Data sharing for organizations, regulators and manufacturers

Multi-party private data sharing.

Gain critical business intelligence, and safety insights from shared, anonymized, member data.

data sharing guide organizations regulators manufacturers

Enterprise level performance and control for companies, public sector and membership organizations. Build on your data to model and reduce future risk, uncover opportunities and reduce costs.

Learn how organizations like FDA, RIFM, Western Growers and fiin use data sharing to uncover opportunities for members.


Gain access to market-wide insights on business, performance, safety and risk.


Compare your performance and build on opportunities. Open up insights impossible to individual organizations or departments alone.


An organization’s own data is limited and blinkered to the information they have access to and can collect. When organizations collaborate to share data, each entity gets access to a broader view of the landscape than would have been possible on their own.


This enhanced view leads to many business benefits including improved horizon scanning, reliable risk analysis, improved trending, predictive analytics, scenario analysis and ultimately more confident business or scientific decisions.


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Or find out more about Data Trusts for organizations, regulators and manufacturers.

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Data Trust - A legal and technical framework for sharing and managing data
“It was a great pleasure to work with Creme and their expert team. They were thorough, efficient, and went above and beyond on ensuring P2’s needs were met. This study with Creme Global enables us to promote our ingredients confidently for use in a huge range of cosmetics and personal care products.”
Dr Theodore Anastasiou, Vice President R&D P2 Science
Dr. Ted Anastasiou
Vice President of R&D at P2

We work with the largest food, cosmetic and chemical brands in the world and also with main industry regulators in both the US and Europe.

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Data Sharing on Creme Global Platform

Gain critical business intelligence
from shared, anonymized data.