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STIMULI TO THE REVISION PROCESS
Stimuli articles do not necessarily reflect the policies
of the USPC or the USP Council of Experts
The Use of Mean
Kinetic
Temperature to Aid Evaluation of Temperature Excursions: Proper and Improper
Application
Chris Anderson,a , b Robert Seevers,a , c Desmond Hunta , d
A BSTRACT This Stimuli article describes the use of mean kinetic temperature (MKT) to evaluate temperature
excursions for shipments of controlled room temperature (CRT) and controlled cold temperature (CCT) pharmaceutical
products. Correct and incorrect uses of MKT are described and supported by examples from actual events. The authors
propose using 30 days to calculate MKT for CRT products and 24 h for controlled cold temperature products, including
excursion time. The objectives of this Stimuli article are to initiate discussion and solicit public comments regarding the new
USP position on how to use MKT to evaluate temperature excursions for the shipment of pharmaceutical drugs.
INTRODUCTION
Temperature excursions happen, although organizations expend a lot of effort to avoid them. Describing the magnitude
of an excursion event as simply a high- or low- temperature event is meaningless without the factor of time. A typical
unplanned excursion has a fluctuation in temperature over a period of time as opposed to a static temperature change.
If the temperature at which the excursion occurred was static over time, it would be a lot easier to evaluate its impact on
product stability.
MEAN
KINETIC
TEMPERATURE
Mean kinetic temperature is a calculation that is considered an isothermal storage temperature that simulates the
non-isothermal effects of storage temperature variation (1). MKT expresses the cumulative thermal stress a drug product
experiences. The use of MKT is considered an acceptable practice for storage and can be considered for excursions during
transit (see Packaging and Storage Requirements ⟨659⟩ ) (2).
The greater the temperature variance of the excursion from the mean , the greater the difference between the
calculated mean and the MKT. The following examples illustrate this point. If a product experiences a low temperature of
29° and a high temperature of 31°, then the calculated mean would be 30° with an MKT of 30.04°. However, if the low
were 20° and the high were 40°, the calculated mean would be 30° and the MKT would be 33.27°. If, instead, the high
were 40° but the low were 30°, the MKT would be 35.85°, 2.58° higher even with the same high temperature as the
previous example. This demonstrates how the variation in the observed temperatures during an excursion can impact the
MKT for a given time period.
Over the years, there have been misunderstandings and misuses of MKT, with the most significant being the use of 52week temperature data to calculate MKT during a temperature excursion. This is problematic because products typically
do not spend 52 weeks in a single location. Thus, the 52-week data used in the MKT calculation would not be a true
reflection of the storage time. This approach skews the results and could potentially lead a company to overlook the impact
of the excursion on the drug product. A closely related concern is the idea that a temperature excursion above a product's
storage temperature can be "fixed" just by lowering the temperature of a warehouse for an appropriate period of time so
that the resulting MKT calculation would provide an acceptable value. This ignores the fact that any degradation due to the
higher temperature is not reversible.
To illustrate this point, two examples of actual events involving CRT are shown here. [ N
(68° –77° F)]
— CRT is defined as 20° –25°
CRT Example 1 (Acceptable 52-Week MKT, Unacceptable Temperatures)
In this example, 52 weeks (365 days) of temperature data were taken from warehouse 1, where temperatures were
recorded every 15 min (see Figure 1). The high temperature and low temperature for a given day were used to calculate
the MKT over the 24-h period. The 52-week MKT was 23.98° (75.16° F), which is within the 20° –25° (68° –77° F) storage
range for CRT products. However, if one looks at the actual temperature data points used (see Table A-1 in Appendix),
there were 175 days with temperatures over 25° (77° F), with day 188 (7/7/2017) being the highest at 33.58° (92.44° F).
The temperature for this single day [with a low of 26.6° (79.88° F)] was outside the storage range for CRT products.
Chapter ⟨659⟩ has an excursion allowance for CRT products of 15° –30° (59° –86° F) with short-term excursions up to 40°,
as long as they are less than 24 h in duration and the MKT is 25° (77° F) or less (2). The single day MKT of 30.7° (87.26°
F) calculated for day 188 does not meet the ⟨659⟩ MKT excursion criteria. As shown in this example, the daily data reveal a
significant problem that is not apparent in the 52-week MKT data (see Figure 1).
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Figure 1. Weekly mean
kinetic
temperature (MKT) for CRT Example 1.
If measuring a 52-week time period is unrealistic, would measuring one day demonstrate the realistic impact of an
excursion on the product? It should be noted that the maximum excursion temperature was within the excursion
allowance of less than 24 h.
A better approach would be to consider the average time that a product spends in a warehouse, which is 30.3 days in the
United States (3). In the following example (Table 1), if a 30-day MKT were calculated from the referenced temperature
at day 188 plus the previous 29 days, the result would be an MKT of 28.98° (84.16° F), which is over 25° (77° F) and is
unacceptable.
Table 1. 30-Day MKTa for CRT Example 1
Temperature (°C)
Temperature (°C)
Temperature (°C)
Dayb
High
Low
Day
High
Low
Day
High
Low
158
24.37
19.58
168
24.19
19.79
178
30.91
23.65
159
22.28
19.56
169
23.69
19.67
179
29.71
22.98
160
23
19.85
170
32.4
25.44
180
29.44
22.84
161
23.5
19.58
171
3210.72
26.01
181
28.49
22.84
162
23.43
18.93
172
31.04
24.61
182
28.64
21.83
163
22
19.34
173
30.52
23.58
183
30.17
22.06
164
22.43
19.54
174
29.6
23.92
184
29.99
23.58
165
22.92
19.56
175
30.98
24.19
185
31.44
24.21
166
23.94
19.34
176
32.27
25.91
186
32
24.83
167
24.92
19.83
177
32.2
27.23
187
33.58
26.6
a MKT calculated for 30 days was 28.98° (84.16° F), which was over 25° (77° F) and therefore unacceptable.
b Day within the 365-day study period.
