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On Machine Learning Approach for the Design of Pharmaceutical Technology of Tablets: Acetyl Salicylic Acid with Atorvastatin

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

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Abstract

The objective of this work is to offer an approach of application of machine learning (ML) in the problem of design of pharmaceutical technology of tablets, which basically consists of choosing qualitative and quantitative content of the corresponding excipients, enabling us necessary values of pharmaceutical and technological characteristics. At the first stage, we choose technology and qualitative content of tablets, including filler, acidity regulator, disintegrant, binder and stabilizer. After selecting excipients ensuring some acceptable values of output variables for tablets, at the second stage, the problem of optimization of some objective variable is considered subject to quantitative content of excipients. An example, which is devoted to the development of a technology of tablets of acetylsalicylic acid with atorvastatin is considered.

Supported by University of Bielsko-Biala.

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Notes

  1. 1.

    It can be some complex of ingredients, as it is shown in Sect. 3.

  2. 2.

    Without loss of generality we look for minimal value.

  3. 3.

    Without loss of generality we choose unique index \(j^*\) for all excipients, which it can be reached by reordering levels.

  4. 4.

    It is example of code for input variable A.

  5. 5.

    The quantity of 18 neurons (i.e. 2/3 of the quantity of input variables) was chosen experimentally with the aim to reach the smallest mean-squared error (MSE).

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Authors and Affiliations

  1. Department of Computer Science and Automatics, University of Bielsko-Biala, 43-309, Bielsko-Biala, Poland

    Vasyl Martsenyuk & Aleksandra Klos-Witkowska

  2. Ternopil State Medical University, Ternopil, 46001, Ukraine

    Taras Hroshovyi & Oksana Trygubchak

Authors
  1. Vasyl Martsenyuk
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  2. Taras Hroshovyi
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  3. Oksana Trygubchak
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  4. Aleksandra Klos-Witkowska
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Corresponding author

Correspondence to Vasyl Martsenyuk .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Martsenyuk, V., Hroshovyi, T., Trygubchak, O., Klos-Witkowska, A. (2019). On Machine Learning Approach for the Design of Pharmaceutical Technology of Tablets: Acetyl Salicylic Acid with Atorvastatin. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_20

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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