Dimension scaling of the stirred vessel configuration.
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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Kumavath and Pratap Deverapalli",dateSubmitted:"October 10th 2012",dateReviewed:"March 18th 2013",datePrePublished:null,datePublished:"October 2nd 2013",book:{id:"3547",title:"Applied Bioremediation",subtitle:"Active and Passive Approaches",fullTitle:"Applied Bioremediation - Active and Passive Approaches",slug:"applied-bioremediation-active-and-passive-approaches",publishedDate:"October 2nd 2013",bookSignature:"Yogesh B. 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\r\n\tMale circumcision is a procedure that has been practiced since the dawn of human culture more than six thousand years ago. It is performed for both medical and non-medical reasons. Despite being a simple procedure, it may lead to a myriad of minor and even crippling complications, if not done properly, such as iatrogenic injury of the glans or the urethra. Several techniques have been used to perform circumcision including the classic open technique, clamp technique, and laser /electrocautery technique with various safety outcomes. Overtime time, there has been an ongoing debate over the pros and cons of cultural circumcision with a significant dichotomy between the opinions of the experts in the field.
\r\n\r\n\tThe main purpose of this book will aim to present a comprehensive overview of the historic background of circumcision in males and the debate over female circumcision. It is intended to be an addition to a description of the different procedural techniques of circumcision highlighting their potential complications.
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He then completed a two-year fellowship in Pediatric Surgery at the University of Iowa-Hospitals and Clinics, USA. Then he joined Chelsea and Westminster Hospital, UK, for another year of fellowship in pediatric surgery. Dr. Zaghal is board certified by the European Board of Pediatric Surgery.\nDr. Zaghal has been a pediatric surgeon and assistant professor of surgery at AUBMC since 2017. He has special interests in minimally invasive and neonatal surgery, and medical education. He is a fellow of the Higher Education Academy. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Starting with Harvey and Greaves, Computational Fluid Dynamics (CFD) has been applied as a powerful tool for investigating the detailed information on the flow in the tank [1-2]. In their work, the impeller boundary condition (IBC) approach has been proposed for the impeller modeling, in which the flow characteristics near the impeller are experimentally measured, and are specified as the boundary conditions for the whole flow field computation [1-4]. Because it depends on the experimental data, IBC can hardly predict the flow in the stirred tank and its applicability is inherently limited. To overcome this drawback, the multiple rotating reference frames approach (MRF) has been developed, in which the vessel is divided into two parts: the inner zone using a rotating frame and the outer zone associated with a stationary frame, for a steady state simulation. Although it can predict the flow field, the computation result is slightly lack of accuracy and needs a longer time for convergence [5]. Sliding mesh approach (SM) is another available approach, in which the inner grid is assumed to rotate with the impeller speed, and the full transient simulations are carried out [6-7]. SM approach gives an improved result, but it suffers from the large computational expense [8]. Moving-deforming grid technique was proposed by Perng and Murthy [9], in which the grid throughout the vessel moves with the impeller and deforms. This approach requires a rigorous grid quality and the computational expenses are even higher than SM [10-11].
\n\t\t\tMomentum source term approach adds momentum source in the computational cells to represent the impeller propelling and the real blades are ignored. In the approach, the generations of the vessel configuration and grids are simpler, and the computational time is shorter and the computational accuracy is higher. However, the determination of the momentum source depends on experimental data or empirical coefficients presently [12-13]. The approach proposed by Pericleous and Patel is based on the airfoil aerodynamics and originally aimed at the two-dimensional flow in the stirred vessels. Xu, McGrath [14] and Patwardhan [15] applied this approach to simulate the three-dimensional flow pattern in a tank with the pitched blade turbines. Revstedt et al. [16] modified the approach for the three-dimensional simulation in a Rushton turbine stirred vessel. In their approach, the determination of the momentum source depends on the specified power number. Dhainaut et al. [13] reported a kind of momentum source term approach in which the fluid velocity is linearly proportional to the radius with an empirical coefficient. In our previous study, we proposed to calculate the momentum source term according to the ideal propeller equation [17], which is related to the rotation speed and radius of the blade [18-20], however, the prediction accuracy is just a little better than MRF method.
