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DOE OSTI2016

Probing primordial features with future galaxy surveys

We study the capability of future measurements of the galaxy clustering power spectrum to probe departures from a power-law spectrum for primordial fluctuations. On considering the information from the galaxy clustering power spectrum up to quasi-linear scales, i.e. k < 0.1 h Mpc{sup −1}, we present forecasts for DESI, Euclid and SPHEREx in combination with CMB measurements. As examples of departures in the primordial power spectrum from a simple power-law, we consider four Planck 2015 best-fits motivated by inflationary models with different breaking of the slow-roll approximation. At present, these four representative models provide an improved fit to CMB temperature anisotropies, although not at statistical significant level. As for other extensions in the matter content of the simplest ΛCDM model, the complementarity of the information in the resulting matter power spectrum expected from these galaxy surveys and in the primordial power spectrum from CMB anisotropies can be effective in constraining cosmological models. We find that the three galaxy surveys can add significant information to CMB to better constrain the extra parameters of the four models considered.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Volume-translated cubic EoS and PC-SAFT density models and a free volume-based viscosity model for hydrocarbons at extreme temperature and pressure conditions

This research focuses on providing the petroleum reservoir engineering community with robust models of hydrocarbon density and viscosity at the extreme temperature and pressure conditions (up to 533 K and 276 MPa, respectively) characteristic of ultra-deep reservoirs, such as those associated with the deepwater wells in the Gulf of Mexico. Our strategy is to base the volume-translated (VT) Peng–Robinson (PR) and Soave–Redlich–Kwong (SRK) cubic equations of state (EoSs) and perturbed-chain, statistical associating fluid theory (PC-SAFT) on an extensive data base of high temperature (278–533 K), high pressure (6.9–276 MPa) density rather than fitting the models to low pressure saturated liquid density data. This high-temperature, high-pressure (HTHP) data base consists of literature data for hydrocarbons ranging from methane to C{sub 40}. The three new models developed in this work, HTHP VT-PR EoS, HTHP VT-SRK EoS, and hybrid PC-SAFT, yield mean absolute percent deviation values (MAPD) for HTHP hydrocarbon density of ~2.0%, ~1.5%, and <1.0%, respectively. An effort was also made to provide accurate hydrocarbon viscosity models based on literature data. Viscosity values are estimated with the frictional theory (f-theory) and free volume (FV) theory of viscosity. The best results were obtained when the PC-SAFT equation was used to obtain both the attractive and repulsive pressure inputs to f-theory, and the density input to FV theory. Both viscosity models provide accurate results at pressures to 100 MPa but experimental and model results can deviate by more than 25% at pressures above 200 MPa.

02 PETROLEUM↗

DOE OSTI2021

Mechanistic basis of post-treatment control of SIV after anti-α4β7 antibody therapy

Treating macaques with an anti-α4β7 antibody under the umbrella of combination antiretroviral therapy (cART) during early SIV infection can lead to viral remission, with viral loads maintained at < 50 SIV RNA copies/ml after removal of all treatment in a subset of animals. Depletion of CD8+ lymphocytes in controllers resulted in transient recrudescence of viremia, suggesting that the combination of cART and anti-α4β7 antibody treatment led to a state where ongoing immune responses kept the virus undetectable in the absence of treatment. A previous mathematical model of HIV infection and cART incorporates immune effector cell responses and exhibits the property of two different viral load set-points. While the lower set-point could correspond to the attainment of long-term viral remission, attaining the higher set-point may be the result of viral rebound. Here we expand that model to include possible mechanisms of action of an anti-α4β7 antibody operating in these treated animals. We show that the model can fit the longitudinal viral load data from both IgG control and anti-α4β7 antibody treated macaques, suggesting explanations for the viral control associated with cART and an anti-α4β7 antibody treatment. This effective perturbation to the virus-host interaction can also explain observations in other nonhuman primate experiments in which cART and immunotherapy have led to post-treatment control or resetting of the viral load set-point. Interestingly, because the viral kinetics in the various treated animals differed—some animals exhibited large fluctuations in viral load after cART cessation—the model suggests that anti-α4β7 treatment could act by different primary mechanisms in different animals and still lead to post-treatment viral control. This outcome is nonetheless in accordance with a model with two stable viral load set-points, in which therapy can perturb the system from one set-point to a lower one through different biological mechanisms.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A Multi-frequency analysis of dark matter annihilation interpretations of recent anti-particle and γ-ray excesses in cosmic structures

