![Page 1: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/1.jpg)
48 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
in non-sterile pharmaceutical preparationsA. Palicz, A. Paul, A. Hofmann, K. Denzel1
ABSTRACTThe SimPlate method was developed and validated for determining microbial count in order to record possible microbial contamination in non-sterile pharmaceutical preparations according to the European Pharmacopoeia (Ph. Eur.). In blank solutions, the validation results showed that the performance of the SimPlate method was in a similar range (between 1 cell to over 106 cells) or better than that obtained with the European Pharmacopoeia pour-plate method. According to the data, the SimPlate method was sufficiently accurate, specific, linear, repeatable and robust to determine the total aerobic microbial count (TAMC, e.g. Pseudomonas aeruginosa, Staphylococcus aureus) and total combined yeast/mould count (TYMC, e.g. Candida albicans, Aspergillus brasiliensis) in the solutions compared to the pour-plate method. Further development demonstrated the interchangeability of the SimPlate method and the pharmacopoeial pour-plate method for the determination of TAMC and TYMC in non-sterile pharmaceutical preparations. A dilution of 1:100 of Mycobacterium phlei e volumine cellulae in NaCl-peptone buffer showed comparable results between the SimPlate method and the pour-plate method for the detection of TAMC and TYMC with a detection limit of 100 CFU/g. Optimal incubation time was found to be between 24-28 h for TAMC and 3 days for TYMC. The microbial count of samples with and without Mycobacterium phlei e volumine cellulae differed by not more than a factor of 2 in accordance with the European Pharmacopoeia. Compared with the pharmacopoeial pour-plate method, the recovery of micro-organisms with the SimPlate method was mostly higher, and never lower (from factor 1 to factor 3). The selected method for the determination of microbial counts was suitable to record possible microbial contamination in Mycobacterium phlei e volumine cellulae extract and showed good correlation with the European Pharmacopoeia pour-plate method. This result opens further applicability for the use of the SimPlate method to determine possible microbial contamination in other non-sterile pharmaceutical preparations.
KEYWORDSTAMC, TYMC, non-sterile pharmaceutical preparations
1. INTRODUCTIONThe microbiological quality of non-sterile pharmaceutical preparations has to meet strict criteria to ensure a low bioburden of finished dosage forms by implementing current guidelines on Good Manufacturing Practice (GMP) during the manufacture, storage and distribution of pharmaceutical preparations. The microbial examination of non-sterile pharmaceutical preparations (enumeration test, specification) has to be performed according to the methods given in general chapters 2.6.12 and 2.6.13 of the European Pharmacopoeia (Ph. Eur.) [1,2].
1 A. Palicz, A. Paul, A. Hofmann, K. Denzel, Phytos Labor für Analytik von Arzneimitteln GmbH & Co. KG, Leibnizstraße 9, 89231 Neu-Ulm, Germany (corresponding author’s email: [email protected]).
![Page 2: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/2.jpg)
Pharmeuropa Bio&SN | February 2016 49
The pour-plate method is often the conventional method of choice for the precise and accurate enumeration of microbial counts in non-sterile pharmaceutical preparations.
To provide simpler, faster and also material-efficient microbial enumeration tests for non-sterile pharmaceutical preparations, the applicability of the SimPlate method was tested. This method is mostly used to determine the most probable number of aerobic micro-organisms in water and foods and is based on a Binary Detection System Technology (BDT) which equates the presence of TAMC and TYMC to the presence of a colour change in the medium [3,4].
There are several reports available which compare the performance of the SimPlate method with the pour-plate method for the microbial enumeration in food and water samples [5-8]. The results of the study by Stillings et al. [5] indicate that the SimPlate method gave results for heterotrophic bacteria in water samples (n = 136) comparable to those of the United States Environmental Protection Agency-approved pour-plate method (plate count agar). The authors suggest that the SimPlate method, due to its ease of use, might provide a good alternative for enumerating heterotrophic bacteria in water samples. Similar results were found by Jackson et al. [9]. The multidose SimPlate method gave a significantly higher count on average than the pour-plate method (Yeast Extract Agar) in the quantification of heterotrophic micro-organisms in water [7]. According to the results, the SimPlate method must be used at 35-37 °C for 48 h. The SimPlate method was easier to handle and read than the pour-plate method. The SimPlate method was also shown to be a suitable and sensitive alternative to the plate count agar method (pour-plate method) for the detection and quantification of food-borne bacteria in 255 food samples representing 15 different food matrices [8].
In a comparative study between the SimPlate method and the pour-plate method (Tryptone Soya Agar) for the enumeration of Escherichia coli on swab samples (n = 588) from beef and lamb carcasses, 270 samples (46 %) were found positive for E. coli by at least one of the methods. Forty-five samples (8 %) were positive only with the SimPlate method, while 28 samples (5 %) were positive only with the pour-plate method. A Cohen’s kappa value (0.74) of the detection/non-detection results showed a high level of agreement between the two methods [10]. The E. coli counts determined by the pour-plate method showed a high concordance correlation with the most probable numbers obtained with the SimPlate method. The SimPlate method was reliable, simple and rapid for the detection of E. coli in these samples. Also the results with the SimPlate method were highly correlated with the results obtained with other test methods (pour-plate method [plate count agar]; Petrifilm aerobic count plates, Redigel total count) for enumerating aerobic micro-organisms in foods [11]. The SimPlate method had a higher counting range requiring fewer dilutions of samples compared to the other methods evaluated. Some foods however, e.g. raw liver, wheat flour and nuts, contain enzymes that give a false-positive reaction on SimPlates. The authors concluded that the SimPlate method is a suitable alternative to the conventional pour-plate method, Petrifilm plate method and Redigel total count method for estimating populations of mesophilic aerobic micro-organisms in a wide range of foods. On the other hand, the SimPlate method failed to detect yeast and moulds in 10 of 42 samples (i.e. 23.8 %) of part-skim mozzarella cheese in a comparative study with the pour-plate (potato dextrose agar plus chlortetracycline), spread plate (dichloran rose Bengal chloramphenicol), Petrifilm and Iso-Grid hydrophobic grid-membrane filtration methods [6].
According to the Ph. Eur. [1] the method chosen for the enumeration of microbial content of non-sterile pharmaceutical preparations must allow testing of a sufficient sample size to judge compliance with the specifications. The suitability of the method chosen must be established. The aim of the present study was to establish the use of the SimPlate method as a faster, simpler and also material-efficient alternative to the pour-plate method for the detection and enumeration of TAMC and TYMC in non-sterile pharmaceutical preparations.
![Page 3: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/3.jpg)
50 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
2. MATERIALS AND METHODS
2.1. ReagentsNaCl for microbiology (Sigma-Aldrich, Germany), NaCl- buffer for microbiology (Merck, Germany), deionised water (Milli-Q Gradient ZMQS5V001 by Millipore, Germany), CASO-agar and Sabouraud-agar (Ph. Eur. / USP – ready to use, Heipha, Germany), TPC-CI medium, TPC-FI medium, Y&M-CI medium, Supplement A and M (ready to use, Coring Systems, Germany), Mycobacterium phlei e volumine cellulae extract (aqueous digestion of cell walls, Sanum Kehlbeck GmbH & Co. KG, Germany).
2.2. Test-organismsPseudomonas aeruginosa (ATCC 9027), Staphylococcus aureus (ATCC 6538), Escherichia coli (ATCC 8739), Bacillus subtilis (ATCC 6633), Salmonella enterica (NCTC 6017), Candida albicans (ATCC 10231) and Aspergillus brasiliensis (ATCC 16404) (all from DSMZ Brunswick, Germany). Inocula of Staphylococcus aureus, E. coli, Pseudomonas aeruginosa, Candida albicans and Salmonella enterica were freshly prepared. Inocula of Bacillus subtilis and Aspergillus brasiliensis were prepared from spore stock solutions. The number of colony-forming units (CFU) in the inoculum was determined by the pour-plate method. When necessary, the titre was adjusted prior to the inoculation of the sample. A volume was used resulting in a calculated CFU <100 per petri dish/SimPlate-dish (Ph. Eur. [1]).
2.3. MaterialsPipettes: Piston-Stroke pipettes 200-1000 µL, 10-100 µL (Biohit, Germany); 10-100 µL (Roth, Germany), 10 - 100 µL (Eppendorf, Germany); Incubators: climacell 707 (qualified 33 °C, MMM medcenter, Czech Republic), type FSK 2600 (qualified to 22 °C, Liebherr, Germany); sterile petri-dishes (Sarstedt, Germany), sterile SimPlate devices (SimPlate is a registered trademark of BioControl systems Inc., USA), serological pipette (Sarstedt, Germany).
2.4. SimPlate method TPC-CI and Y&M-CI media were resuspended in 0.9 % physiological saline solution. In the case of Y&M-CI medium, the 0.9 % physiological saline solution contained Supplement A (1 mL per 100 mL). The solutions were inoculated with less than 100 CFU per SimPlate-dish, mixed and poured onto the centre of sterile SimPlate device plates. Plates were gently swirled and the excess medium was poured off. Controls were also prepared without inoculum. In the experiments, the number of wells with colour changes were counted after incubation for 24 h and 120 h. Wells were counted as positive when colour changes occurred when compared against a background colour (pink, orange, peach, red, brown and white for bacteria and red, white, peach and orange for fungi). For determination of TAMC and TYMC on the plates, a SimPlate-conversion table (obtained from the manufacturer’s manual) was used. The number of micro-organisms per g (mL) was calculated by multiplying the count of micro-organisms per plate by the appropriate dilution factor.
