Role of artificial intelligence in quality profiling and optimization of drug products
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Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In the pharmaceutical industry, one of the sectors with the highest research and development potential today, the development of safe and effective new drug active ingredients and formulations is an expensive and long process. It has rapidly adapted to the developing technologies; modern production tools have been developed to help increase the production quality as a result of the important developments in quality and risk management systems in recent years. The development of these modern tools has resulted in positive outcomes such as increase in quality and decrease in cost of the products, advocating quality while designing instead of testing it as stated in the ICH Q8 guide. With these approaches, it is attempted to reduce the uncertainty and pharmaceutical authorities have published the ICH Q9 guide, which will meet this need and be used to identify risks and made it available to the pharmaceutical industry. This guide defines risk and describes the methodologies that can be applied to identify risks in processes and drug design. The ICH Q8 and ICH Q9 guidelines should be applied together and recommend using statistical tools in the formulation development process. During the formulation development phase, both the design areas and the determination of the most appropriate formulation create very complex data and models while trying to analyze studies in theory and practice, and although there is sufficient knowledge, the human capacity to evaluate the whole data at once is limited. Therefore, it is necessary to get support from various software in order to manage the drug development process more efficiently. Machine learning methods can quickly help create and improve products, increase productivity, consistency, and quality. Machine learning models make predictions based on empirical data and provide an excellent opportunity to develop the most appropriate and effective formulations.
Açıklama
Anahtar Kelimeler
Artificial intelligence, Machine learning, Optimization, Qbd, Quality, Risk assessment
Kaynak
A Handbook of Artificial Intelligence in Drug Delivery
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Mesut, B., Başkor, A., Aksu, N. B. (2023). Role of artificial intelligence in quality profiling and optimization of drug products. A Handbook of Artificial Intelligence in Drug Delivery, 35-54.
