The Cynomolgus Macaque Natural History Model of Pneumonic Tularemia for Predicting Clinical Efficacy Under the Animal Rule.

Francisella tularensis is a highly infectious Gram-negative bacterium that is the etiologic agent of tularemia in animals and humans and a Tier 1 select agent. The natural incidence of pneumonic tularemia worldwide is very low; therefore, it is not feasible to conduct clinical efficacy testing of tularemia medical countermeasures (MCM) in human populations. Development and licensure of tularemia therapeutics and vaccines need to occur under the Food and Drug Administration's (FDA's) Animal Rule under which efficacy studies are conducted in well-characterized animal models that reflect the pathophysiology of human disease. The Tularemia Animal Model Qualification (AMQ) Working Group is seeking qualification of the cynomolgus macaque (Macaca fascicularis) model of pneumonic tularemia under Drug Development Tools Qualification Programs with the FDA based upon the results of studies described in this manuscript. Analysis of data on survival, average time to death, average time to fever onset, average interval between fever and death, and bacteremia; together with summaries of clinical signs, necropsy findings, and histopathology from the animals exposed to aerosolized F. tularensis Schu S4 in five natural history studies and one antibiotic efficacy study form the basis for the proposed cynomolgus macaque model. Results support the conclusion that signs of pneumonic tularemia in cynomolgus macaques exposed to 300-3,000 colony forming units (cfu) aerosolized F. tularensis Schu S4, under the conditions described herein, and human pneumonic tularemia cases are highly similar. Animal age, weight, and sex of animals challenged with 300-3,000 cfu Schu S4 did not impact fever onset in studies described herein. This study summarizes critical parameters and endpoints of a well-characterized cynomolgus macaque model of pneumonic tularemia and demonstrates this model is appropriate for qualification, and for testing efficacy of tularemia therapeutics under Animal Rule.

Interlaboratory comparison of results of an anthrax lethal toxin neutralization assay for assessment of functional antibodies in multiple species.

The anthrax lethal toxin neutralization assay (TNA) will likely be used to correlate the protection offered by new anthrax vaccines in animal models to the immunogenicity that will be provided in humans. TNA data are being generated in several different laboratories to measure the immune responses in rabbits, nonhuman primates, and humans. In order to compare data among species and laboratories, a collaborative study was conducted in which 108 samples from the three species were analyzed in seven independent laboratories. Six of the seven laboratories had participated in an interlaboratory technology transfer of the TNA. Analysis of the titration curves generated by samples from each species indicated that the behaviors of the samples from all species were similar; the upper and lower asymptotes and the slopes of the curves were less than 30% divergent from those for human reference material. Dilutional linearity was consistent among samples from each species, with spike to effective dilution at 50% inhibition (ED(50)) slopes of less than 1.2 for all species. Agreement among the laboratories with consensus values was within 10% of the ED(50)s for all samples and within 7.5% of the quotients of the test sample ED(50) and the reference standard ED(50) (NF(50)s) for all samples. The relative standard deviations obtained when data from all laboratories and for all species were combined were 45% for the ED(50)s and 35% for the NF(50)s. These precision data suggest that the NF(50) readout may normalize the values generated by different laboratories. This study demonstrates that the TNA is a panspecies assay that can be performed in several different laboratories with a high degree of quantitative agreement and precision.

Model selection in ecology and evolution.

Recently, researchers in several areas of ecology and evolution have begun to change the way in which they analyze data and make biological inferences. Rather than the traditional null hypothesis testing approach, they have adopted an approach called model selection, in which several competing hypotheses are simultaneously confronted with data. Model selection can be used to identify a single best model, thus lending support to one particular hypothesis, or it can be used to make inferences based on weighted support from a complete set of competing models. Model selection is widely accepted and well developed in certain fields, most notably in molecular systematics and mark-recapture analysis. However, it is now gaining support in several other areas, from molecular evolution to landscape ecology. Here, we outline the steps of model selection and highlight several ways that it is now being implemented. By adopting this approach, researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.