\n\t\t\tBesides, other methods, such as inner-outer approach, snapshot approach and adaptive force field technique, have been developed, but are less applied[1, 21].
\n\t\t\tIn this study, an equation is proposed to calculate the momentum source term after considering both impeller propelling force and the radial friction effect between the blades and fluid. The flow field in the Rushton turbine stirred vessel was simulated with the CFD model. The available experimental data near the impeller tip and in the bulk region were applied to validate this approach. Moreover, the comparisons of the computational accuracy and time with MRF and SM were carried out.
\n\t\t\n\t\t\t\t\tFig.1 shows the geometry of the investigated standard six-bladed Rushton turbine stirred tank with four equally spaced baffles. The diameter of cylindrical vessel
It is well known that sufficiently fine grids and lower-dissipation discretization schemes can significantly reduce the numerical errors [23]. And the grid resolution on the blades has an important influence on capturing the details of flow near the impeller [23-24]. Grid independence study has been carried out for momentum source term approach with the standard
Geometry of the stirred vessel.
H/T | \n\t\t\t\t\t\t\tC/T | \n\t\t\t\t\t\t\tB/T | \n\t\t\t\t\t\t\tD/T | \n\t\t\t\t\t\t\tK/D | \n\t\t\t\t\t\t\tw/D | \n\t\t\t\t\t\t\th/D | \n\t\t\t\t\t\t
---|---|---|---|---|---|---|
1 | \n\t\t\t\t\t\t\t1/3 | \n\t\t\t\t\t\t\t1/10 | \n\t\t\t\t\t\t\t1/3 | \n\t\t\t\t\t\t\t3/4 | \n\t\t\t\t\t\t\t1/4 | \n\t\t\t\t\t\t\t1/5 | \n\t\t\t\t\t\t
Dimension scaling of the stirred vessel configuration.
Computational mesh for the momentum source term approach simulation.
In order to investigate the computational speed of MRF and SM, they are also applied to simulate the flow field of stirred tank. The total number of computational cells for MRF is 1,652,532 (
Following the assumptions of Euler equation for turbomachinery [25], the momentum source term from the driving of blade is determined as following. For a small area of blade d
Since the rigid body rotational motion of the blade is considered, it is a reasonable assumption that the fluid velocity after being acted on is the same as the velocity of the impeller blade, thus
where
Furthermore, the fluid is continuously impelled out from the impeller region, so there is a relative motion of the fluid along the radial direction of the blade. In order to consider the friction effect on the fluid movement, the friction resistance equation about the finite flat plate based on the boundary layer theory is introduced to calculate the friction force approximately [27]:
\n\t\t\t\twhere
where Re\n\t\t\t\t\t\t
In the previous study, the difference between the ensemble-averaged flow field calculated with the steady-state and the time-dependent approaches was found to be negligible [28-30]. Here, the continuity and momentum equations of motion for three-dimensional incompressible flow, as well as the standard
The free surface was treated as a flat and rigid lid, so a slip wall was given to the surface. The disc, hub and shaft of the Rushton turbine are specified as moving walls. A standard wall function was given to the other solid walls, including the bottom surface, the sidewall and baffles. Second order upwind discretization scheme was adopted for pressure interpolation and the convection term of momentum, turbulent kinetic energy and energy dissipation rate equations, and the discretized equations were solved iteratively by using the SIMPLE algorithm for pressure-velocity coupling.
