Compliance & Validation — Not documented by Atlas
Ask the vendor: Which compliance certifications (HIPAA, 21 CFR Part 11, SOC 2, GxP) do you hold?
Simulations Plus
Publicly traded modeling and simulation software company whose ADMET Predictor and GastroPlus tools use ML for ADMET and PK/PD prediction.
Simulations Plus, Inc. (NASDAQ: SLP), incorporated in 1996 and headquartered in Research Triangle Park, North Carolina (relocated from Lancaster, California), provides established modeling and simulation software including ADMET Predictor for machine-learning ADMET/PK property prediction and PBPK tools such as GastroPlus and MonolixSuite. The software is widely used across pharma and referenced in regulatory submissions. No third-party security certifications were surfaced on public pages at profiling time — request security and validation documentation for regulated use.
- Headquarters
- Research Triangle Park, United States
- Founded
- 1996
- Deployment options
- cloud, on-premise
- Website
- https://www.simulations-plus.com
- https://www.linkedin.com/company/95827
Categories
AI Use Cases
- ADMET & Toxicity Prediction
Vendor Scorecard
57% — Partial coverage. Coverage score — how completely Atlas documents Simulations Plus across 7 buyer-evaluation areas. Reflects available Atlas data, not solution quality.
Deployment & Hosting — Documented
cloud, on premise
Pricing Transparency — Not documented by Atlas
Ask the vendor: What is your pricing model, and what drives total cost of ownership?
Implementation & Onboarding — Not documented by Atlas
Ask the vendor: What is a realistic implementation timeline, and what onboarding support is included?
Organization & Role Fit — Documented
Mid-Size Biotech, Large Pharma, Top 20 Pharma, Drug Discovery, R&D Leadership
Solution Scope — Documented
ADMET Prediction
Company Viability — Documented
Public, $0 raised, Founded 1996
Always ask the vendor
Not captured in Atlas data — confirm directly. Excluded from the score above.
Data Rights & IP
Who owns model outputs? Is our proprietary data used to train models others can access, and where does our data reside?
Model Credibility & Explainability
Can you share validation studies or benchmarks, explain how the model reaches its conclusions, and describe how bias and drift are monitored?
Questions to Ask This Vendor
- Which ADMET Predictor models are best validated for our chemistry?
- What security certifications or audit reports are available for cloud use?
- How do ML predictions integrate with our existing PBPK workflows?
- What training and support are included in the license?