Chapter 10
Bioavailability Studies
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Bioavailability - Bioequivalence (BA/BE) study characteristics
With recently introduced products properly conducted bioavailability studies will have been performed before the product is allowed to be marketed. However products which were approved some time ago may not have been tested as thoroughly. It is therefore helpful to be able to evaluate the testing which may have been undertaken. There are a number of situations where a pharmacist may be required to evaluate bioavailability study testing. When selecting drug products for a prescription, product performance should be a most important criteria. Review of the Electronic Orange Book provided by the F.D.A. is an essential part of this process. Once it is established that two or more products are equivalent, then the choice of brand can be made on the basis of economic factors including cost and availability.
The evaluation of a drug product bioavailability study involves the consideration of various factors.
Drug
The drug substance in each product must be the same. Bioavailability studies are conducted to compare two or more products containing the same chemical substance. We can't compare different chemical substances. The apparent volume of distribution and kel can be quite different for different drug substances, thus no interpretation of the results is possible. The first rule of bioavailability testing is that you compare the drug products with the same drug in each dosage from.
The only time that this rule may be relaxed is in the case of pro-drug administration. A pro-drug is a compound which will form the drug of interest in the body. In this case it may be appropriate to compare the delivery of a dosage form containing the drug with another dosage form containing a pro-drug. This testing is generally conducted to evaluate the usefulness of the pro-drug, rather than a strict comparison of the drug products. Once the usefulness of the pro-drug is demonstrated comparisons between dosage forms all containing the pro-drug should be undertaken to evaluate the drug product performance.
In the case of bioequivalence studies the drug materials must be pharmaceutical equivalents or pharmaceutical alternatives.
Drug product
Figure 10.4.1 Plot of Cp versus Time after IV and IM Administration. NOTE: AUC are the same
Usually the comparison is made between two (or more) similar products, containing exactly the same chemical substance. However, in bioavailability testing different dosage forms can be compared (when they contain the same drug). For example we could compare an IM dosage form with an IV dosage form.
By calculating the AUC values we can determine the absolute bioavailability of the IM dosage form. In this case it appears to be close to 100%. The rate of absorption for the IM dose can be determined also, but of course no comparison is possible.
Figure 10.4.2 Plot of Cp versus Time for A and B with B having Slower Absorption
Alternately we could compare brand A tablet with brand B tablet or capsule.
By comparing the AUC values and ka values we can make comparisons concerning both the extent and rate of absorption. In this case A appears to be faster than B but the extent of absorption doesn't appear to be all that different. These products would not be bioequivalent.
Subjects
A number of factors of concern include health, age, weight, enzyme status, number. Studies with humans must be carefully evaluated and approved by an Institutional Review Board (IRB). There must be an optimal risk/benefit ratio and given that in most bioavailability studies (with healthy volunteers) there is little direct benefit to the individual any risks should be minimal. All subjects must give informed consent that includes a requirement that they be provided with clear descriptions of their risks and benefit to participation.
Health
Usually a study is designed so that each subject takes each product in turn. Thus the effect of the individual subject can be eliminated or reduced. Such a study design is called a cross-over design. Even though each subject will act as their own control it is usually best to have subjects of similar kinetic characteristic so that major variations are not introduced. Thus healthy volunteers are often preferred by drug product evaluation studies. Informed consent should be obtained from each volunteer and some biochemical and medical examination will be used to confirm their medical state. For some drugs there may be special disease states which may cause the exclusion of some volunteers. For example, in one study we looked at propranolol products, and otherwise healthy volunteers with a past history of asthma were excluded from this study.
Age
As you will see later, age can have a significant effect on drug pharmacokinetics. Elderly patients and young children can have quite different kinetics compared with young adults. In the interest of a better matched group, subjects between the ages of 18 to 35 years are preferred. Kinetic changes usually aren't important until age greater than 60.
Weight
The apparent volume of distribution is usually proportional to weight in subjects of normal weight for height. However, in overweight (or underweight) subjects the V in L/kg maybe somewhat different. Again to better match the subjects, normal weights are preferred. Life insurance weight tables may be useful.
Enzyme status
Smokers or subjects taking certain other drugs may have altered kinetics for the drug of interest. This can be caused by alteration of enzyme activity or by drug-drug interactions. These effects add complications to a study and an attempt is usually made to minimize these factors.