2.5. Pour-plate count method (Ph. Eur.)The pour-plate count agars (CASO-agar and Sabouraud-agar) were prepared according to the manufacturer’s manual. The agar solutions were inoculated with less than 100 CFU per petri dish, mixed and poured into sterile petri-dishes. Plates were gently swirled. Controls were also prepared without inoculum. The number of colonies per plate were counted after incubation for 24 h and 120 h.
![Page 4: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/4.jpg)
Pharmeuropa Bio&SN | February 2016 51
2.6. Definitions, calculations and statisticsThe following definitions and equations were used to calculate the results [12]:
Standard deviation (s) was calculated according to the following equation::
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
x = single values;
n = number of values;
EXCEL-function: = STDEV(X1:Xn).
Coefficient of variation (= relative standard deviation, RSD) was calculated according to the following equation: :
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
with
:
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
:
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
= mean value (i.e. arithmetic average of the values);
s = standard deviation;
x = individual measurements;
n = number of individual measurements.
Linear regression (y) was calculated according to the following equation: :
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
with
:
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
:
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
a = slope (EXCEL-function: = SLOPE(Y;X));
b = intercept (EXCEL-function: = INTERCEPT(Y;X));
x = independent value, e. g. concentration of analyte;
y = dependent value, e. g. signal (peak area);
n = number of pairs of variates.
Correlation coefficient (r) was calculated according to the following equation::
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
x = independent value, e. g. concentration of analyte;y = dependent value, e. g. signal (peak area);n = number of pairs of variates;EXCEL-function: = CORREL(Y;X) identical to function =PEARSON(Y;X).
![Page 5: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/5.jpg)
52 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Residual standard deviation (sres) was calculated according to the following equation: :
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
x = independent value, e. g. concentration of analyte;y = dependent value, e. g. signal (peak area);n = number of pairs of variates;EXCEL-function: =STDEV(Y;X).
F-values of regression were calculated by EXCEL analysis tool using the function: =regression(matrixY;matrixX).
Deviations were calculated according to the following equation: :
Group number:
Document number:Monograph type:
The following expressions will appear in the index:
1
Dev% = deviation in per cent;v1 = value 1;v2 = value 2;2 = factor for the calculation of the mean value.
Variances were calculated by EXCEL analysis tool using the function: =FTEST(matrix1;matrix2).
3. RESULTS AND DISCUSSION
The main objective of this study was to show that the SimPlate method is a suitable alternative to the pour-plate method for the detection and enumeration of microbial contamination in non-sterile pharmaceutical preparations. According to the Ph. Eur., any alternative microbiological method shall be validated [13]. For this purpose, the performance and suitability of the SimPlate method for the detection of TAMC and TYMC were compared with the pharmacopoeial pour-plate method in blank solutions i.e. without any pharmaceutical preparation. The accuracy, specificity, linearity, precision, robustness, quantification limit and range of the two methods were compared.
3.1. Method validation3.1.1. Inoculants
The inoculum (CFU/mL) of each organism was determined every test-day using the Ph. Eur. pour-plate method on at least 5 concentrations in parallel. For that, the tested concentration was diluted to less than 100 CFU/plate [1]. Yeasts and moulds were tested as TYMC. All counts of CFU per plate must be under 100, i. e. taking the respective dilution factor into account, inocula have to be in the expected range of < 102 CFU/test, 102 to < 103 CFU/test, 103 to < 104 CFU/test, 105 to < 106 CFU/test and 106 to < 107 CFU/test.
According to our data, all counts of CFU were under 100 (see Table 1). Taking the respective dilution factor into account, inocula were always in the expected range of < 102 CFU/test, 102 to < 103 CFU/test, 103 to < 104 CFU/test, 105 to < 106 CFU/test and 106 to < 107 CFU/test. The acceptance criterion was met.
![Page 6: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/6.jpg)
Pharmeuropa Bio&SN | February 2016 53
3.1.2. Accuracy
The SimPlate and the Ph. Eur. methods were performed in parallel with Bacillus subtilis and Candida albicans at 5 different concentrations [13]. Candida albicans was tested as TYMC. For each organism and concentration, 5 tests were performed with each method. The tests were done in one working session (day 2).
At all concentrations, the SimPlate method provided an estimate of viable micro-organisms of not less than 70 % of the estimate provided by the pharmacopoeial pour-plate method (see Tables 2 and 3). The acceptance criterion (the recovery of the SimPlate method has to be at least 70 % of the Ph. Eur. method [1]) was met. Thus, the accuracy of the SimPlate method was successfully demonstrated using Bacillus subtilis and Candida albicans.
3.1.3. Specificity
According to the Ph. Eur. [13], the specificity of an alternative quantitative method has to be demonstrated using a range of appropriate micro-organisms. With all organisms used, the acceptance criterion for accuracy has to comply, i.e. the SimPlate method must provide an estimate of viable micro-organisms of not less than 70 % of the estimate provided by the pharmacopoeial method. The SimPlate and the pour-plate methods were both performed with each organism listed in Table 1 with a concentration of 103 to <104 CFU/mL to test the specificity. For each organism, 5 tests were performed with each method. Yeasts and moulds were tested as both aerobic micro-organisms and as yeasts and moulds. The tests were done in one working session (day 3).
The SimPlate method provided an estimate of viable micro-organisms of not less than 70 % of the estimate provided by the pharmacopoeial method with a range of different micro-organisms (see Table 4). Thus, the specificity of the SimPlate method was successfully demonstrated using a range of appropriate micro-organisms.
3.1.4. Linearity
The linearity of the SimPlate method must be shown to be within the limits of the Ph. Eur. method (10 CFU to >106 CFU). According to the Ph. Eur., the linearity is shown if the estimated slope of the regression line is significant and if the test for deviation from linearity is non-significant [12].
To test the linearity, the SimPlate method was performed with each organism listed in Table 1 at 5 different concentrations over 3 different working sessions (different day, different operator) [13]. Tests were done in 5 parallels each. Yeasts and moulds were tested as both aerobic micro-organisms and as yeasts and moulds. For statistical evaluation, the results of the SimPlate method were plotted in CFU/test on the y-axis and the inoculum on the x-axis as the mean of 10 measurements multiplied by the respective factor (see Table 1, Tables 5-13 and Figures 1-9). The range of tests went over several orders of magnitude, and small variations in the upper part of the regression line greatly influenced the y-intercept. Hence, as cell counts in the tests were mostly over 100 CFU/test, homogeneity of variances were calculated from log-values and log-values were plotted [14]. Homogeneities of variances for each concentration and for each test session were calculated with the FTEST-function from EXCEL, the p-values are given (values were rounded for the inter-session homogeneities of variances). Homogeneity of variances was checked by the F-test, the p-value is given (see Tables 5-13 and Figures 1-9). The p-value for the regression was given by the regression-analysis tool of Excel (F krit). Linear regression was given, if the F-value was higher than F krit.
The p-value calculated with the F-test function should be >0.05 to show a significant homogeneity of variances. With homogeneity of variances calculated for each concentration, this was not always the case. However, homogeneity of inter-session variances, taking all data from each day into account, showed that p-values were always >0.05 (see Tables 5-13 and
![Page 7: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/7.jpg)
54 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Figures 1-9, p-values are shown in the F-test log column by indication of the individual days). In addition, the linear regression clearly showed the linear correlation with over 98 % (Tables 5-13 and Figures 1-9), F krit was always lower than the F-value. The p-values (F krit) of each regression and the p-values of each slope calculated with other statistical programs (data not shown) were always zero or near zero, and F krit was always lower than the F-value, both indicating the high significance of the estimated slope. The linearity of the SimPlate method was shown to comply with the requirements of the Ph. Eur. method [12] because the estimated slope of the regression line was significant and the test for deviation from linearity was non-significant.
3.1.5. Precision (repeatability and intermediate precision)
According to the Ph. Eur. [13], in order to demonstrate the precision of the alternative quantitative method the coefficient of variation of the results (counts) of the SimPlate method must not be larger than that of the Ph. Eur. method. To estimate the precision, the SimPlate and the Ph. Eur. methods were performed in parallel with one bacterial and one yeast strain (i.e. Bacillus subtilis and Candida albicans) at 2 different concentrations. Candida albicans was tested as TYMC. For each organism and concentration, 5 tests were performed with each method. The tests were done in 1 working session to determine repeatability, but 3 sessions were done altogether (different day, different operator) to estimate the intermediate precision. Variances were calculated for each working session and suspension. As the Ph. Eur. method is done in duplicate [1], cell counts on plates using the Ph. Eur. method were given in pairs. The values of the parallels were grouped for each suspension (e.g. for the two concentrations for each micro-organism for both methods) and used for calculating the variances of the repeatability and for calculating the intermediate precision.
For the SimPlate method calculations were done with the number of positive wells as well as with the converted values which give the cell counts per plate. As the conversion function of SimPlate does not follow a linear function but rather an exponential one (see Figure 10), which increases the variance of the method with higher cell counts artificially, only the results of the counts on the plate are shown. The converted values are also taken into account in the interpretation of the results and in the discussion.
The variances of repeatability, inter-group variance and intermediate precision fluctuated for both methods (see Table 14). The variances of repeatability were around 4 to 40 with the SimPlate method and around 10 to 40 with the Ph. Eur pour-plate method, the inter-group variance ranged from around 30 to 50 (SimPlate) to 50 to 300 (Ph. Eur.).
The intermediate precision was calculated using the repeatability values from the first session and ranged between approximately 60 to 90 (SimPlate) and 60 to 300 (Ph. Eur.).
