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1.
Sci Robot ; 7(67): eabn0495, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1874493

ABSTRACT

Ultrasensitive multimodal physicochemical sensing for autonomous robotic decision-making has numerous applications in agriculture, security, environmental protection, and public health. Previously reported robotic sensing technologies have primarily focused on monitoring physical parameters such as pressure and temperature. Integrating chemical sensors for autonomous dry-phase analyte detection on a robotic platform is rather extremely challenging and substantially underdeveloped. Here, we introduce an artificial intelligence-powered multimodal robotic sensing system (M-Bot) with an all-printed mass-producible soft electronic skin-based human-machine interface. A scalable inkjet printing technology with custom-developed nanomaterial inks was used to manufacture flexible physicochemical sensor arrays for electrophysiology recording, tactile perception, and robotic sensing of a wide range of hazardous materials including nitroaromatic explosives, pesticides, nerve agents, and infectious pathogens such as SARS-CoV-2. The M-Bot decodes the surface electromyography signals collected from the human body through machine learning algorithms for remote robotic control and can perform in situ threat compound detection in extreme or contaminated environments with user-interactive tactile and threat alarm feedback. The printed electronic skin-based robotic sensing technology can be further generalized and applied to other remote sensing platforms. Such diversity was validated on an intelligent multimodal robotic boat platform that can efficiently track the source of trace amounts of hazardous compounds through autonomous and intelligent decision-making algorithms. This fully printed human-machine interactive multimodal sensing technology could play a crucial role in designing future intelligent robotic systems and can be easily reconfigured toward numerous practical wearable and robotic applications.


Subject(s)
COVID-19 , Robotic Surgical Procedures , Wearable Electronic Devices , Artificial Intelligence , Humans , SARS-CoV-2
2.
J Biomed Res ; : 1-13, 2022 Mar 28.
Article in English | MEDLINE | ID: covidwho-1841675

ABSTRACT

High-affinity antibodies are widely used in diagnostics and for the treatment of human diseases. However, most antibodies are isolated from semi-synthetic libraries by phage display and do not possess in vivo affinity maturation, which is triggered by antigen immunization. It is therefore necessary to engineer the affinity of these antibodies by way of in vitro assaying. In this study, we optimized the affinity of two human monoclonal antibodies which were isolated by phage display in a previous related study. For the 42A1 antibody, which targets the liver cancer antigen glypican-3, the variant T57H in the second complementarity-determining region of the heavy chain (CDR-H2) exhibited a 2.6-fold improvement in affinity, as well as enhanced cell-binding activity. For the I4A3 antibody to severe acute respiratory syndrome coronavirus 2, beneficial single mutations in CDR-H2 and CDR-H3 were randomly combined to select the best synergistic mutations. Among these, the mutation S53P-S98T improved binding affinity (about 3.7 fold) and the neutralizing activity (about 12 fold) compared to the parent antibody. Taken together, single mutations of key residues in antibody CDRs were enough to increase binding affinity with improved antibody functions. The mutagenic combination of key residues in different CDRs creates additive enhancements. Therefore, this study provides a safe and effective in vitro strategy for optimizing antibody affinity.

3.
J Med Virol ; 94(8): 3982-3987, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1802454

ABSTRACT

There is a potential risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread through human contact with seafood and the inanimate materials contaminated by the virus. In this study, we examined the stability of the virus in artificial seawater (ASW) and on the surface of selected materials. SARS-CoV-2 (3.75 log10 TCID50 ) in ASW at 22℃ maintained infectious about 3 days and at 4℃ the virus survived more than 7 days. It should be noticed that viable virus at high titer (5.50 log10 TCID50 ) may survive more than 20 days in ASW at 4℃ and for 7 days at 22℃. SARS-CoV-2 on stainless steel and plastic bag maintained infectious for 3 days, and on nonwoven fabric for 1 day at 22℃. In addition, the virus remained infectious for 9 days on stainless steel and non-woven fabric, and on plastic bag for 12 days at 4℃. It is important to highlight the role of inanimate material surfaces as a source of infection and the necessity for surface decontamination and disinfection.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Plastics , Seawater , Stainless Steel
4.
Adv Differ Equ ; 2020(1): 391, 2020.
Article in English | MEDLINE | ID: covidwho-1706509

