Mapping Interindividual Variability of Toxicodynamics Using High-Throughput Transcriptomics and Primary Human Hepatocytes from Fifty Donors.

BACKGROUND: Understanding the variability across the human population with respect to toxicodynamic responses after exposure to chemicals, such as environmental toxicants or drugs, is essential to define safety factors for risk assessment to protect the entire population. Activation of cellular stress response pathways are early adverse outcome pathway (AOP) key events of chemical-induced toxicity and would elucidate the estimation of population variability of toxicodynamic responses. OBJECTIVES: We aimed to map the variability in cellular stress response activation in a large panel of primary human hepatocyte (PHH) donors to aid in the quantification of toxicodynamic interindividual variability to derive safety uncertainty factors. METHODS: High-throughput transcriptomics of over 8,000 samples in total was performed covering a panel of 50 individual PHH donors upon 8 to 24 h exposure to broad concentration ranges of four different toxicological relevant stimuli: tunicamycin for the unfolded protein response (UPR), diethyl maleate for the oxidative stress response (OSR), cisplatin for the DNA damage response (DDR), and tumor necrosis factor alpha (TNFα) for NF-κB signaling. Using a population mixed-effect framework, the distribution of benchmark concentrations (BMCs) and maximum fold change were modeled to evaluate the influence of PHH donor panel size on the correct estimation of interindividual variability for the various stimuli. RESULTS: Transcriptome mapping allowed the investigation of the interindividual variability in concentration-dependent stress response activation, where the average of BMCs had a maximum difference of 864-, 13-, 13-, and 259-fold between different PHHs for UPR, OSR, DDR, and NF-κB signaling-related genes, respectively. Population modeling revealed that small PHH panel sizes systematically underestimated the variance and gave low probabilities in estimating the correct human population variance. Estimated toxicodynamic variability factors of stress response activation in PHHs based on this dataset ranged between 1.6 and 6.3. DISCUSSION: Overall, by combining high-throughput transcriptomics and population modeling, improved understanding of interindividual variability in chemical-induced activation of toxicity relevant stress pathways across the human population using a large panel of plated cryopreserved PHHs was established, thereby contributing toward increasing the confidence of in vitro-based prediction of adverse responses, in particular hepatotoxicity. https://doi.org/10.1289/EHP11891.

A Systematic Review of Human Challenge Trials, Designs, and Safety.

BACKGROUND: Few studies have assessed participant safety in human challenge trials (HCTs). Key questions regarding HCTs include how risky such trials have been, how often adverse events (AEs) and serious adverse events (SAEs) occur, and whether risk mitigation measures have been effective. METHODS: A systematic search of PubMed and PubMed Central for articles reporting on results of HCTs published between 1980 and 2021 was performed and completed by 7 October 2021. RESULTS: Of 2838 articles screened, 276 were reviewed in full. A total of 15 046 challenged participants were described in 308 studies that met inclusion criteria; 286 (92.9%) of these studies reported mitigation measures used to minimize risk to the challenge population. Among 187 studies that reported on SAEs, 0.2% of participants experienced at least 1 challenge-related SAE. Among 94 studies that graded AEs by severity, challenge-related AEs graded "severe" were reported by between 5.6% and 15.8% of participants. AE data were provided as a range to account for unclear reporting. Eighty percent of studies published after 2010 were registered in a trials database. CONCLUSIONS: HCTs are increasingly common and used for an expanding list of diseases. Although AEs occur, severe AEs and SAEs are rare. Reporting has improved over time, though not all papers provide a comprehensive report of relevant health impacts. We found very few severe symptoms or SAEs in studies that reported them, but many HCTs did not report relevant safety data. This study was preregistered on PROSPERO as CRD42021247218.

Assessing the Combined Public Health Impact of Pharmaceutical Interventions on Pandemic Transmission and Mortality: An Example in SARS CoV-2.

To assess the combined role of anti-viral monoclonal antibodies (mAbs) and vaccines in reducing severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) transmission and mortality in the United States, an agent-based model was developed that accounted for social contacts, movement/travel, disease progression, and viral shedding. The model was calibrated to coronavirus disease 2019 (COVID-19) mortality between October 2020 and April 2021 (aggressive pandemic phase), and projected an extended outlook to estimate mortality during a less aggressive phase (April-August 2021). Simulated scenarios evaluated mAbs for averting infections and deaths in addition to vaccines and aggregated non-pharmaceutical interventions. Scenarios included mAbs as a treatment of COVID-19 and for passive immunity for postexposure prophylaxis (PEP) during a period when variants were susceptible to the mAbs. Rapid diagnostic testing paired with mAbs was evaluated as an early treatment-as-prevention strategy. Sensitivity analyses included increasing mAb supply and vaccine rollout. Allocation of mAbs for use only as PEP averted up to 14% more infections than vaccine alone, and targeting individuals ≥ 65 years averted up to 37% more deaths. Rapid testing for earlier diagnosis and mAb use amplified these benefits. Doubling the mAb supply further reduced infections and mortality. mAbs provided benefits even as proportion of the immunized population increased. Model projections estimated that ~ 42% of expected deaths between April and August 2021 could be averted. Assuming sensitivity to mAbs, their use as early treatment and PEP in addition to vaccines would substantially reduce SARS-CoV-2 transmission and mortality even as vaccination increases and mortality decreases. These results provide a template for informing public health policy for future pandemic preparedness.

