Enabling a digital quality ecosystem to deliver the promise of proactive quality
The world’s first AI-enabled platform designed to augment quality management decision-making
End-to-end solution for enterprise quality management
Modernize the Annual Product Quality Review (APQR) process
A library of business applications, each designed to meet a specific life sciences use case
A Library of Business Applications, Each Designed to Meet a Specific Life Sciences Use Case, That Helps Companies Improve Business Outcomes and Product Quality
In today’s fast-paced and ever-changing life sciences industry, companies are constantly seeking ways to improve business outcomes, product quality and patient safety. The Honeywell Life Sciences Applications Suite provides a library of applications for specific life sciences use cases that help companies improve business outcomes, product quality and patient safety.
The suite quickly enables new capabilities and unlocks enterprise-level insights in a way that is flexible, agile, and responsive to the evolving demands of the life sciences industry. It does so without imposing a heavy burden on IT, data infrastructures or resources.
The Honeywell Life Sciences Applications Suite consists of three major components:
The business applications are designed to quickly deliver unique packaged capabilities and insights that are not readily available out-of-the-box from existing solutions and rely on multiple data sources. The suite provides a digital ecosystem of purpose-built applications that adhere to regulatory requirements to help support GxP compliance.
A connective data fabric supports business applications and orchestrates the computing network, storage and software components that work together to deliver data and services, allowing organizations to find, access and combine data from available sources regardless of type and location. It leverages current data sources, IT architecture and systems of record.
The data sources used in the Honeywell Life Sciences Applications Suite are those systems of record that already exist within an organization’s data architecture. Systems of record can take the form of databases, data lakes or warehouses, file or document repositories, streaming sources or other applications (i.e., PLM, LIMS, CTMS, ERP, MES, RIMS, QMS, etc.).