CRT Example 2 (Acceptable 52-Week MKT, Acceptable Temperatures)
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In this example, 52 weeks (365 days) of temperature data were taken from warehouse 2, where temperature was
recorded every 15 min (see Figure 2). The high temperature and low temperature from each day were used to calculate
the MKT. The 52-week MKT was 22.75° (72.95° F), only 1.23° (2.22° F) lower than CRT Example 1. A review of the 52
weeks of data (see Table 2) showed one single-day excursion temperature of 25.56° (78° F) on day 93 (4/3/2017). If one
calculates a 30-day MKT from day 93 backwards, this provides a 30-day MKT of 23.14° (73.65° F), which falls within the
⟨659⟩ excursion allowance. In this example, any day used to calculate a 30-day MKT provides acceptable results. This
example shows that using a 52-week MKT was not a significant problem because excursions occurred on only one day of the
year and there was an acceptable MKT in any 30-day period.
Figure 2. Weekly mean
kinetic
temperature (MKT) for CRT Example 2.
Table 2. 30-Daya MKT for CRT Example 2
Temperature (°C)
Temperature (°C)
Temperature (°C)
Dayb
High
Low
Day
High
Low
Day
High
Low
64
23.33
21.67
74
22.78
22.22
84
23.33
22.78
65
23.89
21.67
75
23
22.22
85
23.33
22.78
66
23.33
22.78
76
23.33
22.22
86
23.33
22.78
67
24.44
23.33
77
23.33
22.22
87
23.89
22.78
68
23.89
23.33
78
23.33
22.22
88
23.89
23.33
69
23.33
22.78
79
23.89
22.78
89
25
22.78
70
22.78
22.22
80
24.44
22.78
90
23.33
22.78
71
23.33
22.22
81
23.89
22.22
91
22.78
22.78
72
23.89
22.22
82
23.89
22.22
92
24.44
22.78
73
22.78
22.22
83
23.33
22.22
93
25.56
23.33
a MKT calculated for 30 days was 23.14° (73.65° F), which was under 25° (77° F) and therefore acceptable.
b Day within the 365-day study period.
Comparing the Same 30-Day Time Period for CRT Examples 1 and 2
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If one compares the same time frame for both examples, the MKT is unacceptable for CRT Example 1 and acceptable for
CRT Example 2 (see Table 3, Table 4, Table 5, and Table 6). Although CRT Example 1 had a high-end temperature
excursion every day, it should be noted that both sites had an acceptable 52-week MKT.
Table 3. Comparison of 30-Daya Temperature Data for CRT Examples 1 and 2
Example 1
Example 2
30-Day MKT
29.06° (84.31° F)
22.75° (72.95° F)
Highest temperature
33.58° (92.44° F)
23.9° (75° F)
Lowest temperature
21.17° (70.11° F)
21.67° (71° F)
a Days 183–212 within the 365-day study period.
Table 4. 30-Daya Temperature Data for CRT Example 1b
Temperature (°C)
Temperature (°C)
Temperature (°C)
Day
High
Low
Day
High
Low
Day
High
Low
183
28.64
21.83
193
32.54
26.34
203
31.47
25.46
184
30.17
22.06
194
32.38
25.84
204
31.64
25.46
185
30.54
23.58
195
32.61
25.86
205
29.12
25.21
186
31.44
24.21
196
31.84
26.18
206
30.69
24.94
187
32
24.83
197
31.69
26.84
207
31.33
24.39
188
33.58
26.6
198
23.89
25.84
208
31.76
24.83
189
33.36
21.62
199
31.84
25.67
209
31.36
24.83
190
33.72
27.02
200
32.45
26.45
210
30.6
23.96
191
28.64
21.83
201
32.54
26.34
211
31.47
25.46
192
30.17
20.06
202
32.38
25.84
212
31.64
25.46
a Days 183–212 within the 365-day study period.
b The data show daily high excursions and an unacceptable 30-day MKT of 29.06° (83.31° F).
Table 5. 30-Daya Temperature Data for CRT Example 2b
Temperature (°C)
Temperature (°C)
Temperature (°C)
Day
High
Low
Day
High
Low
Day
High
Low
183
23.33
22.22
193
23.33
22.78
203
22.78
22.78
184
23.33
22.22
194
22.78
22.22
204
23.33
22.22
185
23.33
195
22.78
22.22
205
22.78
22.22
186
23.33
22.22
196
22.78
22.22
206
22.78
21.67
187
23.33
22.22
197
23.33
22.22
207
23.33
22.22
188
22.78
22.22
198
23.33
22.22
208
22.78
22.22
189
23.33
21.67
199
23.89
22.78
209
23.33
22.22
190
22.78
22.22
200
23.89
22.78
210
22.78
21.67
191
23.33
22.22
201
23.89
22.78
211
22.78
21.67
192
23.33
22.78
202
23.89
22.78
212
23.33
21.67
22.22
a Days 183–212 within the 365-day study period.
b The data show no excursions and an acceptable 30-day MKT of 22.75° (72.95° F).
As these examples demonstrate, a 52-week MKT for a CRT product should never be used. These examples suggest that a
30-day period, or the average number of days that a product remains in a warehouse, provides a realistic MKT to use in
evaluating storage or shipping excursions, as long as an excursion is no longer than a 24-h period. The only exception to
these excursion limits would be a case where the product manufacturer states otherwise.
