Cargando…

Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude

AIMS: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Lei-Yun, Cui, Jia-Jia, OuYang, Qian-Ying, Zhan, Yan, Wang, Yi-Min, Xu, Xiang-Yang, Yu, Lu-Lu, Yin, Hui, Wang, Yang, Luo, Chen-Hui, Guo, Cheng-Xian, Yin, Ji-Ye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283099/
https://www.ncbi.nlm.nih.gov/pubmed/34306260
http://dx.doi.org/10.1007/s13167-021-00247-0
_version_ 1783723132763242496
author Wang, Lei-Yun
Cui, Jia-Jia
OuYang, Qian-Ying
Zhan, Yan
Wang, Yi-Min
Xu, Xiang-Yang
Yu, Lu-Lu
Yin, Hui
Wang, Yang
Luo, Chen-Hui
Guo, Cheng-Xian
Yin, Ji-Ye
author_facet Wang, Lei-Yun
Cui, Jia-Jia
OuYang, Qian-Ying
Zhan, Yan
Wang, Yi-Min
Xu, Xiang-Yang
Yu, Lu-Lu
Yin, Hui
Wang, Yang
Luo, Chen-Hui
Guo, Cheng-Xian
Yin, Ji-Ye
author_sort Wang, Lei-Yun
collection PubMed
description AIMS: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In this study, analyses were performed on 47 well-characterized COVID-19 drugs used in the personalized treatment of COVID-19. METHODS: Clinical trials with published results of drugs use for COVID-19 treatment were collected to evaluate drug efficacy. Drug-to-Drug Interactions (DDIs) were summarized and classified. Functional variations in actionable pharmacogenes were collected and systematically analysed. “Gene Score” and “Drug Score” were defined and calculated to systematically analyse ethnicity-based genetic differences, which are important for the safer use of COVID-19 drugs. RESULTS: Our results indicated that four antiviral agents (ritonavir, darunavir, daclatasvir and sofosbuvir) and three immune regulators (budesonide, colchicine and prednisone) as well as heparin and enalapril could generate the highest number of DDIs with common concomitantly utilized drugs. Eight drugs (ritonavir, daclatasvir, sofosbuvir, ribavirin, interferon alpha-2b, chloroquine, hydroxychloroquine (HCQ) and ceftriaxone had actionable pharmacogenomics (PGx) biomarkers among all ethnic groups. Fourteen drugs (ritonavir, daclatasvir, prednisone, dexamethasone, ribavirin, HCQ, ceftriaxone, zinc, interferon beta-1a, remdesivir, levofloxacin, lopinavir, human immunoglobulin G and losartan) showed significantly different pharmacogenomic characteristics in relation to the ethnic origin of the patient. CONCLUSION: We recommend that particularly for patients with comorbidities to avoid serious DDIs, the predictive, preventive, and personalized medicine (PPPM, 3 PM) strategies have to be applied for COVID-19 treatment, and genetic tests should be performed for drugs with actionable pharmacogenes, especially in some ethnic groups with a higher frequency of functional variations, as our analysis showed. We also suggest that drugs associated with higher ethnic genetic differences should be given priority in future pharmacogenetic studies for COVID-19 management. To facilitate translation of our results into clinical practice, an approach conform with PPPM/3 PM principles was suggested. In summary, the proposed PPPM/3 PM attitude should be obligatory considered for the overall COVID-19 management. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-021-00247-0.
format Online
Article
Text
id pubmed-8283099
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-82830992021-07-19 Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude Wang, Lei-Yun Cui, Jia-Jia OuYang, Qian-Ying Zhan, Yan Wang, Yi-Min Xu, Xiang-Yang Yu, Lu-Lu Yin, Hui Wang, Yang Luo, Chen-Hui Guo, Cheng-Xian Yin, Ji-Ye EPMA J Research AIMS: Coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide. Drug therapy is one of the major treatments, but contradictory results of clinical trials have been reported among different individuals. Furthermore, comprehensive analysis of personalized pharmacotherapy is still lacking. In this study, analyses were performed on 47 well-characterized COVID-19 drugs used in the personalized treatment of COVID-19. METHODS: Clinical trials with published results of drugs use for COVID-19 treatment were collected to evaluate drug efficacy. Drug-to-Drug Interactions (DDIs) were summarized and classified. Functional variations in actionable pharmacogenes were collected and systematically analysed. “Gene Score” and “Drug Score” were defined and calculated to systematically analyse ethnicity-based genetic differences, which are important for the safer use of COVID-19 drugs. RESULTS: Our results indicated that four antiviral agents (ritonavir, darunavir, daclatasvir and sofosbuvir) and three immune regulators (budesonide, colchicine and prednisone) as well as heparin and enalapril could generate the highest number of DDIs with common concomitantly utilized drugs. Eight drugs (ritonavir, daclatasvir, sofosbuvir, ribavirin, interferon alpha-2b, chloroquine, hydroxychloroquine (HCQ) and ceftriaxone had actionable pharmacogenomics (PGx) biomarkers among all ethnic groups. Fourteen drugs (ritonavir, daclatasvir, prednisone, dexamethasone, ribavirin, HCQ, ceftriaxone, zinc, interferon beta-1a, remdesivir, levofloxacin, lopinavir, human immunoglobulin G and losartan) showed significantly different pharmacogenomic characteristics in relation to the ethnic origin of the patient. CONCLUSION: We recommend that particularly for patients with comorbidities to avoid serious DDIs, the predictive, preventive, and personalized medicine (PPPM, 3 PM) strategies have to be applied for COVID-19 treatment, and genetic tests should be performed for drugs with actionable pharmacogenes, especially in some ethnic groups with a higher frequency of functional variations, as our analysis showed. We also suggest that drugs associated with higher ethnic genetic differences should be given priority in future pharmacogenetic studies for COVID-19 management. To facilitate translation of our results into clinical practice, an approach conform with PPPM/3 PM principles was suggested. In summary, the proposed PPPM/3 PM attitude should be obligatory considered for the overall COVID-19 management. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-021-00247-0. Springer International Publishing 2021-07-16 /pmc/articles/PMC8283099/ /pubmed/34306260 http://dx.doi.org/10.1007/s13167-021-00247-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Wang, Lei-Yun
Cui, Jia-Jia
OuYang, Qian-Ying
Zhan, Yan
Wang, Yi-Min
Xu, Xiang-Yang
Yu, Lu-Lu
Yin, Hui
Wang, Yang
Luo, Chen-Hui
Guo, Cheng-Xian
Yin, Ji-Ye
Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
title Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
title_full Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
title_fullStr Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
title_full_unstemmed Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
title_short Complex analysis of the personalized pharmacotherapy in the management of COVID-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
title_sort complex analysis of the personalized pharmacotherapy in the management of covid-19 patients and suggestions for applications of predictive, preventive, and personalized medicine attitude
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283099/
https://www.ncbi.nlm.nih.gov/pubmed/34306260
http://dx.doi.org/10.1007/s13167-021-00247-0
work_keys_str_mv AT wangleiyun complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT cuijiajia complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT ouyangqianying complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT zhanyan complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT wangyimin complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT xuxiangyang complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT yululu complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT yinhui complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT wangyang complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT luochenhui complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT guochengxian complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude
AT yinjiye complexanalysisofthepersonalizedpharmacotherapyinthemanagementofcovid19patientsandsuggestionsforapplicationsofpredictivepreventiveandpersonalizedmedicineattitude