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10.1080/17460441.2021.1883585 http://scihub22266oqcxt.onion/10.1080/17460441.2021.1883585 33543671!ä!33543671 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Expert+Opin+Drug+Discov 2021 ; 16 (9): 977-989 Nephropedia Template TP {{tp|p=33543671|t=2021. Artificial intelligence, machine learning, and drug repurposing in cancer |pdf=|usr=}}{{33543671}} gab.com Text Artificial intelligence, machine learning, and drug repurposing in cancer JO: Expert Opin Drug Discov http://www.kidney.de/pget.php?&tw=1&pmid=33543671 #FOAvip Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means.Areas covered: The authors focus on supervised ML and AI methods that make use of publicly available databases and information resources. While most of the example applications are in the field of anticancer drug therapies, the methods and resources reviewed are widely applicable also to other indications including COVID-19 treatment. A particular emphasis is placed on the use of comprehensive target activity profiles that enable a systematic repurposing process by extending the target profile of drugs to include potent off-targets with therapeutic potential for a new indication.Expert opinion: The scarcity of clinical patient data and the current focus on genetic aberrations as primary drug targets may limit the performance of anticancer drug repurposing approaches that rely solely on genomics-based information. Functional testing of cancer patient cells exposed to a large number of targeted therapies and their combinations provides an additional source of repurposing information for tissue-aware AI approaches. Twit Text FOAVip Artificial intelligence, machine learning, and drug repurposing in cancer ????Expert Opin Drug Discov http://www.kidney.de/pget.php?&tw=1&pmid=33543671 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33543671 #FOAvip English Wikipedia <ref>{{Cite pmid|33543671}}</ref> Artificial intelligence, machine learning, and drug repurposing in cancer #MMPMID33543671 Tanoli Z; Vaha-Koskela M; Aittokallio T Expert Opin Drug Discov 2021[Sep]; 16 (9): 977-989 PMID33543671show ga Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means.Areas covered: The authors focus on supervised ML and AI methods that make use of publicly available databases and information resources. While most of the example applications are in the field of anticancer drug therapies, the methods and resources reviewed are widely applicable also to other indications including COVID-19 treatment. A particular emphasis is placed on the use of comprehensive target activity profiles that enable a systematic repurposing process by extending the target profile of drugs to include potent off-targets with therapeutic potential for a new indication.Expert opinion: The scarcity of clinical patient data and the current focus on genetic aberrations as primary drug targets may limit the performance of anticancer drug repurposing approaches that rely solely on genomics-based information. Functional testing of cancer patient cells exposed to a large number of targeted therapies and their combinations provides an additional source of repurposing information for tissue-aware AI approaches. |*Artificial Intelligence[MESH] |Antineoplastic Agents/pharmacology[MESH] |Big Data[MESH] |COVID-19 Drug Treatment[MESH] |Cost-Benefit Analysis[MESH] |Drug Development/economics/methods[MESH] |Drug Repositioning/economics/*methods[MESH] |Genomics/methods[MESH] |Humans[MESH] |Machine Learning[MESH]Artificial intelligence, machine learning, and drug repurposing in can(epmc).pdf DeepDyve Pubget Overpricing