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Validation is defined as ‘the ability to prove and provide documented evidence that the equipment, process, system, cleaning method etc. are functionally effective, meet the correct standards and are consistently accurate.’ (Wikipedia) It directly links Data Integrity, which is currently a growing area of concern for many Life Science companies.

Data Integrity is described as ‘a fundamental pharmaceutical quality system which ensures medicines are of the required quality.’ (MHRA GMP Data Integrity Definitions and Guidance for Industry March 2015) In an industry which needs to be able to have complete confidence in the data produced, data integrity is critical and no matter where the data sits, its accuracy is the responsibility of the pharmaceutical production company. (This topic will be covered more in our next blog entitled ‘Regulatory Emphasis on Data Integrity.’)

In the pharmaceutical industry most if not all processes need to be validated in one way or another with the protection of the patient in the forefront of the companies mind. Slip ups in validation can damage, if not destroy a company’s reputation overnight, let alone breach compliance regulations.

Trouble is Validation is not a quick fix, as processes and companies evolve so does the need to re-validate. In fact it’s an ever changing environment that requires constant attention in order to prove an ongoing state of compliance. In this regard validation can be described as an ever moving target and it’s easy to see why.

4 Steps to Ensuring Validation Evolves with Production & Process Changes

1. Control – Validation required a vast amount of pre-planning to be successful and accurate. It needs to be a highly organised process with clear responsibilities laid out upfront. It needs to be continuously re-visited.
2. Understanding – The processes being validated need to be crystal clear and understood perfectly by the validator. With critical data points and parameters clearly defined. Critical knowledge needs to be continuously shared and updated throughout the organisation.
3. A Risk Based Approach – The risk to quality, based on scientific knowledge needs to be linked to the risk to the patient. Matrix’s that highlight the likelihood and certainty of a problem occurring with a clear contingency plan (see flow chart below) can help.
   Reference > Potential Problem > Consequence > Cause > Preventative Action > Contingency Plan
   Flow charts, check sheets and process mapping can also strengthen your data integrity position.
4. Planning & Preparation – This is twofold including both a Validation Plan as well as a Project Plan will reduce the risk of things going wrong. Again this needs to be a living a breathing document that is updated as new risks occur.

Validation is and always will be a continuous process, but by utilising experts, team work and preparation it doesn’t have to be a headache. At Zenith we deliver vigorous testing, validation and quality assurance solutions ensuring functional intent and approved design come together in a live environment. To read more about our services offering click here.