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10.1002/adtp.202000034 http://scihub22266oqcxt.onion/10.1002/adtp.202000034 C7235487/?report=reader!7235487!32838027     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Adv+Ther+(Weinh) 2020 ; 3 (7): ä Nephropedia Template TP {{tp|p=32838027|t=2020. Project IDentif AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention |pdf=|usr=}}{{32838027}} gab.com Text Project IDentif AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention JO: Adv Ther (Weinh) http://www.kidney.de/pget.php?&tw=1&pmid=32838027 #FOAvip In 2019/2020, the emergence of coronavirus disease 2019 (COVID?19) resulted in rapid increases in infection rates as well as patient mortality. Treatment options addressing COVID?19 included drug repurposing, investigational therapies such as remdesivir, and vaccine development. Combination therapy based on drug repurposing is among the most widely pursued of these efforts. Multi?drug regimens are traditionally designed by selecting drugs based on their mechanism of action. This is followed by dose?finding to achieve drug synergy. This approach is widely?used for drug development and repurposing. Realizing synergistic combinations, however, is a substantially different outcome compared to globally optimizing combination therapy, which realizes the best possible treatment outcome by a set of candidate therapies and doses toward a disease indication. To address this challenge, the results of Project IDentif.AI (Identifying Infectious Disease Combination Therapy with Artificial Intelligence) are reported. An AI?based platform is used to interrogate a massive 12 drug/dose parameter space, rapidly identifying actionable combination therapies that optimally inhibit A549 lung cell infection by vesicular stomatitis virus within three days of project start. Importantly, a sevenfold difference in efficacy is observed between the top?ranked combination being optimally and sub?optimally dosed, demonstrating the critical importance of ideal drug and dose identification. This platform is disease indication and disease mechanism?agnostic, and potentially applicable to the systematic N?of?1 and population?wide design of highly efficacious and tolerable clinical regimens. This work also discusses key factors ranging from healthcare economics to global health policy that may serve to drive the broader deployment of this platform to address COVID?19 and future pandemics. Twit Text FOAVip Project IDentif AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention ????Adv Ther (Weinh) http://www.kidney.de/pget.php?&tw=1&pmid=32838027 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32838027 #FOAvip English Wikipedia <ref>{{Cite pmid|32838027}}</ref> Project IDentif AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention #MMPMID32838027 Abdulla A; Wang B; Qian F; Kee T; Blasiak A; Ong YH; Hooi L; Parekh F; Soriano R; Olinger GG; Keppo J; Hardesty CL; Chow EK; Ho D; Ding X Adv Ther (Weinh) 2020[Jul]; 3 (7): ä PMID32838027show ga In 2019/2020, the emergence of coronavirus disease 2019 (COVID?19) resulted in rapid increases in infection rates as well as patient mortality. Treatment options addressing COVID?19 included drug repurposing, investigational therapies such as remdesivir, and vaccine development. Combination therapy based on drug repurposing is among the most widely pursued of these efforts. Multi?drug regimens are traditionally designed by selecting drugs based on their mechanism of action. This is followed by dose?finding to achieve drug synergy. This approach is widely?used for drug development and repurposing. Realizing synergistic combinations, however, is a substantially different outcome compared to globally optimizing combination therapy, which realizes the best possible treatment outcome by a set of candidate therapies and doses toward a disease indication. To address this challenge, the results of Project IDentif.AI (Identifying Infectious Disease Combination Therapy with Artificial Intelligence) are reported. An AI?based platform is used to interrogate a massive 12 drug/dose parameter space, rapidly identifying actionable combination therapies that optimally inhibit A549 lung cell infection by vesicular stomatitis virus within three days of project start. Importantly, a sevenfold difference in efficacy is observed between the top?ranked combination being optimally and sub?optimally dosed, demonstrating the critical importance of ideal drug and dose identification. This platform is disease indication and disease mechanism?agnostic, and potentially applicable to the systematic N?of?1 and population?wide design of highly efficacious and tolerable clinical regimens. This work also discusses key factors ranging from healthcare economics to global health policy that may serve to drive the broader deployment of this platform to address COVID?19 and future pandemics. äProject IDentif AI: Harnessing Artificial Intelligence to Rapidly Opti(epmc).pdf DeepDyve Pubget Overpricing