CONTROLLED COLD TEMPERATURE
Controlled Cold Excursions and the Use of MKT
The USP 31–NF 26 General Notices definition of controlled cold temperature (2° –8°), which was omitted in 2010,
allowed short-term excursions (less the 24 h) between 0° and 15° (32° –59° F) as long as the MKT did not exceed 8° (46°
F) (4). The issue with this definition was that it allowed an excursion down to 0° (32° F). Freezing can have a negative
effect on the efficacy and expiry of many refrigerated drugs, especially vaccines and proteins. It should be noted that the
freezing point depression in these drugs is not expected to be large enough to protect them at 0°. However, removing the
short-term excursion allowance is problematic, especially for delivery to caregivers.
Thus, refrigerated delivery or qualified passive thermal protection should be used for the shipment of CCT products (see
Good Storage and Distribution Practices for Drug Products ⟨1079⟩ ) (5). Delayed deliveries, delayed receipts, or short-term
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storage failures can and do happen, and a reasonable allowance for documented excursions should be permitted. It is
proposed that acceptable excursions for CCT products are 2° –15° (36° –59° F) for less than 24 h with an MKT of 8° (46° F)
or below. This MKT should moderate any concerns about long periods of exposure to 15° (59° F).
The following examples are taken from actual events.
CCT Example 1: Controlled Cold-Qualified Passive Shipper
A wholesaler had a cold shipper (i.e., passive thermal packaging system) qualified for 30 h, but chose to run the time in
the qualification thermal chambers out for an additional 24 h (a total of 54 h). When a company shipping a controlled
product works with a service provider to design a qualified shipper, they typically look at their maximum delivery times and
add extra time for a buffer. Although over-qualifying a thermal package costs a significant amount of money, transportation
space, and receiving space, a company may run a qualification test out further than the target time to obtain data to
support possible excursions. If a product in a 30-h shipper was delivered in 32 h and there were no data to support the
additional 2 h, the product would be potentially nonsalable. A company needs temperature data to evaluate against
excursion limits or to provide to the product manufacturer for disposition.
In the shipper qualification case described below (see Figure 3), the additional time (24 h) beyond the 30-h qualification
time yielded a total of 54 h with a high temperature of 11° (51.8° F), a low temperature of 3.4° (38.12° F), and an MKT
of 8° (46.4° F). These data meet the proposed criteria for controlled cold temperature excursions. However, if the data
were outside the proposed ranges, the supply chain member would have data within the tested time period to provide the
temperatures and MKT to the manufacturer for disposition. It is important to note that qualification testing should be
completed for the payloads shipped; this means that wholesalers shipping comingled controlled cold products should
complete qualification testing for minimum and maximum payloads as well as environmental seasons for the geography that
they ship to.
An alternative to using a qualified packaging system would be to use calibrated time– temperature monitors. To obtain
adequate data for calculating mean temperature and MKT, temperature monitors would need to collect data in 15-min
increments. Once downloaded, these data would provide access to time, temperature exposures, and MKT. Most time–
temperature monitors will calculate MKT. The calculated MKT should represent the duration of the trip.
Figure 3. Qualification summary for a controlled cold-qualified passive shipper (CCT Example 1). Worst case of the six tests
(three minimum and three maximum payloads) against a summer profile [high temperature of 11° (51.8° F) and an MKT
of 8° (46.5° F)].
CCT Example 2: Controlled Cold Refrigerated Delivery
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CCT EXAMPLE 2A
In this example (Figure 4), a refrigerated trailer making a 72-h delivery went out of controlled cold temperature range
by going above 8° (46° F) at hour 52 to 8.5° (47.3°). The temperature rose 0.27° every hour until delivery at hour 72.
The excursion lasted 22 h (within excursion limits), the maximum temperature was 13.9° (57.02° F) (within excursion
limits), and the MKT was 10.77° (51.39° F) for the last 24 h (outside the excursion MKT limit). In this case, the product
should be quarantined and the manufacturer(s) should be contacted for disposition.
Figure 4 . Qualification summary for controlled cold refrigerated delivery (CCT Example 2A) with MKT outside the excursion
limit. Temperature went above 8° (46° F) at 52 h and continued to rise until delivery at 72 h with a high temperature of
13.9° (57.02° F). MKT for the last 24 h was 10.77° (51.39° F).
CCT EXAMPLE 2B
In this example (Figure 5), the excursion started at hour 63 and delivery occurred at hour 72. Temperature data
revealed that the excursion duration was 10 h (within excursion limits). The maximum temperature was 10.5° (50.9° F)
and the MKT was 7.45° (45.41° F)—both were within excursion limits.
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Figure 5. Qualification summary for controlled cold refrigerated delivery (CCT Example 2B) with MKT within the excursion
limit. Temperature went above 8° (46° F) at hour 63 and the product was delivered at hour 72 with a high temperature
of 10.5° (50.9° F). MKT for the last 24 h was 7.45° (45.41° F).
Table 6. Comparison of 24-h Dataa from CCT Examples 2A and 2B
Example 2A
Example 2B
2-h
Increment
Temperature (°C)
High
Low
1
6.5
5
Temperature (°C)
High
5.2
2
8.5
7
5
5
3
9.04
8.77
5.3
4.9
4
9.58
9.31
5.8
5.6
5
10.12
9.85
6.3
6
6
10.66
10.39
7.1
6.6
7
11.2
10.93
8
7.4
8
11.74
11.47
8.5
8.5
9
12.28
12.01
8.9
8.7
10
12.82
12.55
9.2
9
11
13.36
13.09
9.7
9.4
12
13.09
13.63
10.5
10
MKT = 10.77° (51.39° F)
Low
5.1
MKT = 7.45° (45.41° F)
a The 24-h period includes excursion time.
