Article ; Online: Pharma's Bio-AI revolution.
2023 Volume 28, Issue 5, Page(s) 103515
Abstract: Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Recently, a dramatic regulatory change ... ...
Abstract | Drug development has become unbearably slow and expensive. A key underlying problem is the clinical prediction challenge: the inability to predict which drug candidates will be safe in the human body and for whom. Recently, a dramatic regulatory change has removed FDA's mandated reliance on antiquated, ineffective animal studies. A new frontier is an integration of several disruptive technologies [machine learning (ML), patient-on-chip, real-time sensing, and stem cells], which when integrated, have the potential to address this challenge, drastically cutting the time and cost of developing drugs, and tailoring them to individual patients. |
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MeSH term(s) | Animals ; Humans ; Artificial Intelligence ; Machine Learning ; Drug Development |
Language | English |
Publishing date | 2023-02-02 |
Publishing country | England |
Document type | Journal Article ; Review |
ZDB-ID | 1324988-5 |
ISSN | 1878-5832 ; 1359-6446 |
ISSN (online) | 1878-5832 |
ISSN | 1359-6446 |
DOI | 10.1016/j.drudis.2023.103515 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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