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Debunking a Common Pharmacy Myth: The 80-125% Bioequivalence Rule

Do you understand the FDA's definition and requirements for bioequivalence?

One of the most common myths I hear from fellow pharmacists is that a generic product must contain between 80% and 125% of the brand-name product in order to be considered bioequivalent. In reality, that isn’t how the FDA determines bioequivalence.

This article walks through the myth of the 80-125% rule, the reality of the FDA’s bioequivalence requirements, the reasons behind the misunderstanding, and the practical implications for pharmacists.

The Myth

When a brand-name product’s patent expires and loses its exclusivity protection, generic versions are permitted to be launched in the market. The FDA requires that the generic product must be determined to be pharmacokinetically bioequivalent to its branded counterpart in order to ensure the generic’s safety and efficacy.

The FDA defines bioequivalence as the absence of a significant difference in the rate and extent to which the active ingredient becomes available when administered at the same molar dose under similar conditions in an appropriately designed study.

Many in health care mistakenly believe that the FDA requirement for bioequivalence permits a generic product to contain anywhere from a minimum of 80% to a maximum of 125% compared with the reference, or brand-name, product. Under this belief, the generic drug concentration could have up to a 45% total variance to the brand-name product.

I’ve personally heard this myth from a number of pharmacy students, technicians, and pharmacists when explaining the difference between generic and brand-name products. Additionally, this myth is frequently perpetuated in message boards, news outlets, and even some pharmacy schools.

The Reality

The truth behind the FDA’s requirements for bioequivalence is actually much more complicated.

In order to determine bioequivalence, a randomized, crossover trial is conducted with both the generic drug being assessed and the brand-name drug as the control. In these studies, a number of pharmacokinetic (PK) parameters are assessed, including maximum serum concentration of a drug (Cmax) and drug exposure over time (AUC).1

These parameters help assess how the rate and extent of the availability of the generic drug compares to the control. As the FDA requires, there must be no significant difference in the rate and extent to be deemed bioequivalent.

It’s true that the PK values are required to fall between 80% and 125% of the reference value in these randomized, crossover trials. More importantly, however, the entire 90% confidence interval (CI) of the observed PK value must also fall between 80% and 125%.

As a general reminder, CIs are ranges of values we can be confident the true result falls, which in this case is 90% of the time.

To explain bioequivalence with an example, imagine that a brand-name product was shown to have an AUC of 100 units in a crossover study. In the same study, let’s say the generic product was shown to have an observed mean AUC of 93 with a calculated 90% CI of 84-110. Because the FDA requires the mean AUC of the generic product as well as its entire 90% CI must fall between 80 and 125 units, this would meet the bioequivalence requirement.

Of course, this is a very simplified explanation. In reality, multiple PK values are being assessed based on ratios of the generic and reference drug, and CIs are being calculated around the observed means. The key takeaway is that because the entire 90% CI has to fall within the 80-125% range, the actual PK values of the generic drug must be very close to the mean PK value of the reference product.

Using the statistical criteria required by the FDA, it would be difficult for any generic product to differ more than 10% from the reference to meet the CI requirements, and it would be nearly impossible to meet the CI requirements if the difference approached 20%.

According to 1 FDA study, the mean difference for AUC values between test and reference products was found to be 3.5% in the 2-year period following the Waxman-Hatch Act, and 80% of the absolute differences between generic products approved since 1984 and the corresponding innovator products were within a 5% range.2

Where did the specific limits of 80% and 125% originate from? According to the FDA this is based on a clinical judgment that a test product with bioavailability that falls outside this range should be denied market access. A 90% CI is used, since a 5% statistical error is allowed at both the upper and the lower limits. Therefore, the total error is 10%, generating the 90% CI.

Reasons Behind the Misunderstanding

At face value, having a predefined upper and lower limit sounds like a logical explanation for determining bioequivalence. In fact, this is exactly how bioequivalence was originally defined.

Bioequivalence testing originated in the early 1970s with the ±20 rule. This allowed bioequivalence to be concluded if the average bioavailability of the test formulation fell within ±20% of the reference formulation’s.

According to a separate study, “the shortcomings of this approach were immediately evident, since such a criterion would theoretically allow the parameters of generic product A to differ from the reference (innovator) product by +20%, while allowing the parameters of generic product B to differ from the reference product by -20%. The net difference between the 2 generic products A and B would then be as much as 40% and, therefore, beyond the limits of therapeutic equivalence as originally conceived.”3

In response, the FDA adopted a powered approach in the early 1980s. However, both approaches were discontinued by the FDA in 1986 because of public concern about bioequivalence and were subsequently replaced by the 90% CI approach in 1992, which remains the current criteria for bioequivalence decisions.

Another reason for the misunderstanding involves the complexity of the FDA’s current requirements. Understanding a predefined range is much more intuitive and easier to grasp than the reality of multiple PK parameters having to fit within a narrow CI.

Finally, because the FDA’s bioequivalence requirements are so frequently misinterpreted, many pharmacy schools are perpetuating the myth. Anecdotally, the 80-125% absolute range is how I recall learning bioequivalence in pharmacy school.

Practical Implications for Pharmacists

Some may claim that the difference between the myth and reality of the 80-125% rule is insignificant. After all, it’s much easier to tell a patient that a generic product can be expected to fall within an 80-125% window then to explain that the PK values and their 90% CIs must fall within that same range.

Because pharmacists are often referred to as medication experts, however, it’s important to understand the true definition and requirements for determining bioequivalence. To claim that a generic product may fall within an 80-125% range to the brand-name product is incorrect and may result in some patients reconsidering taking a generic. After all, that 45% net difference could dissuade generic use.

Besides, “clinicians who do not realize this may favor branded drugs over generics, thereby substantially increasing the cost of treatment, or they may be skeptical of the efficacy of generics, thereby diminishing the placebo element in the psychopharmacologic response to generics if the skepticism is consciously or unconsciously communicated to the patient.”1

Of note, the total cost of brand-name drugs over a 3-year period in the United States was $147 billion, with brand-name drug overuse accounting for as much as $73 billion.

References

1. Andrade C. Bioequivalence of generic drugs: a simple explanation for a US Food and Drug Administration requirement. J Clin Psychiatry. 2015;76(6):e742-e744. doi:10.4088/JCP.15f10094.

2. Buehler G. History of bioequivalence for critical dose drugs. FDA. fda.gov/downloads/%20AdvisoryCommittees/…/UCM209319.pdf. Published April 13, 2010. Accessed June 6, 2016.

3. Henderson JD, Esham RH. Generic substitution: issues for problematic drugs. South Med J. 2001 Jan;94(1):16-21.

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