A Rational Approach for Setting and Maintaining Specifications for Biological and Biotechnology–Derived Products—Part 2

Published on: 
BioPharm International, BioPharm International-07-01-2008, Volume 21, Issue 7
Pages: 40–45

Resolve confusion about measurements.


This paper discusses an approach for the establishment and lifecycle management of biological and biotechnology-derived product specifications. The views presented are consistent with the concept of Quality by Design (QbD), in which critical quality attributes (CQAs) are distinguished from parameters used to monitor process consistency. Specifications and the corresponding limits as applied to CQAs serve to ensure that the product is fit for use, whereas control limits are a manufacturer's tool to monitor shifts and trends in the manufacturing process. In the current paradigm, inappropriate use of specifications creates a disincentive for continuous process understanding; more suitable approaches to analyzing development and manufacturing data are discussed. Statistical methods are presented for deriving and interpreting data against specifications that better manage the risk to the customer of receiving product with diminished safety or efficacy, as well as the risk to the manufacturer of earmarking a satisfactory lot as unacceptable. The recommendations are presented as a rational approach to setting and maintaining specifications, while recognizing that their applicability may not be suitable in all cases, given the heterogeneity of types of regulated biological and biotechnology-derived products and their unique challenges.

The purpose of this paper, which has been developed by the Working Group on Specifications and Formulations of the Pharmaceutical Research and Manufacturers of America (PhRMA) Biologics and Biotechnology Leadership Committee, is to provide guidance on a lifecycle approach to setting global specifications for biological and bio technology-derived products. In the pharmaceutical industry, specifications are legally binding criteria that a product must meet in order to be marketed. They ensure the consistency and quality of the product and help ensure that it is safe and efficacious over the shelf life of the product. Specifications evolve during product development and ideally should embrace future process capability. This is true for biological and biotechnology-derived products for which there may be limited experience at the time of regulatory filings (including the marketing application), and for which early commercial production often is necessary to gain a better understanding of product quality attributes, methods, and limits.


Part 1 of this article, published in the June issue of BioPharm International, included three sections: Terminology, Stages of the Lifecycle of a Product, and Components of a Biological and Biotechnology Product Specification. This part 2 covers the next section, Current Issues Related to the Development of Specifications. The final section, the Suggested Approach for Developing and Maintaining a Total Quality System, will be published in Part 3, in the August issue.


Several issues require resolution to implement a rational approach for setting specifications. These issues relate to the interpretation of measurements relative to limits, and the meaning and use of various types of limits.

Current strategies for developing and maintaining specifications and for interpreting data against specifications do not adequately acknowledge the risks to both the customer and the manufacturer. Although most manufacturers strive to attain an acceptable quality level for their processes and products, a common understanding of the business risks as well as the risks to the customer is necessary to achieve a 21st century vision of quality. Many practices for setting limits are arbitrary and fail to factor in these risks. Some practices strive to achieve unattainable goals, such as guaranteeing that every dosage unit will meet specifications. Other practices are overly restrictive, leading to either disincentives for collecting data or hardships on the part of the manufacturer to investigate and explain apparent out-of-specification results. Still other practices, such as adopting control limits as specifications, hinder process understanding and improvement. The following is a discussion of the practices impeding a rational approach to setting and maintaining specifications for biological and biotechnology-derived products.


Reportable value versus individual measurements

Currently, there are conflicts in thinking and in regulatory guidances regarding whether specifications are applied to individual samples, individual measurements on the same sample, or the average of multiple samples. The International Conference on Harmonization's (ICH) Q1E guideline, Evaluation of Stability Data12 instructs that shelf life be determined from a lower 95% confidence interval on the mean regression line from the analysis of a quality attribute over time, whereas ICH Q6A, Specifications: Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances13 stipulates that individual measurements be held to shelf-life specifications. The recently issued US Food and Drug Administration Guidance for Industry on Investigating Out-of-Specification (OOS) Results for Pharmaceutical Production14 states in one section,

"It may be appropriate to specify in the test method that the average of these multiple assays is considered one test and represents one reportable result," and in another section,

