Thomas A. Little, PhD, is president, Thomas A. Little Consulting and BioAssay Sciences, 12401 North Wildflower Lane, Highland, Utah 84003, USA, drlittle@dr-tom.com.

Thomas A. Little, PhD

Biosimilars go through the same rigorous evaluation of safety and efficacy as any other biological drug product or drug substance. Because there is prior knowledge and a grounded scientific understanding of the reference molecule, drug demonstration of comparability of the biosimilar molecule to a reference molecule may speed up and simplify the regulatory requirements for the biosimilar. Data requirements are determined on a case-by-case basis working with FDA and/or other health authorities (1).

Comparability is multi-faceted and typically includes clinical trials (pharmacokinetic [PK] profiles), animal studies, analytical comparability (functional and or structural) of the molecule, analytical method comparability where possible, process comparability (lot-to-lot), and in-process controls/monitors. Comparability in all cases is with respect to the reference drug/molecule compared to the biosimilar under evaluation.

Comparability for biosimilars is risk-based (2), and the level and complexity of the comparison is commensurate with the risk to safety and efficacy. Also, using a risk-based approach, the statistical method for demonstration of comparability can be likewise grouped into a three-tiered approach for comparison.

It is useful to group comparability methods into three distinct categories. Tier one is the most rigorous basis of comparison and is typically used for critical quality attributes (CQAs), clinical performance, and structural and functional analytical comparability. Tier one also includes process comparability for CQAs as well as analytical method comparability for CQAs. Tier two is for in-process controls or for other lower priority quality attributes that may be included in the characterization of a molecule. Tier three is for in-process monitors or other visual comparisons when a quantitative assessment is not practical or possible (3).

There are two techniques that may be used for determining comparability: 1) equivalence test and 2) K sigma comparison. Minimum sample sizes are three of more lots of the reference molecule and three or more of the comparison product lots. Measuring each reference and comparison lot three to six times will help to improve the understanding of the analytical error of the method. All analytical methods should have been qualified/validated prior to conducting the comparability studies. Equal number of lots in the comparison is recommended but not required. A sample size and power analysis of the comparison study design is generally required to demonstrate that the study design is adequately powered to reliably detect the mean differences used in the comparison.Evaluation of sample uniformity is also desirable but not required.

Tier one: comparability using equivalence test

The word biosimilar indicates that the protein/molecule in the comparability study is not bioidentical. Equivalence testing is used when one wants assurance that the means do not differ by too much. In other words, the means are practically equivalent. A threshold difference acceptance criteria is set for each parameter under test. The means are considered equivalent if the difference in the two groups is significantly lower than the upper practical limit and significantly higher than the lower practical limit. Typically a two one-sided t-test (TOST) is used to demonstrate equivalence once the acceptance criteria has been defined (4). Statistical software such as SAS/JMP should be used in the equivalence testing.

Setting comparability acceptance criteria

There are three different groups of response parameters that are used in an equivalence test: 1) two-sided specifications (upper specification limit [USL] and lower specification limit [LSL]), 2) one-sided USL only or one-sided LSL only, and 3) no specification limits. Practical differences should be viewed relative to a target, tolerance, or as a function of design margin (5). Acceptance criteria should be risk based (2); higher risks should allow only small practical differences and, conversely, lower risks should allow for marginally larger practical differences. Scientific knowledge, product experience, and clinical relevance should be evaluated when justifying the risk. The following risk-based acceptance criteria shown in 

 are not absolutes; however, they are typical risk-based acceptance criteria.

 Description of response parameters for three case scenarios.

 has a practical limit of four between the means of the reference and comparison CQA. The confidence interval must be fully inside the limits to be considered comparable. Sample size and power for every equivalence test must be determined and reported in the comparability report. The example in 

 indicates that, for this CQA, they are comparable. Equivalence tests control for the means difference and for the variation in the samples, the sample size, and a defined risk factor.

 Comparability demonstrated using an equivalence test. CQA is critical quality attributes.

Another acceptable method for showing comparability is based on a K sigma comparison. K sigma means testing is a bit simpler to perform and not as statistically rigorous. It takes the mean difference between the test article minus the reference and divided by the reference standard deviation for multiple lots and measurements per lot. This calculated value is called a z-score, and the absolute value of the z-score is reported as K sigma. Acceptance criteria are normally set at less than or equal to the 1.5 K sigma of the reference to demonstrate comparability. 

 shows the same data used in the equivalence test reported in K sigma.The advantage of this approach is there are no defined specification limits and it uses the sample means and variation to determine comparability.