ABSTRACT

According to the report presented by the World Health Organization, a new member of viruses, namely, coronavirus, shortly 2019-nCoV, which arised in Wuhan, China, on January 7, 2020, has been introduced to the literature. The main aim of this paper is investigating and finding the optimal values for better understanding the mathematical model of the transfer of 2019-nCoV from the reservoir to people. This model, named Bats-Hosts-Reservoir-People coronavirus (BHRPC) model, is based on bats as essential animal beings. By using a powerful numerical method we obtain simulations of its spreading under suitably chosen parameters. Whereas the obtained results show the effectiveness of the theoretical method considered for the governing system, the results also present much light on the dynamic behavior of the Bats-Hosts-Reservoir-People transmission network coronavirus model.

5.
J Pain Symptom Manage ; 64(1): e1-e5, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1701310

ABSTRACT

CONTEXT: Children and young people with life-limiting or life-threatening conditions and their families are potentially vulnerable during COVID-19 lockdowns due to pre-existing high clinical support needs and social participation limitations. OBJECTIVES: To explore the impact of the COVID-19 pandemic and lockdowns on this population. METHODS: Sub-analysis of an emergent COVID-19 related theme from a larger semi-structured interview study investigating priority pediatric palliative care outcomes. One hundred and six United Kingdom-wide purposively-sampled Children and young people with life-limiting or life-threatening conditions, parent/carers, siblings, health professionals, and commissioners. RESULTS: COVID-19 was raised by participants in 12/44 interviews conducted after the United Kingdom's first confirmed COVID-19 case. Key themes included loss of vital social support, disruption to services important to families, and additional psychological distress. CONCLUSION: Continued delivery of child- and family-centered palliative care requires innovative assessment and delivery of psycho-social support. Disruptions within treatment and care providers may compound support needs, requiring cordination for families facing multiagency delays.


Subject(s)
COVID-19 , Palliative Care , Adolescent , Child , Communicable Disease Control , Family/psychology , Humans , Palliative Care/psychology , Pandemics
6.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-312273

