A recurring question we get from our clients is whether it is worth adopting data standards such as CDISC in the early phase of their drug development, and if it is worth spending more to produce SDTM and ADaM packages at an early stage. This question is usually a concern of small biotech not wanting to "risk" money without knowing (yet) the future of their compound.
It's an easy question (for me) to answer: yes it is worth adopting the standards from the very beginning for the following five main reasons:
1. Vendors (CROs) are increasingly familiar with the foundational standards (mainly SDTM and ADaM), and many typically use these standards in their process.
2. If, as a smaller biopharma company you are ultimately looking for a partner to co-develop your compound, then having study data stored and analyzed using CDISC standards, facilitates data-sharing and helps the due-diligence process.
3. Adopting CDISC standards from the outset will contribute to the consolidation of a now well-established clinical trial data language. More widespread use of regulatory-compliant standards reduces the risk of misunderstanding when collecting data (e.g. use of CDASH questions and Controlled Terminology). Moreover, thinking in a “standards-manner” will ultimately benefit the quality of the data you collect. For example, standards can help to ensure that you collect all the data needed to answer your experimental question.
4. Later adjustments or full conversion to data standards at the time of data submission are possible. However, in my experience, such a retrospective approach may lead to an improper conversion (risking proper traceability), and often necessitates heavy post-processing that considerably increases the budget versus the costs involved in adopting standards from the very beginning.
5. One last recommendation is to go with a full-submission ready package from the very beginning thus avoiding “intermediate” approaches such as "SDTM-like" or "ADaM-like". Taking these intermediate approaches is often based on wrong thinking like “ I can fill the gap when it's time to submit" and taking the same line with define.xml, reviewer’s guide and other required submission-ready documents. Remember- these are an essential part of the data-package and retrospective creation might not always be accurate. These materials are also excellent "instruments" to document your data and any significant issues you might have encountered during the data collection and analysis of your study.
A number of our small and mid-size biotech clients have taken this decision and decided to ask us to always “plan” for CDISC, by delivering data in SDTM format and analyzing that data using the ADaM standards. This planning brings improved clarity and reduces the heterogeneity in data formats especially when multiple vendors are in the mix. Such an investment "bears fruit," when it is time to pool data from different studies to support a registration request through the FDA for example.
Angelo Tinazzi is Senior Director, Standards, Systems, CDISC Consulting, Statistical Programming at Cytel Inc. at Cytel. He is a well- published and recognized expert in statistical programming with over 20 years' experience in clinical research. The application of CDISC standards in different therapeutic areas is part of his core expertise since 2003 in particular in the context of data submission to health authorities such as the FDA and PMDA.
Angelo is an authorized CDISC instructor and member of the CDISC ADaM Team as well as the CDISC European Committee where he manages the Italian-speaking CDISC User Network.