Existing drug treatments may be inadequate for all the old and new diseases that people face every day. Therefore, the discovery and development of new drugs is an inevitable necessity to protect human health and treat diseases. Discovering a new drug involves many steps, such as selecting the drug with therapeutic effect from a large number of active compounds, determining the ADMET properties of the drug, and conducting clinical studies to determine its toxicity and side effect profile. It’s a costly and time-consuming process. According to the California Biomedical Research Association, it takes an average of 12 years and $359 million to get a drug from the lab to the patient. With the increase in digitalization in the field of health, as in every field, scientists have resorted to artificial intelligence to solve the problem of cost and time. Pharmaceutical manufacturing companies have made major investments and developed numerous artificial intelligence-based algorithms to be used in different stages of drug discovery. With the use of these algorithms in drug discovery and research, the money and time spent has decreased and efficiency has increased. This mini-review discusses artificial intelligence applications in drug discovery and research.
Primary Language | English |
---|---|
Subjects | Artificial Intelligence (Other) |
Journal Section | Reviews |
Authors | |
Publication Date | December 27, 2024 |
Submission Date | November 18, 2024 |
Acceptance Date | December 13, 2024 |
Published in Issue | Year 2024 Volume: 4 Issue: 2 |
All articles published by JAIDA are licensed under a Creative Commons Attribution 4.0 International License.