ABSTRACT

Background: Adequate perinatal care is essential for maternal and infant health. The novel coronavirus (COVID-19) pandemic is potentially the largest natural disruption to perinatal care in recent history, but these disruptions have yet to be characterized in a rigorous and systematic manner. Our goal was to document COVID-19 induced disruptions to perinatal care across the United States (US) using analyses sensitive to the temporal and geographical variability of the pandemic, and to examine the impact of these healthcare disruptions on maternal mental health.Methods: We performed an observational cross-sectional study of 1,922 postpartum and 3,868 pregnant individuals during the 2020 COVID-19 pandemic. Perinatal individuals were recruited from 15 academic institutions across the US, resulting in a geographically diverse sample. We conducted (1) descriptive analyses on the prevalence and timing of perinatal care disruptions, (2) group difference analyses to compare perinatal care disruptions depending on when and where individuals gave birth, (3) cross correlations to assess the temporal linkage between perinatal care disruptions and COVID-19 infection rates, and (4) hierarchical linear regressions to evaluate the impact of prenatal care and birth protocol disruptions on maternal psychological health.Findings: The COVID-19 pandemic significantly altered perinatal care across the US, both through restriction of in-person support and by shifting the focus of care. These changes occurred unevenly over time and across geographic locations. Changes in COVID-19 infection rates explained 65 to 78% of the variance in perinatal care disruptions from August 2019 to August 2020. Moreover, disruptions to perinatal care were robustly associated with heightened psychological distress in mothers, even after controlling for mental health history, number of pregnancy complications, and general stress about the COVID-19 pandemic.Interpretation: Our analyses reveal widespread disruptions to perinatal care across the US that fluctuated depending on where and when individuals gave birth, demonstrating reactivity and elasticity of the US healthcare system. In addition to influencing health outcomes, disruptions to perinatal care may also exacerbate mental health concerns during the COVID-19 pandemic.Funding Information: This research was supported by the NYU COVID-19 Research Catalyst rant, R34DA050287-S1, R34DA050287-S2, R34DA050254-01S2, R01MH126468, R01MH125870, the Nathaniel Wharton Fund, the Columbia University Population Research Center, R34DA050255, R34DA050255-01S2, the Fralin Biomedical Research Institute at VTC, the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Numbers UL1TR003015 and KL2TR003016, the University of Utah Center for Clinical and Translational Science COVID-19 Research Award, Virginia Commonwealth University School of Nursing Internal Grants Program, Sarah P. Farrell Legacy Research Endowment-Virginia Commonwealth University, 5R03HD096141-02, R01HD085990, R34DA050283-01S2, the USC Center for the Changing Family, the Stanford Institute for Research in the Social Sciences, R34DA050291, R01MH119070, R01MH117177, R34 DA050272-01S1, R01 MH113883, R01 DA046224, R21 MH111978, and R21 HD090493, R37 MH10149, UH3OD023279, and National Center for Advancing Translational Sciences (NCATS) Grant UL1TR001881Declaration of Interests: The authors report no conflicts of interest.Ethics Approval Statement: This study has received Institutional Review Board approval from theNYU Langone Health IRB as well as the local IRBs at each data collection site. All data was collected in accordance with the Helsinki Declaration.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-310879

ABSTRACT

Objective: We aimed to describe the features of 220 nonemergency (mild or common type) COVID-19 patients from a shelter hospital, as well as evaluate the efficiency of antiviral drug, Arbidol in their disease progressions. Methods: . Basic clinical characteristics were described and the efficacy of Arbidol was evaluated based on gender, age, maximum body temperature of the patients. Results: . Basically, males had a higher risk of fever and more onset symptoms than females. Arbidol could accelerate fever recovery and viral clearance in respiratory specimens, particularly in males. Arbidol also contributed to shorter hospital stay without obvious adverse reactions. Conclusions: . In the retrospective COVID-19 cohort, gender was one of the important factors affecting patient's conditions. Arbidol showed several beneficial effects in these patients, especially in males. This study brought more researches enlightenment in understanding the emerging infectious disease.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308538

ABSTRACT

Objective: Twitter data have been increasingly used to address health-related issues. However, little is known about their potential for understanding public opinions and sentiments of the current COVID-19 pandemic. The present study explores public opinion and sentiments about the COVID-19 pandemic using Tweets from 3 popular Coronavirus-related hashtags (#COVID19, #Coronavirus, #SARSCoV2). Results: : Of the 39,726 Tweets analysed, we found that over 60% of words used within Tweets in all hashtags (#COVID19, 63.9%;#Coronavirus: 65.6%;#SARSCoV2: 63.5%) conveyed a negative mood towards the pandemic. Our results also showed similar trends in Tweet volume in #COVID19 and #SARSCoV2, with a spike in the number of Tweets on the 3rd and 6th of April 2020. Further exploration of Tweets in both hashtags revealed similar Twitter discussions related to topics on “Hydroxychloroquine” and “Hospitalisations of the British Prime minister” and “ the attainment of 1 million cases of coronavirus globally”.The findings of this exploratory study indicate that there is potential for using data generated from Twitter to understand general public opinion and sentiments towards the COVID-19 pandemic. However, caution is needed due to several limitations in this study. It is also important for future studies to explore the context around Tweets.

