Cargando…
Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms
Artificial Intelligence (AI)-based formulation development is a promising approach for facilitating the drug product development process. AI is a versatile tool that contains multiple algorithms that can be applied in various circumstances. Solid dosage forms, represented by tablets, capsules, powde...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694557/ https://www.ncbi.nlm.nih.gov/pubmed/36365076 http://dx.doi.org/10.3390/pharmaceutics14112257 |
_version_ | 1784837830171688960 |
---|---|
author | Jiang, Junhuang Ma, Xiangyu Ouyang, Defang Williams, Robert O. |
author_facet | Jiang, Junhuang Ma, Xiangyu Ouyang, Defang Williams, Robert O. |
author_sort | Jiang, Junhuang |
collection | PubMed |
description | Artificial Intelligence (AI)-based formulation development is a promising approach for facilitating the drug product development process. AI is a versatile tool that contains multiple algorithms that can be applied in various circumstances. Solid dosage forms, represented by tablets, capsules, powder, granules, etc., are among the most widely used administration methods. During the product development process, multiple factors including critical material attributes (CMAs) and processing parameters can affect product properties, such as dissolution rates, physical and chemical stabilities, particle size distribution, and the aerosol performance of the dry powder. However, the conventional trial-and-error approach for product development is inefficient, laborious, and time-consuming. AI has been recently recognized as an emerging and cutting-edge tool for pharmaceutical formulation development which has gained much attention. This review provides the following insights: (1) a general introduction of AI in the pharmaceutical sciences and principal guidance from the regulatory agencies, (2) approaches to generating a database for solid dosage formulations, (3) insight on data preparation and processing, (4) a brief introduction to and comparisons of AI algorithms, and (5) information on applications and case studies of AI as applied to solid dosage forms. In addition, the powerful technique known as deep learning-based image analytics will be discussed along with its pharmaceutical applications. By applying emerging AI technology, scientists and researchers can better understand and predict the properties of drug formulations to facilitate more efficient drug product development processes. |
format | Online Article Text |
id | pubmed-9694557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96945572022-11-26 Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms Jiang, Junhuang Ma, Xiangyu Ouyang, Defang Williams, Robert O. Pharmaceutics Review Artificial Intelligence (AI)-based formulation development is a promising approach for facilitating the drug product development process. AI is a versatile tool that contains multiple algorithms that can be applied in various circumstances. Solid dosage forms, represented by tablets, capsules, powder, granules, etc., are among the most widely used administration methods. During the product development process, multiple factors including critical material attributes (CMAs) and processing parameters can affect product properties, such as dissolution rates, physical and chemical stabilities, particle size distribution, and the aerosol performance of the dry powder. However, the conventional trial-and-error approach for product development is inefficient, laborious, and time-consuming. AI has been recently recognized as an emerging and cutting-edge tool for pharmaceutical formulation development which has gained much attention. This review provides the following insights: (1) a general introduction of AI in the pharmaceutical sciences and principal guidance from the regulatory agencies, (2) approaches to generating a database for solid dosage formulations, (3) insight on data preparation and processing, (4) a brief introduction to and comparisons of AI algorithms, and (5) information on applications and case studies of AI as applied to solid dosage forms. In addition, the powerful technique known as deep learning-based image analytics will be discussed along with its pharmaceutical applications. By applying emerging AI technology, scientists and researchers can better understand and predict the properties of drug formulations to facilitate more efficient drug product development processes. MDPI 2022-10-22 /pmc/articles/PMC9694557/ /pubmed/36365076 http://dx.doi.org/10.3390/pharmaceutics14112257 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Jiang, Junhuang Ma, Xiangyu Ouyang, Defang Williams, Robert O. Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms |
title | Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms |
title_full | Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms |
title_fullStr | Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms |
title_full_unstemmed | Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms |
title_short | Emerging Artificial Intelligence (AI) Technologies Used in the Development of Solid Dosage Forms |
title_sort | emerging artificial intelligence (ai) technologies used in the development of solid dosage forms |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694557/ https://www.ncbi.nlm.nih.gov/pubmed/36365076 http://dx.doi.org/10.3390/pharmaceutics14112257 |
work_keys_str_mv | AT jiangjunhuang emergingartificialintelligenceaitechnologiesusedinthedevelopmentofsoliddosageforms AT maxiangyu emergingartificialintelligenceaitechnologiesusedinthedevelopmentofsoliddosageforms AT ouyangdefang emergingartificialintelligenceaitechnologiesusedinthedevelopmentofsoliddosageforms AT williamsroberto emergingartificialintelligenceaitechnologiesusedinthedevelopmentofsoliddosageforms |