Testing fractional doses of COVID-19 vaccines.

Due to the enormous economic, health, and social costs of the COVID-19 pandemic, there are high expected social returns to investing in parallel in multiple approaches to accelerating vaccination. We argue there are high expected social returns to investigating the scope for lowering the dosage of some COVID-19 vaccines. While existing evidence is not dispositive, available clinical data on the immunogenicity of lower doses combined with evidence of a high correlation between neutralizing antibody response and vaccine efficacy suggests that half or even quarter doses of some vaccines could generate high levels of protection, particularly against severe disease and death, while potentially expanding supply by 450 million to 1.55 billion doses per month, based on supply projections for 2021. An epidemiological model suggests that, even if fractional doses are less effective than standard doses, vaccinating more people faster could substantially reduce total infections and deaths. The costs of further testing alternative doses are much lower than the expected public health and economic benefits. However, commercial incentives to generate evidence on fractional dosing are weak, suggesting that testing may not occur without public investment. Governments could support either experimental or observational evaluations of fractional dosing, for either primary or booster shots. Discussions with researchers and government officials in multiple countries where vaccines are scarce suggests strong interest in these approaches.

Secukinumab's effect on structural damage progression in psoriatic arthritis: longitudinal mixture modelling of FUTURE-1 and FUTURE-5.

OBJECTIVES: Peripheral and axial manifestations of psoriatic arthritis (PsA) can lead to irreversible structural damage and chronic disability. Our objective was to explore predictors of radiographic progression and to increase our understanding of treatment effects in subgroups of patients with different rates of structural damage progression. METHODS: We analysed data from two large Phase-3 trials of secukinumab in PsA patients, FUTURE-1 (NCT01392326, n=606) and FUTURE-5 (NCT02404350, n=996), where different posologies ranging from 75 mg to 300 mg were used. We applied a longitudinal Bayesian mixture model with random effects to account for the variability in the repeated radiographic assessments. "Fast progressors" were defined post hoc as patients with a 50% model-estimated probability to progress at least 0.5 mTSS/year faster than an average patient. RESULTS: Higher baseline inflammation and higher body weight were identified as significant predictors of radiographic progression (multivariate model). Model-estimated structural damage progression in an average patient treated with secukinumab 150 mg subcutaneous (s.c.) was slower (0.04 mTSS/year; 95% CI -0.28, 0.34) compared to a patient treated with placebo (0.94 mTSS/year; 95% CI 0.45, 1.45). According to the model, the subgroup of "fast progressors" (hsCRP ≥26 mg/L, body weigth ≥94 kg, inadequate response to prior anti-TNF-alpha, structural damage ≥42 mTSS) treated with secukinumab 150 mg s.c. progressed at 0.56 mTSS/year (95% CI 0.02, 1.09) and 1.46 mTSS/year (95% CI 0.81, 2.11) when treated with placebo. CONCLUSIONS: Greater systemic inflammation and higher body weight at baseline were identified as significant predictors of progression. Even patients with fast radiographic progression could experience a beneficial effect with secukinumab that holds promise to prevent further mobility loss.

Inter-phenotypic differences in CYP2C9 and CYP2C19 metabolism: Bayesian meta-regression of human population variability in kinetics and application in chemical risk assessment.

Quantifying variability in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. In this context, genetic polymorphisms in cytochromes P450 (CYPs) drive inter-phenotypic differences and may result in reduction or increase in metabolism of drugs or other xenobiotics. Here, an extensive literature search was performed to identify PK data for probe substrates of the human polymorphic isoforms CYP2C9 and CYP2C19. Relevant data from 158 publications were extracted for markers of chronic exposure (clearance and area under the plasma concentration-time curve) and analysed using a Bayesian meta-regression model. Enzyme function (EF), driven by inter-phenotypic differences across a range of allozymes present in extensive and poor metabolisers (EMs and PMs), and fraction metabolised (Fm), were identified as exhibiting the highest impact on the metabolism. The Bayesian meta-regression model provided good predictions for such inter-phenotypic differences. Integration of population distributions for inter-phenotypic differences and estimates for EF and Fm allowed the derivation of CYP2C9- and CYP2C19-related UFs which ranged from 2.7 to 12.7, and were above the default factor for human variability in TK (3.16) for PMs and major substrates (Fm >60%). These results provide population distributions and pathway-related UFs as conservative in silico options to integrate variability in CYP2C9 and CYP2C19 metabolism using in vitro kinetic evidence and in the absence of human data. The future development of quantitative extrapolation models is discussed with particular attention to integrating human in vitro and in vivo PK or TK data with pathway-related variability for chemical risk assessment.

