The example below demonstrates the required data structure of one record per analyte per replicate per test condition per timepoint to accurately represent data from a stability study. The resulting structure would require 648 rows to illustrate the 12 analytes shown in the example study we received, done in triplicate under two test conditions at the number of timepoints in the example study.
For conciseness, we have abbreviated the examples below to demonstrate the concepts as follows:
First- we show all 12 analytes as a single replicate, at one time point and one test condition in order to illustrate the variables and terminology required to put together a stability study with assays done in replicate at different time points and varying test conditions, even though only one record per analyte is illustrated.
Second-
Shelf life study has a protocol and provides the results of shelf life studies of tobacco products over time with different conditions and analytes. Generally there are many conditions with at least two with varying temperature, humidity, etc.
The initial table shows the a number of the analytes and test conditions used in Shelf Life studies for tobacco products for one testing condition at one timepoint and one replicate.
Row 1:
Shows the LBTEST of Product Moisture which reflects the percentage of moisture in the substance for the condition noted in LBTSTCND which is Condition 1 (X°C/ Z% RH). Product Moisture is sometimes referred to as "Oven Volatiles".
Rows 4, 6, 8
Shows the NNK, NNN, and TSN tests with the tobacco product "as-is" using the LBSPCCND to show that the tobacco is "FRESH".
Rows 5, 7, 9
Shows the NNK, NNN, and TSN tests with the tobacco product as "Dry weight basis (DWB)" using the LBSPCCND to show that the tobacco is "DRIED".
Rows 2-12:
Show the other analytes used in testing (pH, water activity, NNK, NNN, TSNA, etc.) using the LBTEST and LBTESTCD variables.
Row Captions Debug Message
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*DWB=Dry weight basis. The DWB normalizes the results since starting moisture may vary.
Make sure LOQ is in the dataset - it is important. - JON - I meant to ask you about this....
A Shelf Life study dataset would shows analytes done in different test conditions with replicates over time points. In the interest of brevity for this example, only moisture content using the TEST of Product Moisture (also known as Oven Volatile) percentage is shown in a sample of timepoints in two conditions with replicates. The weeks reflective of Week 1, Week 2, Week 3, etc. which would align with the LBTPTNUM of 2,3, etc. are not shown for visual viewing purposes.
Rows 1-9:
Show the LBTEST of Product Moisture for Condition 1 (X°C/ Z% RH) which is shown in LBTSTCND. The sample of various timepoints that may be used in the testing for product moisture is reflected in LBTPT. The LBTPTNUM shows the numerical version of the planned timepoint. The REPNUM shows the incidence number of a test that is repeated within a given timeframe for the same test.
Rows 10-18:
Show the LBTEST of Product Moisture for Condition 2 Condition 2 (A °C/ B %RH) across the same timepoints shown for Condition 1. The LBGRPID is used to tie together a block of related records in a single domain.