PerkinElmer joins Accenture's cloud-based R&D informatics ecosystem

PerkinElmer has signed on to Accenture’s life science partner ecosystem and will integrate its big data technology and content into the cloud-based platform’s wider efforts in drug discovery and research.

To start, PerkinElmer will make its informatics solutions compatible with Accenture-linked electronic laboratory notebooks, research and clinical data visualization software and chemistry-based analytics and workflow programs.

In addition, PerkinElmer’s Signals line of offerings in lead discovery and translational medicine are slated to be available through Accenture’s ecosystem in the future.

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“Today’s pharmaceutical companies are dealing with tremendous silos of data that are hard to access, expensive to maintain and can create missed opportunities to connect insights that propel new patient therapies,” David Wang, PerkinElmer’s general manager of informatics, said in a statement. “This is the promise of informatics in the lab, and we are pleased to be the largest instrument and informatics solution provider to join the Accenture ecosystem to date.”

RELATED: FDA clears PerkinElmer’s CLIFT lupus diagnostics

Last September, Accenture and Merck partnered with Amazon Web Services to build out a cloud-based research platform aimed at the early stages of drug development, with the goal of creating industry-standard applications for core research activities. Accenture also said it is putting together a precompetitive collaboration to enhance the platform’s capabilities.

Before that, Accenture signed a five-year deal with Roche in 2017 to build a diabetes-focused system that could offer patient-facing digital services, including algorithms to guide personalized treatment recommendations.

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Meanwhile, PerkinElmer has been working with companies such as Sanofi Genzyme and Enzyvant to develop genomic tests for rare diseases, such as lysosomal storage disorders like Farber, Gaucher, Pompe and Fabry diseases. Both efforts are aimed, in part, at better identifying the difficult-to-diagnose conditions and pairing them with drugs currently under development.