Your decisions matter.
Make your scientific data decision-ready.
Iris Scientific bridges lab and computational scientists, project leaders, and informatics and IT teams — translating research needs into practical solutions, connected systems, and reusable data.
Reduce data-cleaning bottlenecks, put your scientific data in context, and connect it across teams and workflows.
How Iris Scientific can help
Focused projects and connected support across strategy, systems, workflows, and decisions.
Landscape analysis
- Current state & priorities
- Requirements & roadmap
- Build vs. buy decisions
- Vendor selection
Repositories & metadata
- Compounds
- Assays
- Governance
- Data hygiene
Production workflows
- Data ingestion & QC
- Lab support workflows
- Automated reporting
- Human-in-the-loop
Modeling & decision support
- Cheminformatics
- SAR analysis
- Modeling-ready data
- Custom solutions
Better-informed decisions. Less manual data work.
Led development and roll-out across a major pharmaceutical company's global R&D sites — cutting analytical variability and enabling transparent, cross-team decisions.
Designed a production-grade pipeline for CRO data at a scaling biotech, eliminating manual data handling and cutting time-to-analysis.
Integrated analysis directly into an assay request system, accelerating mass-spec lab operations.
Identified and implemented a workflow change enabling efficient quality checking — improving data confidence at no added cost.
Diagnose
Understand your needs. Identify opportunities.
Select + design
Evaluate, prototype, and pressure-test options.
Build + operationalize
Make it work in practice. Train users.
First-hand discovery experience. Systems thinking. Practical delivery.
With 20+ years in pharma and biotech discovery, including AstraZeneca and Jnana Therapeutics, my background spans computational chemistry, cheminformatics, and scientific informatics.
I bridge bench and computational scientists, project leaders, managers, informatics and IT teams, vendors, and partners — translating research needs into reusable data, connected systems, and practical workflows that support better decisions and greater value from research investments.