CONCLUSIONS
This article highlights correct and incorrect applications of MKT to provide some perspective on the proper use of this tool.
Examples from actual cases are provided to alert readers to the consequences of applying MKT inappropriately. The
temperature data presented in this article support the conclusion that a 30-day period, or the average time that a product
spends in a warehouse, should be used to calculate MKT for CRT products. In contrast, for controlled cold temperature
products, a 24-h period should be used, and this time span should include the excursion time.
Factors that can lead to temperature excursions should be identified early in the process, and appropriate mitigation
strategies should be executed to eliminate or reduce the risks of excursions (see ⟨1079⟩ ) (5). In the event of short-term
storage or transportation/delivery excursions, MKT is a helpful tool that can aid in evaluating the impact on drug quality
when used in conjunction with USP excursion limits and product labeling (see ⟨659⟩ ) (2).
APPENDIX
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Table A-1. Original Temperature Data (°F) for CRT Example 1
Temperature
(°F)
Temperature
(°F)
Temperature
(°F)
Date
High
Low
Date
High
Low
Date
High
Low
11/1/2016
71.33
64.7
3/2/2017
72.55
62.58
7/1/2017
83.29
73.11
11/2/2016
74.01
62.28
3/3/2017
73.48
63.25
7/2/2017
83.56
71.29
11/3/2016
77.57
68.58
3/4/2017
69.66
64.07
7/3/2017
86.3
71.7
11/4/2016
77.27
67.44
3/5/2017
67.18
64.51
7/4/2017
85.98
74.45
11/5/2016
75.35
66.66
3/6/2017
69.03
61.5
7/5/2017
88.6
75.58
11/6/2016
73.67
65.1
3/7/2017
72.67
61.95
7/6/2017
89.6
76.7
11/7/2016
75.76
64.4
3/8/2017
76.48
64.62
7/7/2017
92.45
79.88
11/8/2016
78.59
66.81
3/9/2017
77.49
66.36
7/8/2017
92.04
81.71
11/9/2016
80.03
69.44
3/10/2017
76.14
67.47
7/9/2017
90.45
80.64
11/10/2016
79.08
68.62
3/11/2017
76.25
67.33
7/10/2017
91.75
81.52
11/11/2016
78.78
68.51
3/12/2017
77.53
67.51
7/11/2017
91.34
80.53
11/12/2016
75.2
68.51
3/13/2017
78.78
67.62
7/12/2017
90.57
79.42
11/13/2016
76.1
67.81
3/14/2017
78.63
67.25
7/13/2017
90.28
78.51
11/14/2016
77.91
67.62
3/15/2017
79.19
68.18
7/14/2017
90.69
78.55
11/15/2016
76.06
67.18
3/16/2017
78.66
67.44
7/15/2017
89.32
79.12
11/16/2016
72.93
65.77
3/17/2017
78.66
67.25
7/16/2017
89.04
78.51
11/17/2016
71.22
62.8
3/18/2017
75.88
67.1
7/17/2017
89.8
78.51
11/18/2016
71.33
60.42
3/19/2017
76.1
67.33
7/18/2017
89.32
78.21
11/19/2016
67.92
60.01
3/20/2017
75.88
67.25
7/19/2017
90.41
79.61
11/20/2016
67.47
62.36
3/21/2017
72.11
67.21
7/20/2017
91.01
78.82
11/21/2016
68.4
62.62
3/22/2017
73.41
67.73
7/21/2017
89.8
77.3
11/22/2016
68.51
60.2
3/23/2017
74.34
67.25
7/22/2017
88.64
77.83
11/23/2016
69.07
60.42
3/24/2017
74.19
66.07
7/23/2017
88.96
77.83
11/24/2016
67.99
60.2
3/25/2017
71.62
66.81
7/24/2017
84.42
77.38
11/25/2016
69.21
60.05
3/26/2017
72.37
67.18
7/25/2017
87.24
76.89
11/26/2016
64.7
60.2
3/27/2017
73.26
67.21
7/26/2017
88.4
75.91
11/27/2016
62.88
61.17
3/28/2017
75.09
66.81
7/27/2017
89.16
76.7
11/28/2016
64.81
59.97
3/29/2017
76.85
67.7
7/28/2017
88.44
76.7
11/29/2016
65.85
60.79
3/30/2017
75.54
67.62
7/29/2017
87.08
75.13
11/30/2016
66.5
59.9
3/31/2017
74.64
67.4
7/30/2017
86.37
74.79
12/1/2016
66.22
60.46
4/1/2017
74.6
66.22
7/31/2017
88.4
75.28
12/2/2016
64.25
60.61
4/2/2017
75.54
67.36
8/1/2017
86.45
83.76
12/3/2016
64.73
60.23
4/3/2017
74.68
68.07
8/2/2017
88.64
81.25
12/4/2016
66.33
60.72
4/4/2017
77.42
67.77
8/3/2017
92.53
82.1
12/5/2016
66.84
60.5
4/5/2017
78.7
67.44
8/4/2017
91.79
80.45
12/6/2016
66.18
60.72
4/6/2017
78.06
67.36
8/5/2017
89.2
77.87
12/7/2016
66.36
60.16