9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-323933

ABSTRACT

Maternal stress exposure during the COVID-19 pandemic may have transgenerational effects, adversely affecting both the pregnant woman and her offspring. Therefore, there is an urgent need to characterize the coping styles and psychosocial distress of pregnant and postpartum women during the COVID-19 pandemic to help mitigate lasting sequalae on both mothers and infants. Here we use latent profile analysis to examine patterns of behavioral coping strategies associated with risk and resiliency to adverse mental and physical health outcomes. Leveraging a large U.S. sample of perinatal women (N = 2,876 pregnant women, N = 1,536 postpartum women), we identified four behavioral phenotypes of coping strategies: (1) passive-coping, characterized by primarily engaging in high levels of screen time, social media use, and eating comfort foods;(2) active-coping, characterized by primarily engaging in high levels of self-care, social support, and limiting media exposure;(3) low-coping, characterized by low levels of all coping strategies;(4) high-coping, characterized by high levels of both active and passive coping strategies. Critically, we found that passive-coping phenotypes were associated with higher levels of depression and anxiety and worsening stress and energy levels in both pregnant and postpartum women. Supplementing passive coping strategies with high levels of active coping strategies (the high-coping profile) lessened adverse outcomes in postpartum women. These behavioral coping phenotypes highlight potential risk and protective factors for perinatal women, which is critical in helping to identify and treat perinatal women most at risk for experiencing mood and affective disorders resulting from the COVID-19 pandemic.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-323888

ABSTRACT

Background: Novel coronavirus disease (COVID-19) is an emerging, rapidly evolving situation. At present, the prognosis of severe and critically ill patients has become an important focus of attention. We strived to develop a prognostic prediction model for severe and critically ill COVID-19 patients.MethodsTo assess the factors associated with the prognosis of those patients, we retrospectively investigated the clinical, laboratory characteristics of confirmed 112 cases of COVID-19 admitted between 21 January to 6 March 2020 from Huangshi Central Hospital, Huangshi Hospital of Traditional Chinese Medicine, and Daye People’s Hospital. We applied machine learning method (survival random forest) to select predictors for 28-day survival and taken into account the dynamic trajectory of laboratory indicators. Results Fifteen candidate prognostic features, including 11 baseline measures (including platelet count (PLT), urea, creatine kinase (CK), fibrinogen, creatine kinase isoenzyme activity, aspartate aminotransferase (AST), activation of partial thromboplastin time (APTT), albumin, standard deviation of erythrocyte distribution width (RBC-SD), neutrophils (%) and red blood cell count (RBC)) and 4 trajectory clusters (changes during hospitalization in the white blood cell (WBC), PLT large cell ratio (P-LCR), PLT distribution width (PDW) and AST), combined with covariates achieved 100% (95%CI: 99%-100%) AUC and reached 87% (95%CI: 84%-91%) AUC in an external validation set. Conclusions Taking advantage of random forest technique and laboratory dynamic measures, we developed a forest model to predict survival outcome of COVID-19 patients, which achieved 87% AUC in the external validation set. Our online tool will help to facilitate the early recognition of patients with high risk.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-323749

ABSTRACT

The outbreak of Covid-19 in China during the Spring Festival of 2020 has changed life as we knew it. To explore its impact on China's economy, we analyse the daily railway passenger volume data during the Spring Festival travel rush and establish two RegARMA models to predict GDP in the first quarter. The models forecast China might lose 4.8 trillion yuan in the first quarter of 2020 due to Covid-19, an expected decrease of 20.69 percent (year-on-year drop 15.60 percent). However, comparing our forecast GDP without Covid-19 (23.2 trillion yuan) with the real GDP (20.65 trillion yuan), there is a smaller drop of 2.55 trillion yuan, a gap of 12.35 percent. The reason for this overestimation is that some positive factors, including macro-control policies, are neglected in these models. With the global spread of Covid-19, China should adopt a policy of focusing on balancing both domestic and external affairs against the instability of the world economy.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-323266

ABSTRACT

The fundamental aim of the present study is to analyse and find the solution for the system of nonlinear ordinary differential equations describing the deadly and most dangerous virus from the lost three months called coronavirus. The mathematical model consisting of six nonlinear ordinary differential equations are exemplified and the corresponding solution is studied within the frame of ?-homotopy analysis transform method (?-HATM). Moreover, a newly defined fractional operator is employed in order to understand more effectively, known as Atangana-Baleanu (AB) operator. For the obtained results, the fixed point theorem is hired to present the exactness as well as uniqueness. For diverse arbitrary order, the behaviour of the outcomes is presented in terms of plots. Finally, the present study may help to examine the wild class of real-world models and also aid to predict their behaviour with respect to parameters considered in the models.