 Comparability via K sigma comparison. CQA is critical quality attribute.

Tier two range tests are applied to in-process controls and those less critical quality attributes for which we still want to demonstrate comparability, but they do not have the same rigor as is used in the tier one equivalence or K sigma means tests. A formal risk assessment is used to determine a tier one, tier two, or tier three approach.

The following is the procedure for setting up and checking a range test:

Using the reference lots only fit for an appropriate distribution (e.g., normal, gamma, Weibull etc.)

Set limits for the range at either 99% (2.576 K sigma) or 99.73% (3 K sigma) (

 Range limits for the reference materials.

Using the reference limits demonstrates the percent of the comparison measurements that are within the reference limits (

 Percent of the biosimilar within the reference range limits. LSL is lower specification limit. USL is upper specification limit.

Acceptance criteria may be set at greater than or equal to 85%, 90%, or 95% based on risk.

Limits set from the reference materials using 3 K sigma are 57.4 and 97.0 and are then applied to the biosimilar to show comparability. Percent actual (

) equals the percent of measurements of the biosimilar that are within the range of the reference samples.

Tier three is used for attributes that are simply monitored during the production process or for quality attributes where quantitative analysis is either not possible or not desirable. Tier three simply uses graphical comparison or pictures of the molecular structure, the growth curve, sensor profile, power in a mixer, etc. In most cases a side-by-side graphical comparison or an overlay of the graphical analysis may be used in the demonstration of comparability. For tier three, no acceptance criteria are used; however, it is important to point out visual comparability where areas are similar and/or differences have been visually detected in the comparison. 

 shows a visual comparison of growth curves by location and change in scale. 

 Visual comparison of scale and location of bioreactor growth curves. VCD is viable cell density.

It is highly recommended to use a risk-based approach when performing biosimilar studies. 

 show examples of how that may be performed. 

 Tier one assessment and summary table. HMW is high molecular weight. LMW is low molecular weight. USL is upper specification limit. LSL is lower specification limit. CQA is critical quality attribute. TOST is two one-sided t-test. CI is confidence interval.

Selection of the responses, placing them in the appropriate tier evaluation based on their merit as a CQA of their influence and uncertainty (risk) on safety and efficacy, stating the method of comparison, defining acceptance criteria, and coming to a conclusion make organizing and reporting comparability clear and concise. A tier three summary table is also recommended to summarize the attributes evaluated in any conclusions.

 Tier 2 assessment and summary table. VCD is viable cell density. HCP is host cell protein. IPC is in process control.

Demonstration of comparability for biosimilars is a critical element for many drug companies. FDA’s involvement in the mapping out of data and study requirements for a specific drug is a critical step in demonstration of comparability. Once study areas have been defined and a clear road map of the attributes, the sampling plans, sample sizes, and methods of comparison have been established, the productivity of the development team in designing and executing protocols for comparability will be greatly improved. Correct organization and appropriate methods for demonstration of comparability aid both internal and regulatory health authority review of reported values in filings and submissions.

, Step 4 version (2005).
3. S. Chow, F. Song, and H. Bai, 

Specifications: Test Procedures and Acceptance Criteria for Biotechnological/Biological Products

Thomas A. Little, PhD, drlittle@bioassaysciences.com, is president of Bioassay Sciences.

Articles

It is important to use correct organization and appropriate methods for demonstrating biosimilar comparability to support regulatory filings.

Determining Comparability of Biosimilars Through Statistical Approaches

A bioassay measures biological activity or potency of a drug product (DP) or drug substance (DS), for which the most important critical quality attribute (CQA) is potency or relative potency if it is compared to a standard. Concentration measures how much of the molecule is in solution, and the bioassay measures how biologically active the protein is. Every biological product such as vaccines, hormones, antibodies, cell therapies, complex therapeutic proteins, and gene therapies all need a bioassay or multiple bioassays to measure biological activity.

	A bioassay is an interesting combination of science and statistical methods to determine potency or relative potency.  The International Council for Harmonization (ICH) does not discuss bioassays to any great degree; however, 

<1034> covers analysis of bioassay data and methods of calculation.

	Failure to develop the bioassay correctly will cause problems with drug approval/licensure, excessive invalids, and excessive out of specification (OOS).  Most of the problems with a bioassay can be avoided with correct development, qualification, validation, and control of the reference standard. 