\n\t\t\tThe power number
In MRF and SM approaches, the power number is usually calculated from the predicted torque [36]:
\n\t\t\t\tin which
In the present study, since the force from blade results in the fluid movement, the impeller power can be calculated from the integration of the momentum source in the impeller region [14], which is called integral power based approach, so the power number is calculated in the following manner in our study:
\n\t\t\t\tin which
\n\t\t\t\t\tFig.3 shows the profiles of the predicted and experimental flow data in the impeller region. Fig.3a gives the comparison of the radial velocity. Escudie and Line [37] summarized the previous experimental works and found due to the differences of the experimental technique and the stirred-vessel configuration, there existed some inconsistencies among the reported results, whereas the maximum of radial velocity was in the range of 0.7-0.87
With regard to tangential velocity, the maxima from Wu and Patterson [38], and Escudie and Line [37] are 0.66
\n\t\t\t\t\tFig.3c shows the comparison of axial velocity. The measured results from Wu and Patterson [38], Escudie and Line [37] are almost the same. The momentum source term approach results match the measured data well in most regions, but predicting the change from the maximum to minimum with several deviations. Compared to standard
In fig.3d, it can be observed that there are two maxima of different magnitudes in the profiles of turbulent kinetic energy, thus the curve is not symmetrical. RSM simulations of momentum source term approach are in accordance with those of standard
Comparison of the results predicted by different impeller approaches and experimental data around impeller tip (a) radial velocity, (b) tangential velocity, (c) axial velocity and (d) turbulence kinetic energy: ○ experimental data (Escudie and Line, 2003),
\n\t\t\t\t\tFig.4 shows the radial profiles of the mean axial velocity at various axial levels. Here,
\n\t\t\t\t\tFig.5 depicts the comparison of predicted and experimental radial velocity component. The high speed impeller discharge streams radially. Radial velocity initially increases and then decreases, attaining the maximum at
Comparison of the results predicted by different impeller approaches and experimental data of the dimensionless mean axial velocity in the bulk region: experimental data [
Comparison of the results predicted by different impeller approaches and experimental data of the dimensionless mean radial velocity in the bulk region: experimental data (Murthy and Joshi, 2008) standard
Comparison of the results predicted by different impeller approaches and experimental data of the dimensionless mean tangential velocity in the bulk region: experimental data (Murthy and Joshi, 2008) standard
\n\t\t\t\t\tFig.6 illustrates the radial profiles of the tangential velocity component. Yianneskis et al [40] pointed out that the baffles reduce the vessel cross-section, which results in higher values for tangential velocity and a reduced pressure, thus generating reverse flows. It may be the reason that negative velocities exist at the levels of
Comparison of the results predicted by different impeller approaches and experimental data of the dimensionless mean turbulent kinetic energy in the bulk region: experimental data (Murthy and Joshi, 2008) standard
\n\t\t\t\t\tFig.7 shows the numerical comparison of turbulent kinetic energy in various positions. At
From the comparisons above, it can be found that predictions of momentum source term approach with RSM turbulent model are in good agreement with the experimental data as well as SM model, although both SM and our model have some deviations in prediction of the upper part for the radial and tangential velocity. The models combined with
\n\t\t\t\t\tFig.8 shows velocity vectors of the vertical plane in the middle of two baffles. It can be seen that after exerting on the momentum source, fluid velocity in the impeller region is very high, and flow gradients are large.
\n\t\t\t\tVelocity vectors of stirred tank in the middle plane.
As the high speed fluid jets outward, initially almost not affected by the surrounding fluid, the velocity contours are dense. The flow impinges on the tank wall, splits up into two parts and changes the direction. The split water flows at last return to impeller region and accelerated again, repeating above-mentioned process which generates two circulation loops of different directions in the upper and lower part of the tank, respectively. It can be observed that the circulation loop ranges above the
\n\t\t\t\t\tFig.9 shows the flow field of stirred tank near the impeller tip. It can be noticed that velocity distributions are not symmetrical about the impeller centre plate (
Velocity vectors in the middle plane near impeller tip.
\n\t\t\t\t\tTable 2 shows the comparison of predicted power numbers with the experimental value. Here, the experimental power numbers reported by Rushton et al. [44-45], Murthy and Joshi [22] are applied in the reference. The quantities obtained by SM model through integral
\n\t\t\t\t\tFig.10 shows a log-log plot of the experimentally obtained and predicted power numbers for nine kinds of Reynolds numbers which cover laminar and turbulent flow regimes. It can be observed that at lower Reynolds numbers the power numbers predicted by momentum source term approach are in good agreement with the experimental data of Rushton et al. [44].
