Caitlyn Krebs
CEO
Nalu Bio
Nalu Bio offers an AI‑powered Endocannabinoid System (ECS) technology platform that accelerates drug discovery by generating thousands of novel, non‑addictive, patentable compounds daily. Trained on 90,000 molecules and 25 GPCR receptors, the platform maps ECS targets to disease pathways, delivering candidates up to five times faster and at lower cost for pharmaceutical and biotech partners developing therapies for inflammatory, immune, and metabolic disorders.
- Artificial Intelligence
- Biotechnology
Updated 5 months ago
Funding
Raised to date
$13.5MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Modern lifestyles characterized by chronic stress, poor diets, and environmental toxins create a biological mismatch that drives rising rates of inflammatory, immune, and metabolic diseases. Existing drug discovery approaches for the endocannabinoid system (ECS) rely on natural cannabinoids with limited bioavailability, intoxicating effects, and inconsistent outcomes, leaving a gap in safe, effective therapeutics.
Solution
Nalu Bio addresses this gap with an AI‑powered ECS Technology Platform that systematically maps the endocannabinoid system and uses deep‑learning models trained on 90,000 compounds and 25 GPCR receptors to generate novel, patentable molecules. The platform accelerates drug discovery by producing thousands of biologically relevant, non‑addictive candidates daily, optimizing for drug‑like properties, safety, and efficacy. By de‑risking and streamlining the design of ECS‑targeted therapeutics, Nalu Bio aims to build a pipeline that can treat inflammatory, immune, and metabolic conditions with precision‑engineered compounds.
Target Audience
Primary customers are pharmaceutical companies and biotech firms seeking to develop novel, non‑addictive therapeutics for inflammatory, immune, and metabolic diseases through ECS modulation.
Features
- AI-driven platform trained on extensive compound and GPCR receptor datasets to predict ECS target interactions
- Daily generation of thousands of novel, patentable molecules optimized for drug‑like properties and safety
- Focus on non‑addictive compounds that modulate CB1 and CB2 receptors, addressing a largely untapped GPCR space
- Integrated deep‑learning pipeline that maps causal relationships between ECS targets and disease pathways
- Accelerated discovery timeline, delivering candidates up to 5× faster and at significantly lower cost than traditional methods