One of the key objectives of oncology first-in-human trials has often been to establish the maximum tolerated dose (MTD). However, targeted therapies might not exhibit dose-limiting toxicities (DLT) ...at doses significantly higher than sufficiently active doses, and there is frequently a limited ability to objectively quantify adverse events. Thus, while MTD-based determination of recommended phase II dose may have yielded appropriate dosing for some cytotoxics, targeted therapeutics (including monoclonal antibodies and/or immunotherapies) sometimes need alternative or complementary strategies to help identify dose ranges for a randomized dose-ranging study. One complementary strategy is to define a biologically efficacious dose (BED) using an "effect marker." An effect marker could be a target engagement, pharmacodynamic, or disease progression marker (change in tumor size for solid tumors or bone marrow blast count for some hematologic tumors). Although the concept of BED has been discussed extensively, we review specific examples in which the approach influenced oncology clinical development. Data extracted from the literature and the examples support improving dose selection strategies to benefit patients, providers, and the biopharmaceutical industry. Although the examples illustrate key contributions of effect markers in dose selection, no one-size-fits-all approach to dosing can be justified. Higher-than-optimal dosing can increase toxicity in later trials (and in clinical use), which can have a negative impact on efficacy (via lower adherence or direct sequelae of toxicities). Proper dose selection in oncology should follow a multifactorial decision process leading to a randomized, dose-ranging study instead of a single phase II dose.
Vaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other subject-specific characteristics evaluated as baseline covariates. ...Understanding the effect of covariates on efficacy is key to decisions by vaccine developers and public health authorities.
This work evaluates the impact of including correlate of protection (CoP) data in logistic regression on its performance in identifying statistically and clinically significant covariates in settings typical for a vaccine phase 3 trial. The proposed approach uses CoP data and covariate data as predictors of clinical outcome (diseased versus non-diseased) and is compared to logistic regression (without CoP data) to relate vaccination status and covariate data to clinical outcome.
Clinical trial simulations, in which the true relationship between CoP data and clinical outcome probability is a sigmoid function, show that use of CoP data increases the positive predictive value for detection of a covariate effect. If the true relationship is characterized by a decreasing convex function, use of CoP data does not substantially change positive or negative predictive value. In either scenario, vaccine efficacy is estimated more precisely (i.e., confidence intervals are narrower) in covariate-defined subgroups if CoP data are used, implying that using CoP data increases the ability to determine clinical significance of baseline covariate effects on efficacy.
This study proposes and evaluates a novel approach for assessing baseline demographic covariates potentially affecting VE. Results show that the proposed approach can sensitively and specifically identify potentially important covariates and provides a method for evaluating their likely clinical significance in terms of predicted impact on vaccine efficacy. It shows further that inclusion of CoP data can enable more precise VE estimation, thus enhancing study power and/or efficiency and providing even better information to support health policy and development decisions.
Respiratory Syncytial Virus (RSV) causes lower respiratory tract infections that can be severe and sometimes fatal. The risk for severe RSV infection is highest in infants and older adults. A safe ...and effective RSV vaccine for older adults represents a serious unmet medical need due to higher morbidity and mortality in this age group. In this randomized, partially double-blind, placebo-controlled, phase 1 dose-escalation study, we evaluated the safety, tolerability and immunogenicity of an investigational messenger ribonucleic acid (mRNA) vaccine encoding the RSV fusion protein (F) stabilized in the prefusion conformation. The study was conducted in healthy younger adults (ages ≥18 and ≤49 years) and healthy older adults (ages ≥60 and ≤79 years). Participants received mRNA-1777 (V171) or placebo as a single intramuscular dose. For each dose level, three sentinel participants were administered open-label mRNA-1777 (V171). Seventy-two younger adults were randomized and administered 25, 100, or 200 µg mRNA-1777 (V171) or placebo, and 107 older adults were randomized and administered 25, 100, 200 or 300 µg mRNA-1777 (V171) or placebo. Primary objectives were safety and tolerability and secondary objectives included humoral and cell-mediated immunogenicity. All dose levels of mRNA-1777 (V171) were generally well tolerated and no serious adverse events related to the vaccine were reported. Immunization with mRNA-1777 (V171) elicited a humoral immune response as measured by increases in RSV neutralizing antibody titers, serum antibody titers to RSV prefusion F protein, D25 competing antibody titers to RSV prefusion F protein, and cell-mediated immune responses to RSV-F peptides.
Next-generation, higher-valency pneumococcal conjugate vaccines (PCVs), 15-valent PCV V114 and 20-valent PCV (PCV20), have been assessed by comparing their immune responses across serotypes shared ...with the 13-valent PCV (PCV13). Without efficacy or real-world vaccine effectiveness (VE) it becomes important to relate IgG titers to VE to aid in the interpretation of the immune response elicited by V114 and PCV20.
We estimated the protective antibody concentrations for each serotype in 7-valent PCV (PCV7) and PCV13 which were then used to predict the serotype-specific VE for each PCV7 and PCV13 non PCV7 serotype present in V114 and PCV20.
The predicted effectiveness of V114 was comparable to PCV7 and PCV13 for 11 of the 13 shared serotypes (1, 4, 5, 6B, 7F, 9 V, 14, 18C, 19A, 19F, and 23F), with improved effectiveness against serotype 3 and decreased effectiveness against serotype 6A. PCV20 had predicted effectiveness comparable to PCV7 and PCV13 for 7 of the 13 shared serotypes (5, 6A, 7F, 9 V, 18C, 19F, and 23F), with decreased effectiveness against the remaining serotypes (1, 3, 4, 6B, 14, and 19A).