\n\t\t\t\tMethods | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tError/% | \n\t\t\t\t\t\t
---|---|---|
Experimental value (Rushton et al., 1950) | \n\t\t\t\t\t\t\t6.07 | \n\t\t\t\t\t\t\t/ | \n\t\t\t\t\t\t
Experimental value (Murthy and Joshi, 2008) | \n\t\t\t\t\t\t\t5.1 | \n\t\t\t\t\t\t\t/ | \n\t\t\t\t\t\t
SM torque based approach (Murthy and Joshi, 2008) | \n\t\t\t\t\t\t\t4.9 | \n\t\t\t\t\t\t\t12.26 | \n\t\t\t\t\t\t
SM integral | \n\t\t\t\t\t\t\t3.9 | \n\t\t\t\t\t\t\t30.17 | \n\t\t\t\t\t\t
MRF torque based approach (Deglon and Meyer, 2006) | \n\t\t\t\t\t\t\t5.40 | \n\t\t\t\t\t\t\t3.31 | \n\t\t\t\t\t\t
Standard | \n\t\t\t\t\t\t\t5.72 | \n\t\t\t\t\t\t\t2.42 | \n\t\t\t\t\t\t
RSM integral power based approach | \n\t\t\t\t\t\t\t5.64 | \n\t\t\t\t\t\t\t0.98 | \n\t\t\t\t\t\t
Power number predictions for different approaches at
Comparison of experimental and predicted power numbers.
The simulations were carried out on a 100 node AMD64 cluster, each node including 2 four-core processors with 2.26 GHz clock speed and 2 GB memory. 80 processors were applied in all the computations. Present study compared the computational speeds of momentum source term approach, MRF and SM, and the required expenses are shown in Table 3. It can be seen that momentum source term approach and MRF using steady state simulations need less computational requirements than SM, and the computational time of momentum source term approach is the least.
\n\t\t\t\tApproach | \n\t\t\t\t\t\t\tMomentum source term | \n\t\t\t\t\t\t\tMRF | \n\t\t\t\t\t\t\tSM | \n\t\t\t\t\t\t
---|---|---|---|
Standard | \n\t\t\t\t\t\t\t48 | \n\t\t\t\t\t\t\t72 | \n\t\t\t\t\t\t\t340 | \n\t\t\t\t\t\t
RSM | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t\t86 | \n\t\t\t\t\t\t\t410 | \n\t\t\t\t\t\t
Comparison of the computational time required by different approaches, h.
An equation to predict the momentum source term is proposed without the help of experimental data in the paper. So the momentum source term approach for CFD prediction of the impeller propelling action has been developed as a tool with predictive capacity. The prediction results of the approach have been compared with the experimental data, MRF and SM model predictions in the literatures. The following conclusions can be drawn from the present work:
\n\t\t\tFor the plate blade of the Rushton turbine stirred vessel, the tangential momentum source added by blade is proposed to be calculated by:
in which
In which
The numerical comparisons of flow field show that the momentum source term approach predictions are in good agreement with the experimental data. It has been also found that the prediction accuracy of momentum source term approach is better than MRF and similar to SM, whereas the computational time of momentum source term approach is the least of the three.
This work is supported by the Ministry of Science and Technology of the People’s Republic of China (grants No. 2006BAC19B02). The authors would like to thank professor Taohong Ye for helpful discussion, the supercomputing center of University of Science and Technology of China for their help in computing.
\n\t\tIn late 2019, cases of pneumonia from unknown origin were detected in Wuhan, China. It was concluded that the cause was a new coronavirus [1, 2]. The World Health Organization (WHO) named the virus SARS-CoV-2 and COVID-19 the associated disease [1, 2]. In the first months of 2020, this disease became a pandemic with a reported high lethality. Since then, the search for treatments has begun.
SARS-CoV-2 is a coronavirus of the beta family and is related to the previously known SARS-CoV [3]. It is transmissible from human to human. The primary transmission is via respiratory droplets. Even so, transmission by other fluids has been reported. The protein that mediates the entry to the host cells is the so-called spike protein. It uses the angiotensin-converting enzyme 2 (ACE2) as a cellular receptor. It primarily affects the lungs and the respiratory system with flu-like symptoms presentation [3]. Nevertheless, it also causes a wide spectrum of conditions from diarrhea to loss of smell and taste. The chief complication due to COVID-19 that can lead to death is pneumonia.
