DrugOME Case Studies
The DrugOme is a computational ecosystem that enables fast, high quality answers to pharma questions. That ecosystem is focused on three functional areas:
1. Competitive intelligence and fast investment decision-making
We have expertise, code, and the data infrastructure to support fast ingestion and analytics on top of most major sources of data to understand the pharma clinical landscape.
Fast access to aggregate clinical trials registry data
Enables rapid assessment of “typical” path to approval in indications based on historical successes and failures
Clinical trial cost model, optimized to variables accessible from registry data
Scenario analysis for any drug across many different clinical trial cost scenarios
Combined competitive intelligence databases with real world data
Fast landscape for approved drugs in indication
Combined FDA APIs with competitive intelligence databases and clinical trials registry
Fast curation of efficacy landscapes for an indication
2. Real World Data expertise
We have access to broad electronic claims data and have the data infrastructure, code, and expertise and have rapidly translated that data into actionable intelligence in many strategic scenarios including:
- Facilitating site selection based on combined analysis of site historical participation with claims analyses of likely best sites
- Assessing likely impact of inclusion/exclusion criteria on clinical trial enrollment
- Validation of investing hypotheses based on observed patient behavior
- Assessing patient demographics and stratification by severity for fine-grained epidemiology of an indication
- Adherence analyses
- Concomitant usage analyses
- Treatment cost
- Sales rep estimation
3. Natural Language Processing infrastructure
We have built a Natural Language Processing infrastructure to enable fast curation when available structured data is inadequate to answer strategic questions. This has enabled:
- Fast summaries of scientific literature for discovery-stage target selection
- Optimized alerts highlighting strategically relevant events
- Deep dives on literature for fast understanding of competitive landscape for pre-clinical targets