Number
The number of subjects included in the study should be sufficient to see any real (maybe 20% variation) differences in bioavailability. Usually 10 - 20 subjects are used in these studies. In clinical studies where the end-point is a clinical response, much larger numbers are required because of the greater variability in clinical response. For drugs which are extensively metabolized there can be considerable between subject variability in AUC, tmax and Cppeak values and a larger number of subjects may be required to produce the required statistical power, the ability to distinguish between non-equivalent products.
Assay
The same assay method should be used for all phases of the study. It is not much use using one assay for product A samples and another assay for product B samples. This wouldn't be done in a single study, however, if you were trying to compare the results from one study with those from another, different assay methods may have been used. For example products A and B may have been compared with one assay method. In another study products B and C may have been compared with a second assay method. Comparison of products A and C may not be valid. One assay method may pick up an interference such as a metabolite which is not indicative of the drug concentration or the bioavailability. The assay method should be sensitive and specific (An, 2018).
Design
Usually a complete cross-over design is used. With this design each subject receives all products with a wash-out period between each dose administration.
Figure 10.4.3 Figure Showing Concentrations After Two Separate Drug Administrations
Some example study designs.
Table 10.4.1 Two Product Example
|
Week 1 |
Week 2 |
Group 1 |
A |
B |
Group 2 |
B |
A |
Table 10.4.2 Three Product Example
|
Week 1 |
Week 2 |
Week 3 |
Group 1 |
A |
B |
C |
Group 2 |
B |
C |
A |
Group 3 |
C |
A |
B |
Group 4 |
A |
C |
B |
Group 5 |
C |
B |
A |
Group 6 |
B |
A |
C |
When more than 3 or 4 products are involved it has been suggested that a different design is used whereby each subject will get maybe 3 or 4 products of a possible 8 to 12. This type of design, possibly an incomplete block design, usually requires more subjects to get the same information, but it does mean that each subject is not required to take as many doses. It is harder to recruit subjects for longer studies.
Data analysis
Statistics
The rate of absorption can be characterized by the ka value and also the time of peak concentration. The extent of drug absorption is characterized by the F value or the peak concentration or total AUC values. Any differences in the average values of these parameters can then be analyzed statistically to determine the significance of the differences. The 5 % confidence levels is usually used as the criteria of acceptance. The analysis of variance is a technique for separating the effect of product, subject, and sequence. The significance of each of these factors can be tested.
Table 10.4.3 Analysis of Variance Table for Three-Way Cross-Over Study
Source of Variation |
Degrees of Freedom |
SS |
MS |
F |
Significance Level |
Total |
35 |
44.6 |
- |
- |
- |
Subject |
11 |
28.3 |
2.58 |
10.1 |
p < 0.001 |
Week |
2 |
0.14 |
0.068 |
0.27 |
n.s. |
Treatment |
2 |
11.0 |
5.55 |
21.8 |
p < 0.001 |
Residual or Error |
20 |
5.09 |
0.255 |
- |
- |
In this example two effects are significant. There appears to be a significant effect due to treatment and subject. This would indicate that the subjects are significantly different from each other and that the treatments are significantly different in terms of the parameter measured. It is quite common that Cp or AUC values are significantly different for different subjects, because of their different weights or size. The different treatments would appear to be NOT bioequivalent.
By these studies the relative bioavailability of two or more products can be determined. Hopefully with proper testing we can ensure that drug products labeled to contain equivalent chemical amounts will be bioequivalent as well.
Generate typical data from a simulated bioavailability study and analyze the data using an Analysis of Variance (ANOVA).
SAS file
DATA BIOAV;
INPUT FORM GROUP SUBJ AUC;
CARDS;
...data here...
PROC MEANS;
PROC ANOVA;
CLASSES FORM GROUP SUBJ;
MODEL AUC = FORM GROUP SUBJ;
MEANS FORM GROUP SUBJ /DUNCAN;
References
- FDA Guidance Statistical Approaches to Establishing Bioequivalence
- An, G., Schmidt, R. L., Mock, D. M., Veng Pedersen, P., & Widness, J. A. (2018). Overlooked Issues on Pharmacokinetics Data Interpretation of Protein Drugs-a Case Example of Erythropoietin. The AAPS Journal, 21(1), 6. http://doi.org/10.1208/s12248-018-0269-7
Student Objectives for this Chapter
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