Accessed date: 01.05.2023. https://www.eczanet.com/rxmediapharma/. google scholar
  • Almotairi N, Mahrous GM, Al-Suwayeh S, Kazi M. Design and optimization of lornoxicam dispersible tablets using Quality by Design (QbD) Approach. Pharmaceuticals 2022;25:15(12):1463. google scholar
  • Mehanna MM, Abla KK. Recent advances in freeze-drying: variables, cycle optimization, and innovative techniques. Pharm Dev Technol 2022;14:27(8):904-23. google scholar
  • Mesut B, Aksu N, Ozsoy Y. Design of sustained release tablet formulations of alfuzosin HCl by means of neuro-fuzzy logic. Lat Am J Pharm 2013;32(9):1288-97. google scholar
  • Özçelik E, Mesut B, Buket AK, Özsoy Y. Quetiapine fumarate extended-release tablet formulation design using artificial neural networks. Turk J Pharm Sci 2017;14(3):213-21. google scholar
  • Aswaissi H, Acar ET. Simultaneous determination of flurbiprofen and thiocolchicoside in pharmaceutical preparations by a validated HPLC method. J Res Pharm (online) 2022;26(3):663-74. google scholar
  • Manwar J, Kumbhar DD, Bakal R, Baviskar S, Manmode R. Response surface based co-optimization of release kinetics and mucoadhesive strength for an oral mucoadhesive tablet of cefixime trihydrate. Bull Fac Pharm Cairo Univ 2016;54(2):227-35. google scholar
  • Galata DL, Zsiros B, Knyihár G, Péterfi O, Mészáros LA, Ronkay F, et al. Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles. Int J Pharm 2023;640:123001. google scholar
  • Sally A, Kassem AA, El-Kamel AH. Design and evaluation of gastroretentive levofloxacin floating mini-tablets-in-capsule system. Saudi Pharmaceutical Journal 2014;22(6):570-9. google scholar
  • Dupont, Kelcosol Pronatal pH 6160, https://www. pharmaexcipients.com/product/protanal-ph-6160kelcosol-nf/. google scholar
  • Mesut B, Tok YP, Alkan B, Vefai MK, Al-Mohaya M, Özsoy Y. Effect of mannitol particle size on melatonin dissolution and tablet properties using a Quality by Design Framework. Risk Manag 2023;2:12-21. google scholar
  • Charoenying T, Opanasopit P, Ngawhirunpat T, Rojanarata T, Akkaramongkolporn P, Patrojanasophon P. Development of a novel tablet-shaped floating 3D-printed device with adjustable floating time as floating drug delivery systems provided zero-order release kinetics. J Drug Deliv Sci Technol 2023;1(84):104506. google scholar

ARTIFICIAL INTELLIGENCE EVALUATION OF RELEASE PROPERTIES OF TABLET FORMULATION CONTAINING FLURBIPROFEN

Yıl 2023, Cilt: 6 Sayı: 3, 332 - 336, 24.10.2023
https://doi.org/10.26650/JARHS2023-1325701

Öz

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.

