[HTML][HTML] A review of disintegration mechanisms and measurement techniques

D Markl, JA Zeitler - Pharmaceutical research, 2017 - Springer
Pharmaceutical solid dosage forms (tablets or capsules) are the predominant form to
administer active pharmaceutical ingredients (APIs) to the patient. Tablets are typically …

[HTML][HTML] Application of artificial neural networks in the process analytical technology of pharmaceutical manufacturing—a review

B Nagy, DL Galata, A Farkas, ZK Nagy - The AAPS Journal, 2022 - Springer
Industry 4.0 has started to transform the manufacturing industries by embracing
digitalization, automation, and big data, aiming for interconnected systems, autonomous …

[HTML][HTML] Real-time release testing of dissolution based on surrogate models developed by machine learning algorithms using NIR spectra, compression force and …

DL Galata, Z Könyves, B Nagy, M Novák… - International Journal of …, 2021 - Elsevier
In this work spectroscopic measurements, process data and Critical Material Attributes
(CMAs) are used to predict the in vitro dissolution profile of sustained-release tablets with …

A quality by design approach in oral extended release drug delivery systems: where we are and where we are going?

AS Sousa, J Serra, C Estevens, R Costa… - Journal of …, 2023 - Springer
Background Oral extended release (ER) delivery systems have quickly gained increasing
importance because of their ability to maintain drug levels in the blood more consistently …

[HTML][HTML] Predicting complexation performance between cyclodextrins and guest molecules by integrated machine learning and molecular modeling techniques

Q Zhao, Z Ye, Y Su, D Ouyang - Acta Pharmaceutica Sinica B, 2019 - Elsevier
Most pharmaceutical formulation developments are complex and ideal formulations are
generally obtained after extensive experimentation. Machine learning is increasingly …

[HTML][HTML] Predicting oral disintegrating tablet formulations by neural network techniques

R Han, Y Yang, X Li, D Ouyang - Asian journal of pharmaceutical sciences, 2018 - Elsevier
Oral disintegrating tablets (ODTs) are a novel dosage form that can be dissolved on the
tongue within 3 min or less especially for geriatric and pediatric patients. Current ODT …

Applications of machine learning in solid oral dosage form development

H Lou, B Lian, MJ Hageman - Journal of Pharmaceutical Sciences, 2021 - Elsevier
This review comprehensively summarizes the application of machine learning in solid oral
dosage form development over the past three decades. In both academia and industry …

[HTML][HTML] Performance appraisal of Trichoderma viride based novel tablet and powder formulations for management of Fusarium wilt disease in chickpea

PC Pradhan, A Mukhopadhyay, R Kumar… - Frontiers in Plant …, 2022 - frontiersin.org
In developing a Trichoderma viride-based biocontrol program for Fusarium wilt disease in
chickpea, the choice of the quality formulation is imperative. In the present study, two types …

Application of artificial intelligence in pharmaceutical and biomedical studies

A Thakur, AP Mishra, B Panda… - Current …, 2020 - ingentaconnect.com
Background: Artificial intelligence (AI) is the way to model human intelligence to accomplish
certain tasks without much intervention of human beings. The term AI was first used in 1956 …

[HTML][HTML] A prediction model based on artificial intelligence techniques for disintegration time and hardness of fast disintegrating tablets in pre-formulation tests

M Momeni, M Afkanpour, S Rakhshani… - BMC Medical Informatics …, 2024 - Springer
Background The pharmaceutical industry is continually striving to innovate drug
development and formulation processes. Orally disintegrating tablets (ODTs) have gained …