13.
Fractal and Fractional ; 6(2):92, 2022.
Article in English | MDPI | ID: covidwho-1674568

ABSTRACT

In this paper, we analyzed and found the solution for a suitable nonlinear fractional dynamical system that describes coronavirus (2019-nCoV) using a novel computational method. A compartmental model with four compartments, namely, susceptible, infected, reported and unreported, was adopted and modified to a new model incorporating fractional operators. In particular, by using a modified predictor–corrector method, we captured the nature of the obtained solution for different arbitrary orders. We investigated the influence of the fractional operator to present and discuss some interesting properties of the novel coronavirus infection.

14.
J Biomed Res ; 36(1): 32-38, 2021 Nov 23.
Article in English | MEDLINE | ID: covidwho-1675185

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has spread throughout the world, which becomes a global public health emergency. Undernourishment prolongs its convalescence and has an adverse effect on its prognosis, especially in diabetic patients. The purpose of this study was to evaluate the prevalence and characteristics of undernourishment and to determine how it is related to the prognostic outcomes in the diabetic patients with coronavirus disease 2019 (COVID-19). A retrospective, multicenter study was conducted in 85 diabetic COVID-19 patients from three hospitals in Hubei Province. All patients were assessed using the European Nutritional Risk Screening 2002 (NRS-2002) and other nutritional assessments when admitted. Of them, 35 (41.18%) were at risk of malnutrition (NRS score ≥3). Severe COVID-19 patients had a significantly lower level of serum albumin and prealbumin and higher NRS score than non-severe patients. Multivariate logistic regression analysis showed that serum prealbumin and NRS score increased the likelihood of progression into severe status ( P<0.05). Meanwhile, single factor and multivariate analysis determined that grade of illness severity was an independent predictor for malnutrition. Furthermore, prealbumin and NRS score could well predict severe status for COVID-19 patients. The malnutrition group (NRS score ≥3) had more severe illness than the normal nutritional (NRS score <3) group ( P<0.001), and had a longer length of in-hospital stay and higher mortality. Malnutrition is highly prevalent among COVID-19 patients with diabetes. It is associated with severely ill status and poor prognosis. Evaluation of nutritional status should be strengthened, especially the indicators of NRS-2002 and the level of serum prealbumin.

15.
Scientific reports ; 12(1), 2022.
Article in English | EuropePMC | ID: covidwho-1652370

ABSTRACT

The impact of COVID-19-related stress on perinatal women is of heightened public health concern given the established intergenerational impact of maternal stress-exposure on infants and fetuses. There is urgent need to characterize the coping styles associated with adverse psychosocial outcomes in perinatal women during the COVID-19 pandemic to help mitigate the potential for lasting sequelae on both mothers and infants. This study uses a data-driven approach to identify the patterns of behavioral coping strategies that associate with maternal psychosocial distress during the COVID-19 pandemic in a large multicenter sample of pregnant women (N = 2876) and postpartum women (N = 1536). Data was collected from 9 states across the United States from March to October 2020. Women reported behaviors they were engaging in to manage pandemic-related stress, symptoms of depression, anxiety and global psychological distress, as well as changes in energy levels, sleep quality and stress levels. Using latent profile analysis, we identified four behavioral phenotypes of coping strategies. Critically, phenotypes with high levels of passive coping strategies (increased screen time, social media, and intake of comfort foods) were associated with elevated symptoms of depression, anxiety, and global psychological distress, as well as worsening stress and energy levels, relative to other coping phenotypes. In contrast, phenotypes with high levels of active coping strategies (social support, and self-care) were associated with greater resiliency relative to other phenotypes. The identification of these widespread coping phenotypes reveals novel behavioral patterns associated with risk and resiliency to pandemic-related stress in perinatal women. These findings may contribute to early identification of women at risk for poor long-term outcomes and indicate malleable targets for interventions aimed at mitigating lasting sequelae on women and children during the COVID-19 pandemic.