4/7/2017
76.59
67.1
8/6/2017
87.88
76.36
12/8/2016
66.66
60.01
4/8/2017
73.75
67.4
8/7/2017
88.48
76.59
12/9/2016
66.1
60.08
4/9/2017
73.89
66.51
8/8/2017
89.92
77.12
12/10/2016
64.88
60.27
4/10/2017
76.4
66.73
8/9/2017
89.12
76.48
12/11/2016
65.36
61.43
4/11/2017
76.21
67.62
8/10/2017
89.28
76.82
12/12/2016
67.55
61.65
4/12/2017
76.48
67.33
8/11/2017
89.56
77.23
12/13/2016
67.96
61.32
4/13/2017
75.2
67.4
8/12/2017
88.12
76.78
12/14/2016
68.03
59.79
4/14/2017
75.24
67.18
8/13/2017
86.22
74.04
12/15/2016
66.18
59.75
4/15/2017
75.28
67.14
8/14/2017
85.82
74.83
12/16/2016
63.77
60.16
4/16/2017
76.18
67.7
8/15/2017
83.87
73.97
12/17/2016
62.84
59.07
4/17/2017
77.15
67.62
8/16/2017
84.18
73.15
12/18/2016
61.58
57.01
4/18/2017
77.12
69.07
8/17/2017
84.65
73
12/19/2016
64.66
57.72
4/19/2017
78.02
67.88
8/18/2017
85.31
74.01
12/20/2016
66.03
57.65
4/20/2017
78.7
67.18
8/19/2017
84.42
73.48
12/21/2016
64.33
61.39
4/21/2017
81.9
67.18
8/20/2017
83.52
72.81
12/22/2016
64.44
61.76
4/22/2017
82.02
70.21
8/21/2017
84.11
73.11
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2019/9/11
44(4) Stimuli to the Revision Process: The Use of Mean Kinetic Temperature to Aid Evaluation of Temperature Excursions: Proper a…
Temperature
(°F)
Temperature
(°F)
Temperature
(°F)
Date
High
Low
Date
High
Low
Date
High
Low
12/23/2016
65.29
62.25
4/23/2017
80.22
70.1
8/22/2017
85.47
72.44
12/24/2016
63.73
60.76
4/24/2017
75.5
68.21
8/23/2017
84.88
74.08
12/25/2016
61.32
57.23
4/25/2017
75.61
67.4
8/24/2017
84.61
74.01
12/26/2016
60.72
56.93
4/26/2017
77.76
67.4
8/25/2017
84.81
72.81
12/27/2016
64.77
56.74
4/27/2017
77.46
71.88
8/26/2017
85.47
73.48
12/28/2016
67.44
58.32
4/28/2017
80.37
67.7
8/27/2017
86.06
75.31
12/29/2016
68.18
59.56
4/29/2017
77.83
69.47
8/28/2017
89.56
85
12/30/2016
65.73
62.66
4/30/2017
79.57
66.92
8/29/2017
92.49
82.71
12/31/2016
63.55
61.21
5/1/2017
81.98
67.96
8/30/2017
93.52
82.64
1/1/2017
62.17
59.07
5/2/2017
83.02
70.14
8/31/2017
95.23
84.77
1/2/2017
62.17
59.97
5/3/2017
83.91
70.96
9/1/2017
95.23
84.92
1/3/2017
62.69
59.04
5/4/2017
84.18
71.4
9/2/2017
93.81
85.78
1/4/2017
63.81
58.32
5/5/2017
80.26
69.81
9/3/2017
94.02
84.34
1/5/2017
64.18
61.32
5/6/2017
71.88
67.07
9/4/2017
89.16
81.52
1/6/2017
66.51
61.35
5/7/2017
71.48
67.59
9/5/2017
89.56
78.63
1/7/2017
64.66
60.83
5/8/2017
75.95
66.59
9/6/2017
89.68
79.99
1/8/2017
66.59
60.94
5/9/2017
76.97
67.44
9/7/2017
89.24
77.68
1/9/2017
65.51
62.92
5/10/2017
73.19
67.66
9/8/2017
88.4
77.72
1/10/2017
64.73
62.28
5/11/2017
79.16
67.55
9/9/2017
85.31
75.5
1/11/2017
66.33
62.66
5/12/2017
78.59
67.03
9/10/2017
87.2
76.74
1/12/2017
64.4
62.43
5/13/2017
76.29
67.18
9/11/2017
89.48
79.27
1/13/2017
65.47
61.5
5/14/2017
76.51
66.99
9/12/2017
88.6
78.74
1/14/2017
65.77
60.46
5/15/2017
70.14
67.14
9/13/2017
85.51
75.69
1/15/2017
64.88
60.2
5/16/2017
72.07
67.77
9/14/2017
80.3
72.59
1/16/2017
66.29
61.24
5/17/2017
69.84
67.92
9/15/2017
80.56
73.15
1/17/2017
66.59
60.76
5/18/2017
76.59
66.7
9/16/2017
80.91
72
1/18/2017
64.66
60.2
5/19/2017
80.45
67.44
9/17/2017
79.99
72.07
1/19/2017
65.25
61.69
5/20/2017
81.25
68.81
9/18/2017
81.06
70.07
1/20/2017
63.81
61.65
5/21/2017
82.64
71.36
9/19/2017
80.95
72.52
1/21/2017
62.58
59.34
5/22/2017
84.61
72.03
9/20/2017
79.27
72.22
1/22/2017
61.43
59.79
5/23/2017
84.53
72.44
9/21/2017
77.49
70.14
1/23/2017
60.64
59.41
5/24/2017
82.44
71.4
9/22/2017
77.49
66.84
1/24/2017
62.73
57.31
5/25/2017
79.01
69.07
9/23/2017
76.1
65.96
1/25/2017
63.06
57.19
5/26/2017
79.23
68.21
9/24/2017
77.15
65.47
1/26/2017
63.25
56.89
5/27/2017
78.93
67.44
9/25/2017
79.54
68.07
1/27/2017
62.73
57.53
5/28/2017
80.03
