Development through Phase II
During development through Phase II clinical trials, one needs to establish characterization of the API, the reference, and
the final drug delivery form. Characterization can be particularly daunting in biopharmaceuticals. Generating references in-house
may be required annually for products such as influenza vaccines. Each year, it is important to evaluate whether a particular
test is necessary to generate a reference standard or is being used as a redundant safety net.
During this phase of development, before administering the drug in Phase I and Phase II clinical trials, analytics are needed
to establish the product's safety, its clinical release, and clinical stability. The analytical methodology at this point
need not be extremely robust, rugged, or validated—only one or two chemists, as opposed to an entire laboratory, should be
required to duplicate the results. While having confidence in the methodology is important, validating rather than qualifying
analytical methods at this stage may increase costs unnecessarily. Further, methodology can be modified as long as safety
and efficacy remain unaffected.
The goal of this phase of development is to submit an application to FDA that will gain approval to proceed to the next steps
in the clinical trial process. Data submitted should meet the requirements of compliance, but it is sometimes tempting to
try to impress the agency with specifications and criteria that go beyond those requirements. A development chemist may develop
a testing methodology that is capable of detecting a higher level of purity than is called for by the drug's specification.
However, such tests may not be rugged and may yield false information that requires additional unnecessary testing. Further,
in approving the drug, FDA may expect the highest standard that the testing is capable of detecting. Companies should review
the submission to ensure that there has been no "specification creep" or "analytical creep" that will cause difficulties in
Phase III clinical trials
During Phase III clinical trials through approval and the lifecycle of the marketed product, the first consideration (after
safety and purity) regarding analytical methods is whether they are quality control (QC)-friendly. The QC department must
be able to run the tests reliably and reasonably quickly from batch to batch. There is no need for an elaborate method that
requires days to run and provides 99.9% certainty when, for example, 95% is acceptable. Equally important is that the method
should not yield false failures. To ensure that the analytical method works for QC and provides accurate data, R&D and QC
should regularly communicate early on in the drug-development process. With a thorough understanding of the QC needs, analytical
development personnel in R&D can create robust methodologies and transfer them successfully the first time, saving time and
avoiding unnecessary costs.
At this point, final characterization of the API, the reference standard, and the dosage form needs to be achieved. In addition,
validation of any process (e.g., growing of the cell cultures, isolation of the active component) that will go into the application
for approval should be performed. Determine what in-process testing will be critical to controlling the process. In addition
to testing safety, potency, and purity at this point, some of the analytical methods adopted must be capable of stability
testing to determine when the drug will go out of compliance. Finally, any analytical methodology should meet all of the appropriate
pharmacopeial standards for validity (i.e., specificity, accuracy, precision, ruggedness).
Although the methodology at this point is virtually "locked," changes can be made. However, changes that require FDA approval
can be costly in terms of internal resources, the costs of submission, and the costs of delay in development. Some companies
submit analytical summaries instead of the full range of data, which can enable minor tweaks in methods without requiring
agency approval. This approach can save time, provide more freedom to operate, and avoid the costs of submission, much in
the way that quality by design (QbD) may provide the freedom to make changes within the design space of a product without
having to secure prior approval.
As part of an overall strategy to control analytical testing costs, you should also review the testing for legacy drugs with
an eye to "methodology creep." Sometimes, for example, the troubleshooting of a product will uncover a problem and lead to
additional testing to characterize that problem. The testing can be extended to other products and become institutionalized.
Over time, this approach can become enormously costly.
In-process testing, the third analytical set, must be sensitive enough to detect issues with the product but not oversensitive
and, therefore, prone to indicating a problem where none exists. It should also be genuinely capable of measuring either the
critical quality attributes (CQAs) or the critical process parameters (CPPs). Often, much of the testing embedded in in-process
applications provides information that is nice to know but may not test a particular CQA or CPP.
In assessing the value of a particular in-process methodology, has the methodology ever accurately predicted a failure? If
not, then it might not be genuinely predictive. Has the methodology ever been used to determine the status of a batch and
has it indicated that the batch should go forward or be put on hold or in quarantine? Has the methodology ever been used to
change a batch? If a batch has been put on hold, has the methodology accurately indicated the need to fortify the batch or
do some additional purification?
If the answer to all three questions is no, then one can conduct a risk assessment to determine whether the test really indicates
a CQA or CPP. Further, the concept of "fail early" is a sound principle when it comes to minimizing the costs of, and recovering
from, a failed batch. Sufficient testing during cell culture is cost-effective because it allows a batch to be abandoned due
to contamination, low product expression, OOS growth curves, improper nutrient or gas consumption, or other problems before
committing to the typically much more expensive downstream processing.