A continuous flow reactor for the flexible production of different formulations: CFD-aided design

The increasing need to improve the sustainability of industrial processes requires more flexible and intensified solutions. For this purpose, nowadays lots of efforts are made to switch from batch to continuous processes, the latter being able to ensure the same processing history to all fluid elements, with a consequent better control of the operating conditions and product quality. The present work aims at developing a continuous flow reactor for the production of several fine chemicals, including medical-surgical aids, but also other substances for specific industrial sectors. The plant is basically an inline reactor equipped with various static mixers and side inlets, and it is conceived to ensure on-site production. This is an important feature also in light of the recent COVID-19 pandemic, which asked for flexible and distributed production of chemicals. Numerical simulations based on computational fluid dynamics are employed to study the performance, in terms of pressure drops and degree of mixing, of different static mixers, that is, the Lightnin Inliner Series 50 and Ross low pressure drop (LPD), combining various elements of mixing and injections in different operating conditions in both laminar and turbulent regimes. The results highlighted how numerical simulations may represent a valid tool for supporting the detailed design of such flow reactors by allowing the evaluation of the optimal design solutions.

Central Nervous System Distribution of the Ataxia-Telangiectasia Mutated Kinase Inhibitor AZD1390: Implications for the Treatment of Brain Tumors

Effective drug delivery to the brain is critical for the treatment of glioblastoma (GBM), an aggressive and invasive primary brain tumor that has a dismal prognosis. Radiation therapy, the mainstay of brain tumor treatment, works by inducing DNA damage. Therefore, inhibiting DNA damage response (DDR) pathways can sensitize tumor cells to radiation and enhance cytotoxicity. AZD1390 is an inhibitor of ataxia-telangiectasia mutated kinase, a critical regulator of DDR. Our in vivo studies in the mouse indicate that delivery of AZD1390 to the central nervous system (CNS) is restricted due to active efflux by P-glycoprotein (P-gp). The free fraction of AZD1390 in brain and spinal cord were found to be low, thereby reducing the partitioning of free drug to these organs. Coadministration of an efflux inhibitor significantly increased CNS exposure of AZD1390. No differences were observed in distribution of AZD1390 within different anatomic regions of CNS, and the functional activity of P-gp and breast cancer resistance protein also remained the same across brain regions. In an intracranial GBM patient-derived xenograft model, AZD1390 accumulation was higher in the tumor core and rim compared with surrounding brain. Despite this heterogenous delivery within tumor-bearing brain, AZD1390 concentrations in normal brain, tumor rim, and tumor core were above in vitro effective radiosensitizing concentrations. These results indicate that despite being a substrate of efflux in the mouse brain, sufficient AZD1390 exposure is anticipated even in regions of normal brain. SIGNIFICANCE STATEMENT Given the invasive nature of glioblastoma (GBM), tumor cells are often protected by an intact blood-brain barrier, requiring the development of brain-penetrant molecules for effective treatment. We show that efflux mediated by P-glycoprotein (P-gp) limits central nervous system (CNS) distribution of AZD1390 and that there are no distributional differences within anatomical regions of CNS. Despite efflux by P-gp, concentrations effective for potent radiosensitization are achieved in GBM tumor-bearing mouse brains, indicating that AZD1390 is an attractive molecule for clinical development of brain tumors.Copyright © 2022 American Society for Pharmacology and Experimental Therapy. All rights reserved.

Computational fluid dynamic analysis of corona virus patients breathing in an airplane

Effective ventilation systems are essential to control the transmission of airborne aerosol particles, such as the SARS-CoV-2 virus in aircraft cabins, which is a significant concern for people commuting by airplane. Validated computational fluid dynamic models are frequently and effectively used to investigate air distribution and pollutant transport. In this study, the effectiveness of different ventilation systems with varying outlet vent locations were computationally compared to determine the best ventilation system for minimizing the risk of airborne transmission. The cabin air conditioning system was optimized to determine how design variables (air inlet temperature, outlet valve width and location, and mass flow rate) affect output parameters, including particle residence time, age of air, and thermal comfort conditions. Inlet mass flow rate was observed to be an influential variable impacting all output parameters, especially on age of air, where it was the most influential. In contrast, the least effective variable was width of the outlet valve, which only affected the particle residence time. Also, Predicted Mean Vote and Predicted Percentage Dissatisfied indices were the most affected by air inlet temperature, which had an inverse relation, while the outlet valve location had the greatest effect on particle residence time. © 2023 Author(s).