The Yin-Yang of CYP3A4: a Bayesian meta-analysis to quantify inhibition and induction of CYP3A4 metabolism in humans and refine uncertainty factors for mixture risk assessment.

Quantifying differences in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. Cytochrome P450 (CYP) 3A4-the major hepatic and intestinal human CYP-and the P-glycoprotein (Pgp) transporter share a vast range of common substrates for which PK may be modulated through inhibition or induction in the presence of grapefruit juice (GFJ) or St. John's wort (SJW), respectively. Here, an extensive literature search was performed on PK interactions for CYP3A4 and Pgp substrates after oral co-exposure to GFJ and SJW. Relevant data from 109 publications, extracted for both markers of acute (Cmax) and chronic [clearance and area under the plasma concentration-time curve (AUC)] exposure, were computed into a Bayesian hierarchical meta-analysis model. Bioavailability (F) and substrate fraction metabolised by CYP3A4 (Fm) were identified as the variables exhibiting the highest impact on the magnitude of interaction. The Bayesian meta-regression model developed provided good predictions for magnitudes of inhibition (maximum 5.3-fold with GFJ) and induction (maximum 2.3-fold with SJW). Integration of CYP3A4 variability, F, Fm and magnitude of interaction provided the basis to derive a range of CYP3A4 and Pgp-related UFs. Such CYP3A4 and Pgp-related UFs can be derived in the absence of human data using in vitro TK evidence for CYP3A4/Pgp inhibition or induction as conservative in silico options. The future development of quantitative in vitro-in vivo extrapolation models for mixture risk assessment is discussed with particular attention to integrating human in vitro and in vivo P/TK data on interactions with pathway-related variability.

Cabozantinib Versus Standard-of-Care Comparators in the Treatment of Advanced/Metastatic Renal Cell Carcinoma in Treatment-naïve Patients: a Systematic Review and Network Meta-Analysis.

BACKGROUND: Cabozantinib has recently been evaluated as a first-line treatment in advanced renal cell carcinoma (aRCC). OBJECTIVE: To indirectly assess efficacy of cabozantinib versus standard-of-care (SoC) comparators in the first-line treatment of aRCC. METHODS: We conducted a systematic literature review (SLR) to identify randomized controlled studies in the first-line setting for aRCC. The outcomes analyzed were overall survival (OS) and progression-free survival (PFS). A network meta-analysis (NMA) was conducted comparing OS and PFS hazard ratios (HRs). RESULTS: Thirteen studies were identified in the SLR to be eligible for inclusion in the NMA. The overall study populations were heterogeneous in terms of risk groups; some studies included favorable risk patients. In intermediate-risk patients, HRs (95% confidence interval) for PFS were 0.52 (0.33, 0.82), 0.46 (0.26, 0.80), 0.20 (0.12, 0.36), and 0.37 (0.20, 0.68) when cabozantinib was compared with sunitinib, sorafenib, interferon (IFN), or bevacizumab plus IFN, respectively. In poor-risk patients, the NMA also demonstrated significant superiority in terms of PFS for cabozantinib; HRs were 0.31 (0.11, 0.90), 0.22 (0.06, 0.87), 0.16 (0.04, 0.64), and 0.20 (0.05, 0.88), when cabozantinib was compared with sunitinib, temsirolimus, IFN, or bevacizumab plus IFN, respectively. When the overall study populations were compared, the results were similar to the subgroup analyses. OS HRs in all analyses favored cabozantinib, but were not statistically significant. CONCLUSIONS: The results suggest that cabozantinib significantly increases PFS in intermediate-, and poor-risk subgroups when compared to standard-of-care comparators. Although overall populations included favorable risk patients in some studies, the results seen were consistent with the subgroup analyses.

A retrospective observational analysis of post-pandemic influenza-related outcomes in the United Kingdom, 2010-2014.

