Therapeutic Area Standards: What are they really?

The fifth reauthorization of the Prescription Drug User Fee Act (PDUFA V) gave rise to the goals that FDA agrees to meet in exchange for the user fees it collects (PDUFA V "goals letter"). Under section XII, part E of the goals letter, FDA agrees to the following:

Clinical Terminology Standards:Using a public process that allows for stakeholder input, FDA shall develop standardized clinical data terminology through open standards development organizations (i.e., the Clinical Data Interchange Standards Consortium (CDISC)) with the goal of completing clinical data terminology and detailed implementation guides by FY 2017.  

1. FDA shall develop a project plan for distinct therapeutic indications, prioritizing clinical terminology standards development within and across review divisions. FDA shall publish a proposed project plan for stakeholder review and comment by June 30, 2013. FDA shall update and publish its project plan annually. 

This section of the goals letter has given risen to the development of so-called "Therapeutic Area (TA) Standards." I was involved in numerous activities associated with TA standards development. I found there exists a substantial amount of confusion or lack of clarity regarding what these are and how they should be managed. I decided to write this post to explore TA standards from a data standards and regulatory review policy perspective that hopefully provides useful insight in what these standards are and how best to manage them in the future. 

Standard vs. Data Standard

When discussing TA standards, it’s useful to draw a distinction between a standard and a data standard. A standard is defined in dictionary.com as “something considered by an authority or by general consent as a basis of comparison; an approved model.”  There are many different kinds of standards: manufacturing standards, measurement standards, data standards, etc.  To understand the distinction, consider a ruler. The ruler can be marked in inches or centimeters. Which ruler is used to measure length depends on the measurement standard that has been selected for the task. Once a measurement standard is selected, then the data standard provides a consistent approach to document and/or share the measurement. If the measurement standard is inches, and the measurement is 10 inches, then the data standard describes whether it’s 10”, 10 in, or 10 inches. This distinction is important when considering TA standards. How to represent a measurement (i.e. an observation) requires two decisions: a business decision (what to measure, which measurement standard to use), followed by a data standards decision (how to standardize the representation of the measurement, which data standard(s) to use).

What is a Therapeutic Area Standard?

I find there is no widely established “standard definition” for a TA standard. One working (perhaps prevailing?) definition is that a TA standard is a data standard for a therapeutic area or indication. I argue that a TA standard is not a data standard. Let’s examine this definition more closely.

Consider a clinical observation, specifically a clinical laboratory test:  glycosylated hemoglobin  (HbA1C). The standardization of HbA1C data is straightforward. CDISC provides controlled terminology for the HbA1C lab test (represented by the NCI Enterprise Vocabulary Services code C64849). The CDISC SDTM Implementation Guide describes how to represent lab test data (which includes HbA1C data) using the LB domain. The result is a numeric value, expressed as a percentage of the total hemoglobin in blood. Anyone conducting a clinical trial that includes the collection of HbA1C need only look at the SDTM IG and CDISC controlled terminology to understand how to standardize this information. No additional data standards are needed.

Consider now a single therapeutic area: Diabetes Mellitus. Let’s assume that, for the purpose of determining efficacy of a new diabetes drug, only one outcome measure is necessary:  the HbA1C.

So what does a Diabetes Mellitus TA Standard then look like? What are we “standardizing” that isn’t already standardized?

One can envision a separate Diabetes TA Standards document that says, “if you’re studying a new drug to treat diabetes, you should collect HbA1C and here is how you should represent HbA1C data using these existing standards: SDTM + CDISC controlled terminology.” For this document to be truly useful, an independent scientific and/or regulatory body should first decide what design features and clinical observations are relevant for diabetes studies. This can be described as a “good clinical research practice guideline” for diabetes. One could consider this a standard but it is not a data standard. Such a guideline is analogous to a manufacturing or building standard. Just as a builder might say: “A hurricane-resistant building must/should contain these materials: ….,” a clinical researcher would say: “A good diabetes study must/should contain HbA1C testing.” 

FDA publishes such guidelines. These are called indication-specific guidances, which help sponsors design their development programs, including clinical trials to support U.S. approval of new drugs for a given indication. I was involved in the development of a standard template for these guidances so that there is consistency in the content and presentation across therapeutic areas. Other organizations may publish similar guidelines: professional societies, other government agencies (e.g. NIH), consortia, etc.

In this simple example, a researcher would only need to read the clinical research guideline for diabetes, and understand how to represent HbA1C data using existing exchange and terminology standards. No additional documentation is necessary. A Diabetes TA user guide is not needed. The “standard” for diabetes trial is the clinical research guideline itself and the existing data standards.

Of course therapeutic areas are much more complicated than this. Each TA has multiple relevant clinical observations, and any given observations may have additional metadata and qualifiers needed to interpret the observation. In this setting a TA “user guide” is useful to demonstrate how to represent all TA-relevant data and meta-data using existing data standards. But the user guide itself is not a data standard. The data standards are the exchange and terminology standards that the user guide references.

So an alternative definition for a TA Standard is a best practice guideline for conducting clinical trials for a specific therapeutic area, with an accompanying illustration (e.g. “user guide”) on how to use existing data standards (exchange and terminology standards) for that TA. If FDA generates the guideline, then it would be an indication-specific guidance, and any available user guide would ideally be incorporated by reference to the guidance.

An analogy would be a best practice specification for designing a kitchen. The kitchen “standard” would say: it must have cabinets, a refrigerator, a sink and faucet, and a stove and oven. It may have a garbage disposal, dishwasher, and trash compactor. The kitchen TA user guide might say, “this is what your kitchen would look like if you use standard Ikea cabinets and General Electric appliances.”

We should all therefore agree that a TA standard is not a data standard. A TA Standard is a use case for existing exchange and terminology standards. The data standard is the exchange and terminology standards that are used to standardize TA-specific data. A TA Standard is a use case for existing exchange and terminology standards.The FDA publishes a Data Standards Catalog that lists the data standards the Agency supports for various use cases. Because TA standards are not data standards, I do not think they belong in the FDA Data Standards Catalog as new data standards that FDA supports.  FDA does need a new approach to convey that the TA use cases are adequately supported by the data standards listed in the catalog. 

So what about the user guides? We should recognize that a TA standard has two components:

1. A clinical research ‘best research practice guideline’ or standard (i.e. the data requirements)
2. A description of how available data exchange and terminology standards can represent the TA data requirements. A user guide may be useful (but not necessary) to illustrate how this is done.

In the trivial example described here, there is really no need for a separate Diabetes TA user guide because it is clear how to represent HbA1C information using existing data standards. The problem arises when the data requirements are complex and the existing data standards do not provide a clear and unambiguous representation of the clinical data. Then, a user guide is helpful and necessary.

For a TA standard to be effective for FDA, the Agency needs to ensure that its regulatory data needs are met. FDA needs a process to ensure that:

1. the TA best practice research guideline is accurate (the TA-specific data requirements; in CDER this is largely a function of the Office of New Drugs(OND)). Ideally this is captured in an indication-specific guidance, and
2. data standards exist (or have been adequately modified) to represent the data requirements in a standard format (in CDER this is likely a collaboration between OND, the Office of Strategic Programs (OSP), the Office of Translational Sciences (OTS) and data standards development organization(s)).