Once the SARS-CoV-2 enters the host cell, the viral RNA is attached to the host ribosome, translating into two large coterminal polyproteins. These proteins are then digested into components by proteolysis for packaging new virions. The papain-like protease (PLpro) and the coronavirus main protease (Mpro) are two proteases involved in this process. SARS-CoV-2 employs RNA-dependent RNA polymerase (RdRp) to replicate the genome of RNA. The four proteins: spike, Mpro, PLpro, and RdRp, are essential to virus assembly and pathogenesis. Mpro and RdRp are the targets for drugs against SARS-CoV-2 [4].
This pandemic has disrupted the global society. Besides global health, it has affected the economy and way of living since most of the interventions to stop the dissemination were non-pharmaceutical. Governments around the world exhorted people to stay at home and social distancing [5].
As a result of the global concern posed by this disease, some experiential recommendations emerged for its treatment. Social networks played a crucial role in the diffusion of these recommendations [6]. A couple of cases are hydroxychloroquine and ivermectin [7]. Much of the supposed evidence was absent or anecdotic. It generated false expectations and misinformation.
There were no previously approved therapeutics for COVID-19 since it was an emerging disease. Later in the pandemic, the WHO authorize the emergency use of some antivirals [8, 9]. The recommendations by other institutions of treatments for use outside of clinical trials were scarce. Such is the case for ivermectin [10].
This chapter aims to review the literature on therapeutics approved by the WHO for emergency use. It will also cover some of the treatments recommended and considered based on empirical results.
It was searched on the therapeutics guidelines published by the WHO [11] and the USA Federal Drug Administration (FDA) [12] for the management of infection by SARS-CoV-2. Based on these results, we searched for more literature in PubMed to obtain evidence from the drugs against SARS-CoV-2.
Besides searching for articles in Pubmed, we used the Google Scholar database to search about treatments against SARS-CoV-2 infection, including the words: Treatment, SARS-CoV-2, COVID-19, Therapeutics, WHO approved COVID-19 drugs, and FDA approved COVID-19 drugs.
The chief inclusion criteria were articles on treatments approved by WHO [11] and FDA [12]. The search also included treatments previously approved for human use but not for COVID-19 and, even so, were used.
There are reports on drugs used empirically for the treatment of COVID-19, and the WHO has made statements on these treatments.
Table 1 shows the drugs of empirical use without approval by the WHO and FDA, for their use against COVID-19 in humans, except in clinical trial settings.
Drug | Indication |
---|---|
Ivermectin | Antiparasitic |
Hydroxychloroquine | Antimalarial |
Nitazoxanide | Antiparasitic |
Azithromycin | Antibiotic |
Some drugs used empirically without approval for emergency use.
Ivermectin is a mixture of 22, 23-dihydroavermectin B1a, and 22, 23-dihydroavermectin B1b. It is macrocyclic lactose with a wide antiparasitic spectrum [10]. Its chemical structure [13], is shown in Figure 1.
Chemical structure of ivermectin. Source. Modified from: PubChem. National Library of Medicine [
It is considered that its action mechanism is by inhibiting the nuclear transport mediated by the heterodimer importin α/β1-responsible for the viral protein’s translocation (HIV-1, SV40)-, necessary for its replication [14, 15, 16]. It has been reported that ivermectin inhibits the SARS-CoV-2 in vitro without stating clearly how it happens [16]. Since then, it was considered a potential treatment.
Even as studies suggest a reduction in mortality, most have methodological deficiencies [17, 18, 19]. Hence, further and rigorous evidence on the use of ivermectin against COVID-19 is necessary. Currently, the use of ivermectin is just recommended in clinical trial settings. Also, the Food and Drug Administration does not recommend the ivermectin use against COVID-19 due to the lack of evidence [20]. The same conclusion is supported by the Sanitary Technologies Assess Department from the Clinical and Sanitary Efficacy Institute [21].
The Pan American Health Organization states that there is no certainty about the risks and benefits from the use of ivermectin [22].
Hydroxychloroquine is a 4-aminoquinoline drug aimed to treat malaria and rheumatologic conditions [22]. In Figure 2, its chemical structure is shown.