In general, variances and intermediate precision of both methods were in the same range, with the SimPlate method sometimes showing comparably lower values and the Ph. Eur. method in contrast comparably higher values. Calculating with the converted values of SimPlate, the intermediate precision of both methods was still within the same range, but the Ph. Eur. method showed generally lower values. Both methods gave coefficients of variation often higher than the usually accepted range of 10-15 % suggested by the Ph. Eur. [13]. Both methods showed a high variability in the coefficients of variation (Ph. Eur. method: around 7-33 %, SimPlate: around 6-24 % [Tables 15-17]), and overall both methods had the same mean of all coefficients of variation (rounded value: Ph. Eur.: 17 %, SimPlate: 16 %). Taking the converted cell counts of SimPlate into the calculation, the values for SimPlate were slightly higher than the Ph. Eur. (values not shown, overall mean of the coefficients of variation: Ph. Eur. method 17 %; SimPlate 19 %).
Overall, the data suggests that the SimPlate method as well as the Ph. Eur. method have high coefficients of variation but both in the same range. In addition, it has to be taken into
![Page 8: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/8.jpg)
Pharmeuropa Bio&SN | February 2016 55
account that the variance in one chosen method due to handling is expected to be 4-10 % with trained operators and should be even higher with operators that are unfamiliar with the method [15]. The operators had acquired experience with the Ph. Eur. method in the laboratory by performing it several times a day over several years, wheras the SimPlate method was, after a short introduction to the operators, performed for the first time. It is expected that with equally trained operators for both methods, the variance in the SimPlate method will improve and the coefficient of variation will be lower, whereas this is not to be expected with the Ph. Eur. method.
From our data we can conclude that the coefficient of variation of the SimPlate method did not exceed the coefficient of variation of the Ph. Eur. method. The acceptance criterion was met, therefore the precision of the SimPlate method was successfully demonstrated using Bacillus subtilis and Candida albicans as test organisms.
3.1.6. Quantification limit (QL)
The limit of quantification of the SimPlate method must not be greater than that of the pharmacopoeial method. The quantification limit of the Ph. Eur. plate-count method is 10 CFU. The data for estimating the linearity were used to define the limit of quantification, i.e. the detection limit was estimated from data obtained with the organisms listed in Table 1 at 5 different concentrations over 3 different working sessions (different day, different operator) and 5 parallel tests each. The scientific literature on the SimPlate method was also evaluated to confirm the findings.
Linearity was shown with all organisms with a correlation coefficient of at least 99 % (see section 3.1.4 Linearity). Hence, to judge the lower limit of the SimPlate method, the y-intercept given by the linear model was used (see Table 18).
For all test organisms, the highly probable linear model gave a y-intercept of nearly zero, which means that the linearity was given down to the smallest entity measurable, i. e. 1 CFU. This finding was confirmed by a study which compared results from the pour-plate method and the SimPlate method in water (here, the y-intercept was 0.06 [9]) and by the distributor of the SimPlate media who states that the change in colour of the sponge and not of a well of the SimPlate indicate the presence of one bacteria in the sample (see the manufacturer’s instructions: conversion table [3,4]). The method was, with this limit of detection, approved by Feldsine et al. [15,16].
In our opinion the quantification limit of the SimPlate method was lower than that of the pharmacopoeial method. The quantification limit for the plate-count method was 10 CFU and 1 CFU for the SimPlate method. Therefore, the acceptance criterion was met.
3.1.7. Range
The accepted range is defined as the least common range where the acceptance criteria of precision, accuracy and linearity are fulfilled. To define the range of the SimPlate method, the data sets for precision, accuracy and linearity were used, i.e. the range was estimated from all data presented in sections 3.1.2, 3.1.4 and 3.1.5. In addition, scientific literature on the SimPlate method was evaluated to confirm the findings.
Accuracy was shown with concentrations lower than 102 CFU and higher than 106 CFU (see section 3.1.2 Accuracy). Precision was shown to be not lower than that of the pharmacopoeial method with concentrations lower than 102 CFU and higher than 106 CFU (see section 3.1.5 Precision). Linearity was shown with all organisms with a correlation coefficient of at least 99 % (see section 3.1.4 Linearity) in a range of lower than 1 CFU/test up to > 102 CFU/test (see sections 3.1.4 Linearity and 3.1.6 Quantification limit).
![Page 9: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/9.jpg)
56 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
The results of accuracy, linearity and precision obtained with the SimPlate method showed that the range was given up to more than 106 per test. The lower limit given by accuracy and precision was < 100, mainly because it was hardly possible to get reliable cell counts more precise than that. The real lower detection limit (limit of quantification) was given with the linear regression and was found to be < 1 cell with the SimPlate method (statistical value; equals 1 cell). For that, the range of the method was defined to be from the lowest possible unit (1 cell) to over 106 cells.
This finding was confirmed by a study which compared results from the pour-plate method and SimPlate in water (highest concentration > 105 [9]). However, as with the pharmacopoeial method, the range of the SimPlate method can be widened using further dilution steps. As described in the manufacturer’s instructions (conversion table), the range of one SimPlate with an undiluted sample is 1-738 cells for bacteria, yeasts and moulds, whereas the pharmacopoeial method gives reliable results from <10-250 CFU for TAMC and <10 to 50 for TYMC with an undiluted sample [1].
According to our data, the range of the SimPlate method was broader than that of the pharmacopoeial method. The acceptance criterion was met.
3.1.8. Robustness
As no official acceptance criterion is given in the Ph. Eur., an F-test was done, providing an informative basis for the evaluation. Ideally, the F-test and the T-test should be ‘not significant’. To define the robustness of the SimPlate method, the data for estimating the precision and the linearity was used. The variances of the repeatability (data from 1 session) and the inter-group variances (data from 3 sessions) were compared with each other and with the respective variances from the pharmacopoeial method. Additionally, the results of the repeatability (variances) and of the two additional data sets for the intermediate precision were compared (F-test). P-values were given and judged.
The precision of the SimPlate method was shown to be not lower than that of the pharmacopoeial method (see section 3.1.5 Precision). Variances in the repeatability of the SimPlate method were roughly in the same range as the respective inter-group variances (see Table 14), the only exception being the last value in the table. Here, the variance of repeatability was exceptionally low; the inter-group variance was in the same range as the other values.
Linearity was shown with all organisms with a correlation coefficient of at least 99 % with a probability of nearly 100 % (see section 3.1.4 Linearity). The F-tests with one exception were ‘not significant’, showing p-values > 0.05 (see Table 19). The variances were homogenous. A linearity with 99 % correlation with a probability of nearly 100 % shows no great deviations over the range of >102 to >106, so the robustness over this range was shown.
The results of the intermediate precision showed that variances of the robustness were in the same range as the inter-group variance. The F-test results suggest that the variances of all sessions were homogenous; i.e. the variance in the repeatability (session 1) is homogeneous with those from the sessions for the intermediate precision. The robustness of the SimPlate method was shown.
3.2. Development and application of the validated SimPlate method for microbiological enumeration in a non-sterile pharmaceutical preparationMycobacterium phlei e volumine cellulae lyophilisate was used as a non-sterile pharmaceutical preparation. During the testing period, negative controls containing medium alone were used to check background colouration and to test possible influences of the incubation conditions on the change of colour of the media. All controls were growth-negative, a colour change due to incubation conditions occured over a period of time ≥ 3 days.
![Page 10: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/10.jpg)
Pharmeuropa Bio&SN | February 2016 57
Inocula of Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Candida albicans and Salmonella enterica were freshly prepared. Inocula of Bacillus subtilis and Aspergillus brasiliensis were prepared from spore stock solutions. Values for CFU in the inocula were determined by the pour-plate method. When necessary, the titre was adjusted prior to the inoculation of the sample. A volume was used resulting in a calculated CFU <100 per petri dish/SimPlate-dish.
3.2.1. Pre-test (without product)
A general pre-test was done without the product to prove that test preparation and handling were done correctly and to verify that, under the given laboratory conditions, the results are clearly detectable. Controls were done by plate count according to the Ph. Eur [1]. Recovery of the SimPlate method was higher by a factor of 1.4 compared to the recovery of the Ph. Eur. method. Growth was easily detectable with pink wells on a violet background (Escherichia coli, data not shown). Therefore, the method worked under the given laboratory conditions and handling according to the manufacturer’s instructions.
3.2.2. Dissolution of the product
To reduce usage of the product to the specification limits defined in the Ph. Eur. [17], i.e. 1 g per enumeration of TAMC and TYMC, dissolution of 2 g of the product in 2 mL of NaCl-peptone buffer was attempted. However, due to the characteristic physical properties of the product, dissolution of 2 g of the product in 2 mL of NaCl-peptone buffer was not possible. The use of Tween and other solvents was assumed to be useless. Consequently 1g of the product was dissolved directly into the TPC-CI SimPlate medium and 100 µL of the inoculum (Bacillus subtilis) was added. The medium was very darkly stained by the product and the colour change due to growth of Bacillus subtilis could not be detected. The negative control containing the medium and the inoculum showed growth between 96 and 120 CFU/g.
3.2.3. Test with the product diluted 1:10
Due to the dark colouration of the TPC-CI SimPlate medium caused by the direct addition of the product, further tests were done with a product dilution of 1:10. 1 g of the product was dissolved in 10 mL of NaCl-peptone buffer [1], 1 mL of this mixture was introduced into the TPC-CI SimPlate medium (or Y&M-CI medium for yeasts and moulds) and 100 µL of inoculum (first with Bacillus subtilis) was added. A negative control containing the medium alone was carried out.