The Fermi-LAT observation of a γ-ray excess from the galactic-centre, as well as the PAMELA, AMS, and AMS-2 anti-particle excesses, and the recent indications of a Fermi-LAT γ-ray excess in the Reticulum II dwarf galaxy have all been variously put forward as possible indirect signatures of supersymmetric neutralino dark matter. These are of particular interest as the neutralino annihilation models which fit these observations must have observable consequences across the frequency spectrum, from radio to γ-ray emission. Moreover, since dark matter is expected to be a major constituent of cosmic structure, these multi-frequency consequences should be common to such structures across the mass spectrum, from dwarf galaxies to galaxy clusters. Thus, in this work we make predictions for the multi-frequency spectra of three well-known sources dominated by dark matter on cluster, galaxy and dwarf galaxy scales, e.g. the Coma cluster, the galaxy M81, and the Draco dwarf galaxy, using models favoured by dark matter interpretations of the aforementioned observations. We pay special attention to the consequences for these models when their cross-sections are renormalised to reproduce the recent γ-ray excess observed in the Reticulum II dwarf galaxy, as well as using cross-sections from the Fermi-LAT dwarf galaxy limits, which throw a dark matter interpretation of this excess into doubt. We find that the multi-frequency data of Coma and Draco are in conflict with the dark matter interpretation of the AMS, PAMELA and Fermi positron excess. Additionally, models derived from Fermi-LAT galactic centre observations, and AMS-2 re-analysis, present similar but less extensive conflicts. Using the sensitivity projections for the Square Kilometre Array, the Cherenkov Telescope Array, as well as the ASTROGAM and ASTRO-H satellites, we determine the detection prospects for a subset of neutralino models that remain consistent with Planck cosmological constraints. Although the SKA has the greatest sensitivity to dark matter models, we demonstrate that ASTRO-H is well positioned to probe the inverse-Compton scattering emissions from neutralino annihilation and identify characteristics of the spectra which contain information about the neutralino mass and annihilation channel. This means that, given environments with favourable X-ray backgrounds, multi-frequency observation with the next generation of experiments will allow for unprecedented sensitivity to the neutralino parameter space as well as offsetting the individual weaknesses of each observation mode. Finally we show that all of the studied models can be better tested with the SKA phase 1.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1993

Metal abundances at z = 3.4

Echelle spectroscopy data were taken of the quasar 0000-263 on the 4m telescope at CTIO in Chile. Three nights of red and three nights of blue data were obtained (about four hours data per night). The resolution is typically 0.4 A at 5000 A (lamda/d(lamda) = 12500) and has good signal-to-noise over the wavelength range 4600 A to 8000 A. To keep the statistics manageable the data were not rebinned, although the instrument was stable enough for each night's data on the object to be co-added. Arc spectra taken between each exposure were also co-added within the nights. During profile fitting the model was convolved with a Gaussian whose width was equal to nearby arc lines, so any broadening generated by the co-adding of data will not affect the final results. Since OI and HI have the same ionization potential (13.6 eV), (O/H) is approximately (OI/HI). Unfortunately, in this data only the 1302 A OI transition is visible, and it is blended with HI in the Lyman Alpha forest. However, OI and NI coexist (the ionization potential for NI is 14.5 eV) and so the NI triplet can constrain the redshift and turbulent width of the OI. When a fit was made to the regions containing OI and NI absorption three systems were apparent with similar redshifts and velocity widths. These three systems were fitted with tied redshifts and turbulent widths, while the other lines in the region were fitted as Lyman-Alpha. The saturated Lyman-Alpha profile was then fitted with three components at the same redshifts as these observed lines, with the line widths tied. Finally, metallicity ratios for the individual lines and their totals were calculated and compared to solar values. The results for the separate clouds from low to high redshift and for the total are presented.

