Enveda
Enveda is a pioneering biotech company dedicated to decoding nature’s chemical code using AI and advanced data science. Their mission is to accelerate drug discovery by organizing, translating, and applying the vast, largely unexplored natural chemical space. By building the world’s largest searchable library of plant-derived molecules and developing foundation models like PRISM, Enveda aims to unlock the potential of natural compounds for human and planetary health, transforming how medicines are discovered and understood.
Industries
Nr. of Employees
medium (51-250)
Enveda
Boulder, Colorado, United States, North America
Products
Oral first-in-class anti-inflammatory small-molecule (early clinical candidate)
Orally administered novel small-molecule anti-inflammatory candidate progressed into Phase 1 clinical testing following preclinical efficacy and safety evaluations.
Gut-preferred oral small-molecule candidate for inflammatory bowel disease (IND-enabling)
Gut-targeted small molecule designed for preferential gastrointestinal exposure with completed IND-enabling studies and planned Phase 1 progression.
Oral small-molecule obesity candidate (IND-enabling)
First-in-class oral small molecule with a hormone-mimetic mechanism that has demonstrated preclinical efficacy and safety supportive of clinical translation.
Portfolio of development-stage natural-product-derived small-molecule programs
A pipeline of multiple development candidates and optimization-stage programs across inflammatory, fibrotic, neurological, and metabolic indications discovered from natural-product libraries and advanced through optimization and IND-enabling activities.
Oral first-in-class anti-inflammatory small-molecule (early clinical candidate)
Orally administered novel small-molecule anti-inflammatory candidate progressed into Phase 1 clinical testing following preclinical efficacy and safety evaluations.
Gut-preferred oral small-molecule candidate for inflammatory bowel disease (IND-enabling)
Gut-targeted small molecule designed for preferential gastrointestinal exposure with completed IND-enabling studies and planned Phase 1 progression.
Oral small-molecule obesity candidate (IND-enabling)
First-in-class oral small molecule with a hormone-mimetic mechanism that has demonstrated preclinical efficacy and safety supportive of clinical translation.
Portfolio of development-stage natural-product-derived small-molecule programs
A pipeline of multiple development candidates and optimization-stage programs across inflammatory, fibrotic, neurological, and metabolic indications discovered from natural-product libraries and advanced through optimization and IND-enabling activities.
Services
AI-enabled natural product discovery platform
Integrated discovery platform combining high-throughput LC-MS/MS profiling, a large searchable library of natural samples, and machine-learning models trained on public and proprietary spectra to identify, prioritize, and annotate bioactive molecules from complex extracts.
Ethnobotany knowledge-graph and prioritization analytics
Curated, computable database of traditional plant uses and scientific literature integrated with phytochemical and spectral data to rank plant and compound hypotheses for targeted screening.
Collaborative disease-priority discovery programs
Strategic collaborations with philanthropic and industry partners to advance discovery programs focused on priority global-health indications using natural-product discovery approaches and shared infrastructure.
AI-enabled natural product discovery platform
Integrated discovery platform combining high-throughput LC-MS/MS profiling, a large searchable library of natural samples, and machine-learning models trained on public and proprietary spectra to identify, prioritize, and annotate bioactive molecules from complex extracts.
Ethnobotany knowledge-graph and prioritization analytics
Curated, computable database of traditional plant uses and scientific literature integrated with phytochemical and spectral data to rank plant and compound hypotheses for targeted screening.
Collaborative disease-priority discovery programs
Strategic collaborations with philanthropic and industry partners to advance discovery programs focused on priority global-health indications using natural-product discovery approaches and shared infrastructure.
Expertise Areas
- Foundation models and self-supervised learning for metabolomics
- Mass-spectrometry-driven natural product discovery
- Large-scale MS/MS dataset assembly and curation
- High-throughput phenotypic and pathway screening
Key Technologies
- Tandem mass spectrometry (LC-MS/MS)
- Self-supervised transformer models for spectra
- Masked peak modeling (spectral masking)
- Spectral embeddings / representation learning