Similarly, the pour-plate method was tested in parallel with 1 mL of the product diluted 1:10. For the tests without product, the microbial counts obtained with the SimPlate method were higher by a factor of 1.3 compared to the counts obtained with the Ph. Eur. method (see Table 20). For the tests with product, the factor was 1.5. Calculation of the factors was done by comparison of the microbial counts after an incubation time of 24 h for the SimPlate method and an incubation time of 3 days for the Ph. Eur. method. For Bacillus subtilis the determined recovery factors of microbial count of samples with and without product ranged within the specification (≤ 2). The background appeared red after the incubation time given by the manufacturer (72 h), in contrast to violet in the negative control. However, the colour change of the medium was clearly detectable and the results were clearly readable.
Subsequently, other strains were tested with this method. With Salmonella enterica, the factors of the test results with product were 1.1 and without product 1.8. After a time span greater than 24 h, the difference in colouration between wells with and without growth was harder to recognise and after an incubation time of 3 days, the difference was no longer detectable (indistinguishable shades of pink and orange in all wells).
With P. aeruginosa the colour changed in nearly all wells if incubation exceeded the times given in the manufacturer’s instructions. Moreover, with addition of the product the difference in colouration between wells with and without growth was hardly recognisable, therefore
![Page 11: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/11.jpg)
58 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
this difference was too faint to obtain reliable results for routine testing. Without product the microbial counts obtained with the SimPlate method were higher by a factor of 2.1 compared to the recovery of the Ph. Eur. method (see Table 20). For Staphylococcus aureus, the SimPlate method with addition of product was not determinable because the difference in colouration between wells with and without growth was hardly recognisable. This difference was too faint to obtain reliable results. The tests without product provided a factor of 1.3.
With E. coli, without product the microbial counts obtained with the SimPlate method were higher by a factor of 1.9 compared to the counts obtained with the Ph. Eur. method (see Table 20). From the tests with product, a factor of 1.7 resulted.
If the SimPlate method was determinable, the recovery factor of microbial count of samples with and without product of all tested bacteria strains, except P. aeruginosa, fulfilled the specification (≤ 2).
With the mould Aspergillus brasiliensis (formerly Aspergillus niger), without addition of product the microbial counts obtained with the SimPlate method were higher by a factor of 1.7 compared to the counts obtained with the Ph. Eur. method (see Table 20). However, detection of growth was only possible due to growth of a mycelium in the wells, all wells appeared yellow after incubation for 56 h and colour change was therefore not detectable. In the negative control, growth was also detectable clearly after the stated minimum incubation times for yeasts and moulds.
With the yeast Candida albicans, without product, the microbial counts obtained with the SimPlate method were higher by a factor of 1.6 compared to the counts obtained with the Ph. Eur. method (see Table 20). However, detection of growth was only possible in the negative control; with product, all wells appeared yellow after an incubation time of 56 h and colour change was not detectable. In the negative control growth was also detectable clearly after the stated minimum incubation times for yeasts and moulds.
In summary, in contrast to the results obtained with Bacillus subtilis, colour changes due to microbial growth could not be detected with all strains in the presence of the diluted product (1:10). For moulds and yeasts, the growth was not reliably detectable after the minimum incubation time given by the manufacturer.
3.2.4. Test with fluorescent media/colour enhancer
Because of the colouration problems caused by the product (1:10 dilution), further tests were done with fluorescent media and media with colour enhancer. Two bacterial strains (Staphylococcus aureus and Pseudomonas aeruginosa) were tested with SimPlate using the fluorescent media (TPC-FI). This medium allows growth detection via fluorescence under UV light instead of by colour change of the wells. Also Aspergillus brasiliensis was tested with SimPlate using a media colour enhancer. Here, the medium is supplemented with supplement M to enhance colour response. Tests were done with a product dilution of 1:10. The differentiation between growth and non-growth in the presence of the product with both test strains (Staphylococcus aureus and Pseudomonas aeruginosa) was not possible with the fluorescent media. The whole plate gave strong background fluorescence. The use of colour enhancer slightly improved the detection of the colour differentiation between bacterial growth and non-growth comparing to the regular medium, however, generally the differences were not sufficiently clear to be used in routine testing (data not shown).
3.2.5. Test with the product diluted 1:100
Since the use of fluorescent media or colour enhancer did not allow better microbial count detection in the product using the SimPlate method at a dilution of 1:10, experiments with further diluted product (1:100) were undertaken. For this 1g of the product was dissolved in 100 mL of NaCl-peptone buffer, 1 mL of this mixture was added to the TPC-CI SimPlate
![Page 12: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/12.jpg)
Pharmeuropa Bio&SN | February 2016 59
medium (or Y&M-CI medium for yeasts and moulds) and 100 µL of inoculum was added. A negative control containing the buffer and medium was carried out. Accordingly, the pour-plate method was tested in parallel with 1 mL of the 1:100 diluted product.
In Table 21 the microbial counts obtained with the SimPlate method compared to the counts obtained with the Ph. Eur. method of the tested strains are represented. Growth was easy to detect by colour change. If the incubation time exceeded the period given in the manufacturer’s instructions the numbers of wells with a colour change were increased for B. subtilis, Salmonella enterica, Escherichia coli and Candida albicans. For P. aeruginosa and Staphylococcus aureus the microbial counts with the SimPlate method were constantly independent of incubation time.
The recovery factors of microbial counts of samples with and without product ranged within the specification of ≤ 2 for both methods. So the specification was fulfilled by all tested strains. Also the factors of the comparison of the microbial counts of the SimPlate method versus the Ph. Eur. method are shown in Table 23.
In summary, with all strains tested the growth was easily detectable with the SimPlate colour change method. Incubation time for detection of bacteria should not exceed 28 h. Colour changes tended to occur in plates incubated longer and gave presumably false positive results. Incubation time for yeasts and moulds should be around 72 h, the minimum incubation time of 56 h given by the manufacturer was not sufficient to show growth under the given laboratory conditions. Therefore further tests were done by incubating the samples for 70 h and 77 h to explore if more reliable results could be obtained with longer incubation times.
3.2.6. Test for determining the minimum and maximum incubation time for TYMC
To explore the optimal incubation time for yeasts and moulds, tests were carried out according to section 2.4. The SimPlate results were read at 56 h, 70 h and 77 h (see Table 22). According to the results of these experiments, the incubation time for yeasts and moulds should be between around 70 h and 77 h. Again, the minimum incubation time of 56 h given by the manufacturer was not sufficient to show growth under the given laboratory conditions. However, for yeasts (Candida albicans) the incubation time of 77 h seemed to yield reliable results, for moulds the incubation time should not exceed 3 days. Therefore, in the testing instruction the incubation time for moulds and yeasts with the SimPlate method should be set at 3 days.
It was shown that the SimPlate method is suitable to determine the microbial count in order to record possible microbial contamination according to the Ph. Eur. in Mycobacterium phlei e volumine cellulae extract. All recovery factors from the validation (with the product) are summarised in Table 23.
The 1:100 solution of Mycobacterium phlei e volumine cellulae extract showed no inhibition of the microbial growth of the micro-organisms listed in Table 23.
4. CONCLUSIONThe SimPlate method was able to detect microbial contamination in a 1:100 dilution of Mycobacterium phlei e volumine cellulae extract under the given laboratory conditions. Using the SimPlate method, the incubation time for the detection of bacteria should not exceed the times given by the manufacturer (1 day). Incubation time for the detection of moulds and yeasts has to be around the maximum incubation time given by the manufacturer (3 days).
In comparison to the pour-plate method carried out according to the Ph. Eur. [1], the incubation time for the detection of bacteria is at least 3 days and 5 days for detection of yeasts and moulds. Therefore with the SimPlate method it is possible to obtain information about microbial contamination of the product sooner than with the pour-plate method.
![Page 13: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/13.jpg)
60 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
The detection with SimPlate was equal or higher (up to a factor of 3) than with the Ph. Eur. method. Only in the case of Candida albicans was a lower detection observed with the SimPlate method in comparison to the Ph. Eur. pour-plate method.
According to our data the SimPlate method, after appropriate validation and optimisation, is recommended for the detection of microbial contamination in other non-sterile pharmaceutical preparations and provides a more sensitive, simpler, faster and also material-efficient alternative to the Ph. Eur. method.
5. ACKNOWLEDGEMENTSThe authors thank Heike Stevens, Katrin Schulze, Stefanie Hofmann and Jutta Bohnacker from Phytos Labor für Analytik von Arzneimitteln GmbH & Co. KG for carrying out the experiments.
6. ABBREVIATIONSATCC: American Type Culture Collection; CFU: Colony-forming units; DSMZ: German Collection of Microorganisms and Cell Cultures; TAMC: Total aerobic microbial count; TYMC: Total combined yeasts and moulds count; Ph. Eur: European Pharmacopoeia
7. REFERENCES[1] Microbiological examination of non-sterile products – microbial enumeration tests,
general chapter 2.6.12, Ph. Eur. 8th Edition Strasbourg, France: Council of Europe; 2013.
[2] Microbiological examination of non-sterile products – test for specified microorganisms, general chapter 2.6.13, Ph. Eur. 8th Edition Strasbourg, France: Council of Europe; 2013.
[3] SimPlate Total Plate Count Colour Indicator (BIOCONTROL, Manufacturer’s manual), 2007.
[4] SimPlate Yeasts and Mold colour indicator (BIOCONTROL, Manufacturer’s manual), 2007.