This study set out to evaluate influenza- and respiratory-related illnesses recorded during primary care physician consultations in England following the H1N1 pandemic in 2009 and to enable the development of a dynamic disease model. Data were obtained from the Clinical Practice Research Datalink of primary care records over four influenza seasons (2010-2014). The primary outcome of the study was incidence of influenza- and respiratory-related diagnoses, calculated per practice and by season and age group. Upper respiratory tract infection diagnoses were most frequently recorded (mean seasonal practice level incidence; 3,762 consultations per 100,000 [SD = 1,989]), and influenza-related diagnoses were least frequently recorded across all seasons, except one. Incidence rates for the under 18 population were higher than those for the general population, in particular for upper respiratory tract infection (range of 8,024-9,950 versus 3,228-4,120, respectively) and otitis media diagnoses (2,668-3,652 versus 782-1,057, respectively). For influenza-related diagnoses, the 65+ age group, the 0 to <2 and 2 to <4 groups had a higher risk (risk ratio = 1.33, 1.12 and 1.16, respectively) than other age groups. This study provides valuable insight into the incidence of influenza- and respiratory-related diagnoses in the primary care setting in England, and suggests a higher burden of disease in young children and the elderly. The study also indicates that some influenza illness is likely to be reported under respiratory-related diagnoses, given the low incidence of influenza-related diagnoses in the study.

Impact of increased influenza vaccination in 2-3-year-old children on disease burden within the general population: A Bayesian model-based approach.

INTRODUCTION: During the 2013-2014 influenza season, Public Health England extended routine influenza vaccination to all 2- and 3-year-old children in England. To estimate the impact of this change in policy on influenza-related morbidity and mortality, we developed a disease transmission and surveillance model informed by real-world data. METHODS: We combined real-world and literature data sources to construct a model of influenza transmission and surveillance in England. Data were obtained for four influenza seasons, starting with the 2010-2011 season. Bayesian inference was used to estimate model parameters on a season-by-season basis to assess the impact of targeting 2- and 3-year-old children for influenza vaccination. This provided the basis for the construction of counterfactual scenarios comparing vaccination rates of ~2% and ~35% in the 2- and 3- year-old population to estimate reductions in general practitioner (GP) influenza-like-illness (ILI) consultations, respiratory hospitalizations and deaths in the overall population. RESULTS: Our model was able to replicate the main patterns of influenza across the four seasons as observed through laboratory surveillance data. Targeting 2- and 3-year-old children for influenza vaccination resulted in reductions in the general population of between 6.2-9.9% in influenza-attributable GP ILI consultations, 6.1-10.7% in influenza-attributable respiratory hospitalizations, and 5.7-9.4% in influenza-attributable deaths. The decrease in influenza-attributable ILI consultations represents a reduction of between 4.5% and 7.3% across all ILI consultations. The reduction in influenza-attributable respiratory hospitalizations represents a reduction of between 1.2% and 2.3% across all respiratory hospitalizations. Reductions in influenza-attributable respiratory deaths represent a reduction of between 0.9% and 2.4% in overall respiratory deaths. CONCLUSION: This study has provided evidence that extending routine influenza vaccination to all healthy children aged 2 and 3 years old leads to benefits in terms of reduced utilization of healthcare resources and fewer respiratory health outcomes and deaths.

Nivolumab versus Cabozantinib: Comparing Overall Survival in Metastatic Renal Cell Carcinoma.

Renal-cell carcinoma (RCC) affects over 330,000 new patients every year, of whom 1/3 present with metastatic RCC (mRCC) at diagnosis. Most mRCC patients treated with a first-line agent relapse within 1 year and need second-line therapy. The present study aims to compare overall survival (OS) between nivolumab and cabozantinib from two recent pivotal studies comparing, respectively, each one of the two emerging treatments against everolimus in patients who relapse following first-line treatment. Comparison is traditionally carried out using the Bucher method, which assumes proportional hazard. Since OS curves intersected in one of the pivotal studies, models not assuming proportional hazards were also considered to refine the comparison. Four Bayesian parametric survival network meta-analysis models were implemented on overall survival (OS) data digitized from the Kaplan-Meier curves reported in the studies. Three models allowing hazard ratios (HR) to vary over time were assessed against a fixed-HR model. The Bucher method favored cabozantinib, with a fixed HR for OS vs. nivolumab of 1.09 (95% confidence interval: [0.77, 1.54]). However, all models with time-varying HR showed better fits than the fixed-HR model. The log-logistic model fitted the data best, exhibiting a HR for OS initially favoring cabozantinib, the trend inverting to favor nivolumab after month 5 (95% credible interval <1 from 10 months). The initial probability of cabozantinib conferring superior OS was 54%, falling to 41.5% by month 24. Numerical differences in study-adjusted OS estimates between the two treatments remained small. This study evidences that HR for OS of nivolumab vs. cabozantinib varies over time, favoring cabozantinib in the first months of treatment but nivolumab afterwards, a possible indication that patients with poor prognosis benefit more from cabozantinib in terms of survival, nivolumab benefiting patients with better prognosis. More evidence, including real-world observational data, is needed to compare effectiveness between cabozantinib and nivolumab.