Prediction of serotype-specific VE values suggests that V114 retains greater effectiveness than PCV20 toward most serotypes present in PCV7 and PCV13.
The potential impact of new pneumococcal conjugate vaccines (PCVs) is assessed by using immune responses to predict their effectiveness against invasive pneumococcal disease (IPD). This analysis ...predicted the serotype-specific effectiveness against IPD of a new 15-valent PCV (V114) for the serotypes shared with a 13-valent PCV (PCV13), in a US pediatric population given a 3 + 1 dosing regimen.
Beginning with the known serotype-specific antibody concentrations after vaccination with placebo, 7-valent PCV (PCV7) and PCV13, reverse cumulative distribution curves were used, along with published serotype-specific vaccine effectiveness of PCV7 and PCV13, to derive a protective antibody concentration (C
p
) for each PCV13 serotype in V114. Serotype-specific effectiveness was predicted using the C
p
estimates and the respective serotype-specific antibody concentrations of placebo and V114 recipients in recent pediatric clinical trials.
Predicted serotype-specific V114 effectiveness values ranged from 86% to 99% for PCV7 serotypes and from 59% to 97% for (non-PCV7) PCV13 serotypes.
V114 serotype-specific effectiveness against IPD in a US pediatric population was predicted to be largely comparable to that of PCV7 and PCV13 for shared serotypes, with models suggesting likelihood of high overall benefit gained from increased serotype 3 effectiveness, and additional protection against serotypes 22 F and 33 F.
Next generation, higher valency pneumococcal conjugate vaccines (PCVs) are assessed and licensed by comparing the immune response across serotypes shared with the PCVs that are standard of care for ...prevention of pneumococcal disease.
Using a previously qualified method we predicted the serotype-specific vaccine effectiveness (VE) against invasive pneumococcal disease of V114 and PCV20 for the serotypes shared with PCV13 in an EU, Russian, and Australian pediatric population that is recommended to receive a 2 + 1 dosing regimen.
The estimated protective antibody concentrations ranged from 0.03 (serotype 23F) to 1.49 µg/mL (serotype 19F). Predicted VE values for V114 ranged from 79% (serotype 5) to 100% (serotype 23F). V114 had comparable effectiveness to PCV13 for all but one of shared serotypes, with predicted higher effectiveness (in V114) against serotype 3 (93% vs. 65%). Predicted VE values for PCV20 ranged from 47% (serotype 3) to 91% (serotype 14). PCV20 predicted VE was lower than PCV13's for serotypes 4, 19F, 23F, 1, 3, 5, 6A, 7F, and 19A.
Predicted serotype-specific VE values suggest that, with a 2 + 1 dosing regimen, V114 will have greater effectiveness than PCV20 against PCV13 serotypes, particularly for the still-prevalent serotype 3. Real-world VE studies will ultimately provide clarity on the effectiveness of novel PCVs and support further confidence in and/or improvements to modeling efforts.
Soil stability, nitrogen and carbon fixation were assessed for eight biological soil crust community types within a Mojave Desert wilderness site. Cyanolichen crust outperformed all other crusts in ...multi-functionality whereas incipient crust had the poorest performance. A finely divided classification of biological soil crust communities improves estimation of ecosystem function and strengthens the accuracy of landscape-scale assessments.
•We developed a refined classification of biological soil crust community types.•We determined soil stability, carbon and nitrogen fixation among community types.•All ecosystem functions varied significantly amongst crust community types.•Our classification better assesses importance of crust communities to an ecosystem.
Respiratory syncytial virus (RSV) infection is a major cause of respiratory illness in infants and the elderly. Although several vaccines have been developed, none have succeeded in part due to our ...incomplete understanding of the correlates of immune protection. While both T cells and antibodies play a role, emerging data suggest that antibody-mediated mechanisms alone may be sufficient to provide protection. Therefore, to map the humoral correlates of immunity against RSV, antibody responses across six different vaccines were profiled in a highly controlled nonhuman primate-challenge model. Viral loads were monitored in both the upper and lower respiratory tracts, and machine learning was used to determine the vaccine platform-agnostic antibody features associated with protection. Upper respiratory control was associated with virus-specific IgA levels, neutralization, and complement activity, whereas lower respiratory control was associated with Fc-mediated effector mechanisms. These findings provide critical compartment-specific insights toward the rational development of future vaccines.
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•Unique antibody profiles are induced by six distinct vaccine platforms•Correlates of protection against RSV differ by compartment•IgA levels, neutralization, and complement are key in the upper respiratory tract•Fc-effector functions correlate with RSV restriction in the lower respiratory tract
Zohar et al. demonstrate compartment-specific correlates of protection against respiratory syncytial virus (RSV) in the upper and lower respiratory tracts. The findings define a collaborative role between the Fab and Fc regions of the antibody in RSV restriction, providing insights into target humoral profiles for future vaccine design.
Excitement around and investment in oncology drug development are at unprecedented levels. To maximize the health impact and productivity of this research and development investment, quantitative ...modeling should impact key decisions in early clinical oncology including Go/No-Go decisions based on early clinical data, and dose selection for late stage studies.
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