// Trust & Security Report
Deep Genomics Inc.
BioFM Platform - an AI-driven biological foundation model platform for RNA disease discovery and genetic medicine development, including BigRNA (variant effect prediction), REPRESS (microRNA binding), and DeepADAR (RNA editing guide design) models
Certifications held
0
Maturity
Growth
Trains on your data
Unknown
Trust center
No
// Certification ledger
Each held certification is backed by a verbatim quote from the vendor's own trust or security page. “Not confirmed” means we could not verify it publicly, not that the vendor lacks it.
> Show 8 unconfirmed / not-held certifications
source: deepgenomics.comNo public evidence found on Deep Genomics website or trust center (no dedicated trust center exists)
source: deepgenomics.comNo public evidence found on Deep Genomics website or trust center (no dedicated trust center exists)
source: deepgenomics.comNo public evidence found on Deep Genomics website, privacy policy, or compliance documentation
source: deepgenomics.comNo public evidence found on Deep Genomics website or compliance documentation
source: deepgenomics.comNo public evidence found on Deep Genomics website or compliance documentation
source: deepgenomics.comPrivacy policy makes no explicit GDPR compliance statement; states service providers 'may be located in U.S., Canada or other foreign jurisdictions' without detailing data transfer safeguards or adequacy decisions
source: deepgenomics.comNo public evidence found on Deep Genomics website or privacy policy
source: deepgenomics.comNo public evidence found on Deep Genomics website or compliance documentation
// Privacy & AI training
Trains on customer data
Not stated
Data processing agreement
Not offered
Data region
Multi-jurisdiction: US, Canada, foreign jurisdictions unspecified. No specific data residency commitments found
Privacy policy does not explicitly state whether customer genomic data is used to train BioFM models. BioFM Platform description mentions 'lab-in-the-loop workflows' with partner organizations (e.g., BioMarin) but does not disclose whether customer data informs model training. Training dataset disclosure mentions 'high-throughput sequencing datasets' and 'in vitro and in vivo data' without specifying source (public vs. proprietary customer data)
// Security controls
Data Protection Measures
Implements 'reasonable administrative, technical and physical measures' to safeguard personal information against theft, loss, and unauthorized access
deepgenomics.comData Retention
Retains personal information 'for no longer than necessary' to fulfill stated purposes or meet legal requirements; specific retention periods not defined
deepgenomics.comThird-Party Access
Personal data shared with service providers (hosting and related functions) located in US, Canada, or foreign jurisdictions; no mention of Data Processing Agreements
deepgenomics.comGovernment Access
May disclose personal information in response to search warrants or legally valid inquiries and to government authorities as required by applicable law
deepgenomics.com// Products & data scope
data: Genomic/RNA data; high-throughput sequencing datasets; in vitro and in vivo biological data
Lab-in-the-loop platform for model training and refinement; used by internal Deep Genomics programs and pharma partners (e.g., BioMarin); physical labs in Toronto and Cambridge, MA
data: Over 1 trillion signals from high-throughput sequencing datasets
Predicts genetic variant effects and on/off-target effects of genetic medicines; core component of BioFM Platform
data: RNA sequence and cellular data
Predicts cell-type-specific microRNA binding and mRNA degradation from RNA sequence
data: RNA editing target data
Designs guide RNAs for ADAR-mediated RNA editing
// What to watch
- No public trust center or dedicated security/compliance page exists
- Generic data protection language ('reasonable measures') without specifics on encryption, standards, or audit frameworks
- Service providers located in multiple jurisdictions without documented Data Processing Agreements (critical gap for GDPR, HIPAA, or genome-regulated data)
- No public compliance certifications despite processing sensitive genomic data and operating as Series C funded company with 108 employees
- Privacy policy does not explicitly state whether customer genomic data is used to train BioFM models—significant gap for AI governance disclosure
- No documented data residency options or commitments (relevant for regulated genomic data in EU, Canada, or US states with genomic privacy laws)
- Absence of formal terms of service (404 errors on standard paths)
- Cross-border data flows mentioned but without adequate safeguard documentation (GDPR SCCs, Standard Contractual Clauses, or adequacy findings not referenced)
// At a glance
Pricing model
Not publicly disclosed; appears to be partnership-based licensing with pharma companies (e.g., upfront payments + milestones)
Self-hostable
No
// How we verified this
Every certification marked HELD is confirmed against a verbatim quote on Deep Genomics Inc.'s own trust, security, or privacy pages. We reject certifications claimed only on third-party aggregators, on a cloud host's behalf, or by a similarly named company.
Last verified 2026-07-07. Compliance changes over time. Always confirm directly with the vendor before relying on any certification for a purchasing or compliance decision.
deepgenomics.com