67.07
9/26/2017
80.26
68.88
1/28/2017
65.1
59.07
5/29/2017
79.54
70.99
9/27/2017
81.25
73.71
1/29/2017
66.22
58.77
5/30/2017
79.19
68.62
9/28/2017
82.94
70.77
1/30/2017
69.58
60.12
5/31/2017
75.76
69.25
9/29/2017
83.33
71.92
1/31/2017
69.47
61.35
6/1/2017
78.36
68.58
9/30/2017
81.1
71.51
2/1/2017
69.07
61.43
6/2/2017
81.83
67.77
10/1/2017
79.19
70.81
2/2/2017
67.59
61.61
6/3/2017
81.41
70.1
10/2/2017
79.35
70.21
2/3/2017
65.88
63.21
6/4/2017
81.02
69.58
10/3/2017
78.13
69.58
2/4/2017
66.47
63.66
6/5/2017
81.71
69.7
10/4/2017
78.66
67.44
2/5/2017
64.7
62.66
6/6/2017
80.15
70.59
10/5/2017
79.8
67.14
2/6/2017
64.21
62.32
6/7/2017
80.49
70.47
10/6/2017
81.21
68.4
2/7/2017
65.73
63.06
6/8/2017
80.07
70.1
10/7/2017
80.91
70.07
2/8/2017
70.07
64.36
6/9/2017
80.03
67.81
10/8/2017
79.23
68.99
2/9/2017
72.89
64.62
6/10/2017
78.82
69.84
10/9/2017
78.51
69.81
2/10/2017
69.03
65.85
6/11/2017
76.93
68.1
10/10/2017
80.26
67.81
2/11/2017
68.81
65.77
6/12/2017
78.44
66.44
10/11/2017
79.16
68.77
2/12/2017
68.81
63.77
6/13/2017
80.49
67.29
10/12/2017
77.76
68.55
2/13/2017
71.4
63.92
6/14/2017
83.06
69.84
10/13/2017
77.72
67.18
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9/13
2019/9/11
44(4) Stimuli to the Revision Process: The Use of Mean Kinetic Temperature to Aid Evaluation of Temperature Excursions: Proper a…
Temperature
(°F)
Temperature
(°F)
Temperature
(°F)
Date
High
Low
Date
High
Low
Date
High
Low
2/14/2017
71.81
65.18
6/15/2017
85.04
71.85
10/14/2017
76.4
66.73
2/15/2017
72.89
64.51
6/16/2017
86.77
73.82
10/15/2017
82.33
73.52
2/16/2017
71.25
64.96
6/17/2017
86.14
74.87
10/16/2017
79.65
71.62
2/17/2017
68.84
66.33
6/18/2017
86.06
74.75
10/17/2017
76.78
70.29
2/18/2017
67.73
64.4
6/19/2017
88.52
76.4
10/18/2017
75.43
66.18
2/19/2017
66.44
64.36
6/20/2017
90.32
77.79
10/19/2017
76.97
66.73
2/20/2017
69.25
64.07
6/21/2017
90.89
78.82
10/20/2017
81.87
70.96
2/21/2017
70.21
65.7
6/22/2017
87.88
76.29
10/21/2017
86.06
79.65
2/22/2017
69.88
65.36
6/23/2017
86.93
74.45
10/22/2017
87.24
80.18
2/23/2017
68.99
63.47
6/24/2017
85.28
75.05
10/23/2017
84.34
74.87
2/24/2017
68.21
61.54
6/25/2017
87.76
75.54
10/24/2017
82.83
72.41
2/25/2017
66.59
61.35
6/26/2017
90.08
78.63
10/25/2017
79.95
70.59
2/26/2017
64.59
62.21
6/27/2017
89.96
81.02
10/26/2017
76.4
68.4
2/27/2017
63.7
61.65
6/28/2017
87.64
74.57
10/27/2017
74.87
69.1
2/28/2017
68.14
61.13
6/29/2017
85.47
73.37
10/28/2017
74.6
68.44
3/1/2017
68.99
60.98
6/30/2017
85
73.11
—
—
—
www.usppf.com/pf/pub/index.html
10/13
2019/9/11
44(4) Stimuli to the Revision Process: The Use of Mean Kinetic Temperature to Aid Evaluation of Temperature Excursions: Proper a…
Table A-2. Original Temperature Data for CRT Example 2
Temperature
(°F)
Temperature
(°F)
Temperature
(°F)
Date
High
Low
Date
High
Low
Date
High
Low
11/1/2016
75
73
3/3/2017
74
71
7/3/2017
74
72
11/2/2016
77
74
3/4/2017
73
71
7/4/2017
74
72
11/3/2016
76
75
3/5/2017
74
71
7/5/2017
74
72
11/4/2016
76
73
3/6/2017
75
71
7/6/2017
74
72
11/5/2016
75
73
3/7/2017
74
73
7/7/2017
73
72
11/6/2016
74
74
3/8/2017
76
74
7/8/2017
74
71
11/7/2016
75
73
3/9/2017
75
74
7/9/2017
73
72
11/8/2016
76
73
3/10/2017
74
73
7/10/2017
74
72
11/9/2016
76
74
3/11/2017
73
72
7/11/2017
74
73
11/10/2016
76
73
3/12/2017
74
72
7/12/2017
74
73
11/11/2016
76
73
3/13/2017
75
72
7/13/2017
73
72
11/12/2016
75
73
3/14/2017
73
72
7/14/2017
73
72
11/13/2016
75
73
3/15/2017
73
72
7/15/2017
73
72
11/14/2016
76
73
3/16/2017
73
72
7/16/2017
74
72
11/15/2016
75
74
3/17/2017
74
72
7/17/2017
74
72
11/16/2016
75
74
3/18/2017
74
72
7/18/2017
75
73
11/17/2016
76
74
3/19/2017
74
72
7/19/2017
75
73
11/18/2016
76
74