[5] Stillings A, Herzig D, Roll B. Comparative Assessment of Newly Developed SimPlateTM method with the Existing EPA-approved Pour Plate Method for the Detection of Heterophilic Plate Count Bacteria in Ozone-treated Drinking Water. Presented at the International Ozone Association Conference Vancouver, Canada, October 13, 1998.
[6] Spangenberg DS, Ingham SC. Comparison of methods for enumeration of yeasts and molds in shredded low-moisture, part-skim mozzarella cheese. J Food Prot 2000;63(4):529-33.
[7] Vulindlu M, Charlett A, Surman S et al. Comparison of agar-based methods for the isolation and enumeration of heterotrophic bacteria with the new multidose IDEXX SimPlate method. Water Sci Technol 2004;50(1):277-80.
[8] Townsend DE, Naqui A. Comparison of SimPlate Total Plate Count test with plate count agar method for detection and quantitation of bacteria in food. J AOAC Int 1998;81(3):563-9.
[9] Jackson RW, Osborne K, Branes G et al. Multiregional Evaluation of the SimPlate Heterotrophic Plate Count Method Compared to the Standard Plate Count Agar Pour Plate Method in Water. Appl Env Mic 2000;453-454.
![Page 14: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/14.jpg)
Pharmeuropa Bio&SN | February 2016 61
[10] Hauge SJ, Nesbakken T, Skjerve E et al. Evaluation of the SimPlate method for enumeration of Escherichia coli in swab samples from beef and lamb carcasses. Int J Food Microbiol 2010;142(1-2):229-33.
[11] Beuchat LR, Copeland F, Curiale MS et al. Comparison of the SimPlate total plate count method with Petrifilm, Redigel, conventional pour-plate methods for enumerating aerobic microorganisms in foods. J Food Prot 1998;61(1):14-8.
[12] Statistical analysis of results of biological assays and tests, general chapter 5.3. Ph. Eur. 8th Edition Strasbourg, France: Council of Europe; 2013.
[13] Alternative methods for control of microbiological quality, general chapter 5.1.6. Ph. Eur. 8th Edition Strasbourg, France: Council of Europe; 2013.
[14] Hübner P, Gautsch S, Thomas Jemmi T. In house-Validierung mikrobiologischer Prüfverfahren. Mitteilungen aus Lebensmitteluntersuchung und Hygiene, 2002;(93):118-139.
[15] Feldsine PT, Leung SC, Lienau AH et al. Enumeration of total aerobic microorganisms in foods by SimPlate total plate count –color indicator methods and conventional culture methods:collaborative study. J AOAC Int 2003;86(2):257-274.
[16] Feldsine PT, Lienau AH, Leung SC et al. Enumeration of total yeasts and molds in foods by the SimPlate yeast and mold –color indicator methods and conventional culture methods: collaborative study. J AOAC Int 2003;86(2):296-313.
[17] Microbiological quality of non-sterile pharmaceutical preparations and substances for pharmaceutical use, general chapter 5.1.4, Ph. Eur. 8th Edition Strasbourg, France: Council of Europe; 2013.
![Page 15: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/15.jpg)
62 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Pseudomonas aeruginosa
Figure 1 – Linearity of SimPlate method with Pseudomonas aeruginosa
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Bacillus subtilis
Figure 2 – Linearity of SimPlate method with Bacillus subtilis
slope 0.99651545
y-intercept 0.10627784
F krit (p-value)
3.8216E-81
F-value 11479.371
correlation coefficient
0.9969382
slope 1.010250828
y-intercept 0.221498942
F krit (p-value)
2.79292E-84
F-value 14045.02794
correlation coefficient
0.997504496
![Page 16: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/16.jpg)
Pharmeuropa Bio&SN | February 2016 63
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Staphylococcus aureus
Figure 3 – Linearity of SimPlate method with Staphylococcus aureus
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Escherichia coli
Figure 4 – Linearity of SimPlate method with Escherichia coli
slope 0.98262079
y-intercept 0.15914002
F krit (p-value)
1.1166E-86
F-value 16385.1294
correlation coefficient
0.99784516
slope 0.98309654
y-intercept 0.22631139
F krit (p-value)
2.1502E-71
F-value 6119.92989
correlation coefficient
0.99429598
![Page 17: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/17.jpg)
64 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
0
1
2
3
4
5
6
7
8
0 2 4 6 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Salmonella enterica
Figure 5 – Linearity of SimPlate method with Salmonella enterica
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Candida albicans (as TAMC)
Figure 6 – Linearity of SimPlate method with Candida albicans (as TAMC)
slope 1.00281418
y-intercept 0.1704531
F krit (p-value)
1.0648E-85
F-value 15385.9464
correlation coefficient
0.99771317
slope 1.00619987
y-intercept -0.10322136
F krit (p-value)
2.1096E-65
F-value 4149.05668
correlation coefficient
0.99148485
![Page 18: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/18.jpg)
Pharmeuropa Bio&SN | February 2016 65
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Candida albicans (as TYMC)
Figure 7 – Linearity of SimPlate method with Candida albicans (as TYMC)
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Aspergillus brasiliensis (as TAMC)
Figure 8 – Linearity of SimPlate method with Aspergillus brasiliensis (as TAMC)
slope 0.99069801
y-intercept -0.01328163
F krit (p-value)
1.0788E-69
F-value 5481.91047
correlation coefficient
0.99361529
slope 1.00811518
y-intercept 0.17211804
F krit (p-value)
6.9445E-72
F-value 6317.37012
correlation coefficient
0.9943879
![Page 19: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/19.jpg)
66 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8
Sim
plat
e (lo
g C
FU/te
st)
Inoculum (log CFU/test)
Aspergillus brasiliensis (as TYMC)
Figure 9 – Linearity of SimPlate method with Aspergillus brasiliensis (as TYMC)
y = 12,746e0,0479x R² = 0,9153
0
100
200
300
400
500
600
700
800
0 20 40 60 80 100
Cell
coun
t per
pla
te
Number of positive wells
Figure 10 – The correlation between the number of positive wells and the cell count per plate measured by the SimPlate method [3, 4]
slope 0.98996656
y-intercept 0.07099427
F krit (p-value)
1.8472E-69
F-value 5399.56988
correlation coefficient
0.99339875
![Page 20: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/20.jpg)
Pharmeuropa Bio&SN | February 2016 67
Table 1 – Microbial counts for the determination of the acceptance criteria (CFU/plate)
Organism Day
Concentration tested (dilution factor)
Mean*< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Cell count on plate (CFU/plate)
Pseudomonas aeruginosa
1 23 27 28 28 16 20 24 21 16 24 23
2 17 16 12 13 12 10 11 13 10 12 13
3 7 16 14 11 13 14 12 12 15 20 13
Bacillus subtilis
1 44 38 50 40 37 43 48 44 45 40 43
2 34 36 37 46 41 40 41 43 37 33 39
3 45 49 50 54 49 44 57 36 51 54 49
Staphylo-coccus aureus
1 67 59 60 54 43 49 60 32 31 38 49
2 26 15 22 32 16 18 24 26 18 19 22
3 31 25 26 38 37 29 40 26 28 31 31
Escherichia coli
1 34 36 35 27 27 23 20 18 22 23 27
2 21 16 16 26 14 20 20 19 23 20 20
3 30 35 37 40 35 46 36 34 37 38 37
Salmonella enterica
1 28 27 32 24 25 26 35 25 37 27 29
2 23 15 20 20 24 15 22 20 16 20 20
3 28 20 33 28 33 39 34 40 22 33 31
Candida albicans
1 62 58 39 41 50 38 46 66 50 52 50
2 61 69 46 63 59 64 65 61 65 49 60
3 24 41 31 21 27 34 27 29 35 36 31
Aspergillus brasiliensis
1 46 54 40 38 37 46 34 51 43 48 44
2 36 39 46 47 41 33 32 34 36 31 38
3 31 30 26 24 21 21 21 24 22 24 24
*values are rounded
