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:

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:

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