Optimal position of air purifiers in elevator cabins for the improvement of their ventilation effectiveness

Ventilation in confined spaces is essential to reduce the airborne transmission of viruses responsible for respiratory diseases such as COVID-19. Mechanical ventilation using purifiers is an interesting solution for elevator cabins to reduce the risk of infection and improve the air quality. In this work, the optimal position and blowing direction of these devices to maximize ventilation and minimize the residence time of the air inside two cabins (large and small) is studied. Special attention is devoted to idle periods when the cabin is not used by the passengers, in order to keep the cabin ambient safe and clean, avoiding that the trapped air in the cabin (after its use) could suppose a reservoir for contaminants. CFD numerical models of two typical cabin geometries, including the discretization of small slots and grilles for infiltration, have been developed. A full 3D URANS approach with a k-epsilon RNG turbulence model and a non-reactive scalar to compute the mean age of air (MAA) was employed. The CFD results have been also validated with experimental measurements from a home-made 1:4 small-scale mock-up. The optimal position of the purifier is on the larger sidewall of the cabins for a downward blowing direction (case 1 of the database). Flow rates in the range of 0.4–0.6 m3/min, depending on the size of the cabin, are sufficient to assure a correct ventilation. Upward blowing may be preferable only if interaction of the jet core with the ceiling or other flow deflecting elements are found. In general, the contribution of infiltrations (reaching values of up to 10%), and how these secondary flows interact with the main flow pattern driven by the purifier, is relevant and not considered previously in the literature. Though an optimal position can improve ventilation considerably, it has been proven that a good choice of the purification flow rate is more critical to ensure an adequate air renewal. © 2022 The Authors

A continuous flow reactor for the flexible production of different formulations

The increasing need to improve the sustainability of industrial processes requires more flexible and intensified solutions. For this purpose, nowadays lots of efforts are made to switch from batch to continuous processes, the latter being able to ensure the same processing history to all fluid elements, with a consequent better control of the operating conditions and product quality. The present work aims at developing a continuous flow reactor for the production of several fine chemicals, including medical-surgical aids, but also other substances for specific industrial sectors. The plant is basically an inline reactor equipped with various static mixers and side inlets, and it is conceived to ensure on-site production. This is an important feature also in light of the recent COVID-19 pandemic, which asked for flexible and distributed production of chemicals. Numerical simulations based on computational fluid dynamics are employed to study the performance, in terms of pressure drops and degree of mixing, of different static mixers, that is, the Lightnin Inliner Series 50 and Ross low pressure drop (LPD), combining various elements of mixing and injections in different operating conditions in both laminar and turbulent regimes. The results highlighted how numerical simulations may represent a valid tool for supporting the detailed design of such flow reactors by allowing the evaluation of the optimal design solutions.

Design of peptide-based coronavirus inhibitors that target disruption of 3CLpro protease self-association

