Tag: pharma

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09 Sep, 2019

Our product backstory

Sinéad McKeown

You might be surprised to hear that Arkivum was formed 7 years ago as a data storage provider. Originally created as an incubator project at the University…

02 Sep, 2019

Arkivum provides pioneering e-archive to Idorsia Pharmaceuticals delivering GxP compliant long-term access to valuable product and clinical trial data

Emma Davenport

Arkivum today announced that Idorsia Pharmaceuticals, headquartered near Basel, Switzerland; has selected Arkivum to safeguard and digitally preserve their valuable research and clinical trial data. A relatively…

23 Jul, 2019

Arkivum demonstrates alignment with regulated Life Sciences data management requirements including GxP regulations, award of ISO 9001 and ISO 27001 certifications and successful customer and partner audits

Emma Davenport

Arkivum, the leading provider of long-term data management and digital preservation solutions, today announced it has achieved pharma-level compliance with the award of ISO 9001:2015 certification, demonstrating…

29 May, 2019

Life sciences laboratories are rapidly becoming data enterprises – Are your departments reaching their full potential?

Emma Davenport

Growing amounts of data and data types make it increasingly difficult for laboratory managers to consolidate their data sources; removing silos and creating a single source of…

10 May, 2019

5 ways to reduce the increasing cost of compliance across your life sciences organization

Sreedhar Tulluri

Compliance is a necessary requirement of doing business within the life sciences industry, and rightly so. However, for life sciences organisations it is costly and complex and…

17 May, 2018

Blog series (part 4): Data degradation in life sciences- The final economic fallacy of long term data being temporarily dynamic and path dependent

Daniel Hickmore

The final economic fallacy is that long term data management is temporarily dynamic and path dependent. I would argue that data is certainly temporarily dependent, but not path dependent. Data is constantly degrading in every temporal dimension; the past, today and..