Cooke, Andrew↗

NASA NTRS2016

CME Flux Rope and Shock Identifications and Locations: Comparison of White Light Data, Graduated Cylindrical Shell Model, and MHD Simulations

Coronal mass ejections (CMEs) are major transient phenomena in the solar corona that are observed with ground-based and spacecraft-based coronagraphs in white light or with in situ measurements by spacecraft. CMEs transport mass and momentum and often drive shocks. In order to derive the CME and shock trajectories with high precision, we apply the graduated cylindrical shell (GCS) model to fit a flux rope to the CME directed toward STEREO A after about 19:00 UT on 29 November 2013 and check the quality of the heliocentric distance-time evaluations by carrying out a three-dimensional magnetohydrodynamic (MHD) simulation of the same CME with the Block Adaptive Tree Solar-Wind Roe Upwind Scheme (BATS-R-US) code. Heliocentric distances of the CME and shock leading edges are determined from the simulated white light images and magnetic field strength data. We find very good agreement between the predicted and observed heliocentric distances, showing that the GCS model and the BATS-R-US simulation approach work very well and are consistent. In order to assess the validity of CME and shock identification criteria in coronagraph images, we also compute synthetic white light images of the CME and shock. We find that the outer edge of a cloud-like illuminated area in the observed and predicted images in fact coincides with the leading edge of the CME flux rope and that the outer edge of a faint illuminated band in front of the CME leading edge coincides with the CME-driven shock front.

Schmidt, J. M.↗

NASA NTRS2019

Surrogate Modeling and Optimization of a Combustor with an Interdigitated Flushwall Injector

Design and Analysis of Computer Experiments (DACE) methods are applied and used to perform surrogate modeling and optimization of a simplified combustor flowpath with an interdigitated flushwall injector. The objectives of the optimization are the thrust potential and combustion efficiency, which are evaluated across a range of flight Mach numbers, duct heights, spanwise spacings, and injection angles. The focus of this work is to highlight the application of a sequential learning approach, in order to learn about the responses of the objective functions over the design space and to identify local regions of interest for further analysis. This approach is contrasted to a previous effort where only a single sampling set was used to fit surrogate models and perform optimization. The optimal solutions resulting from the previous and present approaches are different, due to surrogate model-guided local refinement of the design space allowed by the sequential learning method. The values of the global error estimates between the previous and present approaches are comparable, but the sequential method proved more computationally cost-effective. Further refinement in the optimal regions might be needed to improve predictive capability of surrogate models and to obtain the optimal solutions sets.

Rajiv R Shenoy↗

DOE OSTI2025

bmdrc: Python package for quantifying phenotypes from chemical exposures with benchmark dose modeling

Though chemical exposures are known to potentially have negative impacts on health, including contributing to chronic diseases such as cancer, the quantitative contribution of risk is not fully understood for every chemical. A commonly used approach to quantify levels of risk is to measure the proportion of organisms (such as a total number of zebrafish on a plate or mice in a cage) with abnormal behavioral responses or morphology at increasing concentrations of chemical exposure. A particular challenge with processing the proportional data from these assays is the appropriate estimation of chemical concentration levels that result in malformations or acute toxicity, as these values typically vary between experimental measurements. The recommended approach by the Environmental Protection Agency (EPA) is to fit benchmark dose curves with specific filters and model fitting steps, which are crucial to properly processing the proportional data. Several tools exist for the fitting of benchmark dose response curves, but none are standalone Python libraries built to process both morphological and behavioral data as proportions with all the EPA recommended filters, filter parameters, models, and model parameters. Thus, here we present the benchmark dose response curve (bmdrc) Python library, which was built to closely follow these EPA guidelines with helpful visualizations of filters and fitted model curves, and reports for reproducibility purposes. bmdrc is open-source and has demonstrated utility as a support package to an existing web portal for information on chemicals (https://srp.pnnl.gov). Our package will support any toxicology analysis where the response is a proportional value at increasing levels of a concentration of a chemical or chemical mixture.