![Page 21: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/21.jpg)
68 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 2 – Comparison of the accuracy between the Ph. Eur. pour-plate and SimPlate methods using Bacillus subtilis
ConcentrationOrganism/ ID parallel test
Result Ph. Eur. method Result SimPlate method
Recovery
(% SimPlate
of Ph. Eur.)*Count on
plateMean
Total cell count
(dilution factor
included)
Count on
plate
CFU (converted from table)
Total cell count
(dilution factor
included)
< 102
(Factor: 1)
I 52 50 51 51 33 84 84
II 46 39 42.5 42.5 39 104 104
III 42 38 40 40 42 116 116
IV 38 53 45.5 45.5 46 132 132
V 36 41 38.5 38.5 32 80 80
mean - 43.5 - 103.2 237
102 to < 103
(Factor: 10)
I 34 45 39.5 395 44 124 1240
II 49 38 43.5 435 40 108 1080
III 50 37 43.5 435 36 94 940
IV 52 47 49.5 495 36 94 940
V 42 50 46 460 29 70 700
mean - 444 - 980 221
103 to < 104
(Factor: 100)
I 46 34 40 4000 28 68 6800
II 40 35 37.5 3750 32 80 8000
III 33 36 34.5 3450 36 94 9400
IV 38 39 38.5 3850 36 94 9400
V 45 36 40.5 4050 37 96 9600
mean - 3820 - 8640 226
105 to < 106
(Factor: 10 000)
I 33 41 37 370 000 35 90 900 000
II 37 52 44.5 445 000 32 80 800 000
III 49 51 50 500 000 30 74 740 000
IV 33 39 36 360 000 43 120 1 200 000
V 48 49 48.5 485 000 41 112 1 120 000
mean - 432 000 - 952 000 220
106 to < 107
(Factor: 100 000)
I 50 48 49 4 900 000 43 120 12 000 000
II 50 56 53 5 300 000 37 96 9 600 000
III 48 47 47.5 4 750 000 26 62 6 200 000
IV 53 46 49.5 4 950 000 38 100 10 000 000
V 44 44 44 4 400 000 33 84 8 400 000
mean - 4 860 000 - 9 240 000 190
* values are rounded
![Page 22: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/22.jpg)
Pharmeuropa Bio&SN | February 2016 69
Table 3 – Comparison of the accuracy between the Ph. Eur. pour-plate and SimPlate methods using Candida albicans (as TYMC)
ConcentrationOrganism/ ID parallel test
Result Ph. Eur. method Result SimPlate method
Recovery
(% SimPlate of Ph. Eur.)*
Count on plate
Mean
Total cell count
(dilution factor
included)
Count on
plate
CFU (converted from table)
Total cell count
(dilution factor
included)
< 102
(Factor: 1)
I 16 23 19.5 19.5 24 56 56
II 17 27 22 22 32 80 80
III 20 20 20 20 27 64 64
IV 21 20 20.5 20.5 19 42 42
V 19 18 18.5 18.5 20 46 46
mean - 20.1 - 57.6 287
102 to < 103
(Factor: 10)
I 18 25 21.5 215 16 36 360
II 23 19 21 210 20 46 460
III 20 26 23 230 20 46 460
IV 24 17 20.5 205 17 38 380
V 18 20 19 190 22 50 500
mean - 210 - 432 206
103 to < 104
(Factor: 100)
I 17 24 20.5 2050 25 58 5800
II 23 27 25 2500 16 36 3600
III 17 19 18 1800 16 36 3600
IV 20 26 23 2300 19 42 4200
V 20 26 23 2300 13 28 2800
mean - 2190 - 4000 183
105 to < 106
(Factor: 10 000)
I 29 25 27 270 000 8 16 160 000
II 24 22 23 230 000 6 12 120 000
III 20 17 18.5 185 000 12 26 260 000
IV 23 25 24 240 000 9 18 180 000
V 18 19 18.5 185 000 11 24 240 000
mean - 222 000 - 192 000 86
106 to < 107
(Factor: 100 000)
I 23 27 25 2 500 000 13 28 2 800 000
II 28 26 27 2 700 000 13 28 2 800 000
III 16 20 18 1 800 000 12 26 2 600 000
IV 23 22 22.5 2 250 000 11 24 2 400 000
V 21 17 19 1 900 000 8 16 1 600 000
mean - 2 230 000 - 2 440 000 109* values are rounded
![Page 23: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/23.jpg)
70 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 4 – Comparison of the specificity between the pour-plate (Ph. Eur.) and SimPlate methods
Organism/ ID parallel test
Result Ph. Eur. method Result SimPlate method% SimPlate of
Ph. Eur. *Count on plate CFU x 102 /mL Count on plate CFU x 102 /mL
Pseudomonas aeruginosa
I 7 14 10.5 8 16
II 18 9 13.5 12 26
III 10 6 8 12 26
IV 13 7 10 9 18
V 15 10 12.5 7 14
mean - 10.9 - 20 183
Staphylococcus aureus
I 25 28 26.5 16 36
II 41 34 37.5 18 40
III 23 27 25 18 40
IV 26 30 13 20 46
V 25 18 21.5 17 38
mean - 27.7 - 40 144
Escherichia coli
I 26 34 30 23 54
II 59 36 47.5 23 54
III 26 40 33 22 50
IV 34 24 29 18 40
V 32 34 33 19 42
mean - 34.5 - 48 139
Bacillus subtilis
I 38 41 39.5 34 86
II 36 47 41.5 25 58
III 40 47 43.5 34 86
IV 47 32 39.5 28 68
V 48 37 42.5 31 76
mean - 41.3 - 74.8 181
Salmonella enterica
I 27 30 28.5 16 36
II 27 32 29.5 19 42
III 29 31 30 16 36
IV 30 36 33 20 46
V 38 29 33.5 36 94
mean - 30.9 - 50.8 164
Candida albicans (as TAMC)
I 24 31 27.5 19 42
II 28 30 29 23 54
III 20 35 27.5 16 36
IV 42 18 30 21 48
V 22 29 25.5 14 30
mean - 27.9 - 20 72
* values are rounded
![Page 24: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/24.jpg)
Pharmeuropa Bio&SN | February 2016 71
Organism/ ID parallel test
Result Ph. Eur. method Result SimPlate method% SimPlate of
Ph. Eur. *Count on plate CFU x 102 /mL Count on plate CFU x 102 /mL
Candida albicans (as TYMC)
I 37 30 33.5 15 32
II 48 33 40.5 22 50
III 36 40 38 15 32
IV 60 35 47.5 13 28
V 35 23 29 17 38
mean - 37.7 - 36 95
Aspergillus brasiliensis (as TAMC)
I 27 33 30 26 62
II 25 31 28 29 70
III 30 25 27.5 20 46
IV 28 32 30 24 56
V 26 30 28 17 38
mean - 28.7 - 54.4 190
Aspergillus brasiliensis (as TYMC)
I 26 19 22.5 20 46
II 30 25 27.5 21 48
III 23 34 28.5 25 58
IV 22 26 24 16 36
V 19 25 22 22 50
mean - 24.9 - 47.6 191* values are rounded
![Page 25: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/25.jpg)
72 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 5 – Linearity of SimPlate method with Pseudomonas aeruginosa
ID of Parallels (values counted/converted from table) F-test log(p-value)< 102
(Factor: 1)102 to < 103
(Factor: 10)103 to < 104
(Factor: 100)105 to < 106
(Factor: 10 000)106 to < 107
(Factor: 100 000)
Day 1 Day 1/2=0.898
14 30 12 26 9 18 20 46 13 28 0.1331281
20 46 17 38 11 24 9 18 9 18 0.06018749
12 26 11 24 11 24 17 38 5 10 0.264695
8 16 18 40 13 28 13 28 11 24 0.14251431
10 22 19 42 11 24 13 28 11 24 0.54268758
Day 2 Day 2/3=0.999
6 12 9 18 9 18 6 12 8 16 0.1492703
6 12 8 16 5 10 6 12 10 22 0.02755252*
8 16 7 14 8 16 8 16 5 10 0.9377317
5 10 8 16 10 22 6 12 7 14 0.13821462
6 12 8 16 7 14 8 16 9 18 0.38790773
Day 3 Day 1/3=0.898
9 18 6 18 8 16 8 16 9 18 0.94550199
8 16 5 10 12 26 6 12 13 28 0.67991944
11 24 10 22 12 26 11 24 10 22 0.29702905
12 26 9 18 9 18 7 14 11 24 0.98541023
19 42 6 12 7 14 13 28 13 28 0.15353701
* p-value is <0.05
Table 6 – Linearity of SimPlate method with Bacillus subtilis
ID of Parallels (values counted/converted from table) F-test log(p-value)< 102
(Factor: 1)102 to < 103
(Factor: 10)103 to < 104
(Factor: 100)105 to < 106
(Factor: 10 000)106 to < 107
(Factor: 100 000)
Day 1 Day 1/2=0.941
30 74 35 90 24 56 35 90 32 80 0.72352253
26 62 35 90 22 50 40 108 30 74 0.96539327
25 58 28 68 35 90 29 70 29 70 0.29342451
30 74 26 62 32 80 30 74 33 84 0.72629463
41 112 25 58 33 84 35 90 28 68 0.07386233
Day 2 Day 2/3=0.847
33 84 44 124 28 68 35 90 43 120 0.68048759
39 104 40 108 32 80 32 80 37 96 0.26338114
42 116 36 94 36 94 30 74 26 62 0.82027735
46 132 36 94 36 94 43 120 38 100 0.69072619
32 80 29 70 37 96 41 112 33 84 0.84807179
Day 3 Day 1/3=0.905
29 70 14 30 34 86 30 74 29 70 0.95327049
20 46 28 68 25 58 30 74 35 90 0.24670356
26 62 21 48 34 86 33 84 42 116 0.40321851
31 76 22 50 28 68 33 84 28 68 0.96151699
36 94 33 84 31 76 41 112 36 94 0.10376822
![Page 26: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/26.jpg)
Pharmeuropa Bio&SN | February 2016 73
Table 7 – Linearity of SimPlate method with Staphylococcus aureus
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day 1/2=0.996
30 74 19 42 25 58 26 62 24 56 0.06925517
