Determination of Levadopa and Benserazide Active Ingredients Used in Parkinson's Treatment by Artificial Neural Networks Method

Ahmet Hakan Aktaş

Makale detayları

Determination of Levadopa and Benserazide Active Ingredients Used in Parkinson's Treatment by Artificial Neural Networks Method

Yazarlar:

Ahmet Hakan Aktaş

Yayıncı:

Dokuz Eylul University

Dergi:

Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi Vol.25 Issue 74, pp.329-337

Belge Tipi:

Makale

Yayın Tarihi:

5/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001289554

pISSN:

1302-9304

Anahtar kelimeler:

Özet:

 In this study, the determinations of levadopa and benserazide active ingredients in the tablet drug sample were carried out by ultraviolet visible region spectroscopy without applying any separation process at the same time and the obtained data were evaluated by artificial neural networks ANN chemometric method. At the end of the study, the least squares method PLS was applied to compare the method used. In the study, the pure spectra of the active ingredients were obtained and then their synthetic mixtures were prepared. The ata obtained from these mixtures were evaluated with ANN and the method was applied to the tablet sample purchased from the market. The data obtained in the study were also analyzed statistically, and the root mean square RMS data, which is an important data group in the ANN method, was found to be quite small. In addition, the calculated recovery values are quite high and their standard deviations are small enough. The results obtained with the help of the applied chemometric method are extremely fast, simple and reliable results.

 In this study, the determinations of levadopa and benserazide active ingredients in the tablet drug sample were carried out by ultraviolet visible region spectroscopy without applying any separation process at the same time and the obtained data were evaluated by artificial neural networks ANN chemometric method. At the end of the study, the least squares method PLS was applied to compare the method used. In the study, the pure spectra of the active ingredients were obtained and then their synthetic mixtures were prepared. The ata obtained from these mixtures were evaluated with ANN and the method was applied to the tablet sample purchased from the market. The data obtained in the study were also analyzed statistically, and the root mean square RMS data, which is an important data group in the ANN method, was found to be quite small. In addition, the calculated recovery values are quite high and their standard deviations are small enough. The results obtained with the help of the applied chemometric method are extremely fast, simple and reliable results.

 In this study, the determinations of levadopa and benserazide active ingredients in the tablet drug sample were carried out by ultraviolet visible region spectroscopy without applying any separation process at the same time and the obtained data were evaluated by artificial neural networks ANN chemometric method. At the end of the study, the least squares method PLS was applied to compare the method used. In the study, the pure spectra of the active ingredients were obtained and then their synthetic mixtures were prepared. The ata obtained from these mixtures were evaluated with ANN and the method was applied to the tablet sample purchased from the market. The data obtained in the study were also analyzed statistically, and the root mean square RMS data, which is an important data group in the ANN method, was found to be quite small. In addition, the calculated recovery values are quite high and their standard deviations are small enough. The results obtained with the help of the applied chemometric method are extremely fast, simple and reliable results.

 Bu çalışmada, tablet ilaç numunesinde bulunan levadopa ve benserazid etken maddelerinin aynı anda miktar tayinlerine hiçbir ayırma işlemi uygulanmaksızın ultraviyole görünür bölge spektroskopisi ile tayinleri gerçekleştirilmiş ve elde edilen veriler yapay sinir ağları ANN kemometrik yöntemi ile değerlendirilmiştir. Çalışmanın sonunda kullanılan yöntemi karşılaştırmak amacıyla kısmi en küçük kareler yöntemi PLS uygulanmıştır. Yapılan çalışmada etken maddelerin saf haldeki spektrumları elde edilmiş takiben sentetik karışımları hazırlanmıştır. Bu karışımlardan elde edilen veriler ANN ile değerlendirilmiş ve yöntem piyasadan alınan tablet numunesine uygulanmıştır. Çalışmada elde edilen veriler istatistiksel olarak da incelenmiş, ANN yönteminde önemli bir veri grubu olan karekök ortalama hata RMS verileri oldukça küçük bulunmuştur. Ayrıca hesaplanan geri kazanım değerleri oldukça yüksek, standart sapmaları ise yeterince küçüktür. Uygulanan kemometrik yöntem yardımıyla elde edilen sonuçlar son derece hızlı, basit ve güvenilir sonuçlardır.

Makale detayları

Determination of Levadopa and Benserazide Active Ingredients Used in Parkinson's Treatment by Artificial Neural Networks Method

Yazarlar:

Ahmet Hakan Aktaş

Yayıncı:

Dokuz Eylul University

Dergi:

Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi Vol.25 Issue 74, pp.329-337

Belge Tipi:

Makale

Yayın Tarihi:

5/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001289554

pISSN:

1302-9304

Drug

Levadopa

Benserazid

Artificial Neural Networkİlaç

Levadopa

Benserazid

Yapay sinir ağları

Sayı

Makale detayları

Yazarlar: Ahmet Hakan Aktaş

Yayıncı: Dokuz Eylul University

Dergi: Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi Vol.25 Issue 74, pp.329-337

Belge Tipi: Makale

Yayın Tarihi: 5/2023

Belge Dili: Türkçe

Document ID (Org No.): 2001289554

pISSN: 1302-9304

Sayı

Yazarlar:

Ahmet Hakan Aktaş

Yayıncı:

Dokuz Eylul University

Dergi:

Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi Vol.25 Issue 74, pp.329-337

Belge Tipi:

Makale

Yayın Tarihi:

5/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001289554

pISSN:

1302-9304