Superfund↗

DOE OSTI2020

Probing Transit Timing Variation and Its Possible Origin with 12 New Transits of TrES-3b

We present 12 new transit light curves of the hot-Jupiter TrES-3b observed during 2012−2018 to probe the transit timing variation (TTV). By combining the midtransit times determined from these 12 transit data with those reestimated through uniform procedure from 71 transit data available in the literature, we derive new linear ephemeris and obtain the timing residuals that suggest the possibility of TTV in the TrES-3 system. However, the frequency analysis shows that the possible TTV is unlikely to be periodic, indicating the absence of an additional body in this system. To explore the other possible origins of TTV, the orbital decay and apsidal precession ephemeris models are fitted to the transit time data. We find the decay rate of TrES-3b to be P-dot {sub q}=−4.1±3.1 ms yr{sup −1}, and the corresponding estimated modified stellar tidal quality factor of Q{sub ∗}{sup ′}∼1.11×10{sup 5} is consistent with the theoretically predicted values for the stars hosting the hot-Jupiters. The shift in the transit arrival time of TrES-3b after 11 years is expected to be T {sub shift} ∼ 69.55 s, which is consistent with the rms of the timing residuals. Besides, we find that the apsidal precession ephemeris model is statistically less probable than the other considered ephemeris models. It is also discussed that despite the fact that the linear ephemeris model appears to be the most plausible model to represent the transit time data, the possibility of the orbital decay cannot be completely ruled out in the TrES-3 system. To confirm this, further high-precision and high-cadence follow-up observation of transits of TrES-3b would be important.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Mathematical modeling and parameter estimation of MFI membranes for para/ortho‐xylene separation

Abstract A mathematical model of a membrane with a thin, oriented, and selective MFI layer, which also includes contributions from defects, pore blockages, support layer, and external mass transfer, was formulated based on the Maxwell‐Stefan equations. It was validated using reported (Kim et al., Angew Chemie Int Ed, 2018, 57:480–485; Jeon et al., Nature, 2017, 543:690–694) para/ortho‐xylene separation data from five MFI membranes. The diffusivities of the xylenes were considered to be the same for all membranes, while the thickness and the density of defects and pore blockage were treated as unique properties of each membrane, and their contributions were estimated by fitting the model to the corresponding separation data. The effects of these properties and the role of permeate pressure on the separation performance were subsequently analyzed. The proposed modeling, parameter estimation, and analysis framework allow one to quantitatively interpret the variation of separation performance, to understand separation bottlenecks, and to provide guidance for designing membranes with desired performance.

Liu, Jingjun↗

DOE OSTI2014

Metal-poor dwarf galaxies in the SIGRID galaxy sample. II. The electron temperature-abundance calibration and the parameters that affect it

In this paper, we use the Mappings photoionization code to explore the physical parameters that impact on the measurement of electron temperature and abundance in H II regions. In our previous paper, we presented observations and measurements of physical properties from the spectra of 17 H II regions in 14 isolated dwarf irregular galaxies from the SIGRID sample. Here, we analyze these observations further, together with three additional published data sets. We explore the effects of optical thickness, electron density, ionization parameter, ionization source, and non-equilibrium effects on the relation between electron temperature and metallicity. We present a standard model that fits the observed data remarkably well at metallicities between one-tenth and 1 solar. We investigate the effects of optically thin H II regions, and show that they can have a considerable effect on the measured electron temperature, and that there is evidence that some of the observed objects are optically thin. We look at the role of the ionization parameter and find that lower ionization parameter values give better fits at higher oxygen abundance. We show that higher pressures combined with low optical depth, and also κ electron energy distributions at low κ values, can generate the apparent high electron temperatures in low-metallicity H II regions, and that the former provides the better fit to observations. We examine the effects of these parameters on the strong line diagnostic methods. We extend this to three-dimensional diagnostic grids to confirm how well the observations are described by the grids.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

