Data Falsification in Pharmaceutical Industry

Falsification of analytical and manufacturing data is not rare these days. You may think only one or two such cases are found yearly but studies show that about 50% of data and pharmaceuticals are unreliable. In most of the cases, even companies don’t know about this data fabrication. In most cases, it is done by the personnel due to over workload or sometimes they produce backdated records.

What is Data Falsification?

Data falsification exactly refers to the manipulation, deletion or fabrication of data to hide the true results of testing, manufacturing or any compliance. Data falsification includes changing the date of record or backdating the data, entering any false text results, deleting or modifying chromatograms, creation or modification of batch records and hiding deviation or OSS results.

These activities are done intentionally to pass the regulatory inspections, avoid rejection or to meet product specifications but these are unethical activities and cost the company integrity and compromise customer satisfaction.

The Importance of Authentic and Reliable Data

In the pharmaceutical industry, authenticity and integrity of data have greater value than other industries because pharmaceutical manufacturers medicine. A patient taking medicines should get effective and reliable treatment. It is not only to follow the regulatory guidelines but also need to follow ethical practices during manufacturing of medicines. Data manipulation or fabrication of data used in research studies conducted in any company can break people’s trust and cause serious issues.

Why It Happens

There are several causes identified behind this data falsification, some important are listed here.

1. Pressure of work

Pharmaceutical manufacturing is highly regulated and has a lot of work for employees. Documentation must be done at the time of work is being done. Due to this workload, employees falsify data to avoid these data errors without understanding that this is also a data error.

2. Lack of Training

In the pharmaceutical industry, training plays an important role in avoiding errors. Inadequate training can lead to data falsification. Every employee must be properly trained to know the importance of data integrity.

3. Poor Quality Culture

A culture of quality in any pharmaceutical company plays an important role to avoid issues related to ethics. But in some companies, quality is pushed backward to meet the production targets. In such places, data falsification is very common.

4. Week Quality System

Inadequate quality supervision, poor documentation and lack of internal audits create opportunities for data falsification.

Regulatory Consequences due to Data Falsification

Regulatory agencies like the USFDA, EMA and WHO take data integrity issues very seriously. Data manipulation is not only unethical but also an illegal activity. Common consequences that occur during regulatory inspections include:

1. Warning Letters

The FDA issues warning letters when they observe any data manipulation. These warning letters are publicly available and damage the company's reputation.

2. Import Alerts

Regulatory agencies can ban companies from exporting products to their countries if they find any company to be involved in any unethical activity.

3. Product Recalls

If falsified data is found to be linked to any released product, recall of that product is mandatory. It harms the company’s ethical values as well as commercial.

4. Criminal Charges

Individuals involved in these unethical activities can face prosecution, fines and even imprisonment.

It happened with Ranbaxy Laboratories in 2013 when they paid $500 million in fines after they were found involved in data fabrication submitted to the FDA. This was shocking news for the pharmaceutical world and this put data integrity in focus.

Impact on Patient Safety

Data manipulation can compromise patient safety because due to false results patient may receive an inadequate drug dose. A low dose may delay his treatment and a high dose can lead to serious health complications.

Common Areas Where Falsification Occurs

Data manipulation may occur in any of the pharmaceutical manufacturing stages from the manufacturing process to final product testing. But common areas are:

1. Analytical Testing

In quality control labs, alteration of chromatograms, fake analysis on instruments that don’t have audit trails or failure to record OOS results are common data manipulations.

2. Manufacturing Floor

In the manufacturing area backdated entries, false cleaning log entries, or recording false equipment checks are very common.

3. Stability Testing

In stability studies, data of falsification is done by analyzing a controlled sample instead of a stability sample to pass it.

QC Documentation

Data manipulation is very common in QC where original data is discarded and new values are rewritten to meet the specifications. It is widely done for instrument calibrations. This data is fabricated very wisely and in such a way that most of the times FDA inspectors fails to recognize this false calibration data.

Regulatory agencies have published guidelines for good documentation practices to prevent such issues. ALCOA principles state that data must be Attributable, Legible, Contemporaneous, original and accurate.

How to Prevent Data Falsification

Data falsification in pharmaceuticals is a serious issue and can be prevented by following these methods.

1. Establish a Strong Quality Culture

Monument must lead to build a quality culture by prioritizing quality over production. The ethical behavior of employees should be encouraged and rewarded. It will create a culture of ethics and quality.

2. Employee Training

Employees must know the importance of data integrity and regulatory expectations. Regular training of the staff should be a part of the compliance program. Actual training programs must be conducted instead of just filling out the attendance forms.

3. Implement Audit Trails

Enable auditors in all software systems to record any change in data. This adds transparency in the records and discourages tampering.

4. Routine Internal Audits

Internal audits play a crucial role in finding false data. Internal audits must be conducted to monitor the data logs, batch records and test results to identify manipulations in an early stage.

5. Whistleblower Protection

A whistleblower is a person who reports unethical practices. Safe channels for employees should be available to report unethical practices without any fear.

6. Clear SOPs:

How to record, review and manage data in every stage of manufacturing and testing must be written clearly in standard operating procedures.

Companies don’t save money by falsifying the analytical or manufacturing data. In most cases, companies do not know about this data manipulation and employees do it on their own to save time or relax. Company management must take it seriously and appoint a generated person to find such activities. If you have any questions related to data integrity and data falsification, feel free to contact us.

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