3/20/2017
75
73
7/20/2017
75
73
11/19/2016
76
74
3/21/2017
76
73
7/21/2017
75
73
11/20/2016
74
73
3/22/2017
75
72
7/22/2017
73
73
11/21/2016
74
73
3/23/2017
75
72
7/23/2017
74
72
11/22/2016
74
73
3/24/2017
74
72
7/24/2017
73
72
11/23/2016
74
73
3/25/2017
74
73
7/25/2017
73
71
11/24/2016
74
73
3/26/2017
74
73
7/26/2017
74
72
11/25/2016
74
73
3/27/2017
74
73
7/27/2017
73
72
11/26/2016
74
73
3/28/2017
75
73
7/28/2017
74
72
11/27/2016
74
73
3/29/2017
75
74
7/29/2017
73
71
11/28/2016
74
73
3/30/2017
77
73
7/30/2017
73
71
11/29/2016
74
73
3/31/2017
74
73
7/31/2017
74
71
11/30/2016
75
74
4/1/2017
73
73
8/1/2017
73
72
12/1/2016
76
74
4/2/2017
76
73
8/2/2017
73
72
12/2/2016
75
73
4/3/2017
78
74
8/3/2017
73
72
12/3/2016
74
73
4/4/2017
74
71
8/4/2017
73
71
12/4/2016
74
73
4/5/2017
73
71
8/5/2017
72
71
12/5/2016
73
72
4/6/2017
72
71
8/6/2017
73
71
12/6/2016
74
73
4/7/2017
74
71
8/7/2017
73
71
12/7/2016
74
73
4/8/2017
74
71
8/8/2017
72
71
12/8/2016
74
73
4/9/2017
76
71
8/9/2017
73
71
12/9/2016
74
72
4/10/2017
74
73
8/10/2017
73
72
12/10/2016
73
72
4/11/2017
75
73
8/11/2017
73
71
12/11/2016
73
71
4/12/2017
75
73
8/12/2017
73
71
12/12/2016
74
72
4/13/2017
75
72
8/13/2017
73
71
12/13/2016
74
73
4/14/2017
76
71
8/14/2017
73
71
12/14/2016
74
72
4/15/2017
74
72
8/15/2017
74
71
12/15/2016
73
72
4/16/2017
74
72
8/16/2017
73
71
12/16/2016
72
71
4/17/2017
74
73
8/17/2017
73
72
12/17/2016
72
71
4/18/2017
75
72
8/18/2017
73
71
12/18/2016
74
72
4/19/2017
75
71
8/19/2017
73
71
12/19/2016
73
71
4/20/2017
75
72
8/20/2017
73
71
12/20/2016
73
71
4/21/2017
73
71
8/21/2017
73
71
12/21/2016
74
72
4/22/2017
71
70
8/22/2017
73
72
12/22/2016
74
72
4/23/2017
75
69
8/23/2017
73
72
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11/13
2019/9/11
44(4) Stimuli to the Revision Process: The Use of Mean Kinetic Temperature to Aid Evaluation of Temperature Excursions: Proper a…
Temperature
(°F)
Temperature
(°F)
Temperature
(°F)
Date
High
Low
Date
High
Low
Date
High
Low
12/23/2016
74
73
4/24/2017
75
71
8/24/2017
73
72
12/24/2016
73
73
4/25/2017
73
71
8/25/2017
74
71
12/25/2016
74
72
4/26/2017
72
71
8/26/2017
73
71
12/26/2016
73
71
4/27/2017
75
72
8/27/2017
73
71
12/27/2016
75
73
4/28/2017
75
73
8/28/2017
73
71
12/28/2016
74
73
4/29/2017
75
73
8/29/2017
73
71
12/29/2016
73
72
4/30/2017
75
72
8/30/2017
73
71
12/30/2016
73
72
5/1/2017
73
72
8/31/2017
73
71
12/31/2016
73
72
5/2/2017
73
72
9/1/2017
73
71
1/1/2017
74
72
5/3/2017
75
71
9/2/2017
73
71
1/2/2017
73
72
5/4/2017
77
72
9/3/2017
73
71
1/3/2017
73
73
5/5/2017
74
72
9/4/2017
72
71
1/4/2017
74
73
5/6/2017
74
72
9/5/2017
73
71
1/5/2017
73
72
5/7/2017
75
72
9/6/2017
73
71
1/6/2017
73
72
5/8/2017
74
72
9/7/2017
72
71
1/7/2017
72
71
5/9/2017
74
71
9/8/2017
73
71
1/8/2017
72
71
5/10/2017
76
72
9/9/2017
74
71
1/9/2017
72
71
5/11/2017
75
73
9/10/2017
73
72
1/10/2017
72
71
5/12/2017
75
72
9/11/2017
73
72
1/11/2017
75
72
5/13/2017
73
72
9/12/2017
74
71
1/12/2017
75
73
5/14/2017
72
71
9/13/2017
73
71
1/13/2017
75
73
5/15/2017
73
71
9/14/2017
73
71
1/14/2017
73
71
5/16/2017
74
72
9/15/2017
73
71
1/15/2017
73
72
5/17/2017
76
73
9/16/2017
73
71
1/16/2017
73
71
5/18/2017
76
73
9/17/2017
73
71
1/17/2017
74
72
5/19/2017
75
73
9/18/2017
73
71
1/18/2017
73
73
5/20/2017
76
72
9/19/2017
72
71
1/19/2017
74
72
5/21/2017
76
72
9/20/2017
72
71
1/20/2017
74
73
5/22/2017
74
71
9/21/2017
72
71
1/21/2017
75
73
5/23/2017
73
71
9/22/2017
72
71
1/22/2017
74
73
5/24/2017
74
71
9/23/2017
72
71
1/23/2017
73
72
5/25/2017
72
72
9/24/2017
73
71
1/24/2017
73
72
5/26/2017
73
71
9/25/2017
73
71
1/25/2017
74
72
5/27/2017
75
71
9/26/2017
74
71
1/26/2017
74
73
5/28/2017
74
71
9/27/2017