Chemical structure of hydroxychloroquine. Source: Modified from PubChem. National Library of Medicine [
Due to the inhibition of SARS-CoV-2 in vitro, it was considered a potential treatment for COVID-19 [24]. Hydroxychloroquine received much public attention even at high political levels. It caused such a phenomenon that most random trials studying it were unable to finish properly, and those that were completed did not show any benefit [25].
Currently, the WHO makes a strong recommendation against its use in its latest therapeutics guidelines [11, 26].
Nitazoxanide and its metabolite Tizoxanide could inhibit the in vitro growth of the canine coronavirus S-378 [26]. Wang M et al. [25] have reported that Nitazoxanide could also inhibit the SARS-CoV-2 growth (Figure 3).
Chemical structure of Nitazoxanide. Source: Modified from PubChem. National Library of Medicine [
Early studies suggested a beneficial effect of Nitazoxanide by reducing the disease severity of COVID-19 [28, 29]. Rocco et al [30], reported that Nitazoxanide did not show a difference in preventing admission to the intensive care unit for COVID-19 patients with pneumonia. In this study, it was showed a difference in secondary outcomes such as hospital discharge.
There are few studies analyzing Nitazoxanide. So far, there is no evidence of a significant benefit for the COVID-19 treatment. The evidence on the use of nitazoxanide is scarce. The WHO does not include this drug in its living guideline for therapeutics and COVID-19 [11].
Azithromycin is an antibiotic mainly prescribed for bacterial diseases and belongs to the family of macrolide [31]. This drug has been considered for COVID-19 treatment due to in vitro results. Its chemical structure is shown in Figure 4.
Chemical structure of azithromycin. Source: Modified from PubChem. National Library of Medicine [
Oldenburg et al. [31], reported the results of a clinical trial involving azithromycin as a candidate. The primary outcome was the resolution of symptoms. It was not found a statistically significant effect between the experimental and the control group. From 23 secondary outcomes, only 5 showed statistically significant differences [33].
Azithromycin was chiefly used with other drugs. As it was used in combination with hydroxychloroquine, its effect and possible harms could not be clearly distinguished [34]. Nevertheless, so far, it is not recommended for COVID-19 treatment. The WHO only includes this drug tangentially in its therapeutics and COVID-19 living guideline while mentioning its use accompanied by hydroxychloroquine [11].
In the following sections, we review some of the therapeutics and their recommendation status by the WHO [11] and FDA [12]. Table 2 shows the drugs and treatments against COVID-19 treated in this section.
Drug | Indication | Dose | Observations |
---|---|---|---|
Molnupiravir | For patients with mild COVID-19 with hospitalization risk. | 800 mg (four pills) twice a day for 5 days | Do not administer in children or pregnant women. There are no data about its safety. |
Casirivimab-Imdevimab | Do not recommend for variants. | Intravenous. Ranging from 1200–2400 mg the total dose | The hospitalization risk decreases by 85%. |
Ritonavir-Nirmatrelvir | Recommended as early as possible within the first 5 days since the onset of symptoms. | 300 mg (two 150 mg tablets) of nirmatrelvir and 100 mg of ritonavir every 12 hours daily for 5 days | |
Remdesivir | Recommended as early as possible within the first 7 days since the onset of symptoms. | Intravenous administration for 3 consecutive days with the following scheme: Day one: 200 mg Day two and three: 100 mg | Conditional recommendation since the existence of potentially most beneficial treatments. |
Favipiravir | Not standardized yet | In animal models, it has potentiated the effect of molnupiravir. |
Drugs for the emergency use against COVID-19.
Molnupiravir is a drug originally designed to treat viruses such as influenza. In recent months, it has been proposed for use against COVID-19 [35]. The chemical structure is shown in Figure 5.
Chemical structure of Molnupiravir. Source: Modified from PubChem. National Library of Medicine [
In the study by Jayk Bernal et al. [37], the molnupiravir group had better outcomes than the placebo one. The chief outcome was hospitalization or death. Even as the sex was imbalanced, further analysis showed that the effect remained. There were no statistically significant differences regarding adverse events among the groups.