3CLpro is a highly conserved main protease found in coronaviruses, which makes it an attractive target for the development of broad-spectrum coronavirus inhibitors. Its homodimer plays an essential role in coronavirus replication. The SGFRKMAF peptide spanning the N-finger domain of 3CLpro is known to disrupt dimerization, however, its mode of action is not fully understood. We used the conformation of this peptide segment in the observed protein crystal structure as the basis for developing leads for coronavirus dimerization inhibitors. We investigated the interaction of the SGFRKMAF peptide with the 3CLpro monomer in blind docking simulations using a representative ensemble of its conformational states. We identified 8 basins of attraction, distinct regions where the peptide accumulates at the 3CLpro monomer surface. Two binding regions dominate: one, located at the groove between domains II and III of the monomer, and the other at the interface region where dimerization takes place. Peptide binding at these two regions resulted in stable peptide-protein complexes in 90 ns fully solvated molecular dynamics simulations. Using protein-protein docking simulations, we found that peptide binding to at least one of the monomers at the dimer interface region is likely to disrupt 3CLpro dimerization through blocking the "hot spot" residues that predominantly account for dimer stabilization. Peptide binding to the interface region in one of the monomers, and to the groove between domains II and III in the other monomer, leads also to disruption of the native dimer structure. The peptide binding constant at the interface region relative to other regions (K-in/out) was estimated to be similar to 0.12 at 310 K, suggesting that at thermodynamic equilibrium the peptide does not solely bind to one of the basins, corroborating the view of a cooperative mechanism between the two basins. In order to optimize the potential of the SGFRKMAF peptide to disrupt 3CLpro dimerization via preferential binding to the interface region, we conducted systematic mutation of the M6 and F8 residues, sites identified as key to blocking hot spot regions in the observed dimer structure. We found that the [M6F, F8S], [M6I, F8Q], [M6Q, F8T] and [M6T, F8I] mutations result in an increase of K-in/out by at least one order of magnitude, with the [M6F, F8S] mutation (the SGFRKFAS peptide) showing the highest value of K-in/out (similar to 2.53). These mutant peptides are, therefore, candidates for peptide-based lead structures in the development of broad-spectrum coronavirus inhibitors.

Dynamics of COVID-19 pandemic in India and Pakistan: A metapopulation modelling approach.

India has been the latest global epicenter for COVID-19, a novel coronavirus disease that emerged in China in late 2019. We present a base mathematical model for the transmission dynamics of COVID-19 in India and its neighbor, Pakistan. The base model was rigorously analyzed and parameterized using cumulative COVID-19 mortality data from each of the two countries. The model was used to assess the population-level impact of the control and mitigation strategies implemented in the two countries (notably non-pharmaceutical interventions). Numerical simulations of the basic model indicate that, based on the current baseline levels of the control and mitigation strategies implemented, the pandemic trajectory in India is on a downward trend. This downward trend will be reversed, and India will be recording mild outbreaks, if the control and mitigation strategies are relaxed from their current levels. By early September 2021, our simulations suggest that India could record up to 460,000 cumulative deaths under baseline levels of the implemented control strategies, while Pakistan (where the pandemic is comparatively milder) could see over 24,000 cumulative deaths at current mitigation levels. The basic model was extended to assess the impact of back-and-forth mobility between the two countries. Simulations of the resulting metapopulation model show that the burden of the COVID-19 pandemic in Pakistan increases with increasing values of the average time residents of India spend in Pakistan, with daily mortality in Pakistan peaking in mid-August to mid-September of 2021. Under the respective baseline control scenarios, our simulations show that the back-and-forth mobility between India and Pakistan could delay the time-to-elimination of the COVID-19 pandemic in India and Pakistan to November 2022 and July 2022, respectively.

A chemical engineer's take of COVID-19 epidemiology.

SARS-CoV-2, a novel coronavirus spreading worldwide, was declared a pandemic by the World Health Organization 3 months after the outbreak. Termed as COVID-19, airborne or surface transmission occurs as droplets/aerosols and seems to be reduced by social distancing and wearing mask. Demographic and geo-temporal factors like population density, temperature, healthcare system efficiency index and lockdown stringency index also influence the COVID-19 epidemiological curve. In the present study, an attempt is made to relate these factors with curve characteristics (mean and variance) using the classical residence time distribution analysis. An analogy is drawn between the continuous stirred tank reactor and infection in a given country. The 435 days dataset for 15 countries, where the first wave of epidemic is almost ending, have been considered in this study. Using method of moments technique, dispersion coefficient has been calculated. Regression analysis has been conducted to relate parameters with the curve characteristics.