"In cases where a series of assay results (to produce a single reportable result) are required by the test procedure and some of the individual results are OOS, some are within specification, and all are within the known variability of the method, the passing results are no more likely to represent the true value for the sample than the OOS results. For this reason, a firm should err on the side of caution and treat the reportable average of these values as an OOS result, even if that average is within specification." 14

These incongruities create undue concern on the part of manufacturers and regulators alike. Although manufacturers strive to obtain reliable information on products through strategic study design and adequate replication, they are likely to be penalized when a single measurement is OOS. This situation creates a disincentive for collecting data.15 The regulator, faced with the question of whether or not to question an OOS measurement, will likely deem a satisfactory result OOS in accordance with the more restrictive of these rules.

Quality control measures should guarantee that the product on the market conforms to the attributes of materials tested during development. In development, clinical lots are tested and described by the average of measurements made on the lot. The average may be obtained from a single dosage unit or multiple dosage units. In this way, quality attributes of the lot are mapped to clinical response in the population of patients receiving the lot.

Figure 1 illustrates this relationship for a bioassay. A sample of dosage units is taken from each of three clinical lots and then tested in a bioassay. The reportable value for each lot is the average of the measurements on these dosage units, and these reportable values are used to set the specifications for the product (represented as a normal curve). Another sample of dosage units is administered to patients in the clinical trial, and the clinical response to these is reported as the clinical outcome (here, 95% response). Post-licensure, samples are taken from a commercial lot and compared to the specifications derived during development. When the reportable value for the commercial lot falls within the specifications, it is inferred that patients receiving this lot will experience the same clinical benefit as those studied in the clinical trial (i.e., 95% response).

Figure 1

Holding commercial product to the same standard as development materials will help guarantee that the clinical response will be similar to that observed during development. However, measurements on individual dosage units or individual measurements on the same dosage unit should not be held to specifications established during development, because clinical doses were not tested prior to clinical administration, and thus there is no link between measurements made on individual doses and clinical outcome.

Specifications versus control limits

Using control limits as specifications will hinder a manufacturer's ability to monitor product and to make process improvements. The advantage of maintaining a separation between specifications and control limits is that the customer is adequately protected through properly defined specifications, and the manufacturer is protected from discarding product that is fit for use. This distinction promotes attention to process shifts or trends without affecting product distribution, and the manufacturer is encouraged to improve its process to reap the benefits of improved process capability. Improved process capability means fewer failures, and thus greater capacity to provide safe and effective product to the market.

Furthermore, the vision of Quality by Design and design space cannot be achieved when control limits are used as specifications. The design space may be viewed as the region of process settings that yields acceptable product (i.e., product that meets specifications). When control limits are used as specifications, the design space reverts to the control space for the process, leaving no opportunity for process improvement.

The ideal relationship between limits and process spaces is illustrated in Figure 2. Two response factors (X1 and X2) are studied across the knowledge space, yielding a response surface in the quality attribute (panel 1). The response surface intersects the lower specification limits (LSL, panel 2) and upper specification limits (USL, panel 3) to yield the design space (panel 4). The control space represents a normal operating range for the factors, falling well within the design space (panel 5). Product that is manufactured within this control space will yield measurements falling within the upper and lower control limits (UCL and LCL in panel 6). As long as a control space falls within the design space, the associated control limits will fall within the specifications, yielding good process capability and the opportunity for process improvement.

Figure 2

Interpreting data from annual stability studies and process validation

Another conflict exists in the guidance documents regarding establishing shelf life and interpreting individual stability results. ICH Q1E, Evaluation of Stability Data promotes the use of statistical methods for establishing the shelf life of the product. As mentioned previously, this approach uses the confidence bound on the mean regression line. However, individual stability measurements are more variable than is predicted by the confidence bound, and are thus likely to become OOS throughout shelf life. This is illustrated in Figure 3. Following ICH Q1E, a regression analysis is performed on development stability data, yielding a lower 95% confidence bound (dashed curve) that intersects a minimum requirement for potency (dotted line), predicting 24-month shelf life for the product. However, measurements from an annual stability lot are not restricted by the confidence bound but instead by a prediction bound (dotted curve). The probability of experiencing one or more OOS measurements throughout the shelf life of the annual lot is predicted from this example assuming the annual lot degrades like the development lot, and the assay variability is the same as that observed from the development study. The proportions of measurements that are predicted to fall below the minimum requirement at 12, 18, and 24 months are 5%, 9%, and 18% respectively. The probability of experiencing one or more OOS measurements is calculated as:

Figure 3

Prob (OOS)

=1 – Prob (No OOS)

=1 – Prob (No OOS at 12 mos.)

* Prob (No OOS at 18 mos.)

* Prob (No OOS at 24 mos.)

=1 – 0.95 * 0.91 * 0.82 = 0.29

Thus, in this case, material that was judged to have 24-month shelf life by ICH Q1E has a ~30% probability of yielding an OOS result over the course of an annual stability study.

This contradiction has fostered strategies that protect against stability OOS results that have little or negative impact on product quality. A minimalist approach to stability testing is engendered during development, because frequent measurements may result in early OOS results that shorten the apparent shelf life of the product. Often, companies file shelf life limits (which should contain stability measurements through shelf life) that are artificially wide because of adjustment for statistical multiplicity (i.e., the increased probability of failure, with multiple testing; one adjusts for multiplicity by making the interval wider), and are thus unable to capture meaningful changes in product stability. As with release testing, the current environment discourages enhanced designs to study the stability of the final product or to monitor the stability of product on the market. Stability data should be analyzed in a way that promotes data collection to achieve better product understanding.

This risk is likewise borne in validation studies. Samples are taken from multiple locations of the production process, or at multiple levels of a process parameter, and subject to specifications. As with stability testing, in which multiple samples are taken over time, validation samples are subject to excess risk of OOS due to multiplicity, which acts as a disincentive to collecting data for better process understanding.


The purpose of this paper, which has been developed by the Biologics and Biotechnology Working group on specifications of the Pharmaceutical Research and Manufacturers of America (PhRMA), is to provide guidance on a lifecycle approach to setting global specifications for biological and biotechnology-derived products.

Part 1 of this article, published in the June issue of BioPharm International, included three sections: Terminology, Stages of the Lifecycle of a Product, and Components of a Biological and Biotechnology Product Specification. This part 2 covers the next section, Current Issues Related to the Development of Specifications. The final section, the Suggested Approach for Developing and Maintaining a Total Quality System, will be published in Part 3, in the August issue.

Timothy Schofield is senior director, nonclinical statistics, at Merck Research Laboratories, Merck & Co., West Point, PA, and the corresponding author, timothy_schofield@merck.com 215.652.6801; Izydor Apostol, PhD, is scientific director, analytical and formulation sciences, at Amgen Inc., Thousand Oaks; Gerhard Koeller, PhD, is vice president, quality and compliance biopharmaceuticals, at Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany; Susan Powers, PhD, is biotech quality technology leader, Wyeth Pharmaceuticals, Collegeville ,PA; Mary Stawicki is associate director, regulatory affairs biopharm CMC, at GlaxoSmithKline, Collegeville, PA, and Richard A. Wolfe, PhD, is director and team leader, biopharma operations, at Pfizer Global Manufacturing, Chesterfield, MO.


12. International Conference on Harmonization (ICH). Q1E, Evaluation of stability data. Geneva, Switzerland; 2003.

13. ICH. Q6A, Specifications for new drug substances and products. Geneva, Switzerland; 1999.

14. US Food and Drug Administration. Guidance for Industry: Investigating out of specification (OOS) test results for pharmaceutical production. Rockville, MD: 2006.

15. Foust L, Diener M, Gorko MA, Hofer J, Larner G, LeBlond D, Lewis J, Sandell D, Schofield T, Vukovinsky K, Warner E. Overcoming disincentives to process understanding in the pharmaceutical CMC environment. Pharm Technol. 2007 Sept;31(9):108–115.