Destekleyen Kurum

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Proje Numarası

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Teşekkür

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Kaynakça

  • Hedaya MA, El-Masry SM, Helmy SA. Physiologically relevant model to establish the in vivo-in vitro correlation for etamsylate controlled release matrix tablets. J Drug Deliv Sci Technol 2021;1(66):102864. google scholar
  • Moussa E, Siepmann F, Flament MP, Benzine Y, Penz F, Siepmann J, et al. Controlled release tablets based on HPMC: lactose blends. J Drug Deliv Sci Technol 2019;1(52):607-17. google scholar
  • Paolini MS, Fenton OS, Bhattacharya C, Andresen JL, Langer R. Polymers for extended-release administration. Biomed Microdevices 2019;21(2):45. google scholar
  • Cascone S, Lamberti G, Titomanlio G, d’Amore M, Barba AA. Measurements of non-uniform water content in hydroxypropylmethyl- cellulose based matrices via texture analysis. Carbohydr Polym 2014;103:348-54. google scholar
  • Rogers TL, Hewlett KO, Theuerkauf J, Balwinski KM. Assessing how the physical properties of enhanced powder flow of HPMC affect process control during direct compression of matrix tablets. Tablets Capsule (October) 2013;14-22. google scholar
  • Mandal S, Basu SK, Sa B. Sustained release of a water-soluble drug from alginate matrix tablets prepared by wet granulation method. AAPS PharmSciTech 2009;10(4):1348-56. google scholar
  • Geraili A, Xing M, Mequanint K. Design and fabrication of drug‐delivery systems toward adjustable release profiles for personalized treatment. View 2021;2(5):20200126. google scholar
  • Shaheen N, Shahiq uz Zaman. Development of fast dissolving tablets of flurbiprofen by sublimation method and its in vitro evaluation. Braz J Pharm Sci 2018;54(4):e17061. google scholar
  • RxMedia, 2023, Majezik 200 mg SR Kapsül, Accessed date: 01.05.2023. https://www.eczanet.com/rxmediapharma/. google scholar
  • Almotairi N, Mahrous GM, Al-Suwayeh S, Kazi M. Design and optimization of lornoxicam dispersible tablets using Quality by Design (QbD) Approach. Pharmaceuticals 2022;25:15(12):1463. google scholar
  • Mehanna MM, Abla KK. Recent advances in freeze-drying: variables, cycle optimization, and innovative techniques. Pharm Dev Technol 2022;14:27(8):904-23. google scholar
  • Mesut B, Aksu N, Ozsoy Y. Design of sustained release tablet formulations of alfuzosin HCl by means of neuro-fuzzy logic. Lat Am J Pharm 2013;32(9):1288-97. google scholar
  • Özçelik E, Mesut B, Buket AK, Özsoy Y. Quetiapine fumarate extended-release tablet formulation design using artificial neural networks. Turk J Pharm Sci 2017;14(3):213-21. google scholar
  • Aswaissi H, Acar ET. Simultaneous determination of flurbiprofen and thiocolchicoside in pharmaceutical preparations by a validated HPLC method. J Res Pharm (online) 2022;26(3):663-74. google scholar
  • Manwar J, Kumbhar DD, Bakal R, Baviskar S, Manmode R. Response surface based co-optimization of release kinetics and mucoadhesive strength for an oral mucoadhesive tablet of cefixime trihydrate. Bull Fac Pharm Cairo Univ 2016;54(2):227-35. google scholar
  • Galata DL, Zsiros B, Knyihár G, Péterfi O, Mészáros LA, Ronkay F, et al. Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles. Int J Pharm 2023;640:123001. google scholar
  • Sally A, Kassem AA, El-Kamel AH. Design and evaluation of gastroretentive levofloxacin floating mini-tablets-in-capsule system. Saudi Pharmaceutical Journal 2014;22(6):570-9. google scholar
  • Dupont, Kelcosol Pronatal pH 6160, https://www. pharmaexcipients.com/product/protanal-ph-6160kelcosol-nf/. google scholar
  • Mesut B, Tok YP, Alkan B, Vefai MK, Al-Mohaya M, Özsoy Y. Effect of mannitol particle size on melatonin dissolution and tablet properties using a Quality by Design Framework. Risk Manag 2023;2:12-21. google scholar
  • Charoenying T, Opanasopit P, Ngawhirunpat T, Rojanarata T, Akkaramongkolporn P, Patrojanasophon P. Development of a novel tablet-shaped floating 3D-printed device with adjustable floating time as floating drug delivery systems provided zero-order release kinetics. J Drug Deliv Sci Technol 2023;1(84):104506. google scholar
Toplam 20 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Klinik Tıp Bilimleri (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Burcu Mesut 0000-0003-2838-1688

Yavuz Selim Çelik 0000-0001-9601-4615

Proje Numarası -
Yayımlanma Tarihi 24 Ekim 2023
Gönderilme Tarihi 11 Temmuz 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 6 Sayı: 3

Kaynak Göster

MLA Mesut, Burcu ve Yavuz Selim Çelik. “ARTIFICIAL INTELLIGENCE EVALUATION OF RELEASE PROPERTIES OF TABLET FORMULATION CONTAINING FLURBIPROFEN”. Sağlık Bilimlerinde İleri Araştırmalar Dergisi, c. 6, sy. 3, 2023, ss. 332-6, doi:10.26650/JARHS2023-1325701.