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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | USE OF ARTIFICIAL INTELLIGENCE IN NOVEL DISSOLUTION ENHANCEMENT TECHNIQUES |
| Authors Name: | AKSHAY BABAN JADHAV , Indrajeet D. Gonjari , Pranita K. More , Divya B. Jagdale , Shreevidya M. Yamatkar |
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IJNRD_214108
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| Published Paper Id: | IJNRD2402255 |
| Published In: | Volume 9 Issue 2, February-2024 |
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| Abstract: | Intelligent modelling, which aids in knowledge conception, problem solving, and decision making, is the aim of artificial intelligence (AI). The first studies of what is now called artificial intelligence (AI) were carried out in 1943 by Walter Pits and Warren McCulloch. It used to be believed that artificial intelligence (AI) was only used in engineering. However, artificial intelligence (AI) is now widely applied in the pharmacy sector across a wide range of areas, including hospital pharmacy, drug discovery, formulation development for drug delivery, marketing, management, and marketing. Artificial neural network (ANN) techniques are widely used in pharmaceutical research for data filtering and experimental outcome prediction. Regression analysis and a backpropagation network were used in this work to model a new dissolution outcome prediction and screen system. Drug research and the development of drug delivery formulations involve a large number of Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs) and Recurrent Neural Networks (RNNs). The technology's promise in quantitative structure-property relationship (QSPR) or quantitative structure-activity relationship (QSAR) has been validated, and several drug discovery implementations have been studied. De novo design also promotes the creation of pharmacological compounds with significantly novel properties in terms of intended or ideal attributes. Robots are used by doctors nowadays for a range of medical procedures since they are more dependable than people, have more sophisticated work features, and can finish any task swiftly and effectively. We draw the conclusion that artificial intelligence (AI) is the burgeoning subject that is affecting every business, including pharmacy, and that more work must be done in this area in order to advance the state of the art and carry out fresh investigations. Because of the way the input data was prepared, the relevant data could still be used to train the ANN model even after the formulation composition was changed. This system uses the reference line regression methodology (RLRM) and the effective data regression method (EDRM) to predict dissolution results with a high accuracy rate. Nevertheless, compared to the orthogonal experiment, it requires a smaller database. Additionally, this system implements a decision tree-based data screen function. The drug prediction system created by this artificial neural network (ANN) model is distinct. |
| Keywords: | Artificial Intelligence, Artificial Neural Networks (ANNs), Dissolution Techniques, Theories of Dissolution, Long Short-Term Memory Networks (LSTMs), EDRM, RLRM |
| Cite Article: | "USE OF ARTIFICIAL INTELLIGENCE IN NOVEL DISSOLUTION ENHANCEMENT TECHNIQUES", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 2, page no.c487-c500, February-2024, Available :http://www.ijnrd.org/papers/IJNRD2402255.pdf |
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2402255 Registration ID: 214108 Published In: Volume 9 Issue 2, February-2024 DOI (Digital Object Identifier): Page No: c487-c500 Country: Satara, Maharashtra, India Research Area: Pharmacy Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2402255 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2402255 |
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ISSN: 2456-4184
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