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Posts about Data Integrity

Blog Home | Tag: Data Integrity
January 21, 2020

Why Validation projects fail

Many validation projects invariably overrun budgets and fail to meet schedules. This conundrum often results in management eyeing validation costs suspiciously. Under cost containment pressures from management, there is a tendency to cut corners which results in an increased compliance risks.

December 19, 2019

Digital Transformation Pharma 4.0 Impressive technology, but what about people

This current era of biopharmaceutical manufacturing is a most challenging and exciting time for our industry. Technology breakthroughs, intensifying competition, and continually rising performance expectations from patients, stakeholders, pressure from government bodies for cost reduction, and regulators necessitate rapid change in execution.

May 9, 2019

Managing cybersecurity (SaaS environment)

Hello and welcome to the first installment of our new blog series, “Managing Cybersecurity in a SaaS Environment.” Throughout the year, we will be posting articles on various cybersecurity topics.

February 5, 2018

Validation Data Integrity

During validation, a significant amount data and information is generated during the lifecycle of GMP systems that requires data integrity. This data and information includes validation lifecycle data for critical manufacturing equipment, process control systems, laboratory instruments and computer systems.

January 17, 2018

Requirements Traceability Matrix in the Life Sciences Industry

Unfortunately, the manual process required for creating a Requirements Traceability Matrix is very time consuming, inefficient and not cost effective due to the amount of resources and time required to maintain them during the lifecycle.

November 10, 2017

Blockchain and Data Integrity

First, let’s talk about blockchain, which is a bunch of blocks linked together. Each block contains data which can be linked to another block, forming a block chain.

March 13, 2017

Data Integrity by Design

Each of the above is important. However, the critical point is that data integrity should be designed into the system right from the beginning. Data integrity should be at the forefront of system development (i.e, design).