73
72
1/27/2017
74
73
5/29/2017
72
71
9/28/2017
74
72
1/28/2017
73
72
5/30/2017
74
71
9/29/2017
73
71
1/29/2017
73
72
5/31/2017
73
72
9/30/2017
73
71
1/30/2017
74
72
6/1/2017
74
71
10/1/2017
72
71
1/31/2017
74
71
6/2/2017
74
71
10/2/2017
72
70
2/1/2017
75
74
6/3/2017
73
71
10/3/2017
72
71
2/2/2017
76
74
6/4/2017
73
71
10/4/2017
73
71
2/3/2017
75
73
6/5/2017
72
72
10/5/2017
73
71
2/4/2017
75
74
6/6/2017
72
72
10/6/2017
74
71
2/5/2017
75
74
6/7/2017
74
72
10/7/2017
73
71
2/6/2017
76
74
6/8/2017
74
72
10/8/2017
73
71
2/7/2017
75
74
6/9/2017
74
71
10/9/2017
72
71
2/8/2017
76
74
6/10/2017
73
71
10/10/2017
72
71
2/9/2017
75
73
6/11/2017
74
72
10/11/2017
73
72
2/10/2017
74
73
6/12/2017
76
72
10/12/2017
72
71
2/11/2017
74
74
6/13/2017
77
72
10/13/2017
73
71
2/12/2017
74
73
6/14/2017
73
72
10/14/2017
73
71
2/13/2017
74
74
6/15/2017
73
71
10/15/2017
72
71
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2019/9/11
44(4) Stimuli to the Revision Process: The Use of Mean Kinetic Temperature to Aid Evaluation of Temperature Excursions: Proper a…
Temperature
(°F)
Temperature
(°F)
Temperature
(°F)
Date
High
Low
Date
High
Low
Date
High
Low
2/14/2017
75
74
6/16/2017
73
71
10/16/2017
72
71
2/15/2017
75
74
6/17/2017
73
71
10/17/2017
72
71
2/16/2017
75
74
6/18/2017
74
71
10/18/2017
73
70
2/17/2017
75
74
6/19/2017
73
72
10/19/2017
73
71
2/18/2017
75
74
6/20/2017
73
72
10/20/2017
73
71
2/19/2017
75
74
6/21/2017
73
72
10/21/2017
72
71
2/20/2017
75
72
6/22/2017
74
71
10/22/2017
73
71
2/21/2017
74
71
6/23/2017
74
72
10/23/2017
72
71
2/22/2017
75
72
6/24/2017
74
72
10/24/2017
72
71
2/23/2017
76
72
6/25/2017
73
72
10/25/2017
72
71
2/24/2017
77
74
6/26/2017
73
71
10/26/2017
72
71
2/25/2017
77
74
6/27/2017
73
71
10/27/2017
73
71
2/26/2017
74
72
6/28/2017
74
71
10/28/2017
73
71
2/27/2017
74
71
6/29/2017
73
72
10/29/2017
72
70
2/28/2017
75
72
6/30/2017
74
72
10/30/2017
71
71
3/1/2017
75
73
7/1/2017
74
72
10/31/2017
72
71
3/2/2017
75
72
7/2/2017
74
72
—
—
—
REFERENCES
1. Seevers RH, Hofer J, Harber P, Ulrich DA, Bishara R. The use of mean kinetic temperature (MKT) in the
handling, storage, and distribution of temperature sensitive pharmaceuticals. Pharmaceutical Outsourcing.
2009;10(3):30–39.
2. USP. Packaging and Storage Requirements ⟨659⟩ . In: USP 41–NF 36. Rockville, MD: USP; 2017:529–534.
3. Center for Healthcare Supply Chain Research. Factbook: The Facts, Figures and Trends in Healthcare (2015–2016).
86th ed. Arlington, VA: Center for Healthcare Supply Chain Research; 2016:15.
4. USP. General Notices. In: USP 31–NF 26. Rockville, MD: USP; 2008:10.
5. USP. Good Storage and Distribution Practices for Drug Products ⟨1079⟩ . In: USP 40–NF 35. Rockville, MD: USP;
2017:1242–1252. New title proposed in PF 44(4) [July–Aug. 2018]: Risks and Mitigation Strategies for the Storage
and Transportation of Finished Drug Products ⟨1079⟩ .
a Packaging and Distribution Expert Committee. The authors did not declare any perceived or actual conflicts of interest related to the
subject matter of this Stimuli article. The views presented in this article do not necessarily reflect those of the organizations for which
the authors work. No official support or endorsement by these organizations is intended or should be inferred.
b Director, Quality Systems, Cardinal Health.
c Senior Advisor, Pearl Pathways.
d Correspondence should be addressed to: Desmond Hunt, PhD, Principal Scientific Liaison, US Pharmacopeial Convention, 12601
Twinbrook Parkway, Rockville, MD, 20852-1790; tel +1.301.816.8341; email: dgh@usp.org.
www.usppf.com/pf/pub/index.html
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