Artificial intelligence in drug development: reshaping the therapeutic landscape
Artificial intelligence (AI) is transforming medication research and development, giving clinicians new treatment options. Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boost...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-02-01
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| Series: | Therapeutic Advances in Drug Safety |
| Online Access: | https://doi.org/10.1177/20420986251321704 |
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| _version_ | 1850081765348081664 |
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| author | Sarfaraz K. Niazi Zamara Mariam |
| author_facet | Sarfaraz K. Niazi Zamara Mariam |
| author_sort | Sarfaraz K. Niazi |
| collection | DOAJ |
| description | Artificial intelligence (AI) is transforming medication research and development, giving clinicians new treatment options. Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. Furthermore, generative AI is accelerating the development and re-engineering of medicinal molecules to cater to both common and rare diseases. Although, to date, no AI-generated medicinal drug has been FDA-approved, HLX-0201 for fragile X syndrome and new molecules for idiopathic pulmonary fibrosis have entered clinical trials. However, AI models are generally considered “black boxes,” making their conclusions challenging to understand and limiting the potential due to a lack of model transparency and algorithmic bias. Despite these obstacles, AI-driven drug discovery has substantially reduced development times and costs, expediting the process and financial risks of bringing new medicines to market. In the future, AI is expected to continue to impact pharmaceutical innovation positively, making life-saving drug discoveries faster, more efficient, and more widespread. |
| format | Article |
| id | doaj-art-b1f2318ce80d4fe7b6113f2b14302cea |
| institution | DOAJ |
| issn | 2042-0994 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Therapeutic Advances in Drug Safety |
| spelling | doaj-art-b1f2318ce80d4fe7b6113f2b14302cea2025-08-20T02:44:39ZengSAGE PublishingTherapeutic Advances in Drug Safety2042-09942025-02-011610.1177/20420986251321704Artificial intelligence in drug development: reshaping the therapeutic landscapeSarfaraz K. NiaziZamara MariamArtificial intelligence (AI) is transforming medication research and development, giving clinicians new treatment options. Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. Furthermore, generative AI is accelerating the development and re-engineering of medicinal molecules to cater to both common and rare diseases. Although, to date, no AI-generated medicinal drug has been FDA-approved, HLX-0201 for fragile X syndrome and new molecules for idiopathic pulmonary fibrosis have entered clinical trials. However, AI models are generally considered “black boxes,” making their conclusions challenging to understand and limiting the potential due to a lack of model transparency and algorithmic bias. Despite these obstacles, AI-driven drug discovery has substantially reduced development times and costs, expediting the process and financial risks of bringing new medicines to market. In the future, AI is expected to continue to impact pharmaceutical innovation positively, making life-saving drug discoveries faster, more efficient, and more widespread.https://doi.org/10.1177/20420986251321704 |
| spellingShingle | Sarfaraz K. Niazi Zamara Mariam Artificial intelligence in drug development: reshaping the therapeutic landscape Therapeutic Advances in Drug Safety |
| title | Artificial intelligence in drug development: reshaping the therapeutic landscape |
| title_full | Artificial intelligence in drug development: reshaping the therapeutic landscape |
| title_fullStr | Artificial intelligence in drug development: reshaping the therapeutic landscape |
| title_full_unstemmed | Artificial intelligence in drug development: reshaping the therapeutic landscape |
| title_short | Artificial intelligence in drug development: reshaping the therapeutic landscape |
| title_sort | artificial intelligence in drug development reshaping the therapeutic landscape |
| url | https://doi.org/10.1177/20420986251321704 |
| work_keys_str_mv | AT sarfarazkniazi artificialintelligenceindrugdevelopmentreshapingthetherapeuticlandscape AT zamaramariam artificialintelligenceindrugdevelopmentreshapingthetherapeuticlandscape |