With a growing focus on CDISC standards from FDA, more companies are considering converting legacy data. Here are five questions you should consider:

1. How long will it take and how much will it cost? Any legacy conversion project will require a substantial investment of effort by experienced personnel. The time and cost required for the conversion will be dependent on several factors, including number of studies, complexity of study designs, therapeutic area, number of unique data domains, similarity of input data to SDTM structures, and quality of input data and documentation. If possible, get started as soon as possible after the end of Phase II meeting with FDA.

2. What problem are you trying to solve with the legacy conversion? Clearly understanding the goals for your conversion will help you weigh potential benefits and costs. Some common reasons for undertaking a conversion of legacy data to CDSIC standards include:

• FDA asks for SDTM and/or ADaM formatted datasets.
• Data across studies lack uniformity and would lead to a challenging database for a reviewer at FDA to understand and use.
• Data across studies needs to be standardized for archival or data mining purposes.
• Interaction between multiple stakeholders requires a data exchange standard.

3. Have you had a discussion with FDA about whether the work is necessary? In many cases, the answer will be yes. It is still in your best interests to ask and confirm. Some cases where legacy conversion may not be necessary include:

• Phase I studies or non-pivotal phase II studies.
• Your company has an internal standard which has been implemented uniformly across all studies in a submission. The database and documentation are already high quality.
• A legacy conversion will negatively impact traceability.

4. What will be the impact to the traceability of analysis data that was previously created or submitted? You need to understand this upfront to make an informed decision about moving forward with a legacy conversion. If you undertake a legacy conversion, this is critical input to your planning. Some traceability issues include:

• If clinical data is converted to SDTM, there is no longer traceability from the clinical data to analysis data.
• If analysis data is converted to ADaM:
  (1) If original source data is not used, traceability is lost.
  (2) Even if the original source data is used as input, if analysis data is converted to ADaM, the displays and analysis were not produced from the converted analysis datasets. Results will have to be re-generated to ensure that they match the original results (in the CSR).

5. Do you have all the necessary documentation for all studies that are a component of the legacy conversion? Missing documentation could present a substantial hurdle to the documentation process. Documentation you will need includes:

• Annotated CRFs
• Protocols
• Data management plans
• Input clinical datasets
• Format libraries
• Additional documentation about the clinical database