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

Release time:2023-02-02

Impact Factor:8.836

DOI number:10.1007/s13167-021-00247-0

Affiliation of Author(s):Central South University

Teaching and Research Group:Department of Clinical Pharmacology, Xiangya

Journal:EPMA J

Place of Publication:England

Funded by:National Natural Science Foundation of China

Key Words:COVID-19 . Predictive preventive personalized medicine (PPPM/3 PM) . Drug-to-drug interaction . Pharmacogenomics . Ethnicity-based differences . Future healthcare . Gene score . Drug score . Optimal medication . Personalized treatment . Individual outcomes . Molecular mechanisms . Pharmacogenetics . Comorbidities . Ritonavir . Daclatasvir . Sofosbuvir . Ribavirin . Interferon alpha-2b . Chloroquine . Hydroxychloroquine . Ceftriaxone . Ritonavir . Daclatasvir . Prednisone . Dexamethasone . Ribavirin . HCQ . Ceftriaxone . Zinc . Interferon beta-1a . Remdesivir . Levofloxacin . Lopinavir . Human immunoglobulin G . Losartan

Abstract: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.

Co-author:Yi-Min Wang, Xiang-Yang Xu, Lu-Lu Yu, Hui Yin, Yang Wang, Chen-Hui Luo

First Author:Lei-Yun Wang, Jia-Jia Cui, Qian-Ying OuYang, Yan Zhan

Indexed by:Article

Correspondence Author:Cheng-Xian Guo, Ji-Ye Yin

Discipline:Medicine

First-Level Discipline:Pharmaceutical Science

Document Type:J

Page Number:1-18

ISSN No.:1878-5077

Translation or Not:no

Date of Publication:2021-09-12

Included Journals:SCI

Links to published journals:https://www.springer.com/13167