Chemetrian FAQs

Getting Started

What is Chemetrian?

Chemetrian is a machine learning platform designed specifically for chemistry applications. We enable chemists, materials scientists, and researchers to leverage ML techniques across the entire chemical discovery and development pipeline including reaction optimization, molecular property prediction, and more.

How do I get started with Chemetrian?

Getting started is straightforward. If you are an individual, you can sign up for a 1 month free trial. Or, schedule a consultation with our team to discuss your specific chemistry challenges. We'll work with you to understand your goals, assess your data infrastructure, and create a customized onboarding plan. Our team provides hands-on training and ongoing support to ensure successful implementation.

Do I need programming or machine learning experience to use Chemetrian?

No programming experience is required. Chemetrian is built with chemists in mind, featuring an intuitive interface that makes sophisticated machine learning accessible. Throughout the software there are educational suggestions to help guide users, we provide an educational documentation site, and our team is available for consultation via email or meeting.

What types of chemistry problems can Chemetrian help solve?

Chemetrian addresses a wide range of chemistry challenges including:

• Molecular property prediction: Predict reactivity, selectivity, ADMET, and other properties.
• Reaction optimization: Find optimal conditions for yield, selectivity, and other reaction metrics.
• Materials design: Discover new materials with desired properties.
• Catalyst screening: Predict and optimize catalyst performance.
• Formulation development: Optimize complex mixtures and formulations.
• Drug discovery: Accelerate lead identification and optimization.

What tools does Chemetrian offer?

• Bayesian optimization: Use machine learning to optimize reaction parameters with minimal number of experiments via active learning.
• Predictive modeling: Train machine learning models to predict target properties and then screen molecules in silico to guide experiments.
• Chemical space analysis: Compare, explore, and filter molecular structures using dimensionality reduction and clustering.
• Descriptor calculation: Calculate cheminformatic and quantum-chemical descriptors for training machine learning models and understanding molecular properties using automated pipelines.

What is the difference between Design of Experiments (DoE) and Bayesian Optimization?

While Design of Experiments requires planning and running a fixed set of experiments upfront to map out the design space, Bayesian Optimization uses machine learning to adaptively learn from each experiment and intelligently select the next most informative one. This adaptive approach allows Bayesian Optimization to find optimal conditions with up to 95% fewer experiments than exhaustive screening or traditional DoE, dramatically reducing time, cost, and resource consumption in reaction optimization.

Does Chemetrian build custom tools?

Chemetrian takes substantial feedback from users and makes changes based on user suggestions and needs. Custom solutions are also available via consultation.

How much data do I need to get started?

None. The platform will guide the first experiments you need to get started. The first round of experiments will vary by application:

• Reaction optimization: The Bayesian optimization tool will suggest 10 initial experiments, then the model will be iteratively improved via active learning.
• Property prediction: As few as 10 data points.

What industries can benefit from Chemetrian?

Chemetrian serves diverse sectors:

• Pharmaceuticals
• Specialty chemicals
• Agrochemicals
• Materials science
• Flavors & fragrances
• Academic research

Sustainability & Compliance

Can Chemetrian help with sustainable chemistry goals?

Yes! ML can significantly reduce the environmental impact of chemistry:

• Fewer experiments: Reduce reagent waste and energy consumption
• Greener solvents: Predict and optimize for environmentally friendly alternatives
• Improved atom economy: Optimize reaction conditions for minimal waste
• Predictive toxicity: Screen for safer compounds early in development

Is Chemetrian compliant with regulatory standards?

Chemetrian is designed to support regulatory compliance:

• Audit trails: Complete documentation of all modeling decisions
• Data provenance: Track data sources and transformations
• Validation protocols: Rigorous model validation for regulatory submissions
• 21 CFR Part 11 compliance: Available for pharmaceutical applications
• Good Machine Learning Practice (GMLP): Following emerging FDA guidance

We can work with your regulatory team to ensure appropriate documentation and validation.

Data Security & Privacy

How is my data protected?

We take data security seriously:

• End-to-end encryption: Data encrypted in transit and at rest
• Secure cloud infrastructure: Multi-tenant AWS deployment with enterprise-grade security
• On-premises deployment option: For organizations with strict data sovereignty requirements
• Access controls: Role-based permissions and authentication

Is my proprietary data used to train models for other companies?

No. Your proprietary data is strictly segregated and used only for your projects unless you explicitly grant permission otherwise. We offer:

• Private model training: Models built exclusively on your data
• Data isolation: Complete separation between different organizations
• IP protection: Clear ownership of your data and custom models

Technical Details

How are models validated?

Chemetrian uses machine learning models that have been validated by scientific literature. Additionally, users can build and validate their own models.

What about model explainability and interpretability?

Understanding why a model makes specific predictions is crucial in chemistry. Chemetrian provides:

• Feature importance calculations: Identify which molecular features or conditions drive predictions, providing fundamental chemical insights on the system.
• Model visualization: Methods for visualizing the entire prediction space of models to inform experimental decisions.

When should I use machine learning vs. traditional chemistry approaches?

Machine learning is particularly valuable when:

• The design space is large and you want to minimize experiments
• Relationships between variables are complex and non-linear
• You have historical data that could inform new projects
• Speed is critical (screening, early-stage discovery)
• Multiple competing objectives need balancing

Traditional approaches remain irreplaceable for mechanism elucidation, novel chemistry, problems where data is unavailable, and other situations.

What makes Chemetrian different from general-purpose ML platforms?

Chemetrian is purpose-built for chemistry with:

• Chemical representations: Native support for chemical representations like SMILES, 3D structures and quantum-chemical descriptors
• Physics-based calculations: Calculation of descriptors using physics-based, quantum methods
• Domain-specific algorithms: Methods developed specifically for chemistry problems
• Chemistry-first interface: Designed for chemists, not data scientists
• Education: Users are guided with best practices throughout the software

Pricing & Support

How is Chemetrian priced?

We offer flexible pricing models to match different organizational needs:

• Academic
• Enterprise
• Custom group rates

Contact our team for a customized quote based on your requirements.

Can Chemetrian be used as an educational tool?

Yes, our software has already been used in undergraduate organic chemistry curricula and we are excited to continue promoting machine learning education for scientists.

What kind of support is included?

All Chemetrian group subscriptions include:

• Onboarding and training: Initial setup and team education
• Technical support: Access to our chemistry and ML experts
• Regular check-ins: Proactive support to ensure success
• Software updates: Continuous improvements and new features
• Documentation: Comprehensive guides and tutorials

Premium support packages with dedicated success managers are available for enterprise clients.

How long does implementation typically take?

Tools are ready for immediate integration into optimization and property prediction workflows even without any data. We work closely with your team to minimize disruption and accelerate time-to-value.

Still Have Questions?

Can't find what you're looking for? Our team is here to help.

Contact us to discuss your specific needs, check out our documentation website, or book a consultation to see Chemetrian in action.