Immune malfunction or misrecognition of healthy cells and tissue, termed autoimmune disease, is implicated in more than 80 disease conditions and multiple other secondary pathologies. While pan-immunosuppressive therapies like steroids can offer limited relief for systemic inflammation for some organs, many patients never achieve remission, and such drugs do not cross the blood-brain barrier, making them ineffective for tackling neuroinflammation. Especially in the brain, unintended activation of microglia and astrocytes is hypothesized to be directly or indirectly responsible for multiple sclerosis, amyotrophic lateral sclerosis, Parkinson's disease, and Alzheimer's disease. Recent studies have also shown that targeting inflammasomes and specific immune targets can be beneficial for these diseases. Furthermore, our previous studies have shown targeting NF-κB and NLRP3 through brain penetrant Nanoligomer cocktail SB_NI_112 (abbreviated as NI112) can be therapeutic for several neurodegenerative diseases. Here, we show safety-toxicity studies, followed by pharmacokinetics and biodistribution in small- (mice) and large-animal (dog) studies of this inflammasome-targeting Nanoligomer cocktail NI112. We conducted studies using four different routes of administration: intravenous, subcutaneous, intraperitoneal, and intranasal, and identified the drug concentration over time using inductively coupled plasma mass spectrometry in the blood serum, the brain (including different brain regions), and other target organs such as liver, kidney, and colon. Our results indicate that the Nanoligomer cocktail has a strong safety profile and shows high biodistribution (F ∼ 0.98) and delivery across multiple routes of administration. Further analysis showed high brain bioavailability with a ratio of NI112 in brain tissue to blood serum of ∼30%. Our model accurately shows dose scaling, translation between different routes of administration, and interspecies scaling. These results provide an excellent platform for human clinical translation and prediction of therapeutic dosage between different routes of administration.