	Essential steps in developing a bioassay

	Developing and validating a bioassay requires 12 essential steps, including determining the science that creates the signal that indicates biological activity and the dose response as well as number of doses used in the bioassay. In addition, one must develop a reference for relative potency as well as determine the method of calculation and design the bioassay calculator. Another step involves evaluating the robustness of the bioassay method while optimizing set points and limits. The other steps include standardizing and automating the bioassay, evaluating specificity and stability indicating, qualifying the bioassay, validating it, and monitoring reference potency as well as conducting stability checks. 

Determine signal indicating biological activity


	Every bioassay generates a signal based on the activity of the molecule. The signal measures the change in protein concentration/dilution and biological activity. Each bioassay uses a specific technique to measure the change in activity or potency. It may react with the presence of another analyte in solution, modify cellular DNA, stimulate the immune response, cause florescence, stimulate hormonal activity, generate antibodies, measure toxicity, etc. The action of the drug generates a signal that can be measured with light, weight, or concentration.  

	There are two different types of signals that can be generated by a bioassay, a linear dose response and a sigmoidal (s-shaped) dose response. Either approach may be used. Sigmoidal bioassay designs are preferred if there is a clear saturation in the dose response and there is no compelling reason to limit the number of doses. One solution does not fit all bioassays, however, and each bioassay needs to be evaluated based on the data at hand to ensure the right approach is used. This is particularly true for gene therapy and cell therapy bioassays.


	If a sigmoidal design is used, a four- or five-parameter logistics (4PL or 5PL) curve is fit to the data. Nine doses are recommended to fit a 4PL model, three doses in the lower asymptote, three doses in the upper asymptote, and three doses in the linear range. If a parallel line analysis (PLA) fit is used, a minimum of four doses is recommended within the linear range. Dose masking allows for the identification and removal of a dose at the low or high end of the dose curve. Three consecutive doses are required by guidance. Dose and curve fitting selection are among the most critical aspects of bioassay development.


	A reference is selected to evaluate potency relative to the reference. This helps to control for cell-line variation, sample handing, animal biological activity, reagent effects, food sources, media, etc. References are often selected from early clinical lots so that there is a clinical connection and clinical relevance associated with the reference. Secondary references are measured and created to provide an understanding of quality should the primary reference be retired or depleted. Calculator design should control/correct for difference in standards.

	In defining bioassays and relative potency, the 

	“Because of the inherent variability in biological test systems (including that from animals, cells, instruments, reagents, and day-to-day and between-lab), an absolute measure of potency is more variable than a measure of activity relative to a Standard. This has led to the adoption of the relative potency methodology. Assuming that the Standard and Test materials are biologically similar, statistical similarity (a consequence of the Test and Standard similarity) should be present, and the Test sample can be expected to behave like a concentration or dilution of the Standard. Relative potency is a unitless measure obtained from a comparison of the dose-response relationships of Test and Standard drug preparations.”


	There are two primary methods by which a bioassay potency and relative potency are calculated; 4PL with nine plus doses and PLA with four doses. In cases where animal life is a consideration, PLA is preferred. In cases where there is no clear upper asymptote, PLA is required. This is often the case with infectious viral vectors. For PLA, the doses must be carefully selected to stay in the linear range. 

shows the two methods of calculation.  Potency is the difference in the intercepts for the PLA, and Potency is the inflection point (50% change in activity) from the 4PL curve. Relative potency is calculated using the following equation, potency reference/potency test article * 100.  The ratio depends on the bioassay and how the activity is measured.

Characterize robustness, optimize set points and limits

 <1033> states that a bioassay needs to be characterized for robustness during development. Normally this is accomplished with a risk assessment (what can influence accuracy and repeatability) followed by a designed experiment with critical factors that may influence the bioassay. Normally three determinations are performed at the 100% target dilution for each experimental run. Accuracy and repeatability are evaluated for each of the run conditions, and the method is optimized to find the most stable conditions of the bioassay. A design space is created where the assay is accurate and repeatable and the edge of failure analysis indicates limits for critical reagent concentration, temperature, pH, etc.


