Estimating the Optimal Dexketoprofen Pharmaceutical Formulation with Machine Learning Methods and Statistical Approaches

Atakan Başkor; Yağmur Pirinçci Tok; Burcu Mesut; Yıldız Özsoy; Tamer Uçar

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자료유형: 학술저널

저자정보: Atakan Başkor (Bahcesehir University) Yağmur Pirinçci Tok (Istanbul University) Burcu Mesut (Istanbul University) Yıldız Özsoy (Istanbul University) Tamer Uçar (Bahcesehir University)

저널정보: 대한의료정보학회 Healthcare Informatics Research Healthcare Informatics Research 제27권 제4호

발행연도: 2021.10

수록면: 279 - 286 (8page)

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Objectives: Orally disintegrating tablets (ODTs) can be utilized without any drinking water; this feature makes ODTs easy touse and suitable for specific groups of patients. Oral administration of drugs is the most commonly used route, and tabletsconstitute the most preferable pharmaceutical dosage form. However, the preparation of ODTs is costly and requires longtrials, which creates obstacles for dosage trials. The aim of this study was to identify the most appropriate formulation usingmachine learning (ML) models of ODT dexketoprofen formulations, with the goal of providing a cost-effective and timereducingsolution. Methods: This research utilized nonlinear regression models, including the k-nearest neighborhood (k-NN), support vector regression (SVR), classification and regression tree (CART), bootstrap aggregating (bagging), randomforest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) methods, as well as the t-test, topredict the quantity of various components in the dexketoprofen formulation within fixed criteria. Results: All the modelswere developed with Python libraries. The performance of the ML models was evaluated with R2 values and the root meansquare error. Hardness values of 0.99 and 2.88, friability values of 0.92 and 0.02, and disintegration time values of 0.97 and10.09 using the GBM algorithm gave the best results. Conclusions: In this study, we developed a computational approach toestimate the optimal pharmaceutical formulation of dexketoprofen. The results were evaluated by an expert, and it was foundthat they complied with Food and Drug Administration criteria.

#Machine Learning #Statistics #Data Analysis #Dexketoprofen Trometamol #Pharmaceutical Preparations

참고문헌 (23)

참고문헌 신청

Ezcurdia M / 1998 / Comparison of the efficacy and tolerability of dexketoprofen and ketoprofen in the treatment of primary dysmenorrhea / J Clin Pharmacol (38):65S~73S

Kara I / 2011 / The effects of preemptive dexketoprofen use on postoperative pain relief and tramadol consumption / Agri 23(1):18~21

Mesut B / 2013 / Design of sustained release tablet formulations of alfuzosin HCl by means of neurofuzzy logic / Lat Am J Pharmacy 32(9):1288~1297

Selma Dere / 2020 / Prediction of Drug–Drug Interactions by Using Profile Fingerprint Vectors and Protein Similarities / Healthcare Informatics Research 26(1):42~49

Ahamad MM / 2020 / A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients / Expert Syst Appl 160:113661

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