Chemistry Reference
In-Depth Information
solvents used, to include solvents such as isopropanol that are too viscous to use in
conventional LC analyses. Many different buffer types and additives are used in
HPLC mobile phases (Table 3.3); however, given the propensity to develop methods
compatible with MS, or to use other evaporative-type detectors (ELSD, CAD), vola-
tile components are most often used.
3.5 metHod optImIzAtIon
During method optimization, the initial set of conditions that has evolved from the
first stages of development can be improved or maximized in terms of selectivity,
resolution, peak shape, efficiency, and run or inject to inject cycle time. When opti-
mizing any method, an attempt should be made to provide analytical figures of merit
or specifications that are required to meet the assay requirements defined at the initial
stages of method development. Results obtained during method development can then
be measured against the desired specifications to determine how optimization should
proceed. A target must be established; without adequate and definitive requirements
or specifications, a method cannot be truly optimized. Evaluating the method against
the predetermined specifications at this early stage should reveal the direction addi-
tional optimization experiments need to take to meet the method specifications.
If the initial analytical data derived from method development appears prom-
ising, it is time to evaluate its performance quantitatively. Initially, most work on
method development and optimization is performed with analytical standards. In
general, the analytical figures of merit generated to evaluate the method are also
derived using standards. The scope of the method evaluation should be broad enough
to include generation of information that is immediately usable for confirmation or
identification of the analyte in any sample, for example, UV or mass spectra. Method
optimization goals include increased sensitivity, peak symmetry and resolution, and
a lack of analyte co-elutions.
As with method development, optimization of the method can follow either of
two general approaches—manual or computer software driven—and the types of
systems and software discussed in Section 3.1 for method development can also be
used for method optimization. The manual approach commonly involves varying
one experimental variable at a time, while holding all others constant, and recording
changes in response. This univariate approach to system optimization is slow, time
consuming, potentially expensive, and may miss the effects between variables (e.g.,
the effects of heat on pH). In the second approach, optimization using computer-
driven software, higher efficiency/throughput can be obtained while experimental
input is minimized. Automated software approaches can be applied to many appli-
cations. In addition, they are capable of significantly reducing the time, energy, and
cost of virtually all instrumental method development, and can be useful to verify
that the optimized method satisfies the stated goals of the method.
Certain general criteria are often considered a part of a “prevalidation” study:
• Chromatographic resolution is adequate.
• Limits of detection or quantitation that provide an adequate signal-to-noise
response.
