Article: Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents.
Evidence-based complementary and alternative medicine : eCAM
2022 Volume 2022, Page(s) 6201067
Abstract: Spectacular developments in molecular and cellular biology have led to important discoveries in cancer research. Despite cancer is one of the major causes of morbidity and mortality globally, diabetes is one of the most leading sources of group of ... ...
Abstract | Spectacular developments in molecular and cellular biology have led to important discoveries in cancer research. Despite cancer is one of the major causes of morbidity and mortality globally, diabetes is one of the most leading sources of group of disorders. Artificial intelligence (AI) has been considered the fourth industrial revolution machine. The most major hurdles in drug discovery and development are the time and expenditures required to sustain the drug research pipeline. Large amounts of data can be explored and generated by AI, which can then be converted into useful knowledge. Because of this, the world's largest drug companies have already begun to use AI in their drug development research. In the present era, AI has a huge amount of potential for the rapid discovery and development of new anticancer drugs. Clinical studies, electronic medical records, high-resolution medical imaging, and genomic assessments are just a few of the tools that could aid drug development. Large data sets are available to researchers in the pharmaceutical and medical fields, which can be analyzed by advanced AI systems. This review looked at how computational biology and AI technologies may be utilized in cancer precision drug development by combining knowledge of cancer medicines, drug resistance, and structural biology. This review also highlighted a realistic assessment of the potential for AI in understanding and managing diabetes. |
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Language | English |
Publishing date | 2022-04-25 |
Publishing country | United States |
Document type | Journal Article ; Review ; Retracted Publication |
ZDB-ID | 2171158-6 |
ISSN | 1741-4288 ; 1741-427X |
ISSN (online) | 1741-4288 |
ISSN | 1741-427X |
DOI | 10.1155/2022/6201067 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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