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VW Scandal – Data Integrity Issue?

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Photo by: Dave Granlund

Data integrity is the fundamental property of any information. In its original meaning, data integrity refers to consistency and accuracy both within itself and in the context of real life.

Today, we make many decisions based on captured data, and we get used to trusting it. For instance, we see the weather forecast and decide whether to go out at the weekend or not; we check the schedule of a train online and decide if we need to leave the house yet. People trust that information as long as it is consistent.

We get used to not questioning the data quality when we take these decisions. Moreover, sometimes the importance of decisions is higher than the grade of reliability of information. If information is inconsistent or wrong, we can steer ourselves in the wrong direction as a result of mismatches, misconduct, errors and fraud.

This is exactly what has happened with VW, with its catastrophic environmental fraud in cheating with emissions tests. The result: VW’s CEO lost his job; billions were wiped from the company’s shares; and the German economy faces a bigger threat than the Greek crisis.

The basic rule of data integrity was broken. Moreover, breaking this rule always has consequences in industry or research.

What can pharma learn from the VW scandal?

How important is data integrity in pharma and in clinical trials? In clinical trials, data integrity matters even more, because it goes beyond information about cars: it is all about patients’ health, safety, and life.

Imagine that, through data manipulation, a medicine appears on the market which is neither effective nor safe. (Indeed, this happened with Novartis and its medicine Diovan in Japan in 2013 when Novartis tried to promote it for reducing the risk of strokes and heart failures.) Alternatively, a good medicine, which can cure a disease, will not appear, because evidence through data mismatches will not be statistically strong enough. This happened, for example, with the Motexafin Gadolinium Phase III for cancer therapy study, as two centers in France delayed the onset of treatment and skewed the statistics.

There are many advantages to data having integrity: it fosters research, opens nature’s secrets, sustains trust. However, the consequences of data not having integrity are significant and can sometimes lead to economic and reputation collapse, as happened with VW.

We believe that data integrity is the most important requirement for scientific research and informed decisions. We appeal to pharma companies to establish a habit of proving their data integrity as a basis for trust in medicine and clinical research.

 

Truly yours, Cyntegrity

By | 2016-11-16T18:35:42+00:00 October 2, 2015|Blog|0 Comments

About the Author:

Professional in the integration of data-driven Risk-based Monitoring (RbM) process in international clinical trials of pharmacology. Speaker at regional and global conferences such as: DIA, PharmaForum, PharmaDay, DGGF, etc. 10+ years of experience in data quality projects and biostatistics for the pharmaceutical industry. Life passion: improving clinical research with RbM, driving the RbM research to new frontiers for CROs, pharma and biotech companies.

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