The FDA updated its Guidance for Industry as it relates to validating methods for drugs and biologics.
Rushing into validation can lead to failed validation runs involving repeating assay runs.
Excessive repeat rate during validation does not support the level of confidence expected for validated methods. Understanding the requirements for a method to be considered validated helps with the decision-making process to move from development to validation.
Using Design of Experiments (DOE) can help collect a larger dataset using fewer assay runs to support the decision to move from development to validation. More data points can support statistical analysis used to set acceptance criteria for the method during validation.
Data from DOE can also help analysts understand the limits of the assay and which robustness parameters to confirm during validation. Also, having a thorough understanding of regulatory agency expectations can prevent unnecessary problems with setting the acceptance criteria for bioanalytical methods.
This 3-hour webinar will describe essential practices for bringing analytical methods from development through validation in laboratories supporting biologic products as well as qualification or validation of methods used in clinical laboratories.
The methods that are selected for each test condition must be developed with validation in mind. These methods should be rugged selective, and specific.
Validated methods are also necessary to establish stability of large molecules. The ability to detect differences in responses between the stable drug and partially degraded drug should be significant in the validated method.
Why you should Attend:
Method validation guidance has become increasingly more consistent. Regulatory agency documents now offer firm guidance on expectations on assay method performance to meet the status as validated for intended purpose.
Specific criteria for system suitability and acceptance criteria for validation parameters has evolved with input from Sponsors and laboratories performing testing. Yet, with the availability of solid guidance documents, some laboratory personnel may still struggle with completing validation of bioanalytical methods. A main concern is ruggedness of the method during active long-term use for analysis of analytes in matrix.
Adopting solid principals for development and optimization of the method should result in an assay that is expected to meet ruggedness, precision, accuracy, selectivity, sensitivity, dilutional linearity, and specificity.
Although there is typically no set number of assay runs to complete development and optimization, collecting the most data with the minimum number of plates should be considered. However, the number of plates run should be sufficient to assess ruggedness prior to the formal validation.
The validation should be designed to accomplish the purpose in a minimum number of runs. When proper development is not performed and the decision to move into validation does not have enough supporting data, assay failure during validation can result.
Failures of runs during validation can lead to interruption of the validation with subsequent additional method development required prior to entering validation again.
This is not just time-consuming with an impact on timelines but uses reagents, that may be critical, without producing usable data.
This webinar is designed to walk attendees through steps to consider during method development that support the decision to proceed to validation.
Validation parameters will also be discussed following the recently published Bioanalytical Method Validation guidance.
Areas Covered in the Session:
- Understanding "validation"
- Defining what procedures are required for the drug or biologic testing
- Developing new test methods
- Selecting the reference material/standard
- Confirmation testing of the reference material/standard
- Qualifying reagents - determining critical reagents
- Defining the validation procedure - the protocol
- Writing the methods to be validated
- Using compendial methods
- Acceptance criteria and statistical methods
- Setting ranges and specifications post validation
- Training and documentation
- Life cycle management - revalidation (changes in methods)
Who Will Benefit:
- Validation scientists in bioanalytical or clinical laboratories
- Development scientists in bioanalytical or clinical laboratories
- QA Documentation Specialists
- Regulatory Specialists
- Directors of Outsourcing
- Method trainers
- Statistical staff