3D modeling of electric fields in the LUX detector

This work details the development of a three-dimensional (3D) electric field model for the LUX detector. The detector took data to search for weakly interacting massive particles (WIMPs) during two periods. After the first period completed, a time-varying non-uniform negative charge developed in the polytetrafluoroethylene (PTFE) panels that define the radial boundary of the detector's active volume. This caused electric field variations in the detector in time, depth and azimuth, generating an electrostatic radially-inward force on electrons on their way upward to the liquid surface. To map this behavior, 3D electric field maps of the detector's active volume were generated on a monthly basis. This was done by fitting a model built in COMSOL Multiphysics to the uniformly distributed calibration data that were collected on a regular basis. The modeled average PTFE charge density increased over the course of the exposure from -3.6 to -5.5 μC/m 2 . Here, from our studies, we deduce that the electric field magnitude varied locally while the mean value of the field of ~200 V/cm remained constant throughout the exposure. As a result of this work the varying electric fields and their impact on event reconstruction and discrimination were successfully modeled.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1990

Long-Term Trends in the Concentrations of SF6, CHClF2, and COF2 in the Lower Stratosphere from Analysis of High-Resolution Infrared Solar Occultation Spectra

Long-term trends in the concentrations of SF6, CHClF2 (CFC-22), and COF2 in the lower stratosphere have been derived from analysis of ca. 1980 and more recent infrared solar occultation spectra recorded near 32 deg N latitude at approx. 0.02/ cm resolution. Consistent sets of line parameters and spectral calibration methods have been used in the retrievals to minimize systematic error effects. Quoted error limits are 1 sigma estimated precisions. The SF6 and CHClF2 results are based on spectra recorded by balloon-borne interferometers in March 1981 and June 1988 and a comparison of these results with the Atmospheric Trace Molecule Spectroscopy (ATMOS) Experiment/Spacelab 3 measurements obtained in May 1985 near 30 deg N latitude. In the 13-18 km altitude range the mean measured SF6 mixing ratio in parts per trillion by volume (pptv) increased from 1.17 +/- 0.21 in March 1981 to 2.02 +/- 0.20 pptv in June 1988, and the CHClF2 mixing ratio below 15 km altitude increased from 51 +/- 8 pptv in March 1981 to 102 +/- 10 pptv in June 1988. The CHClF2 retrievals used new empirical CHClF2 line parameters derived from 0.03/cm resolution laboratory spectra recorded at six temperatures between 203 and 293 K; the derived mixing ratios are approx. 30% higher than obtained with earlier sets of line parameters, thereby removing a large discrepancy noted previously between IR and in situ measurements of CHClF2. Assuming an exponential growth model for fitting the trends, SF6 and CHClF2 mean increase rates of 7.4% +/- 1.9% and 9.4% +/- 1.3% /year, are obtained, respectively, which correspond to cumulative increases by factors of approx. 1.7 and -2.0 in the concentrations of these gases over the 7.2-year measurement period. Analysis of spectra recorded in October 1979 and April 1989 yields COF2 volume mixing ratios that are respectively 0.44 +/- 0.17 and 1.21 +/- 0.24 times the ATMOS/Spacelab 3 values, from which an average COF2 increase rate of 10.3 +/- 1.8%/ year over this time period has been estimated. The present results are compared with previously reported observations and trends and with one-dimensional model calculations. The model calculated trends are in reasonably good agreement with the observations.

Rinsland, C. P.↗

DOE OSTI2019

Modeling the Connection between Subhalos and Satellites in Milky Way–like Systems

We develop a comprehensive and flexible model for the connection between satellite galaxies and dark matter subhalos in dark matter-only zoom-in simulations of Milky Way (MW)–mass host halos. We systematically identify the physical and numerical uncertainties in the galaxy–halo connection and simulations underlying our method, including (i) the influence of host halo properties; (ii) the relationship between satellite luminosities and subhalo properties, including the effects of reionization; (iii) the relationship between satellite and subhalo locations; (iv) the relationship between satellite sizes and subhalo properties, including the effects of tidal stripping; (v) satellite and subhalo disruption due to baryonic effects; and (vi) artificial subhalo disruption and orphan satellites. To illustrate our approach, we fit this model to the luminosity distribution of both classical MW satellites and those discovered in the Sloan Digital Sky Survey by performing realistic mock observations that depend on the luminosity, size, and distance of our predicted satellites, and we infer the total satellite population that will be probed by upcoming surveys. As a result, we argue that galaxy size and surface brightness modeling will play a key role in interpreting current and future observations, as the expected number of observable satellites depends sensitively on their surface brightness distribution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Flux flattening in axion monodromy inflation

