Pharmaceuticals & Life Science
Advances in artificial intelligence and new and emerging data sources now allow pharmaceutical companies to gain significant efficiencies in the targeting of new therapies and to demonstrate the value of late-stage clinical and newly approved products.
What We Do
ClosedLoop’s data science platform combines leading-edge AI tools and automation capabilities with healthcare specific content and expertise - enabling healthcare data scientists to build accurate and explainable predictive models with speed and ease.
ClosedLoop.ai uses a variety of data sources to create accurate predictions and surface new insights.
Don’t reinvent the wheel. ClosedLoop.ai’s catalog of risk models cover the most common and valuable use cases and are fully editable and extensible to meet your needs. No data-science degree required.
POINT AND CLICK SIMPLE
Easily create risk-scores and predictions for a variety of outcomes in just a few clicks, or use the API and be up and running in under an hour.
24-HOUR ZERO RISK TRIAL
Explore the predictive value of your data without a large upfront investment of time or money. Ask about the 24-hour zero-risk pilot today.
The ClosedLoop Platform for Pharma & Life Science
ClosedLoop.ai is an AI-based predictive analytics platform that uncovers insights in vast amounts of disparate healthcare data, including clinical trials, real world clinical and claims data, genomic, social, and environmental data. ClosedLoop can identify biomarkers that are predictive of treatment response, and select patient groups most likely to benefit from treatment. ClosedLoop.ai continues to get smarter as it absorbs more data – identifying new relationships and novel insights. ClosedLoop’s platform can be used to answer questions like:
- Biomarkers: Which patients will have an increased success rate based on biological factors?
- Drug-Combinations: Which drug combinations are most likely to be successful?
- Segmentation: Which groups of patients respond differently to treatment?
- Strategy: Which subpopulations should be included/excluded based off of predicted success rates?
- Responsive: Which patients are responding to treatment?
- Events: Which patients are most likely to experience adverse reactions?
- Effectiveness: How will clinical trial results translate into real world effectiveness?
- Value: What improvement in outcomes will a new treatment generate over existing therapies?
- Switching: Which factors are most relevant in understanding which patients switch drugs?
- Marketing: Which physicians can we market to?
Proof of Concept in 5 Easy Steps
Let's Get to Know You
First, we’d enjoy getting to know your organization and goals with Artificial Intelligence. Having an understanding of your current risk stratification process and intervention programs will help uncover how ClosedLoop can provide the most value to you and your team.
Determine Use Case & Data Discussion
Based on your available sources of data, we will define a single use case for the initial proof of concept. Plan to have a member from your technical team to discuss the workflow of the data transfer.
Sign a BAA / NDA
Your data is valuable. Before any data is transferred, a BAA/NDA will be signed.
Send raw healthcare data via SFTP or API
Get a Predictive Model in 24 Hours
24 hours after receiving your data we will provide a report demonstrating how much signal is present in each of your data sources and how accurate our predictions can be.
How Can ClosedLoop Help Improve Patient Outcomes & Lower the Total Cost of Care For Your Organization?
Get in touch today to speak with a member of the ClosedLoop team