Did you know that 84% of the 4 billion prescriptions written each year are for generic drugs? Clearly, generics are a big business. Regulatory agencies, such as the FDA, require generic drug manufacturers to show that generic drugs are bioequivalent to the reference drug.
Bioequivalence (BE) studies can also be required for pharmaceutical variations made to drugs. These pharmaceutical variations might include changes in manufacturing site, raw material suppliers, or minor changes in formulation. Conducting bioequivalence studies is time-consuming and expensive. In this blog post, I’ll discuss how an alternative method— the Level A IVIVC (in vitro in vivo correlation)— can support waivers for BE studies to save time and money.
What is IVIVC?
When a sponsor makes variations to a drug, regulatory agencies require several pieces of supporting evidence that demonstrates that the product is still safe and effective. This evidence can include:
- Quality Overall Summary
- Batch data
- Stability data
- Level A IVIVC
IVIVC is built on the premise that the in vitro dissolution characteristics of a drug can serve as a surrogate for a BE study. This type of analysis is attractive to sponsors because dissolution assays are cheaper and faster to perform than clinical testing. It also provides reassurance that a positive benefit/risk balance for patients is maintained throughout the life of a drug. There are several levels of IVIVC. They are as follows:
Level A correlation
An IVIVC that correlates the entire in vitro and in vivo profiles has regulatory relevance and is called a Level A Correlation. This level of correlation is the highest category of correlation and represents a point-to-point relationship between the in vitro dissolution rate and the in vivo input rate of the drug from the dosage form.
Level A correlation is the most preferred since it may allow a bio waiver for changes in manufacturing site, raw material suppliers, and minor changes in formulation. The purpose of Level A correlation is to define a direct relationship between in vivo data such that measurement of in vitro dissolution rate alone is sufficient to determine the biopharmaceutical rate of the dosage form.
Level B correlation
The level B IVIVC is based on the principles of statistical moment analysis. In this level of correlation, the mean in vitro dissolution time (MDT vitro) of the product is compared to either mean in vivo residence time (MRT) or the mean in vivo dissolution time (MDT vivo). A level B correlation does not uniquely reflect the actual in vivo plasma level curves. Also, in vitro data from such a correlation could not be used to justify the extremes of quality control standards. Hence, it is least useful for regulatory purposes.
Level C correlation
Level C correlation relates one dissolution time point (t50%, t90%, etc.) to one mean pharmacokinetic parameter such as AUC (the area under the concentration-time curve), Tmax (the time after administration of a drug when the maximum plasma concentration is reached) or Cmax (peak concentration). This is the weakest level of correlation. Only a partial relationship between absorption and dissolution is established since it does not reflect the complete shape of plasma drug concentration time curve, which is the critical factor that defines the performance of a drug product.
Due to its obvious limitations, the usefulness of a Level C correlation is limited in predicting in vivo drug performance. In the early stages of formulation development, Level C correlations can be useful when pilot formulations are being selected. Waiver of an in vivo bioequivalence study (biowaiver) is generally not possible.
Multiple Level C correlations
This level refers to the relationship between one or more pharmacokinetic parameters of interest (Cmax, AUC, or any other suitable parameters) and the amount of drug dissolved at several time points in the dissolution profile. Multiple Level C correlations may be used to justify a biowaiver provided that the correlation has been established over the entire dissolution profile with one or more pharmacokinetic parameters of interest. A multiple Level C correlation should be based on at least three dissolution time points covering the early, middle, and late stages of the dissolution profile. The development of a level A correlation is also possible, when multiple Level C correlations are achieved at each time point for the same parameter such that the effect on the in vivo performance of any change in dissolution can be assessed.
Level D correlation
It is not a formal correlation. It is a semi quantitative (qualitative analysis) and rank order correlation and is not considered useful for regulatory purposes. It can serve as an aid in the development of a formulation or processing procedure.
How are PK parameters predicted from drug dissolution profiles?
This can be achieved by first establishing an IVIVC model for a given API and the release technology used in the formulation development for a series of formulations with different release rates. When there is a new variation to the target (or marketed) formulation to be approved, the plasma concentration vs. time profiles are predicted using an IVIVC model for the existing product dissolution profile, and the dissolution profiles corresponding to the 10% lower and 10% upper dissolution limits.
The following pharmacokinetic parameters, Cmax and AUC, can then be calculated from the predicted concentration-time profiles for the target, upper limit (UL), and lower limit (LL). The Cmax and AUC ratios between each curve (UL/LL, UL/target, and LL/target) is then calculated. Finally, these data are used to assess whether the drug batches are bioequivalent to each other and whether the proposed dissolution limits are appropriately supported. Most importantly, this analysis reveals whether the proposed formulation change will significantly impact the quality, safety, or efficacy of the drug.
What are some tools to help me with this work?
The IVIVC Toolkit for Phoenix WinNonlin is a software tool that can be used for developing the Level A IVIVC correlation outlined in a FDA guidance to correlate the in vitro dissolution profile of a dosage form with the in vivo PK profile. Pharmacokineticists and formulation scientists can use it to:
- Generate supporting data using IVIVC for biowaivers for expensive bioequivalent studies
- Support deconvolution and convolution methods
- Run multiple inputs over multiple responses at once
- Easily manage data and workflow through the IVIVC wizard
- Use custom correlation equations
- Assess the time-scale of dissolution experiments in Levy plots
- Summarize deconvolution and correlation results in plots
Watch this webinar to learn more!
We hosted a webinar with Dr. Terry Shepard of the Medicines and Healthcare Products Regulatory Agency (MHRA). Watch this webinar to learn the regulatory applications of IVIVC including the specification settings and biowaivers. She also explained the implications of:
- Choice of IR reference formulation
- Choice of test MR formulations
- Study design
- MR formulation program design
Accompanying Dr. Shepard was Dr. Venkateswari Muthukrishnan from Certara, who presented a case study where IR data was used to estimate the UIR and further develop an IVIVC model to select the optimal formulation. I hope that you’ll watch it and let me know what you think in the comments section!
