Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.     

Inter‐serotype reassortment among epizootic haemorrhagic disease viruses in the United States

First described in 1955 in New Jersey, epizootic haemorrhagic disease (EHD) causes a severe clinical disease in wild and domestic ruminants worldwide. Epizootic haemorrhagic disease outbreaks occur in deer populations each year from summer to late autumn. The etiological agent is EHD virus (EHDV) which is a double‐stranded segmented icosahedral RNA virus. EHD virus utilizes point mutations and reassortment strategies to maintain viral fitness during infection. In 2018, EHDV serotype 2 was predominantly detected in deer in Illinois. Whole genome sequencing was conducted for two 2018 EHDV2 isolates (IL41747 and IL42218) and the sequence analyses indicated that IL42218 was a reassortant between different serotypes whereas IL41747 was a genetically stable strain. Our data suggest that multiple strains contribute to outbreaks each year.     

Serological Responses of Raccoons and Striped Skunks to Ontario Rabies Vaccine Bait in West Virginia during 2012–2016

Since the 1990s, oral rabies vaccination (ORV) has been used successfully to halt the westward spread of the raccoon rabies virus (RV) variant from the eastern continental USA. Elimination of raccoon RV from the eastern USA has proven challenging across targeted raccoon (Procyon lotor) and striped skunk (Mephitis mephitis) populations impacted by raccoon RV. Field trial evaluations of the Ontario Rabies Vaccine Bait (ONRAB) were initiated to expand ORV products available to meet the rabies management goal of raccoon RV elimination. This study describes the continuation of a 2011 trial in West Virginia. Our objective was to evaluate raccoon and skunk response to ORV occurring in West Virginia for an additional two years (2012–2013) at 75 baits/km² followed by three years (2014–2016) of evaluation at 300 baits/km². We measured the change in rabies virus-neutralizing antibody (RVNA) seroprevalence in targeted wildlife populations by comparing levels pre- and post-ORV during each year of study. The increase in bait density from 75/km² to 300/km² corresponded to an increase in average post-ORV seroprevalence for raccoon and skunk populations. Raccoon population RVNA levels increased from 53% (300/565, 95% CI: 50–57%) to 82.0% (596/727, 95% CI: 79–85%) during this study, and skunk population RVNA levels increased from 11% (8/72, 95% CI: 6–20%) to 39% (51/130, 95% CI: 31–48%). The RVNA seroprevalence pre-ORV demonstrated an increasing trend across study years for both bait densities and species, indicating that multiple years of ORV may be necessary to achieve and maintain RVNA seroprevalence in target wildlife populations for the control and elimination of raccoon RV in the eastern USA.     

On estimands arising from misspecified semiparametric rate-based analysis of recurrent episodic conditions

Marginal rate-based analyses are widely used for the analysis of recurrent events in clinical trials. In many areas of application, the events are not instantaneous but rather signal the onset of a symptomatic episode representing a recurrent infection, respiratory exacerbation, or bout of acute depression. In rate-based analyses, it is unclear how to best handle the time during which individuals are experiencing symptoms and hence are not at risk. We derive the limiting value of the Nelson-Aalen estimator and estimators of the regression coefficients under a semiparametric rate-based model in terms of an underlying two-state process. We investigate the impact of the distribution of the episode durations, heterogeneity, and dependence on the asymptotic and finite sample properties of standard estimators. We also consider the impact of these features on power in trials designed to test intervention effects on rate functions. An application to a trial of individuals with herpes simplex virus is given for illustration.     

Epithelial ovarian cancer risk: A review of the current genetic landscape

Ovarian cancer is the fourth most common cause of cancer-related death in women in the developed world, and one of the most heritable cancers. One of the most significant risk factors for epithelial ovarian cancer (EOC) is a family history of breast and/or ovarian cancer. Combined risk factors can be used in models to stratify risk of EOC, and aid in decisions regarding risk-reduction strategies. Germline pathogenic variants in EOC susceptibility genes including those involved in homologous recombination and mismatch repair pathways are present in approximately 22% to 25% of EOC. These genes are associated with an estimated lifetime risk of EOC of 13% to 60% for BRCA1 variants and 10% to 25% for BRCA2 variants, with lower risks associated with remaining genes. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) thought to explain an additional 6.4% of the familial risk of ovarian cancer, with 34 susceptibility loci identified to date. However, an unknown proportion of the genetic component of EOC risk remains unexplained. This review comprises an overview of individual genes and SNPs suspected to contribute to risk of EOC, and discusses use of a polygenic risk score to predict individual cancer risk more accurately.