String theory models of axion monodromy inflation exhibit scalar potentials which are quadratic for small values of the inflaton field and evolve to a more complicated function for large field values. Oftentimes the large field behaviour is gentler than quadratic, lowering the tensor-to-scalar ratio. This effect, known as flattening, has been observed in the string theory context through the properties of the DBI+CS D-brane action. We revisit such flattening effects in type IIB flux compactifications with mobile D7-branes, with the inflaton identified with the D7-brane position. We observe that here, with a generic choice of background fluxes, flattening effects are larger than previously observed, allowing to fit these models within current experimental bounds. In particular, we compute the cosmological observables in scenarios compatible with closed-string moduli stabilisation, finding tensor-to-scalar ratios as low as r ~ 0.04. These are models of single field inflation in which the inflaton is much lighter than the other scalars through a mild tuning of the compactification data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Connecting the Light Curves of Type IIP Supernovae to the Properties of Their Progenitors

Abstract Observations of core-collapse supernovae (CCSNe) reveal a wealth of information about the dynamics of the supernova ejecta and its composition but very little direct information about the progenitor. Constraining properties of the progenitor and the explosion requires coupling the observations with a theoretical model of the explosion. Here we begin with the CCSN simulations of Couch et al., which use a nonparametric treatment of the neutrino transport while also accounting for turbulence and convection. In this work we use the SuperNova Explosion Code to evolve the CCSN hydrodynamics to later times and compute bolometric light curves. Focusing on Type IIP SNe (SNe IIP), we then (1) directly compare the theoretical STIR explosions to observations and (2) assess how properties of the progenitor’s core can be estimated from optical photometry in the plateau phase alone. First, the distribution of plateau luminosities ( L 50 ) and ejecta velocities achieved by our simulations is similar to the observed distributions. Second, we fit our models to the light curves and velocity evolution of some well-observed SNe. Third, we recover well-known correlations, as well as the difficulty of connecting any one SN property to zero-age main-sequence mass. Finally, we show that there is a usable, linear correlation between iron core mass and L 50 such that optical photometry alone of SNe IIP can give us insights into the cores of massive stars. Illustrating this by application to a few SNe, we find iron core masses of 1.3–1.5 M ⊙ with typical errors of 0.05 M ⊙ . Data are publicly available online on Zenodo: doi: 10.5281/zenodo.6631964 .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Improving intermolecular interactions in DFTB3 using extended polarization from chemical-potential equalization

Semi-empirical quantum mechanical methods traditionally expand the electron density in a minimal, valence-only electron basis set. The minimal-basis approximation causes molecular polarization to be underestimated, and hence intermolecular interaction energies are also underestimated, especially for intermolecular interactions involving charged species. In this work, the third-order self-consistent charge density functional tight-binding method (DFTB3) is augmented with an auxiliary response density using the chemical-potential equalization (CPE) method and an empirical dispersion correction (D3). The parameters in the CPE and D3 models are fitted to high-level CCSD(T) reference interaction energies for a broad range of chemical species, as well as dipole moments calculated at the DFT level; the impact of including polarizabilities of molecules in the parameterization is also considered. Parameters for the elements H, C, N, O, and S are presented. The Root Mean Square Deviation (RMSD) interaction energy is improved from 6.07 kcal/mol to 1.49 kcal/mol for interactions with one charged species, whereas the RMSD is improved from 5.60 kcal/mol to 1.73 for a set of 9 salt bridges, compared to uncorrected DFTB3. For large water clusters and complexes that are dominated by dispersion interactions, the already satisfactory performance of the DFTB3-D3 model is retained; polarizabilities of neutral molecules are also notably improved. Overall, the CPE extension of DFTB3-D3 provides a more balanced description of different types of non-covalent interactions than Neglect of Diatomic Differential Overlap type of semi-empirical methods (e.g., PM6-D3H4) and PBE-D3 with modest basis sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