31 76 25 58 34 86 36 94 22 50 0.49978599
29 70 24 56 22 50 22 50 26 62 0.09831761
32 80 32 80 23 54 27 64 22 50 0.84039807
34 86 36 94 24 56 29 70 21 48 0.22054733
Day 2 Day 2/3=0.944
19 42 20 46 13 28 13 28 13 28 0.47326472
16 36 14 30 9 18 14 30 14 30 0.81416426
11 24 12 26 11 24 19 42 10 22 0.00456382*
18 40 15 32 4 8 15 32 10 22 0.98667962
16 36 17 38 14 30 11 24 9 18 0.22835478
Day 3 Day 1/3=0.947
19 42 14 30 16 36 21 48 16 36 0.01743577*
20 46 16 36 18 40 17 38 15 32 0.3676756
21 48 15 32 18 40 13 28 8 16 0.13082848
15 32 20 46 20 46 15 32 20 46 0.853441
10 22 13 28 17 38 18 40 16 36 0.02412929** p-value is <0.05
Table 8 – Linearity of SimPlate method with Escherichia coli
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day 1/2=0.954
16 36 20 46 13 28 14 30 7 14 0.71797946
13 28 17 38 18 40 6 12 13 28 0.5542185
9 18 11 24 11 24 13 28 9 18 0.64548145
14 30 9 18 21 48 18 40 11 24 0.13703181
17 38 15 32 18 40 12 26 17 38 0.33910644
Day 2 Day 2/3=0.891
19 42 19 42 17 38 14 30 21 48 0.12775711
15 32 12 26 12 26 18 40 14 30 0.08784005
26 62 17 38 14 30 13 28 19 42 0.39683041
18 40 19 42 20 46 12 26 14 30 0.54723181
17 38 11 24 17 38 11 24 20 46 0.75547782
Day 3 Day 1/3=0.846
19 42 24 56 23 54 30 74 32 80 0.06752929
21 48 23 54 23 54 18 40 17 38 0.02905497*
24 56 21 48 22 50 30 74 27 64 0.2016191
21 48 23 54 18 40 31 76 25 58 0.34988238
20 46 27 64 19 42 27 64 23 54 0.51128035
* p-value is <0.05
![Page 27: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/27.jpg)
74 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 9 – Linearity of SimPlate method with Salmonella enterica
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day 1/2=0.844
21 48 19 42 28 68 21 48 17 38 0.40235119
21 48 18 40 20 46 15 32 16 36 0.00204584*
17 38 11 24 18 40 17 38 20 46 0.91010152
24 56 20 46 17 38 18 40 11 24 0.69240721
24 56 26 62 28 68 20 46 17 38 0.43399933
Day 2 Day 2/3=0.993
14 30 16 36 11 24 18 40 30 74 0.89754543
14 30 17 38 12 26 17 38 23 54 0.00262385*
11 24 16 36 19 42 15 32 17 38 0.59872778
20 46 16 36 10 22 11 24 20 46 0.17141466
17 38 18 40 18 40 15 32 13 28 0.59075391
Day 3 Day 1/3=0.850
13 28 10 22 16 36 21 48 15 32 0.47550391
17 38 21 48 19 42 20 46 19 42 0.90442196
18 40 18 40 16 36 20 46 21 48 0.52431982
23 54 13 28 20 46 17 38 19 42 0.31498315
18 40 19 42 36 94 19 42 28 68 0.80151175
* p-value is <0.05
Table 10 – Linearity of SimPlate method with Candida albicans (as TAMC)
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day1/2=0.882
28 68 35 90 31 76 19 42 26 62 0.02950657*
18 40 25 58 26 62 29 70 20 46 0.90721625
23 54 38 100 23 54 26 62 25 58 0.93598269
29 70 26 62 24 56 17 38 30 74 0.42955906
27 64 31 76 16 36 28 68 30 74 0.16343833
Day 2 Day2/3=0.586
12 26 19 42 15 32 5 10 12 26 0.05090648
12 26 14 30 15 32 12 26 15 32 0.62638009
13 28 23 54 14 30 11 24 11 24 0.82064835
14 30 14 30 23 54 6 12 6 12 0.10464203
12 26 16 36 20 46 10 22 16 36 0.21745374
Day 3 Day1/3=0.692
10 22 8 16 19 42 20 46 17 38 0.77377083
8 16 7 14 23 54 16 36 25 58 0.54772509
10 22 7 14 16 36 25 58 16 36 0.75909836
12 26 13 28 21 48 22 50 23 54 0.36796503
12 26 11 24 14 30 22 50 18 40 0.85832444
* p-value is <0.05
![Page 28: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/28.jpg)
Pharmeuropa Bio&SN | February 2016 75
Table 11 – Linearity of SimPlate method with Candida albicans (as TYMC)
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day1/2=0.568
24 56 26 62 22 50 32 80 27 64 0.30165795
28 68 24 56 17 38 37 96 27 64 0.61286253
24 56 23 54 23 54 32 80 30 74 0.48101544
20 46 26 62 16 36 36 94 25 58 0.0392185*
22 50 21 48 22 50 32 80 23 54 0.2194779
Day 2 Day2/3=0.526
24 56 16 36 25 58 8 16 13 28 0.99057822
32 80 20 46 16 36 6 12 13 28 0.83001881
27 64 20 46 16 36 12 26 12 26 0.73695891
19 42 17 38 19 42 9 18 11 24 0.42907096
20 46 22 50 13 28 11 24 8 16 0.84839783
Day 3 Day1/3=0.949
14 30 12 26 15 32 16 36 17 38 0.30685342
11 24 15 32 22 50 13 28 26 62 0.47419423
10 22 15 32 15 32 14 30 18 40 0.70803509
18 40 13 28 13 28 10 22 28 68 0.16322508
10 22 10 22 17 38 16 36 21 48 0.16164494
* p-value is <0.05
Table 12 – Linearity of SimPlate method with Aspergillus brasiliensis (as TAMC)
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day1/2=0.848
18 40 9 18 23 54 20 46 18 40 0.79526511
16 36 18 40 22 50 16 36 16 36 0.13112492
26 62 22 50 24 56 18 40 16 36 0.05644481
24 56 17 38 25 58 14 30 21 48 0.89586547
12 26 18 40 21 48 20 46 13 28 0.27870493
Day 2 Day2/3=0.908
17 38 30 74 48 142 35 90 30 74 0.0427919*
32 80 23 54 38 100 30 74 34 86 0.53625124
31 76 27 64 36 94 36 94 37 96 0.95301771
27 64 27 64 32 80 42 116 33 84 0.92288
30 74 21 48 32 80 39 104 37 96 0.3046095
Day 3 Day1/3=0.939
25 58 17 38 26 62 28 68 21 48 0.02604161*
20 46 15 32 29 70 24 56 19 42 0.34544457
22 50 22 50 20 46 22 50 20 46 0.0506061
22 50 18 40 24 56 20 46 24 56 0.97279111
24 56 25 58 17 38 28 68 28 68 0.95151629
* p-value is <0.05
![Page 29: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/29.jpg)
76 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 13 – Linearity of SimPlate method with Aspergillus brasiliensis (as TYMC)
ID of Parallels (values counted/converted from table) F-test log
(p-value)< 102
(Factor: 1)
102 to < 103
(Factor: 10)
103 to < 104
(Factor: 100)
105 to < 106
(Factor: 10 000)
106 to < 107
(Factor: 100 000)
Day 1 Day 1/2=0.973
14 30 10 22 15 32 20 46 11 24 0.78345784
19 42 10 22 21 48 17 38 13 28 0.08161935
14 30 14 30 11 24 16 36 17 38 0.28056911
16 36 19 42 17 38 13 28 10 22 0.45285846
14 30 10 22 18 40 15 32 10 22 0.6139364
Day 2 Day 2/3=0.956
13 28 13 28 18 40 13 28 13 28 0.45451293
13 28 14 30 21 48 16 36 13 28 0.86331577
19 42 11 24 16 36 15 32 12 26 0.74100135
14 30 15 32 22 50 24 56 9 18 0.88454065
13 28 13 28 17 38 20 46 19 42 0.89163809
Day 3 Day 1/3=0.983
20 46 16 36 20 46 20 46 15 32 0.63163845
24 56 20 46 21 48 19 42 19 42 0.05973219
27 64 17 38 25 58 24 56 19 42 0.44395614
23 54 19 42 16 36 15 32 17 38 0.5420626
23 54 13 28 22 50 26 62 28 68 0.71146824
Table 14 – Calculation of the inter-group variances, the variances of repeatability and the intermediate precision values for the comparison of the precision between the pour-plate (Ph. Eur.) and SimPlate methods
Strain (concentration)
MethodInter-group
varianceRepeatability
(variance)Intermediate
precision
Rounded values of
inter-group variance
Rounded values of
repeatability (variance)
Bacillus subtilis (< 102)
Ph. Eur. 69.5816092 39.61111111 109.1927203 70 40
SimPlate 51.68571429 35.3 86.98571429 52 35
Bacillus subtilis
(106 to < 107)
Ph. Eur. 46.53333333 14.48888889 61.02222222 47 14
SimPlate 26.78095238 40.3 67.08095238 27 40
Candida albicans
(< 102)
Ph. Eur. 246.0413793 9.877777778 255.9191571 246 10
SimPlate 45.02857143 28.3 73.32857143 45 28
Candida albicans
(106 to < 107)
Ph. Eur. 298.9609195 16.01111111 314.9720307 299 16
SimPlate 52.35238095 4.3 56.65238095 52 4
![Page 30: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/30.jpg)
Pharmeuropa Bio&SN | February 2016 77
Table 15 – Comparison of the precision between the pour-plate (Ph. Eur.) and SimPlate methods, working session 1 (day 2)
Organism/ID parallel test Counts on plate
< 102 (Factor: 1) 106 to < 107 (Factor: 100 000)
Ph. Eur. SimPlate Ph. Eur. SimPlate
Bacillus subtilis
I 52 50 33 50 48 43
II 46 39 39 50 56 37
III 42 38 42 48 47 26
IV 38 53 46 53 46 38
V 36 41 32 44 44 33
