Mechanistic modeling projections of antibody persistence after homologous booster regimens of COVID-19 vaccine Ad26.COV2.S in humans.

Mechanistic model-based simulations can be deployed to project the persistence of humoral immune response following vaccination. We used this approach to project the antibody persistence through 24 months from the data pooled across five clinical trials in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-seronegative participants following vaccination with Ad26.COV2.S (5 × 1010 viral particles), given either as a single-dose or a homologous booster regimen at an interval of 2, 3, or 6 months. Antibody persistence was quantified as the percentage of participants with detectable anti-spike binding and wild-type virus neutralizing antibodies. The projected overall 24-month persistence after single-dose Ad26.COV2.S was 70.5% for binding antibodies and 55.2% for neutralizing antibodies, and increased after any homologous booster regimen to greater than or equal to 89.9% for binding and greater than or equal to 80.0% for neutralizing antibodies. The estimated model parameters quantifying the rates of antibody production attributed to short-lived and long-lived plasma cells decreased with increasing age, whereas the rate of antibody production mediated by long-lived plasma cells was higher in women relative to men. Accordingly, a more pronounced waning of antibody responses was predicted in men aged greater than or equal to 60 years and was markedly attenuated following any homologous boosting regimen. The findings suggest that homologous boosting might be a viable strategy for maintaining protective effects of Ad26.COV2.S for up to 24 months following prime vaccination. The estimation of mechanistic modeling parameters identified the long-lived plasma cell pathway as a key contributor mediating antibody persistence following single-dose and homologous booster vaccination with Ad26.COV2.S in different subgroups of recipients stratified by age and sex.

Mechanistic Model Describing the Time Course of Humoral Immunity Following Ad26.COV2.S Vaccination in Non-Human Primates.

Mechanistic modeling can be used to describe the time course of vaccine-induced humoral immunity and to identify key biologic drivers in antibody production. We used a six-compartment mechanistic model to describe a 20-week time course of humoral immune responses in 56 non-human primates (NHPs) elicited by vaccination with Ad26.COV2.S according to either a single-dose regimen (1 × 1011 or 5 × 1010 viral particles [vp]) or a two-dose homologous regimen (5 × 1010 vp) given in an interval of 4 or 8 weeks. Humoral immune responses were quantified by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-specific binding antibody concentrations as determined by spike protein-enzyme-linked immunosorbent assay. The mechanistic model adequately described the central tendency and variability of binding antibody concentrations through 20 weeks in all vaccination arms. The estimation of mechanistic modeling parameters revealed greater contribution of the antibody production mediated by short-lived cells as compared with long-lived cells in driving the peak response, especially post second dose when a more rapid peak response was observed. The antibody production mediated by long-lived cells was identified as relevant for generating the first peak and for contributing to the long-term time course of sustained antibody concentrations in all vaccination arms. The findings contribute evidence on the key biologic components responsible for the observed time course of vaccine-induced humoral immunity in NHPs and constitute a step toward defining immune biomarkers of protection against SARS-CoV-2 that might translate across species. SIGNIFICANCE STATEMENT: We demonstrate the adequacy of a mechanistic modeling approach describing the time course of binding antibody concentrations in non-human primates (NHPs) elicited by different dose levels and regimens of Ad26.COV2.S. The findings are relevant for informing the mechanism-based accounts of vaccine-induced humoral immunity in NHPs and translational research efforts aimed at identifying immune biomarkers of protection against SARS-CoV-2 infection.

Quantifying Antibody Persistence After a Single Dose of COVID-19 Vaccine Ad26.COV2.S in Humans Using a Mechanistic Modeling and Simulation Approach.

Understanding persistence of humoral immune responses elicited by vaccination against coronavirus disease 2019 (COVID-19) is critical for informing the duration of protection and appropriate booster timing. We developed a mechanistic model to characterize the time course of humoral immune responses in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-seronegative adults after primary vaccination with the Janssen COVID-19 vaccine, Ad26.COV2.S. The persistence of antibody responses was quantified through mechanistic modeling-based simulations. Two biomarkers of humoral immune responses were examined: SARS-CoV-2 neutralizing antibodies determined by wild-type virus neutralization assay (wtVNA) and spike protein-binding antibodies determined by indirect spike protein enzyme-linked immunosorbent assay (S-ELISA). The persistence of antibody responses was defined as the period of time during which wtVNA and S-ELISA titers remained above the lower limit of quantification. A total of 442 wtVNA and 1,185 S-ELISA titers from 82 and 220 participants, respectively, were analyzed following administration of a single dose of Ad26.COV2.S (5 × 1010 viral particles). The mechanistic model adequately described the time course of observed wtVNA and S-ELISA serum titers and its associated variability up to 8 months following vaccination. Mechanistic model-based simulations show that single-dose Ad26.COV2.S elicits durable but waning antibody responses up to 24 months following immunization. Of the estimated model parameters, the production rate of memory B cells was decreased in older adults relative to younger adults, and the antibody production rate mediated by long-lived plasma cells was increased in women relative to men. A steeper waning of antibody responses was predicted in men and in older adults.

SARS-CoV-2 binding and neutralizing antibody levels after Ad26.COV2.S vaccination predict durable protection in rhesus macaques.

