Objectives: Orally disintegrating tablets (ODTs) can be utilized without any drinking water; this feature makes ODTs easy to use and suitable for specific groups of patients. Oral administration of drugs is the most commonly used route, and tablets constitute the most preferable pharmaceutical dosage form. However, the preparation of ODTs is costly and requires long trials, which creates obstacles for dosage trials. The aim of this study was to identify the most appropriate formulation using machine learning (ML) models of ODT dexketoprofen formulations, with the goal of providing a cost-effective and timereducing solution.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), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) methods, as well as the t-test, to predict the quantity of various components in the dexketoprofen formulation within fixed criteria.Results: All the models were developed with Python libraries. The performance of the ML models was evaluated with R2 values and the root mean square error. Hardness values of 0.99 and 2.88, friability values of 0.92 and 0.02, and disintegration time values of 0.97 and 10.09 using the GBM algorithm gave the best results.Conclusions: In this study, we developed a computational approach to estimate the optimal pharmaceutical formulation of dexketoprofen. The results were evaluated by an expert, and it was found that they complied with Food and Drug Administration criteria.

The objective of the current study was to develop an optimized formulation for orally disintegrating tablets (ODTs) containing melatonin. Different particle sizes of mannitol (i.e., filler) were used to study the effects on dissolution and tablet properties using a quality by design (QbD) approach. The quality target product profile was identified, then critical quality attributes (CQAs) were determined. Risk assessment was performed using the Failure Mode Effect Analysis (FMEA) method to identify and rank critical material attributes and process parameters. Thirty-four formulations were prepared and tested. Box-Behnken design (BBD) with response surface methodology was applied to assess the effect of independent factors on CQAs. Finally, the most suitable formulation in terms of tablet properties was determined with Minitab. Specification tests were applied to confirm that the optimized formula met USP requirements. Mannitol with a small particle size had the fastest disintegration time and dissolution rate in ODT formulations containing melatonin.

The present investigation was carried out to develop a taste-masked, orally disintegrating tablet containing Dexketoprofen for evaluating the effect of the coating amount on the product’s quality attributes via Quality by Design (QbD) systematical roadmap. Dexketoprofen, S(+)-enantiomer of bitter taste ketoprofen, involves an arylalkil group which is the most frequently used analgesic in the management of acute and chronic pain. To overcome of bitter-taste of the active pharmacological ingredients should apply a taste-masking approach. For this purpose, the bitter taste dexketoprofen particles were coated with a pH-dependent methacrylates polymer in which one of the method of taste-masking approaches. The experimental design was enforced with a four-factor, three-level Box–Behnken method within the framework of response surface modeling (RSM). A ready to use matrix excipient, Eudragit RS 30D, dextrates, aroma, and tablet pressing force were chosen as independent factors, and were assessed on four dependent factors: dissolution rate, disintegration time, tablet hardness, and friability %. Our findings indicate that when tablet pressing force is applied at 250 PSI, the tablets disintegrate within 1 minute, and the friability value is under 1%. Disintegration time increases as the coating amount increases. However, the Pareto charts shows engrossingly that the dissolution rate is affected mainly by tablet pressing force in first, third, and fifth time points, and by matrix excipient and coating in the 10th, 15th, 20th, and 30th time points. It was concluded that the QbD study helped to understand how the coating amount and process variables impacted the dissolution rate, disintegration time, tablet hardness, and friability % of the Dexketoprofen orally disintegrating tablet (ODT) finished product.

Nanokristal teknolojisi partikül boyutu 1000 nanometre (nm)'nin altında, herhangi bir taşıyıcı sisteme ihtiyaç duymadan katı ilaç partikülerinin üretilmesini sağlar. Sudaki çözünürlüğü düşük ilaçların partiküllerinin boyutunun küçültülmesi ile, yüzey alanlarının artması ve difüzyon tabakasının kalınlığının azaltılması k çözünürlük hızının da artışına yol açar. Buna bağlı olarak, absorpsiyon bölgesinde artan konsantrasyon gradienti bağırsak lümeni ve kan arasındaki pasif difüzyon yoluyla permeasyonu ve emilimi teşvik etmektedir. Dolayısıyla Biyofarmasötik Sınıflandırma Sistemi (BCS) Sınıf II ve IV'e ait ilaç molekülleri için nanokristal teknolojisi yaklaşımını kullanarak biyoyararlanımlarını geliştirmek ve/veya arttırmak oldukça önemlidir. Nanometre boyutunda ilaç partikülü elde edebilmek için yukarıdan aşağıya (top-down) ve aşağıdan yukarıya (bottom-up) yöntemlerinden yararlanılmaktadır. İlaç endüstrisinde uygulama kolaylığı, tekrar edilebilirliği ve ölçeklendirilebilmesi nedeniyle bilyeli değirmende yaş öğütme (BWM) ve yüksek basınçlı homojenizasyon (HPH) olarak alt bölümlere ayrılan yukarıdan aşağıya yöntemleri tercih edilmektedir. Nanokristal teknolojisi ile ilaç endüstrisinde hâlihazırda tedavide onaylanmış olan ilaç moleküllerinin daha az yan etki, daha düşük dozlar ve daha hızlı etki başlangıcı sağlayarak yeni dozaj formlarının geliştirilmesi ve yeni ilaç moleküllerinin daha iyi bir biyoyararlanımla formüle edilebilmesi amaçlanmaktadır.