Chemistry Reference
In-Depth Information
tAble 5.3
example robustness Factor selection and limits for a gradient method
Factor
limit range (±)
Initial hold time
a
10%-20% of segment time.
Slope and length
The slope is set by the initial %B and the final %B, as well as the gradient length. It
is recommended to adjust the lengths by 10%-20% and allow the slope to vary.
Final hold time
Adjusted according to the last eluting compound and varied accordingly.
Note:
Factors and limits listed here are in addition to many of the factors considered in an isocratic method.
a
It is increasingly common for gradient methods to have an initial hold time to accommodate transfer to
instruments with different dwell volumes.
For any chromatographic run, there are a myriad of results generated. Typical
results investigated for robustness studies include critical pair resolution, efficiency
(N), retention time of the main components, tailing factor, area, height, and quan-
titative results such as amounts. Note that there are different ways of measuring
some of these factors; standard operating procedures (SOPs) or other documentation
should specify how the results were calculated. If a quantitative result is desired, it is
necessary to measure both samples and standards. Replication of the design points
can also improve the estimate of the effects. In addition, it is a good idea to measure
results for multiple peaks, as compounds will respond differently according to their
physicochemical characteristics, for example, ionizable versus neutral compounds
that might be present in the same mixture.
5.4 AnAlyzIng tHe results
Once the design has been chosen, the factors and limits determined, and the chro-
matographic results generated, the real work starts. All of that data must be ana-
lyzed, and at this point, many analytical chemists begin to search out their resident
statistician. Ultimately, the limits uncovered by the robustness study, determined
in the data treatment or observed in the graphs, are used to set system suitability
specifications.
While consulting and collaborating with a good statistician for robustness studies
is always a good idea, there are many tools available to assist the analyst in analyz-
ing the results.
Statistical software is available from a variety of sources. There are add-in
programs for Excel, and popular commercially available software such as SPSS
(Chicago, Illinois or spss.com), JMP (Cary, North Carolina or JMP.com), or Minitab
(State College, Pennsylvania, or minitab.com). Third-party software adds to the vali-
dation process, as it too must be validated.
Chromatography data systems (CDSs) are also available that perform many of
the requisite calculations and reporting for robustness studies [16]. But unlike third-
party software, CDSs have the advantage that the data is traceable, validation need
only be performed once, and the entire audit trail, relational database, reporting, etc.,