Modeling the viral load dependence of residence times of virus-laden droplets from COVID-19-infected subjects in indoor environments.

In the ongoing COVID-19 pandemic situation, exposure assessment and control strategies for aerosol transmission path are feebly understood. A recent study pointed out that Poissonian fluctuations in viral loading of airborne droplets significantly modifies the size spectrum of the virus-laden droplets (termed as "virusol") (Anand and Mayya, 2020). Herein we develop the theory of residence time of the virusols, as contrasted with complete droplet system in indoor air using a comprehensive "Falling-to-Mixing-Plate-out" model that considers all the important processes namely, indoor dispersion of the emitted puff, droplet evaporation, gravitational settling, and plate out mechanisms at indoor surfaces. This model fills the existing gap between Wells falling drop model (Wells, 1934) and the stirred chamber models (Lai and Nazarofff, 2000). The analytical solutions are obtained for both 1-D and 3-D problems for non-evaporating falling droplets, used mainly for benchmarking the numerical formulation. The effect of various parameters is examined in detail. Significantly, the mean residence time of virusols is found to increase nonlinearly with the viral load in the ejecta, ranging from about 100 to 150 s at low viral loads (<104 /ml) to about 1100-1250 s at high viral loads (>1011 /ml). The implications are discussed.

Polyvinyl Alcohol-Based 3D Printed Tablets: Novel Insight into the Influence of Polymer Particle Size on Filament Preparation and Drug Release Performance.

Three-dimensional printing (3DP) by fused deposition modeling (FDM) has gained momentum as a promising pharmaceutical manufacturing method due to encouraging forward-looking perspectives in personalized medicine preparation. The current challenges the technology has for applicability in the fabrication of solid dosage forms include the limited range of suitable pharmaceutical grade thermoplastic materials. Hence, it is important to investigate the implications of variable properties of the polymeric carrier on the preparation steps and the final output, as versatile products could be obtained by using the same material. In this study, we highlighted the influence of polyvinyl alcohol (PVA) particle size on the residence time of the mixtures in the extruder during the drug-loaded filament preparation step and the consequent impact on drug release from the 3D printed dosage form. We enhanced filament printability by exploiting the plasticizing potential of the active pharmaceutical ingredient (API) and we explored a channeled tablet model as a design strategy for dissolution facilitating purposes. Our findings disclosed a new perspective regarding material considerations for the preparation of PVA-based solid dosage forms by coupling hot melt extrusion (HME) and FDM-3DP.

Temporal and Spatial Variation of Radon Concentrations in Environmental Water from Okinawa Island, Southwestern Part of Japan.

In this study, to get a better understanding in characterizing groundwater and ensure its effective management, the radon concentrations in water samples were measured through Ryukyu limestone in southern Okinawa Island, Japan. Water samples were collected from a limestone cave (Gyokusendo cave, dropping water) and two springs (Ukinju and Komesu, spring water), and the radon concentrations were measured by liquid scintillation counters. The radon concentrations in the samples from the Gyokusendo cave, and Ukinju and Komesu springs were 10 ± 1.3 Bq L-1, 3.2 ± 1.0 Bq L-1, and 3.1 ± 1.1 Bq L-1, respectively. The radon concentrations showed a gradually increasing trend from summer to autumn and decreased during winter. The variation of radon concentrations in the dripping water sample from the Gyokusendo cave showed a lagged response to precipitation changes by approximately 2-3 months. The estimated radon concentrations in the dripping water sample were calculated with the measured radon concentrations from the dripping water obtained during the study period. Based on our results, groundwater in the Gyokusendo cave system was estimated to percolate through the Ryukyu limestone in 7-10 days, and the residence time of groundwater in the soil above Gyokusendo cave was estimated to be approximately 50-80 days. This work makes a valuable contribution to the understanding of groundwater processes in limestone aquifers, which is essential for ensuring groundwater sustainability.