Singh et al. [35] conclude that the current evidence suggests that molnupiravir is effective for the prevention of hospitalization and deaths in mild COVID-19 patients. Nevertheless, further evidence is needed for the case of moderate and severe COVID-19 patients. Even far, Extance [38], mentions that the existence of only one pivotal study indicates that the evidence is very limited.
The WHO recommends the use of this drug conditionally due to the absence of data about long-term harms that may cause its use [11].
Casirivimab and imdevimab are monoclonal antibodies that target sites in the receptor binding domain of the SARS-CoV-2 spike glycoprotein [39]. The administration via has been one of the chief difficulties for their extensive use—its administration is intravenous.
The RECOVERY Collaboration Group included this treatment in their analysis [39]. They noted that casirivimab-imdevimab reduced the mortality significatively among seronegative patients (those without previously mounted humoral response).
The WHO recommends it conditionally. The reasons are that other drugs have proven to be more effective and safer. Also, these drugs are easiest to administer [11].
Nirmatrelvir is a drug designed to treat covid-19 by targeting its main protease [40]. It has been administered with ritonavir. Figure 6 shows the chemical structure of nirmatrelvir and ritonavir.
Chemical structure of: (A) nirmatrelvir; and (B) ritornavir. Source: modified from PubChem. National Library of Medicine [
Hammond et al. [40] report that the incidence of hospitalization or death was lower by approximately 6% points in the treatment group than in the control group—observed in the interim and final analysis. The difference among adverse events was not statistically significant.
Its first approval for conditional use was issued in the United Kingdom on December 31, 2021. Since then, other countries have approved this drug in different modalities, such as for emergency use [43].
It is one of the few drugs strongly recommended by the WHO [11].
It is a combination of drugs that aim to inhibit the protease of SARS-CoV-2 and its use was motivated by previous experiences against SARS [44]. Figure 7 shows the chemical structure of lopinavir.
Chemical structure of Lopinavir. Source: Modified from Pubchem. National Library of Medicine [
Cao et al. [44] did not find any statistically significant difference between the control and experimental group in their trial. The primary outcome they took was the decrease of two points on a severe scale or discharge. They recommend further studies to prove or discard benefits from ritonavir–lopinavir.
The WHO makes a recommendation against the use of this combination [11].
Remdesivir is another drug that inhibits SARS-CoV-2 and was considered for its use due to previous research on its effect on SARS and MERS [46]. The chemical structure is shown in Figure 8.
Chemical structure of remdesivir. Source: Modified from Pubchem. National Library of Medicine [
According to Beigel et al. [46], remdesivir outperformed placebo in their clinical trial, which consisted of 1062 patients. They took discharge or hospitalization for monitoring as primary outcome. The patients in the remdesivir group reached the primary outcome approximately 5 days before the patients in the placebo group. In their trial, they administered remdesivir intravenously for three consecutive days with the following regime:
Day one: 200 mg
Day two and three: 100 mg (each day)
Wang Y et al. [48] did not find a statistically significant benefit from the use of remdesivir. Nevertheless, the samples consisted of 237 participants, and a numerical difference among the groups was observed—supporting the use of remdesivir.
Spinner et al. [49], conducted a clinical trial comparing 5- and10-day treatment versus standard care for patients with moderate COVID-19. The differences in the primary outcome (degree on a seven-point scale) were statistically significant between the 5-day group and the standard care group. It was not observed for the differences between the 10-day group and the standard care group. Even though some results were statistically significant different, the authors are uncertain of the clinical importance.
The WHO conditionally recommends remdesivir. They suggest using it in the first 7 days after the onset of symptoms [11].
Favipiravir is a drug with an active agent that halts viral replication of SARS-CoV-2 [50, 51]; its chemical structure is shown in Figure 9.
Chemical structure of favipiravir. Source: Modified from Pubchem. National Library of Medicine [
Manabe et al. [51] conducted a systematic review and meta-analysis on the use of favipiravir against SARS-CoV-2. They found evidence supporting the use of favipiravir to clear the virus. It was observed in various studies a viral clearance around the seventh day after the start of treatment. However, they suggest further analysis and controlled clinical trials since the evidence was heterogeneous and not straightforwardly comparable. Also, they conclude it is necessary for further research on the dose regime to have definitive conclusions.