16.
Cereb Cortex ; 2022 Jan 20.
Article in English | MEDLINE | ID: covidwho-1642319

ABSTRACT

The Coronavirus disease of 2019 (COVID-19) and measures to curb it created population-level changes in male-dominant impulsive and risky behaviors such as violent crimes and gambling. One possible explanation for this is that the pandemic has been stressful, and males, more so than females, tend to respond to stress by altering their focus on immediate versus delayed rewards, as reflected in their delay discounting rates. Delay discounting rates from healthy undergraduate students were collected twice during the pandemic. Discounting rates of males (n=190) but not of females (n=493) increased during the pandemic. Using machine learning, we show that prepandemic functional connectome predict increased discounting rates in males (n=88). Moreover, considering that delay discounting is associated with multiple psychiatric disorders, we found the same neural pattern that predicted increased discounting rates in this study, in secondary datasets of patients with major depression and schizophrenia. The findings point to sex-based differences in maladaptive delay discounting under real-world stress events, and to connectome-based neuromarkers of such effects. They can explain why there was a population-level increase in several impulsive and risky behaviors during the pandemic and point to intriguing questions about the shared underlying mechanisms of stress responses, psychiatric disorders and delay discounting.

18.
Open Forum Infectious Diseases ; 8(Supplement_1):S362-S363, 2021.
Article in English | PMC | ID: covidwho-1569969
19.
Open forum infectious diseases ; 8(Suppl 1):S373-S373, 2021.
Article in English | EuropePMC | ID: covidwho-1564195

ABSTRACT

Background Molnupiravir (MOV, MK-4482, EIDD-2801) is an orally administered prodrug of N-hydroxycytidine (NHC, EIDD-1931), a nucleoside with broad antiviral activity against a range of RNA viruses. MOV acts by driving viral error catastrophe following its incorporation by the viral RdRp into the viral genome. Given its mechanism of action, MOV activity should not be affected by substitutions in the spike protein present in SARS-CoV-2 variants of concern which impact efficacy of therapeutic neutralizing antibodies and vaccine induced immunity. We characterized MOV activity against variants by assessing antiviral activity in vitro and virologic response from the Phase 2/3 clinical trials (MOVe-In, MOVe-Out) for treatment of COVID-19. Methods MOV activity against several SARS-CoV-2 variants, was evaluated in an in vitro infection assay. Antiviral potency of NHC (IC50) was determined in Vero E6 cells infected with virus at MOI ~0.1 by monitoring CPE. Longitudinal SARS-CoV-2 RNA viral load measures in participants enrolled in MOVe-In and MOVe-Out were analyzed based on SARS-CoV-2 genotype. Sequences of SARS-CoV-2 from study participants were amplified from nasal swabs by PCR and NGS was performed on samples with viral genome RNA of >22,000 copies/ml amplified by primers covering full length genome with Ion Torrent sequencing to identify clades represented in trial participants. SARS-CoV-2 clades were assigned using clade.nextstrain.org. Results In vitro, NHC was equally effective against SARS-CoV-2 variants B.1.1.7 (20I), B.1351 (20H), and P1 (20J), compared with the original WA1 (19B) isolate. In clinical trials, no discernable difference was observed in magnitude of viral response measured by change from baseline in RNA titer over time across all clades represented including 20A through 20E and 20G to 20I. No participants at the time of the study presented with 20F, 20J, or 21A. Conclusion Distribution of clades in participants in MOVe-In and MOVe-Out was representative of those circulating globally at the time of collection (Oct 2020 – Jan 2021). Both in vitro and clinical data suggest that spike protein substitutions do not impact antiviral activity of MOV and suggest its potential use for the treatment of SARS-CoV-2 variants. Disclosures Jay Grobler, PhD, Merck & Co., Inc. (Employee, Shareholder) Julie Strizki, PhD, Merck & Co., Inc. (Employee, Shareholder) Nicholas Murgolo, PhD, Merck & Co., Inc. (Employee, Shareholder) Wei Gao, PhD, Merck & Co., Inc. (Employee, Shareholder) Youfang Cao, PhD, Merck & Co. (Employee) Ying Zhang, PhD, Merck & Co., Inc. (Employee, Shareholder) Jiejun Du, PhD, Merck & Co., Inc. (Employee, Shareholder) Manoj Nair, PhD, Merck & Co., Inc. (Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Yaoxing Huang, PhD, Merck & Co., Inc. (Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Yang Luo, PhD, Merck & Co., Inc. (Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) Daria Hazuda, PhD, Merck & Co., Inc. (Employee, Shareholder) David D. Ho, MD, Merck & Co., Inc. (Grant/Research Support, Scientific Research Study Investigator, Research Grant or Support) David D. Ho, MD, Brii Biosciences (Individual(s) Involved: Self): Consultant;Merck (Individual(s) Involved: Self): Research Grant or Support;RenBio (Individual(s) Involved: Self): Consultant, Founder, Other Financial or Material Support, Shareholder;WuXi Biologics (Individual(s) Involved: Self): Consultant

