ABSTRACT
A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowledge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic.
ABSTRACT
Dexamethasone (DEX) is a potent synthetic glucocorticoid used for the treatment of variety of inflammatory and immune-mediated disorders. The RECOVERY clinical trial revealed benefits of DEX therapy in COVID-19 patients. Severe SARS-CoV-2 infection leads to an excessive inflammatory reaction commonly known as a cytokine release syndrome that is associated with activation of the toll like receptor 4 (TLR4) signaling pathway. The possible mechanism of action of DEX in the treatment of COVID-19 is related to its anti-inflammatory activity arising from inhibition of cytokine production but may be also attributed to its influence on immune cell trafficking and turnover. This study, by means of pharmacokinetic/pharmacodynamic modeling, aimed at the comprehensive quantitative assessment of DEX effects in lipopolysaccharide-challenged rats and to describe interrelations among relevant signaling molecules in this animal model of cytokine release syndrome induced by activation of TLR4 pathway. DEX was administered in a range of doses from 0.005 to 2.25 mg·kg-1 in LPS-challenged rats. Serum DEX, corticosterone (CST), tumor necrosis factor α, interleukin-6, and nitric oxide as well as lymphocyte and granulocyte counts in peripheral blood were quantified at different time points. A minimal physiologically based pharmacokinetic/pharmacodynamic (mPBPK/PD) model was proposed characterizing the time courses of plasma DEX and the investigated biomarkers. A high but not complete inhibition of production of inflammatory mediators and CST was produced in vivo by DEX. The mPBPK/PD model, upon translation to humans, may help to optimize DEX therapy in patients with diseases associated with excessive production of inflammatory mediators, such as COVID-19. SIGNIFICANCE STATEMENT: A mPBPK/PD model was developed to describe concentration-time profiles of plasma DEX, mediators of inflammation, and immune cell trafficking and turnover in LPS-challenged rats. Interrelations among DEX and relevant biomarkers were reflected in the mechanistic model structure. The mPBPK/PD model enabled quantitative assessment of in vivo potency of DEX and, upon translation to humans, may help optimize dosing regimens of DEX for the treatment of immune-related conditions associated with exaggerated immune response.
Subject(s)
COVID-19 , Lipopolysaccharides , Humans , Rats , Animals , Dexamethasone/pharmacology , Toll-Like Receptor 4 , Cytokine Release Syndrome/drug therapy , COVID-19 Drug Treatment , SARS-CoV-2 , Anti-Inflammatory Agents/pharmacology , Inflammation/drug therapy , Immunity , Inflammation MediatorsABSTRACT
A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowl-edge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic.