SAP Mejoral 500 Bioequivalence Study.pdf. Version Document Identifier Effective Date eldo_clinical_doc Reason For Issue

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1 Page 1 of 8 1 OBJECTIVE 1.1 General Demonstrate the bioequivalence of test medication MEJORAL 500 TABLETS from GLAXOSMITHKLINE MÉXICO S.A. DE C.V., compared to reference medication TYLENOL CAPLETS, marketed by JANSSEN CILAG DE MÉXICO, S. de R.L. DE C.V. in Mexico, both products containing 500 mg of paracetamol and after oral administration of a single dose in healthy fasting volunteers. 1.2 Specific Establish the C max, T max, area under the curve of zero at t (AUC 0-t ) and the area under the curve of zero to infinity (AUC 0-inf ), for each formulation of tablets with 500 mg of paracetamol (A, reference product, Tylenol Caplets and B, test product, Mejoral Tablets) Statistical comparison of bioavailability for the pharmaceutical formulations studied, containing metformina, to establish or nor the existence of bioequivalence. 2 EXPERIMENTAL DESIGN The design of the study complies with the provisions in Official Mexican Standard NOM-177-SSA1-2013, which establish the tests and procedures to demonstrate a medication is interchangeable. Requirements to which Authorized Third Parties must be subject when performing interchangeability tests. Requirements to perform biocompatibility studies. Requirements to which Authorized Third Parties, Research Centers, or Hospitals performing biocompatibility tests must be subject to. Study was monocenter, single blind, randomized, single dose, two periods, two sequences, crossover, in healthy volunteers under feeding conditions. A total of 28 healthy volunteers, men and women, will participate in the study, with a washout period of 72 hours between the two phases of administration. Each one of the 28 volunteers will be randomized to receive one of two possible sequences of medication administration (AB or BA), where treatment A corresponds to reference medication and B to test medication. All volunteers completing the study (appraisable) will be included in the corresponding statistical analysis. Volunteers will be considered clinically healthy through the following laboratory and imaging tests: PREPARED BY: REVIEWED/AUTHORIZED BY REVIEWED/AUTHORIZED BY: Responsible of Pharmacokinetics/ Responsible for Biostatistics Quality Assurance Manager Quality Deputy Manager DATE: DATE: Page 1 of 9

2 Page 2 of 8 Complete medical history. Hematological analysis: leucocytes, erythrocytes, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, corpuscular hemoglobin mean concentration, red cell distribution width, platelets, neutrophils, lymphocytes, monocytes, eosinophils, basophiles, LUC (large unstained cells). Blood chemistry of 27 elements. Urinalysis. Hepatitis B and C test. HIV test. Vdrl VDRL test. FSH follicle-stimulating hormone to women. β-hcg to women during screening visit. Test to detect substance abuse during screening visit and before each study period. Alcohol consumption test during screening visit and before each study period. Qualitative pregnancy test during screening visit and before each study period. Electrocardiogram Treatments were as follow: Reference medication (treatment A) International Common Denomination (ICD) Generic Denomination Commercial Name Pharmaceutical Form Formula Administration Dose Lot Expiration Manufacturer SSA Registry Paracetamol Paracetamol Tylenol Caplets Tablets Each tablet contains 500 mg paracetamol 500 mg (one tablet) <Pending> <Pending> JANSSEN CILAG DE MÉXICO, S. DE R.L. DE C.V.. 140M87 SSA Page 2 of 9

3 Page 3 of 8 Test medication (treatment B) International Common Denomination (ICD) Generic Denomination Commercial Name Pharmaceutical Form Formula Administration Dose Lot Paracetamol Paracetamol Mejoral 500 Tablets Tablets Each tablet contains 500 mg paracetamol 500 mg <Pending> Expiration < Pending > Manufacturer GLAXOSMITHKLINE Each volunteer was assigned one of the two sequences of the study (AB or BA), in consecutive order according to their arrival to the IFaB facility, and to the randomization list created for the study, and given by the Responsible of Biostatistics to the Clinical Area. Blood samples were collected and processed to obtain the plasma before each administration (predose samples) and at 0.250, 0.333, 0.500, 0.667, 0.833, 1.000, 1.250, 1.500, 1.750, 2.000, 4.000, 6.000, 8.000, y hours, after the administration of each medication. 3 HYPOTHESIS Ho: The rate (difference for log transform) between the average bioavailability of test medication and reference medication not belonging to a range of % for the ABC and the C max. Ha: The rate (difference for log transform) between the average bioavailability of test medication and reference medication belonging to a range of % for the ABC and the C max. 4 SOFTWARE VERIFICATION The verification of software Phoenix/WinNonlin version 6.4., will be performed according to the provisions in PNO EST-PAQ-003 current version, which establishes that such verification will be carried out according to the chapter Testing the Installation in the current Getting Started Guide manual, using the examples contained in that same chapter. 5 DATABASE DESCRIPTION AND GENERATION Page 3 of 9