The WHO only mentions favipiravir tangentially as a drug that might improve the outcomes by combining it with molnupiravir, observed in animal models [11].
After the approval and research on treatments, there are two chief questions to address. The first question is how to distribute the drugs with equity. The other point is how they perform in the face of new SARS-CoV-2 variants.
Regarding the distribution of the treatments, the ones administered orally present clear advantages over the ones administered intravenously. Nevertheless, as pointed out by Bajaj and Stanford [53], there are important challenges to address. So far, the inequities detected are the manufacturing and pricing obstacles, and some countries buying most of the current stock [53].
In the face of new SARS-CoV-2, some studies have addressed the question on which therapeutics remain effective for COVID-19. According to the review made by Fernandes et al. [54], the currently approved antivirals, such as molnupiravir, ritonavir-nirmatrelvir, and remdesivir remain as effective for variants of concern as for the early versions of SARS-CoV-2. Mainly due to their mechanisms of action.
Two years ahead of the COVID-19 pandemic start, plenty of treatment options have been investigated. Only a few of them have resulted in effective and safe alternatives. The WHO [11] and the FDA [12] keep updated on the sources and status of the scientific evidence of each proposal. According to the WHO, ritonavir-nirmatrelvir outperforms other proposed therapeutics.
As SARS-CoV-2 continues mutating, an open question is whether these treatments will remain effective for these new versions. The evidence shows that they are for spike-mutated versions of the virus.
Finally, even though some drugs have been approved, availability is not even in the countries. The factors behind this include the distribution systems and logistics besides costs.
The authors declare no conflict of interest.
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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:189,paginationItems:[{id:"221831",title:"Prof.",name:"Niansheng",middleName:null,surname:"Tang",slug:"niansheng-tang",fullName:"Niansheng Tang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221831/images/system/221831.jpeg",biography:"Niansheng Tang is a Professor of Statistics and Dean of the School of Mathematics and Statistics, Yunnan University, China. He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"417317",title:"Mrs.",name:"Chiedza",middleName:null,surname:"Elvina Mashiri",slug:"chiedza-elvina-mashiri",fullName:"Chiedza Elvina Mashiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"352140",title:"Dr.",name:"Edina",middleName:null,surname:"Chandiwana",slug:"edina-chandiwana",fullName:"Edina Chandiwana",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"342259",title:"B.Sc.",name:"Leonard",middleName:null,surname:"Mushunje",slug:"leonard-mushunje",fullName:"Leonard Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"347042",title:"Mr.",name:"Maxwell",middleName:null,surname:"Mashasha",slug:"maxwell-mashasha",fullName:"Maxwell Mashasha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"2941",title:"Dr.",name:"Alberto J.",middleName:"Jorge",surname:"Rosales-Silva",slug:"alberto-j.-rosales-silva",fullName:"Alberto J. 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In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11401,editor:{id:"67907",title:"Dr.",name:"Amidou",middleName:null,surname:"Samie",slug:"amidou-samie",fullName:"Amidou Samie",profilePictureURL:"https://mts.intechopen.com/storage/users/67907/images/system/67907.jpg",biography:"Dr. Amidou Samie is an Associate Professor of Microbiology at the University of Venda, in South Africa, where he graduated for his PhD in May 2008. He joined the Department of Microbiology the same year and has been giving lectures on topics covering parasitology, immunology, molecular biology and industrial microbiology. He is currently a rated researcher by the National Research Foundation of South Africa at category C2. He has published widely in the field of infectious diseases and has overseen several MSc’s and PhDs. His research activities mostly cover topics on infectious diseases from epidemiology to control. His particular interest lies in the study of intestinal protozoan parasites and opportunistic infections among HIV patients as well as the potential impact of childhood diarrhoea on growth and child development. He also conducts research on water-borne diseases and water quality and is involved in the evaluation of point-of-use water treatment technologies using silver and copper nanoparticles in collaboration with the University of Virginia, USA. 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