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10.1186/s40360-021-00519-5 http://scihub22266oqcxt.onion/10.1186/s40360-021-00519-5 34674775!8529228!34674775     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BMC+Pharmacol+Toxicol 2021 ; 22 (1): 61 Nephropedia Template TP {{tp|p=34674775|t=2021. Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19 |pdf=|usr=}}{{34674775}} gab.com Text Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19 JO: BMC Pharmacol Toxicol http://www.kidney.de/pget.php?&tw=1&pmid=34674775 #FOAvip BACKGROUND: The emergence and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in thelate 2019 has caused a devastating global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19). Although vaccines have been and are being developed, they are not accessible to everyone and not everyone can receive these vaccines. Also, it typically takes more than 10 years until a new therapeutic agent is approved for usage. Therefore, repurposing of known drugs can lend itself well as a key approach for significantly expediting the development of new therapies for COVID-19. METHODS: We have incorporated machine learning-based computational tools and in silico models into the drug discovery process to predict Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles of 90 potential drugs for COVID-19 treatment identified from two independent studies mainly with the purpose of mitigating late-phase failures because of inferior pharmacokinetics and toxicity. RESULTS: Here, we summarize the cardiotoxicity and general toxicity profiles of 90 potential drugs for COVID-19 treatment and outline the risks of repurposing and propose a stratification of patients accordingly. We shortlist a total of five compounds based on their non-toxic properties. CONCLUSION: In summary, this manuscript aims to provide a potentially useful source of essential knowledge on toxicity assessment of 90 compounds for healthcare practitioners and researchers to find off-label alternatives for the treatment for COVID-19. The majority of the molecules discussed in this manuscript have already moved into clinical trials and thus their known pharmacological and human safety profiles are expected to facilitate a fast track preclinical and clinical assessment for treating COVID-19. Twit Text FOAVip Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19 ????BMC Pharmacol Toxicol http://www.kidney.de/pget.php?&tw=1&pmid=34674775 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34674775 #FOAvip English Wikipedia <ref>{{Cite pmid|34674775}}</ref> Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19 #MMPMID34674775 Aminpour M; Delgado WEM; Wacker S; Noskov S; Houghton M; Tyrrell DLJ; Tuszynski JA BMC Pharmacol Toxicol 2021[Oct]; 22 (1): 61 PMID34674775show ga BACKGROUND: The emergence and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in thelate 2019 has caused a devastating global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19). Although vaccines have been and are being developed, they are not accessible to everyone and not everyone can receive these vaccines. Also, it typically takes more than 10 years until a new therapeutic agent is approved for usage. Therefore, repurposing of known drugs can lend itself well as a key approach for significantly expediting the development of new therapies for COVID-19. METHODS: We have incorporated machine learning-based computational tools and in silico models into the drug discovery process to predict Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles of 90 potential drugs for COVID-19 treatment identified from two independent studies mainly with the purpose of mitigating late-phase failures because of inferior pharmacokinetics and toxicity. RESULTS: Here, we summarize the cardiotoxicity and general toxicity profiles of 90 potential drugs for COVID-19 treatment and outline the risks of repurposing and propose a stratification of patients accordingly. We shortlist a total of five compounds based on their non-toxic properties. CONCLUSION: In summary, this manuscript aims to provide a potentially useful source of essential knowledge on toxicity assessment of 90 compounds for healthcare practitioners and researchers to find off-label alternatives for the treatment for COVID-19. The majority of the molecules discussed in this manuscript have already moved into clinical trials and thus their known pharmacological and human safety profiles are expected to facilitate a fast track preclinical and clinical assessment for treating COVID-19. |*COVID-19 Drug Treatment[MESH] |*Drug Discovery/methods[MESH] |*Drug Repositioning[MESH] |Animals[MESH] |Antiviral Agents/adverse effects/*toxicity[MESH] |Captopril/therapeutic use[MESH] |Cardiotoxins/toxicity[MESH] |Catechols/therapeutic use[MESH] |Computational Biology[MESH] |Cytochrome P-450 Enzyme System/metabolism[MESH] |Humans[MESH] |Indomethacin/therapeutic use[MESH] |Linezolid/therapeutic use[MESH] |Liver/drug effects[MESH] |Mice[MESH] |Models, Biological[MESH] |Nitriles/therapeutic use[MESH] |Rats[MESH] |Reproduction/drug effects[MESH] |Software[MESH]Computational determination of toxicity risks associated with a select(epmc).pdf DeepDyve Pubget Overpricing