4 Page 4 of 8 The database corresponding to code decoding will be carried out by the Pharmacokineticist and the Quality Assurance Responsible, and must contain for each drug the information of the volunteer, period, sampling date, nominal sampling time, real sampling time, concentration and identification code for each sample, these information will be transferred to the corresponding Phoenix/WinNonlin template to perform the pharmacokinetic and statistical analysis. Both, databases and results obtained from them will be integrated to Master File with the corresponding printed copy. The treatment and sequences information will be added after PK estimation. In general, all the subjects must be included in the statistical analysis, except for the following cases: Investigation subjects that in a crossover design miss one of the study periods. Investigation subjects that in a crossover design do not provide appraisable data, both in test medication as in reference test, must not be included in the statistical analysis according to Appendix C Standards NOM SSA Subjects with predose plasma concentrations. In this case, those volunteers with a predose concentration less or equal to 5% of their C max value obtained in the same period, may be included without any adjustment in all the corresponding pharmacokinetic calculations and statistical analysis; otherwise, volunteer must be eliminated from the bioequivalence evaluation. An investigation subject without measurable concentrations or with very low plasma concentrations for the reference medication or those in which the pharmacokinetic profile has not been appropriately characterized (T max, C max and elimination half-life determined with a minimum of three data (independent to C max ), must not be included in the statistical analysis. An investigation subject is considered to have very low concentrations if the AUC is less than 5% of the geometric mean of the AUC for the reference medication (it must be calculated without the inclusion of the data from investigation subjects with atypical values). The exclusion of data due to this reason will only be accepted under scientific justification and prior review of the case by the COFEPRIS. The elimination of volunteers due to vomit or diarrhea. Data from investigation subjects who experienced vomit or diarrhea within the therapeutic dosification interval (in this case 16 hours [Tylex, 2015]), in a given period, may be eliminated from the statistical analysis. If a sample shows a non-quantifiable or non-detectable value during the profile, such value will be considered as aberrant, will be marked as XX in the database, and will not be considered for the calculation of the pharmacokinetic parameters. 5.1 DEMOGRAPHIC AND STATISTICAL DATA Demographic data for age, weight, size, and body mass index (BMI) for the volunteers enrolled in the study and which were provided by the Clinical Unit will be transferred to the SAS template to perform the corresponding descriptive statistics, through the calculation of the media, standard deviation, Standard Error, Minimum Value, Median, Maximum Value, and Coefficient of Variation. 5.2 DRUG CONCENTRATION IN BIOLOGICAL FLUIDS DATA Descriptive statistics will be performed from the code decoding database, for each sampling time (nominal) and medication, calculating the number of data for each time (N), media, standard deviation, Standard Error, Minimum Value, Median, Maximum Value, and Coefficient of Variation. Page 4 of 9

5 Page 5 of COMPARATIVE INDIVIDUAL PLASMA PROFILES Comparative graphs will be generated for plasma concentration against real time for both medications and volunteer, at normal scale and at semilogarithmic scale. 5.4 COMPARATIVE AVERAGE PLASMA PROFILES From the results of descriptive statistics mentioned in paragraph 5.2, comparative graphs will be generated for media concentration (± standard error) against nominal time for both medications, at normal scale and at semilogarithmic scale. 5.5 CALCULATION OF PHARMACOKINETIC PARAMETERS From plasma concentration and real time data for each volunteer, the following pharmacokinetic parameters must be calculated using Phoenix/WinNonlin 6.4 computer software: o C max : Maximum plasma concentration obtained in a graphic form, from the plasma concentration profile with respect to time. o T max : Time elapsed from the administration until the maximum plasma concentration takes place, obtained in a graphic form, from the plasma concentration profile with respect to time. o AUC 0-t : Area under the curve of plasma concentration from the administration to 16 hours (last sampling time) calculated by the trapezoid method. o AUC 0-inf : Area under the curve of plasma concentration from the administration to time extrapolated to infinite. o K el : constant of elimination: Calculated from the lineal portion of the plasma concentration profile with respect to time (in semilogarithmic scale) o Elimination half-life: Calculated from the ratio Ln(2)/K el o TMR 0-inf : Mean residence time extrapolated to infinite time. 5.6 DESCRIPTIVE STATISTICS OF PHARMACOKINETIC PARAMETERS Once the pharmacokinetic parameters have been calculated, the corresponding descriptive statistic will be performed per treatment, considering at least the number of data for each parameter (N), geometric mean, arithmetic mean, standard deviation, Standard Error, Minimum Value, Median, Maximum Value, and Coefficient of Variation. To facilitate the comparison of the pharmacokinetic parameters of T max, C max, AUC 0-t and AUC 0-inf the following must be reported for each subject: administration sequence of medications, value of pharmacokinetic parameter obtained in the treatments, as well as the difference, ratio, and natural logarithm of the ratio, between treatments, if applicable. The report may include histograms of these tabulated values, since visually they may provide the basis for the evidence of bioequivalence. 5.7 BIOEQUIVALENCE STATISTICS A database must be generated containing at least the following variables: Page 5 of 9