Several COVID-19 vaccines have recently gained authorization for emergency use. Limited knowledge on duration of immunity and efficacy of these vaccines is currently available. Data on other coronaviruses after natural infection suggest that immunity to SARS-CoV-2 might be short-lived, and preliminary evidence indicates waning antibody titers following SARS-CoV-2 infection. In this work, we model the relationship between immunogenicity and protective efficacy of a series of Ad26 vectors encoding stabilized variants of the SARS-CoV-2 Spike protein in rhesus macaques and validate the analyses by challenging macaques 6 months after immunization with the Ad26.COV2.S vaccine candidate that has been selected for clinical development. We show that Ad26.COV2.S confers durable protection against replication of SARS-CoV-2 in the lungs that is predicted by the levels of Spike-binding and neutralizing antibodies, indicating that Ad26.COV2.S could confer durable protection in humans and immunological correlates of protection may enable the prediction of durability of protection.

Oxycodone Effect on Pupil Constriction in Recreational Opioid Users: A Pharmacokinetic/Pharmacodynamic Meta-Analysis Approach.

INTRODUCTION: Understanding the effect of oxycodone pharmacokinetics (PK) on µ-opioid receptor binding benefits from an integrated approach to compiling the results of multiple studies. The current pharmacokinetic/pharmacodynamic (PK/PD) model analysis brings together various studies to support the interpretation of newly collected PK/PD data, putting the new results into the perspective of the full concentration-effect curve. METHODS: A two-step modeling approach was applied to characterize the PK of oxycodone and its PK/PD relationship for the pupil diameter as a biomarker for µ-opioid receptor binding in recreational opioid users. First, a model-based meta-analysis (MBMA) was used to quantify the state-of-the-art knowledge from seven published studies, each of which contained part of the data needed for full characterization. Subsequently, the estimated parameters with uncertainty from the MBMA were used as prior information for a model developed on newly collected clinical data after intranasal administration in a clinical abuse potential trial. RESULTS: The inclusion of intravenous data in the MBMA showed that the PK of oxycodone can be described by a two-compartmental model, and allowed for the estimation of absolute bioavailability after intranasal and oral administration. A hysteresis loop was observed when plotting plasma concentrations and pupil constriction, which was approximated using an effect compartment. The totality of literature data enabled the identification of a Hill equation for the drug effect. The model with prior information fitted successfully to the newly collected data, where most parameter estimates had their confidence intervals overlapping with the prior distribution. The new data led to a slightly lower intranasal absorption rate constant, explaining the longer apparent half-life of oxycodone in the newly collected data. The PK/PD model parameters were confirmed by the new data, leading to the following estimates: half maximal inhibitory concentration (IC50) of 26.5 ng/mL, maximum pupil restriction of 66.0% from baseline, and a Hill factor of 1.05. CONCLUSIONS: The new data confirmed the PK profile and the PK/PD relationship identified using the MBMA, resulting in similar parameter estimates except for the intranasal absorption rate constant. The latter was lower than in the MBMA and explained the slightly longer apparent half-life of oxycodone in the newly collected data.

Noise-aided computation within a synthetic gene network through morphable and robust logic gates.

An important goal for synthetic biology is to build robust and tunable genetic regulatory networks that are capable of performing assigned operations, usually in the presence of noise. In this work, a synthetic gene network derived from the bacteriophage λ underpins a reconfigurable logic gate wherein we exploit noise and nonlinearity through the application of the logical stochastic resonance paradigm. This biological logic gate can emulate or "morph" the AND and OR operations through varying internal system parameters in a noisy background. Such genetic circuits can afford intriguing possibilities in the realization of engineered genetic networks in which the actual function of the gate can be changed after the network has been built, via an external control parameter. In this article, the full system characterization is reported, with the logic gate performance studied in the presence of external and internal noise. The robustness of the gate, to noise, is studied and illustrated through numerical simulations.

Unstable periodic orbits and noise in chaos computing.

Different methods to utilize the rich library of patterns and behaviors of a chaotic system have been proposed for doing computation or communication. Since a chaotic system is intrinsically unstable and its nearby orbits diverge exponentially from each other, special attention needs to be paid to the robustness against noise of chaos-based approaches to computation. In this paper unstable periodic orbits, which form the skeleton of any chaotic system, are employed to build a model for the chaotic system to measure the sensitivity of each orbit to noise, and to select the orbits whose symbolic representations are relatively robust against the existence of noise. Furthermore, since unstable periodic orbits are extractable from time series, periodic orbit-based models can be extracted from time series too. Chaos computing can be and has been implemented on different platforms, including biological systems. In biology noise is always present; as a result having a clear model for the effects of noise on any given biological implementation has profound importance. Also, since in biology it is hard to obtain exact dynamical equations of the system under study, the time series techniques we introduce here are of critical importance.

Logical stochastic resonance with correlated internal and external noises in a synthetic biological logic block.

Following the advent of synthetic biology, several gene networks have been engineered to emulate digital devices, with the ability to program cells for different applications. In this work, we adapt the concept of logical stochastic resonance to a synthetic gene network derived from a bacteriophage λ. The intriguing results of this study show that it is possible to build a biological logic block that can emulate or switch from the AND to the OR gate functionalities through externally tuning the system parameters. Moreover, this behavior and the robustness of the logic gate are underpinned by the presence of an optimal amount of random fluctuations. We extend our earlier work in this field, by taking into account the effects of correlated external (additive) and internal (multiplicative or state-dependent) noise. Results obtained through analytical calculations as well as numerical simulations are presented.

Measurement of the optical parameters of the Virgo interferometer.

The Virgo interferometer, aimed at detecting gravitational waves, is now in a commissioning phase. Measurements of its optical properties are needed for the understanding of the instrument. We present the techniques developed for the measurement of the optical parameters of Virgo. These parameters are compared with the Virgo specifications.