	Generally, SAS or SAS/JMP are recommended as software for bioassay development and validation because they are the only fully programable/customizable solutions that allow for all of the below items. Other canned bioassay software have serious restrictions that make them undesirable for bioassay computation and reporting. Elements of the calculator design for a bioassay include the following: 

		Complete all data entry and quality control data for integrity	

 transform the data as appropriate (dose and or response) for model fitting	

		Identify and remove within dose outliers (Jackknife z)	

		Identify the subset of doses to be used (PLA only, dose masking)	

		Remove between dose (model) outliers (Jackknife or Studentized Residuals)	

		Check systems suitability/positive control	

		Check test article and reference validity	

		Calculate potency and relative potency and 95% confidence intervals	

		If out of specification or the confidence interval is too wide run additional n where indicated in the standard operating procedures (run rules for the bioassay)	

		Combine n=1 or more to determine the reportable result and 95% confidence interval or declare the bioassay run invalid.

Systems suitability and evaluating parallelism


	There are several techniques for the evaluation of parallelism. 

provides a summary of methods for the evaluation of parallelism. Other systems suitability criteria include the measurement of a known control, relative variation (%CV) of repeated measures, and curve depth for signal strength. Systems suitability most often is the EC50 of the reference standard (positive control).


	Develop the code/script for the bioassay. Make sure to generate all reports as PDFs. Extract all critical tracking and trending data from the bioassay and store all reportable information and results in a table form for easy analysis. Update the LIMS system and, where possible, automate all calculations and data transfer.

	Specificity is normally evaluated as a part of bioassay development or validation. There are two different ways of showing assay specificity or selectivity. The first method indicates only the specific protein generates a signal and blanks/placebos or other proteins generate no signal. The second is interference of other materials such as media, formulation buffer, forced degradation materials. Any interference is demonstrated by a shift in the intercept when spiked in. It can also be viewed as the change in accuracy in the presence of interfering compounds.


	Normally as part of development there is a desire to show the bioassay is stability indicating. This is done by thermal, light, pH or chemical degradation of the protein and measuring the change in potency. Normally 4 to 5 time points is desired and a statistically significant linear or none linear change in the signal is sufficient to prove the bioassay is stability indicating.

		To qualify a bioassay the following is recommended:

		Accuracy, five concentrations, n=6 or more at each concentration	

		Repeatability, five concentrations, n=6 or more at each concentrations	

		Dilutional linearity, five concentrations exceeding the upper specification limit (USL) and lower specification limit (LSL)	

		Range where the bioassay is accurate, repeatable, and linear	

		Intermediate precision, design of experiment (DOE) design to isolate the analyst, day, and instrument variance components.


	To validate a bioassay, the following is recommended:

		Repeatability, five concentration, n=6 or more at each concentrations	

		Dilutional linearity, five concentrations exceeding the USL and LSL	

		Intermediate precision, DOE design to isolate the analyst, day, and instrument variance components	

		Robustness, set point, and operational range	

		Stability indicating, significant change in signal under degraded conditions.

Monitor/control reference potency and check stability


	It is critical to monitor the performance of the bioassay over time. The unconstrained EC50 standard is generally considered the best measure of the stability and consistency of the assay. To detect if assay drift is a method issue or standard issue a comparison to the unconstrained EC50 should be made. If both the reference and the test are drifting, it is change in the assay over time but no impact to relative potency. If the test is stable and the reference is trending, it will impact relative potency and should be corrected or a new reference selected.

	Bioassays are powerful tests of relative potency and biological activity but need care in the design of the assay and the analysis to make sure they are a reliable indication of the change in potency. Validation of the assay will demonstrate the accuracy, repeatability, and linearity of the assay and its fit for use in the measurement of relative potency. Care in the selection of the dose response, outlier detection and removal, masking, transformation, and weighting will make the assay more stable and repeatable. 

	1. USP, <1032>, “Design and Development of Biological Assay,” 

(US Pharmacopeial Convention, Rockville, MD, December 2015).
	2. USP, <1034>, “Analysis of Biological Assays,” 

(US Pharmacopeial Convention, Rockville, MD, December 2015).
	3. USP, <1033>, “Biological Assay Validation,” 

(US Pharmacopeial Convention, Rockville, MD, December 2015).
	4. T. Little, 

, is president and CEO of BioAssay Sciences. 

To whom correspondence should be addressed.


	Vol. 32, No. 11
	November 2019
	Pages: 42–45

	When referring to this article, please cite it as T.A. Little, “Essentials in Bioassay Development,” 

Bioassays are critical for determining drug substance and drug product potency, which is why it is important to understand the fundamentals of developing an effective bioassay.