6 Page 6 of 8 Subject, sequence, period, medication, T max, C max, AUC 0-t and AUC 0-inf. From this database, bioequivalence statistics will be generated with logarithmically transformed data. Statistical tests and their acceptance criteria are detailed in Standard Operating Procedure EST-BIO-004 Guideline for the Pharmacokinetic and Statistical Evaluation. The main interest in the bioequivalence evaluation is to limit the risk of erroneously accepting the bioequivalence of a medication. This risk, also called Consumer Risk shall be limited to values less than 5%. Confidence intervals will be determined by parametric statistical methods (ANOVA). ANOVA From the pharmacokinetic parameters an analysis of variance will be applied to the logarithm of the pharmacokinetic parameters: ABC and C max ; using a crossover design at random for the two treatments, two periods and two sequences (2x2). The statistical model is: Y = + Se + Su + P + F + ijkl i j( i) k l ijkl; Where: Y ijkl = Pharmacokinetic parameters to evaluate, possible log-transformed. µ = General media of the pharmacokinetic parameter to evaluate. Se i = Effect of the administration sequence. Su j(i) = Effect of the subject nested in the sequence (inter-subject variability). P k = Effect of the administration period. F l = Effect of the medication (treatment). ijkl = Experimental error (intra-subject variability). The ANOVA will be performed in the Phoenix/WinNonlin software, considering the sum of squares type III, assessing the following effects: Sequence Period Formulation The presence of a possible effect of the formulation is tested with the hypothesis by using as an error term a ε: Ho : F r = F p Ha : F p vs. r F The presence of a possible effect of the administration period is tested with the hypotheses: Ho : P = P 1 2 Ha : P P vs. 1 2 The presence of a possible effect of the sequence of administration is tested with the following hypothesis, by using as error term the subject nested in the sequence. Ho : Se r = Se p Ha : Se p vs. r Se Page 6 of 9

7 Page 7 of 8 Statistical criterion to evaluate the effect of the period and sequence: it is determined there is no effect of the Product, Period and Sequence, if the value of the probability obtained is higher than Classic confidence intervals The statistic for the bioequivalence will consist in evaluating the difference between the assessed treatments, through the logarithmic comparison of the pharmacokinetic parameters: C max, ABC 0-t and ABC 0-inf. The statistical analysis will be performed on the bioequivalence of the medications considering the construction of classic confidence intervals, and it will conclude in favor of the bioequivalence if the calculated limits are included within the range of 80 to 125% for C max and ABC, this with logarithmically transformed data. They must be analyzed with a confidence level of 90% and the power of the statistical test must be higher than 0.8. Consider that the statistical power is commonly used as the basis for determining the number of volunteers. However, once bioequivalence statistics is applied, the value of the power obtained represents the significance of value estimation but not of a range of values. In this sense, the confidence intervals provide more information on the range of values that the estimator may take, thus they have more credibility than the value estimation. Therefore, the value of the power might only be taken as a merely descriptive value, but not conclusive. The power is related with the level of protection for the manufacturer (beta = 0.2), thus the possibility of concluding bioequivalence when it does not exist is null when confidence intervals result in compliance [Schuirmann, 1987]. Bioequivalence decision must be based in the compliance of the classical confidence interval. Schuirmman DJ. A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. J Pharmacokinet Biopharm, 1987, 15: Limit tests Limit tests are based on the rejection of the bioequivalence null hypothesis to conclude, with a level of significance alpha (0.05) and confidence level at 90%, that products are bioequivalent. Limit tests that will be applied are the two one-sided test of Shuirmann and the test of Anderson Hauck on the ratio between the means of the test and reference medications, for pharmacokinetic parameters of C max, ABC 0-t and ABC 0-inf. Classic confidence intervals must be within % Limit test conclude in favor of Bioequivalence if the probability that the ratio is lower than 80% and higher than 125 %, is less than Extreme Data The identification of extreme data will be performed using the SAS software version 9.2. The criterion to consider extreme data will be ± 2 according to NOM-177-SSA Determination of inter-subject and intra-subject extreme values will be performed with logarithmically transformed data. To facilitate their interpretation graphs will be elaborated in an open format, including residuals obtained in all the subjects participating in the study, both periods, for the pharmacokinetic Page 7 of 9

8 Page 8 of 8 parameters in which bioequivalence is based. The determination of the extreme data may be supplemented with bar-graphs and box diagrams. The elimination of extreme data must be statistically and scientifically justified, it must also be demonstrated that the data from such volunteer are also influential. In the event that the elimination of a volunteer shall apply due to extreme data, the bioequivalence statistical analysis must be performed with and without the data from such volunteer, and both results must be presented in the report. 6 CONCLUSION From the results generated in the statistical analysis a conclusion will be drawn on the acceptance or rejection of the null hypothesis, i.e., if the relation between the values of C max, AUC 0-t and AUC 0-inf of the reference medications (medication A) and the test medication (medication B), and for both drugs, is higher than 20%. Page 8 of 9

9 1.0; CURRENT; Most-Recent; Effective d580ad181d 07-Jul :54:05 SIGNATURE PAGE 07-Jul :33:21 Approved 07-Jul :53:43 Biostatistics Approval Page 9 of 9