Effective Validation in Pharmaceutical Manufacturing

Validation can be defined as written proof showing that a process system or equipment is working as it was meant to be. In reality, however, successful validation is much more complicated than simply going through the protocol steps and obtaining signatures.

An important question that has to be answered during validation is whether or not the process is really running as planned and how this can be proved.

In pharmaceutical production, this differentiation is important. An ideally planned validation report will not compensate for weak understanding of the process, poor sampling, unsuitable acceptance criteria and too many fluctuations.

Good validation starts with knowledge of the process and ends with keeping the process under control.

Factors Contributing to Validation Effectiveness

There are a few characteristics that determine whether a validation program is effective:

• It is defined by science.
• It pertains to product and process knowledge.
• It adopts proper risk-management practices.
• Acceptance criteria are established before implementation.
• Sample represents the population properly.
• Deviations are properly analyzed.
• Data are being analyzed and interpreted rather than just collected.

The goal should not be to produce vast amounts of documents. The goal is to provide enough evidence for making a conclusion based on scientific reasoning.

Begin With Process Understanding

It is important to have an understanding of the process before one can start validation.

Prior to writing the validation protocol, the team should have learned about:

• Critical Quality Attributes (CQAs)
• Critical Process Parameters (CPPs)
• Material properties
• Equipment capabilities
• Process variability
• Normal ranges of operation
• Possible failure modes
• Sources of variation

If, for example, the granulation process much relies on the moisture content at the endpoint, the validation plan needs to demonstrate how moisture great affects the compression process and quality of the end product.

Merely noting that the granulation time was established for three batches will not be so helpful as realizing how each process parameter affects the parameters of the end-product.

Use Risk Assessment Properly

Risk assessment is one of the most effective tools for creating and implementing the relevant validation plan.

Using tools like FMEA, HACCP, fault-tree analysis, etc. would give necessary information about process steps that need more attention in terms of their risks.

That is why risk assessment must answer:
What variables can influence the product quality?

The outcomes from the process above have to affect the following things:

• Location of sampling
• Sampling frequency
• Acceptance criteria
• Requirements for qualifications
• Monitoring strategy
• Scope of validation

One of the major disadvantages is that risk assessment is done only to have a document prepared while the validation plan has already been planned. Risk assessment must influence validation strategy from the very beginning.

Define a Clear Validation Scope

The validation procedure should expressly pinpoint which matters are being established.
The scope should encompass things like:

• Qualification of equipment
• Qualification of utilities
• Validation of methods
• Validation of cleaning methods
• Validation of analytical methods
• Validation of computerized systems
• Validation of packing procedures
• Validation of transportation methods

All the tasks should have clearly defined scope and parameters.

For example, the process validation should clarify what manufacturing steps, what types of equipment, what batch sizes and what regime it covers.

Establish Scientifically Justified Acceptance Criteria

The criteria must be established before conducting the validation exercises.

The criteria should take into account the following aspects:

• Product specifications
• Development data
• Regulatory issues
• Process capabilities
• Previous experience
• Risk analysis
• Scientific understanding

The acceptance criterion should never be altered only because the results of the validation are not satisfactory.

In case the required criteria are not met, the acceptable procedure is the analysis of the outcomes and their influence on the validation results.

Sampling Is a Critical Part of Validation

Wrong sampling in validation can turn a good validation study into something useless.

The sampling plan ought to factor in:

• Variability of the process
• Design of the equipment
• Product properties
• Essential process steps
• Beginning, middle and end of processing
• Location of equipment
• Worst-case scenarios

The method of sampling should have scientific reasoning for the choice of sampling that goes beyond the historic number of sampling results.

Sampling Method should provide evidence of the consistency of the process in making uniform samples during the manufacturing period.

Challenge the Process

Validation must prove the efficacy of the process and not merely verify the best possible operational practices.

Validation studies must take into account conditions of challenge when there is a scientific justification for that:

• Maximum and minimum speeds of operation
• Upper and lower temperatures
• Maximal hold times
• Variations in the load of equipment
• Worst case-products
• The longest duration of the process

The goal is to know the limits of the process being validated. This becomes especially useful in case of subsequent changes in the conditions of production processes.

Handle Deviations in a Scientific Way

A deviation in a validation case does not mean that validation process as a whole has failed.

The deviation needs evaluation in terms of:

• Cause of the deviation
• Effect on the product
• Effect on the process
• Validity of data
• Impact on validation
• Chance of recurrence
• Need for taking corrective action

For example, an equipment alarm due to a temporary sensor failure can have a completely different effect on the process than a deviation occurring due to uncontrolled process variability.

The validation report should reveal the effect of a deviation on the final conclusion rather than merely listing them.

Review Data as a Whole

Validation should be associated with significant data analysis.

Depending on the activity, evaluation may consist of:

• Mean and standard deviation
• Process capability
• Trend analysis
• Variability assessment
• Comparison of validation batches
• Statistical analysis
• Link between CPPs and CQAs

Relying solely on whether results have passed specifications gives a distorted view of what is taking place in process.

Process can be said to be operating within specifications while it is gradually changing to an unacceptable condition.

Validation as a Process Activity

The work of validation does not complete the moment the final report is finished.

Time of producing routine products calls for continuous monitoring for the maintenance of a consistently validated state.

Key information includes:

• Deviations
• Out-of-Specification results
• Out-of-Trend results
• Complaints
• Yield trends
• Environmental monitoring
• Maintenance history
• Process capability
• Change controls

Continued Process Verification allows obtaining and using the normal manufacturing data to ensure efficient operation of the process in the future.

Most Frequent Causes of Ineffective Validation

Validation programs can often be harmed by the following frequent issues:

• Repeating old methodologies without evaluating the steps involved.
• Weak connections between critical quality attributes (CQAs) and critical process parameters (CPPs).
• Insufficient risk evaluation.
• Unjustifiable acceptance criteria.
• Poor sampling.
• Differences in equipment ignored.
• Deviations are treated as paperwork.
• Inadequate statistical analysis.
• Lack of use of the knowledge from the development stage.
• Failure to repeat validation work before a significant change.

One of the essential lessons of validation work is that the validity of validation does not depend on the amount of testing. A well-thought-out study using significant sample sizes and scientifically established challenges usually provides more information than a large study that does not answer key questions about a process.

Building a Strong Validation Program

The effective pharmaceutical validation system can be formed by some basic principles such as:
1. Understand: Get to know the methods, equipment used and risks of the product.
2. Evaluate: Determine critical factors by means of scientific risk appraisal.
3. Challenge: Prove the effectiveness using realistic testing conditions.
4. Measure: Gather valid and representative data.
5. Evaluate: Study variations and relationships instead of merely meeting specifications.
6. Conclude: Make scientifically grounded conclusions about validation.
7. Monitor: Keep evaluating in the process of completing validation.
Thus, this technology turns validation into monitoring of quality and process rather than a one-time activity for regulatory purposes.

Successful validation essentially involves showing control through facts. A validated process is much more than just producing the bare minimum three acceptable batches or delivering a validation report. A validated process must prove that the understanding of the particular manufacturing process is sound, that all critical features are suitably controlled and that the variation is within acceptable limits and that the level of quality is obtained every time.

The best validation programs commence even at the stage of product development with an emphasis on evaluation of risks. They also have a scientifically-based set of acceptance criteria and thoroughly analyze the process data.

When validation is perceived in this way, it transforms from merely being the necessity for good manufacturing practice.

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