Public platform for science, technology, society, and environmental information
Data, methods, and evidence
Data and evidence on Cannabis and cannabinoids
Kannabium relates biological, omics, geospatial, socioeconomic, and environmental data to describe Cannabis sativa, molecular structures, and cannabinoid interactions in vertebrates. Every result identifies its sources, methods, evidence, and interpretive limits.
01 · Cannabinoid ecosystem
Which data constitute the cannabinoid ecosystem?
At Kannabium, the integrated Plantae–Animalia cannabinoid ecosystem refers to an organized set of biological data — including genomic and metabolomic data — alongside geospatial, socioeconomic, and environmental information. At the species level, these resources describe the botany, ecology, distribution, and socioeconomic relevance of Cannabis sativa; at the molecular level, they connect its phytochemical diversity with evidence on cannabinoid interactions in vertebrates. Together, they support analysis of how biological resources are produced, transformed, studied, regulated, and used.
The platform organizes this material into scientific portals, maps, and case studies. Its pathways introduce bioinformatics and data-analysis methods with stated sources and interpretive criteria. Data curation and governance are represented by the AromaCann brand, which brings together the principles and controls that guide documentation, quality, access, and responsible data reuse.
- Connect dispersed records while retaining the origin and context of each item.
- Document the use of artificial intelligence and the criteria used to evaluate its outputs.
- Define technical standards and conditions of use that support interpretation and reuse.
- Build the capacity to consult sources, assess evidence, and communicate findings.
Published scientific portals
Species, enzyme, and receptor: three scales of analysis
The portals dedicated to Cannabis sativa, THCA synthase, and the CB1 receptor retain their own scopes, methods, sources, and interpretive limits. Their relationships are presented without equating distinct classes of evidence.
01 · Species-level data
Cannabis sativa
Taxonomic, botanical, genomic, phytochemical, geospatial, historical, and socioeconomic records organized around a defined species identity.
Review the species data02 · Plantae enzyme structure
THCA synthase
Experimentally determined enzyme structure, catalytic context, residue-level evidence, source provenance, and interactive structural analysis.
Review the THCA synthase structure03 · Animalia receptor structure
CB1 receptor
Conformational states selected from published structures, ligand contexts, structural complexes, signaling biology, and molecular visualization linked to source structures.
Review the CB1 receptor structuresThree analytical pathways
Pathways for analyzing markets, biological data, and the production chain
Choose a pathway according to the question: technology and regulatory comparisons, reproducible computational analysis, or research on the production chain.
Evidence workflow
Sources, normalization, analysis, and publication
The curation workflow records data origin, version, identifiers, and conditions of use. As records are organized and their relationships interpreted, readers should be able to identify the methods and limits behind each result.
- 01 Sources and datasets Origin, version, identifiers, access conditions, and limitations.
- 02 Normalized records Entities, units, fields, and evidence classes standardized.
- 03 Analysis and interpretation Methods, comparisons, uncertainties, and conclusions documented.
- 04 Applications Scientific, technological, social, and environmental uses delimited.
- 05 Web publication Review status, provenance, and limitations disclosed.
Cannabis sativa–vertebrate molecular axis
From THCA biosynthesis to CB1 receptor modulation
In the selected pathway, THCA synthase catalyzes the conversion of CBGA into THCA in Cannabis sativa. THCA decarboxylation produces Δ⁹-THC, a compound that interacts with cannabinoid receptor type 1 (CB1R) in vertebrates. Kannabium keeps the enzymatic, chemical, structural, pharmacological, and historical evidence used to describe this axis distinct.
Other published products
Maps, computational methods, and technology-market analysis
Infrastructure and governance
Artificial-intelligence systems depend on documented data, controlled infrastructure, and defined rules for access, use, and accountability.
BioDev & Data Curation · editorial principle
Data-governance requirements
Responsibilities, quality, access, and reuse
Governance defines responsibilities and criteria for quality, access, and reuse. Documenting data origin and transformations makes it possible to examine how each result was obtained. AromaCann relates these principles to research, computational applications, and personal-data protection.
- Platform status
- Active development
- Public content
- Continuous technical and editorial review
- Scientific claims
- Linked to declared evidence and limitations
- Governance module
- AromaCann available