20.
Open forum infectious diseases ; 8(Suppl 1):S362-S363, 2021.
Article in English | EuropePMC | ID: covidwho-1563956

ABSTRACT

Background Molnupiravir (MOV) is an orally administered ribonucleoside prodrug of β-D-N4-hydroxycytidine (NHC) against SARS-CoV-2. Here we present viral dynamics analysis of Phase 2 clinical virology data to inform MOV Phase 3 study design and development strategy. Methods An Immune-Viral Dynamics Model (IVDM) was developed with mechanisms of SARS-CoV-2 infection, replication, and induced immunity, which together describe the dynamics of viral load (VL) during disease progression. Longitudinal virology data from ferret studies (Cox, et al. Nat. Microbiol 2021:6-11) were used to inform IVDM, which was further translated to human by adjusting parameter values to capture clinical data from MOVe-IN/MOVe-OUT studies. Different placements of drug effects (on viral infectivity vs. productivity) and representations of immune response were explored to identify the best ones to describe data. A simplified 95% drug effect was implemented to represent a highly effective dose of MOV. Results IVDM showed data were best described when MOV acts on viral infectivity, consistent with the error catastrophe mechanism of action. A cascade of innate and adaptive immune response and a basal level activation enabled durable immunity and continued viral decay after treatment end. IVDM reasonably describes VL and viral titer data from animals and humans. Influence of MOV start time was explored using simulations. Consistent with the ferret studies, simulations showed when treatment is started within the first week post infection, MOV reduces viral growth, resulting in a lower and shortened duration of detectable VL. When started later (e.g. >7 days since symptom onset), the magnitude of drug effect is substantially diminished in a typical patient with an effective immune response which reduces VL prior to treatment start. Further work is needed to model response in patients with longer term infection, where MOV drug effects may have more persistent utility. Conclusion A COVID-19 IVDM developed using multiscale MOV virology data supports drug action on viral infectivity and importance of interplay of treatment and immune response and can describe infection time course and drug effect. IVDM provided mechanistic interpretations for VL drug effect in clinical studies. Disclosures Youfang Cao, PhD, Merck & Co. (Employee) Wei Gao, PhD, Merck & Co., Inc. (Employee, Shareholder) Ruthie Birger, PhD, Merck (Employee) Julie Stone, PhD, Merck & Co., Inc. (Employee, Shareholder)

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