| _version_ | 1866902017760296960 |
|---|---|
| author | Boomisha S. D.*, Jemmy Christy H. |
| author_facet | Boomisha S. D.*, Jemmy Christy H. |
| contents | <p><span>Artificial intelligence (AI) is the technology and science of creating intelligent machines by using algorithms which the machine adheres to in order to mimic human cognitive functions like learning and problem solving. Artificial intelligence (AI) is the term used to describe computer programs that simulate the mechanisms that support the intellect of humans, including as engagement, deep learning, reasoning, adaptation, and sensory comprehension. It aims to mimic human cognitive functions. This article examines the prospective applications of AI in drug discovery, emphasizing significant developments and their possible effects. Target identification is being expedited by AI-driven predictive modeling, which is also expediting the identification of prospective medication candidates. An expedient and economical substitute for conventional drug development is provided by AI's capacity to mine data for drug repurposing. Artificial Intelligence enhances patient recruiting and trial management in clinical trials, leading to better efficiency and results. The combination of AI with large data and omics technology is yielding new insights, and in silico testing is predicting the safety and effectiveness of pharmaceuticals. Collaborative platforms driven by AI are also accelerating research and promoting open innovation. This paper highlights the enormous influence artificial intelligence (AI) is expected to have on drug discovery, with the potential to produce novel and efficient treatments that would significantly improve global healthcare.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14907864 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI in Drug Discovery Boomisha S. D.*, Jemmy Christy H. Artificial Intelligence, Drug Discovery, Machine Learning, Structure – based drug design, Ligand – based drug design <p><span>Artificial intelligence (AI) is the technology and science of creating intelligent machines by using algorithms which the machine adheres to in order to mimic human cognitive functions like learning and problem solving. Artificial intelligence (AI) is the term used to describe computer programs that simulate the mechanisms that support the intellect of humans, including as engagement, deep learning, reasoning, adaptation, and sensory comprehension. It aims to mimic human cognitive functions. This article examines the prospective applications of AI in drug discovery, emphasizing significant developments and their possible effects. Target identification is being expedited by AI-driven predictive modeling, which is also expediting the identification of prospective medication candidates. An expedient and economical substitute for conventional drug development is provided by AI's capacity to mine data for drug repurposing. Artificial Intelligence enhances patient recruiting and trial management in clinical trials, leading to better efficiency and results. The combination of AI with large data and omics technology is yielding new insights, and in silico testing is predicting the safety and effectiveness of pharmaceuticals. Collaborative platforms driven by AI are also accelerating research and promoting open innovation. This paper highlights the enormous influence artificial intelligence (AI) is expected to have on drug discovery, with the potential to produce novel and efficient treatments that would significantly improve global healthcare.</span></p> |
| title | AI in Drug Discovery |
| topic | Artificial Intelligence, Drug Discovery, Machine Learning, Structure – based drug design, Ligand – based drug design |
| url | https://doi.org/10.5281/zenodo.14907864 |