Factors Affecting the Interpretation of Canine and Nonhuman Primate Clinical Pathology

Abstract

Interpreting canine and nonhuman primate clinical pathology data from preclinical studies can be challenging. Relatively few animals are tested (typically beagles and macaques), and they often undergo study-related procedures (eg, sample collection for pharmacokinetic analysis) that can affect clinical pathology test results. Data interpretation requires an understanding of the significance of each test, species differences for each test, normal interanimal and intraanimal variability, the effects of study design variables, and supporting data from other disciplines. Interpretation of hematology, coagulation, clinical chemistry, and urinalysis parameters are discussed, with emphasis on species peculiarities and study design variables that may affect clinical pathology test results.

Hematologic reference intervals in Cynomolgus (Macaca fascicularis) monkeys

“…The increase of MCV is consistent with previously reported higher MCV after sexual maturity in males [25]. Moreover, the higher MCV and MCH observed in Vietnamese monkeys were in agreement with the lower RBC reported in similar animals [2,13], the size and number of erythrocytes varying in that the smaller the red cell the more there are per unit of blood [15]. It is likely that the statistically non-significant effect of origin was due to the small number of monkeys from Nafovanny.…”

“…An origin effect was only observed for RBC, HGB, HCT, and RDW. To our knowledge, only a few studies have investigated the possible effect of geographic origin on hematologic analytes in Cynomolgus . As observed in our study, RBC counts were higher in Cynomolgus from Mauritius than from South‐East Asia , but HGB and HCT were the same .…”

“…To our knowledge, only a few studies have investigated the possible effect of geographic origin on hematologic analytes in Cynomolgus [5,8,13]. As observed in our study, RBC counts were higher in Cynomolgus from Mauritius than from South-East Asia [8,13], but HGB and HCT were the same [13]. The HGB concentration in Vietnamese monkeys was significantly higher [8], but the difference with Mauritius and Philippines Cynomolgus was low (mean difference of 1 g/dl in females and 0.5 g/dl in males) and considered without clinical significance.…”

Integrated analysis of toxicity data of two pharmaceutical immunosuppressants and two environmental pollutants with immunomodulating properties to improve the understanding of side effects—A toxicopathologist׳s view

“…In addition, the incidence of outliers in clinical chemistry or hematology and unusual histopathologic findings in controls is surveyed in larger databases. Laboratory-specific and inter-laboratory data collections aid in the interpretation of findings seen in dosed animals (Deschl et al, 2002;Elmore and Peddada, 2009;Hall and Everds, 2003;Kobayashi et al, 2010). For example, in normally distributed data and a large sample size, roughly 1 in 22 observations will differ by twice the standard deviation or more from the mean.…”

Biomarker Applications in the Pharmaceutical Industry

“…Rather multiple biomarkers, including serum bilirubin, serum aspartate aminotransferase and antibodies to viral antigen, are considered. While the assessment of multiple parameters is most often approached qualitatively [45], algorithmic approaches to formally evaluated multiple endpoints (i.e., multivariate analyses) have been explored in the past [41]. With the advent of 'omic' technologies allowing the simultaneous measurements of tens to thousands of endpoints, multivariate analysis has led to the concept of the 'signature', wherein a specific algorithmic evaluation of a defined, multiple endpoint becomes the biomarker [46].…”