1647-P: Nonhuman Primate Obesity Model for the Translation of Target-Based Precision Medicine

The prevalence of obesity has increased worldwide in the past few decades. Because of the similarity of their absorption, distribution, metabolism, and excretion profile compared to that of humans, non-human primates (NHP) models are highly valuable in predicting the clinical response to new drugs for obesity associated disease, particularly for biological products such as siRNA, oligo and antibodies. Reported here are our profiling of the characteristic features from > 2000 obese male cynomolgus monkeys (Macaca fascicularis), either spontaneous or induced with a KBI proprietary high fat diet (HFD). Multiple methods were used for the profiling, such as body weight, food intake, crown-rump length (for BMI calculation) measurement, MRI or DXA scanning for body fat, tissue biopsy, and clinical chemistry measurement. Based on the results from >200 monkeys, we have defined the reference range of BMI in healthy monkeys (20.05 to 36.73 kg/m2). Therefore, monkeys with BMI >40 kg/m2 were used for the obesity-related metabolic studies. Monkeys with BMI >40 kg/m2 were observed with significantly higher liver fat fraction (9.5 ± 4.8% vs 4.3 ± 0.5%, p <0.01) and % fat (42.36 ± 8.24% vs 18.47 ± 4.43%, p<0.0001) compared to monkeys with BMI <40 kg/m2. Compared with obese monkeys on low fat diet, the obese monkeys on HFD displayed more severe dyslipidemia and a greater incidence of diabetes and liver fibrosis. Furthermore, monkeys showed similar response as observed in humans after the administration of reference or test compounds, such as liraglutide, semaglutide, inclisiran, pioglitazone, empagliflozin etc. Significant reduction in food intake (-38.5 ± 14.4%) and body weight (-10.9 ± 4.7%) was observed after administration of Liraglutide for 6 weeks. Administration of a novel FGF21 analog for 11 weeks resulted a reduction in liver fat fraction (-40.3±18.8%). These findings indicate that our non-human primate obesity model is uniquely valuable for the translation of target-based precision medicine for humans. Disclosure S. Ji: None. Z. zhu: None. G. Wang: None. J.A. Gabriel: None. R.M. Perez: None. L. Yang: None.