Variances* 39.6 35.3 14.5 40.3
Standard deviation 5.970762095 5.314132102 3.611094017 5.678027827
Mean 43.5 38.4 48.6 35.4
Coefficient of variation 13.73 13.84 7.43 16.04
Candida albicans (as TYMC)
I 16 23 24 23 27 13
II 17 27 32 28 26 13
III 20 20 27 16 20 12
IV 21 20 19 23 22 11
V 19 18 20 21 17 8
Variances* 9.9 28.3 16.0 4.3
Standard deviation 2.981610303 4.758150901 3.796050579 1.854723699
Mean 20.1 24.4 22.3 11.4
Coefficient of variation 14.83 19.50 17.02 16.27*values are rounded
Table 16 – Comparison of the precision between the pour-plate (Ph. Eur.) and SimPlate methods, working session 2 (day 1)
Organism/ID parallel test Counts on plate
< 102 (Factor: 1) 106 to < 107 (Factor: 100 000)
Ph. Eur. SimPlate Ph. Eur. SimPlate
Bacillus subtilis
I 36 22 30 28 38 32
II 47 35 26 32 37 30
III 33 34 25 38 29 29
IV 36 32 30 40 40 33
V 45 49 41 44 41 28
Variances* 65.4 40.3 28.2 4.3
Standard deviation 7.673982017 5.678027827 5.040833264 1.854723699
Mean 36.9 30.4 36.7 30.4
Coefficient of variation 20.80 18.68 13.74 6.10
Candida albicans (as TYMC)
I 54 48 24 64 67 27
II 32 49 28 61 59 27
III 47 46 24 49 53 30
IV 60 47 20 61 57 25
V 43 42 22 47 61 23
Variances 54.4 8.8* 41.4* 6.8*
Standard deviation 6.997142274 2.653299832 6.106553856 2.332380758
Mean 46.8 23.6 57.9 26.4
Coefficient of variation 14.95 11.24 10.55 8.83 *values are rounded
![Page 31: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/31.jpg)
78 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 17 – Comparison of the precision between the pour-plate (Ph. Eur.) and SimPlate methods, working session 3 (day 3)
Organism/ID parallel test Counts on plate
< 102 (Factor: 1) 106 to < 107 (Factor: 100 000)
Ph. Eur. SimPlate Ph. Eur. SimPlate
Bacillus subtilis
I 26 27 29 35 42 29
II 24 32 20 45 39 35
III 30 40 26 40 47 42
IV 26 35 31 40 33 28
V 31 33 36 50 40 36
Variances* 23.8 35.3 26.8 32.5
Standard deviation 4.630334761 5.314132102 4.908156477 5.099019514
Mean 30.4 28.4 41.1 34
Coefficient of variation 15.23 18.71 11.94 15.00
Candida albicans (as TYMC)
I 22 13 14 40 22 17
II 15 8 11 34 22 26
III 8 15 10 17 23 18
IV 11 16 18 24 25 28
V 8 13 10 28 21 21
Variances* 19.7 11.8 46.0 23.5
Standard deviation 4.205948169 3.072458299 6.437390776 4.335896678
Mean 12.9 12.6 25.6 22
Coefficient of variation 32.60 24.38 25.15 19.71 *values are rounded
Table 18 – y-intercept given by the various linear models of each test organism (values are taken from Tables 5-13 and Figures 1-9)
Test organism y- intercept
Pseudomonas aeruginosa 0.10627784
Bacillus subtilis 0.221498942
Staphylococcus aureus 0.15914002
Escherichia coli 0.22631139
Salmonella enterica 0.1704531
Candida albicans (TAMC) -0.10322136
Candida albicans (TYMC) -0.01328163
Aspergillus brasiliensis (TAMC) 0.17211804
Aspergillus brasiliensis (TYMC) 0.07099427
![Page 32: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/32.jpg)
Pharmeuropa Bio&SN | February 2016 79
Table 19 – Tests of homogeneity of variances (F-test) for the comparison of the precision between the pour-plate (Ph. Eur.) and SimPlate methods
Method Strain (concentration) Session 1 / 2 Session 2 / 3 Session 1 / 3
Ph. Eur.
Bacillus subtilis (< 102) 0.466234542 0.148354556 0.460479217
Bacillus subtilis (106 to < 107) 0.334658401 0.937965895 0.374105935
Candida albicans (< 102) 0.018149254* 0.145444453 0.319967749
Candida albicans (106 to < 107) 0.172864906 0.877672886 0.131451255
SimPlate
Bacillus subtilis (< 102) 0.9009383 0.9009383 0.313695112
Bacillus subtilis (106 to < 107) 0.05218752 0.075539 0.839900692
Candida albicans (< 102) 0.284192886 0.7830977 0.417625844
Candida albicans (106 to < 107) 0.667874595 0.256980062 0.12874611
* p-value is <0.05
Table 20 – Microbial counts of tested strains (CFU/plate) - inoculations were done in products diluted 1:10
Strain Incubation timeSimPlate
Recovery*Plate count
Recovery*with product
without product
with product
without product
Bacillus subtilis
24h 27 23 1.2 n. p. -
28h 27 23 1.2 n. p. -
48h 27 24 1.1 n. p. -
3 days (Ph. Eur.) 32 24 1.3 18 18 1.0
Salmonella enterica
24h 25 37 1.5 n. p. -
40h 21 50 2.4 n. p. -
3 days (Ph. Eur.) n. d. 66 - 22 21 1.0
Pseudomonas aeruginosa
24h n. d. 17 - n. p. -
40h n. d. 58 - n. p. -
3 days (Ph. Eur.) n. d. 87 - 9 8 1.1
Staphylococcus aureus
24h n. d. 14 - n. p. -
40h n. d. 84 - n. p. -
3 days (Ph. Eur.) n. d. 92 - 12 11 1.1
Escherichia coli
24h 32 36 1.1 n. p. -
28h 32 37 1.2 n. p. -
48h 24 40 1.7 n. p. -
3 days (Ph. Eur.) 0** 56 - 19 19 1.0
Aspergillus brasiliensis
56h n. d. n. d. - n. p. -
72h n. d. 24 - n. p. -
5 days (Ph. Eur.) 39 48 1.2 25 29 1.2
Candida albicans
56h n. d. n. d. - n. p. -
72h n. d. 13 - n. p. -
5 days (Ph. Eur.) n. d. 13 - 9 8 1.1
*results are rounded; **colouration is the same in all wells; n.d: not determinable; n. p: not performed
![Page 33: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/33.jpg)
80 Alternative to Ph. Eur. pour-plate method for detection of microbial contamination
Table 21 – Microbial counts of tested strains (CFU/plate) - inoculations were done in product diluted 1:100
Strains Incubation timeSimPlate
Recovery*Plate count
Recovery*with product
without product
with product
without product
Bacillus subtilis
24h 75 81 1.1 n. p. -
28h 77 81 1.1 n. p. -
3 days (Ph. Eur.) n. d. n. d. - 31 27 1.1
Salmonella enterica
24h 54 44 1.2 n. p. -
28h 56 46 1.2 n. p. -
3 days (Ph. Eur.) n. d. n. d. - 24 27 1.1
Pseudomonas aeruginosa
24h 21 16 1.3 n. p. -
28h 21 16 1.3 n. p. -
3 days (Ph. Eur.) 23 22 1.0 8 7 1.1
Staphylococcus aureus
24h 33 30 1.1 n. p. -
28h 33 30 1.1 n. p. -
3 days (Ph. Eur.) 33 30 1.1 26 30 1.2
Escherichia coli
24h 34 39 1.1 n. p. -
28h 47 39 1.2 n. p. -
3 days (Ph. Eur.) n. d. n. d. - 22 25 1.1
Aspergillus brasiliensis
56h 0 0 - n. p. -
72h 43 48 1.1 n. p. -
5 days (Ph. Eur.) 52 50 1.0 19 21 1.1
Candida albicans
56h 0 0 - n. p. -
72h 16 17 1.1 n. p. -
5 days (Ph. Eur.) n. d. n. d. - 18 21 1.2
*results are rounded; n.d: not determinable; n. p.: not performed
Table 22 – Microbial counts of Candida albicans and Aspergillus brasiliensis (CFU/plate). Inoculations were done in product diluted 1:100
Strain Incubation timeSimPlate
Recovery*Plate count
Recovery*with product
without product
with product
without product
Candida albicans
56h 0 0 - n. p. -
70h 24 31 1.3 n. p. -
77h 24 31 1.3 n. p. -
5 days (Ph. Eur.) n. d. n. d. 15 21 1.4
Aspergillus brasiliensis
56h 0 0 - n. p. -
70h 131 172 1.3 n. p. -
77h 139 174 1.3 n. p. -
5 days (Ph. Eur.) ** ** - 53 52 1.0
*results are rounded; ** growth not detectable, colour change on the whole plate; n. d.: not determinable; n. p.: not performed
![Page 34: Alternative to Ph. Eur. pour-plate method for detection of ... · for detection of microbial contamination in non-sterile pharmaceutical preparations A. Palicz, A. Paul, A. Hofmann,](https://reader033.vdocument.in/reader033/viewer/2022051601/5ae035e07f8b9a97518cf333/html5/thumbnails/34.jpg)
Pharmeuropa Bio&SN | February 2016 81
Table 23 – Summary of all values from the validation (product diluted 1:100)
Test organism
Recovery
factor SimPlate
Recovery
factor Ph. Eur. Method
Factor
SimPlate vs. Ph. Eur.
Bacteria
Pseudomonas aeruginosa 1.3 1.1 2.3
Staphylococcus aureus 1.1 1.2 1.0
Bacillus subtilis 1.1 1.1 3.0
Salmonella enterica 1.2 1.1 1.6
Escherichia coli 1.2 1.1 1.6
Yeasts and Moulds
Candida albicans 1.1 1.2 1.2
Aspergillus brasiliensis 1.1 1.1 2.3