APR Nov/Dec 2022 - 21

« DRUG DEVELOPMENT
in a synthetic route (e.g., closer to a final API step is riskier than
earlier steps), and stage of development or clinical trial (severity of
risk is higher at later stages). Gauges to assess risk severity levels
are defined in Table 1 rows with blue shading. These considerations
or differentiators can be used as a tool for analytical teams to help
assess their analytical risks (see Table 1).
Table 1
Risk Differentiator
Probability
Method type/
complexity/
instrument
Performance/
experience
Stage
Severity
Lower Risks
General and
familiar methods
using common
instruments
Well understood
Early-stage
development
Proximity to API Early-steps
Needs / purpose
Gather
knowledge only
Medium
Risks
Common and/
or simple
methods using
widely available
instruments
Reasonably well
understood
Mid-stage
development
1-2 steps from
API (Quality
control steps)
Control method
Higher Risks
Specific and/or
complex methods
requiring unique
instruments
Not common or
well understood
Late-stage
development
API step
CQA test
Figure 2 helps to visualize the " line of acceptable risk " generated
using complexity of analytical methodology and performance risk
with project stage.7
This highlights that risk tolerance at early stages
is relatively larger and decreases as clinical development progresses,
which Table 1 captures for risk survey assessors. The risk survey
program is designed to meet the early stage needs by performing a
" top down " , holistic analytical control evaluation. Late-stage projects,
however, have much lower tolerance to analytical risks and must be
suitable for routine quality control analysis, which is beyond the scope
of this article.
Covered within these categories are:
* Method types, which can range from stability-indicating
methods to specific trace impurity analysis (e.g., nitrosamines).
* Method analytical target profiles, which are typically linked to
process control limits or release specifications.
* Physicochemical properties that can include presence of UV
chromophores, solubility, hygroscopicity, static nature, etc.
Table 2 lists the most common analytical risk categories we have
encountered to help project teams evaluate soft spots in their
controls and acts as a common check list to drive consistent practices
across teams. Note, some of these categories may overlap, such as
enantiomeric control and chromatographic selectivity.
Risk banding
Risk analysis is the qualitative or quantitative process of measuring the
likelihood of occurrence and severity of harms and must be performed
across each of the identified risk categories. The evaluation of the
harm and potential impact to quality should be based on scientific
knowledge and ultimately link to the protection of the patient.1
In
Figure 2. Acceptable analytical method performance
risk across stages.
Risk categories of early and mid-stage projects
Risk categories are utilized to aid in risk identification. The risk
categories were collated from: molecular structure and related unique
material properties; historical data, as would come from method
transfer experience; ICH guideline requirements, including release
specification guidance; and other drug substance analytical activities.
our analytical group, the risk level of each category is measured by
comparing the analytical method's observed performance to expected
quality and scientific requirements, as well as historical experience. For
example, widely spaced analytes in an isocratic LC method are much
lower risk than a multiple stage gradient LC method just meeting
baseline resolution requirements.
When the observed performance of the method is significantly better
than the regulatory and scientific requirements, the risk level is banded
as " low " . When the performance of the analytical method meets but
approaches the limit of regulatory or scientific expectancy, the risk
level is defined as " medium " . When the performance of analytical
method fails to meet either regulatory or scientific expectancies, the
risk level is defined as " high " . High risk scenarios can occur with rapidly
changing projects and expectations. For example, process changes can
generate entirely new impurity profiles, which may challenge existing
methods. Even a defined process can become high risk if robustness
studies performed near to the risk survey identify gaps (e.g, co-eluting
impurities are found during a peak homogeneity check). Additionally,
acceptable risk in the earliest phase may present as high risk if they are
nearing a transfer or stage transition due to tightening requirements.
Table 3 lists a few illustrative examples of risk banding. Over time, we
have compiled the more common risk categories and criteria across
method type combinations (e.g., LC-UV for organic impurities or GCFID
for residual solvents) to aid analytical teams' assessments. The
selected parameters are generally the more technically challenging
aspects of the method or the more important quality aspects of
the method. For less common category and method combinations,
historical data is evaluated, literature is surveyed, and/or additional
SMEs are consulted.
Implementation of risk surveys
The analytical risk survey was founded on both a scientific and
practical approach for evaluating present and future process control
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APR Nov/Dec 2022

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