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Rho can perform data analysis for bioequivalence using WinNonLin.  Please click here to contact us and learn more about this service.

Rho puede realizar análisis de datos de bioequivalencia con WinNonlin. Por favor haga clic aquí para contactarnos y obtener más información acerca de este servicio.

Transitioning a study from one CRO to another is a difficult task that can be made easier by creating a transition plan that accounts for the objectives and concerns of all stakeholders -- you (the Sponsor), the existing CRO, the new CRO, study sites, and other providers (e.g. drug supply vendor, central labs, central IRBs). 

In our experience, the following areas are of primary concern when transitioning projects:

• Established, clear and realistic goals for the transition process.
• The existing CRO’s cooperation in transition process.
• Ensuring data and information transfers are accurate and complete.
• Assessing potential roadblocks and implementing preventive processes and solutions.

Work with the new CRO to accomplish the following early in the process:

• Conduct a comprehensive analysis of existing issues and challenges.
• Establish a communication plan for the initial transition.
• Establish a transition leader committed to a seamless transfer to act as a central point of contact.
• Assess the transitioning CRO’s systems, processes, and quality.
• Create a transition plan to be approved by all key stakeholders.

Our Data Standards experts at Rho believe there are both advantages and disadvantages to converting to CDISC SDTM format. Here are a few:

Selecting the right CRO to handle your CDISC work can be a daunting task.  As you evaluate potential partners, it’s critical that you consider factors beyond whether or not they have a CDISC certification. This list provides 10 criteria that can help you make an informed decision about which CRO is right for your CDISC project or program.  A successful CRO should:

• Have experience mapping and programming clinical data to SDTM for individual studies, for an entire submission, and for legacy conversions.
• Demonstrate an understanding of the validation requirements for SDTM data and the define files and should have validation tools endorsed by FDA.
• Be able to explain how metadata requirements drive SDTM programming efforts.
• Have tools that create efficiencies across multiple studies.
• Express familiarity with XML and related technologies.
• Have tools to produce a CDISC compliant define.xml file as well as other CDISC deliverables.
• Understand how to integrate SDTM and analysis work to meet your deadlines.
• Be involved in CDISC committees and working groups.
• Have completed multiple submissions to FDA.
• Have a technical acceptance rate of more than 90%.
• Have a dedicated CDISC group with extensive CDISC training.
• Demonstrate an understanding of how CDISC models fit into the life cycle of a drug development project and how CDISC standards fit into a regulatory submissions strategy.

We asked Jeff Abolafia, one of our CDISC experts, to answer this question. Jeff is the co-founder of the Research Triangle Park CDISC Users Group, has been involved in the development of CDISC standards, and has 20 years of experience with data standards and CDISC. Here are some of his thoughts:

• Be proactive. Discuss your database strategy with FDA early in the project’s life cycle. Also, begin your SDTM CDISC work prior to and in conjunction with the analysis work. Develop a submission strategy early in the process so it can be implemented for key Phase II and III studies. Implementing a submission strategy while studies are ongoing will allow you to avoid costly legacy conversions. Legacy conversions near the end of the drug development life cycle can reduce the quality of the data, draw key resources away from compiling the submission, and ultimately delay the submission and its approval.

• If you plan to keep the SDTM work in-house, plan sufficient time and resources to adequately train your staff. Viewing these standards simply as a collection of data structures and documentation requirements is tempting, but ultimately problematic. Their impact extends throughout the statistical computing environment of any organization dealing with FDA. For example, Statisticians must be trained in SDTM to use SDTM inputs more efficiently, Project managers must understand the new work streams and work flow, and Regulatory personnel must understand SDTM to plan a submission strategy and discuss it with FDA.

• If you are going to contract with a CRO to do your CDISC work, choose a CRO that is very experienced in successfully completing SDTM/ADaM work. Ask for a listing of their experience and check their references.Having a collaborative and trusting relationship with your CDISC partner is critical. Some specific criteria you should consider in your selection include:
  • Number of submissions to FDA in CDISC format.
  • Technical acceptance rate of submissions to FDA.
  • Tools available for producing CDISC deliverables.
  • Expertise of staff, including members of CDISC professional groups and people who publish or present on CDISC related topics.

For a more comprehensive list of criteria to consider when selecting a CDISC vendor, click here.

With a growing focus on CDISC standards from FDA, this is an increasingly common question. 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

An adaptive study design is one that examines the data as it is collected and then makes changes to (or adapts) the study to optimize the amount of information gathered by the study. There are many different varieties, including the following:

• Sample size recalculations
• Adaptive randomizations
• Bayesian dose escalation studies
• Seamless phase II/III designs
• Pruning designs

Each of these examples looks at different parts of the study (eg, the stratification factors of the randomization) and then allocates the future subjects based on what we’ve observed so far. Each one optimizes different aspects of the study, however, so they have vastly different benefits.

Depending on the type of adaptive design, the benefits of an adaptive design can include the following:

• Smaller trials
• Reduced development time
• Ability to change the direction of a study part way through
• Opportunities to fix bad assumptions
• More balance across treatment groups

Which type of adaptive design to use and whether you should be using one at all depend on the challenges you face for the therapy being studied. Different therapeutic areas face very different challenges in drug development and, therefore, can benefit from different types of optimized studies. Since each new therapy is unique, you should consult an expert at an early stage in your development planning cycle. These are key factors in determining whether an adaptive design is appropriate:

• Time to observing the endpoint relative to the enrollment time
• Phase of development
• Amount of current knowledge about the new intervention
• Needs of the company

No, a safety database is not a regulatory requirement, but electronic submissions of expedited safety reports are required by several countries other than the United States. The FDA does not mandate that expedited safety reports be submitted electronically; electronic submission is voluntary at this time. However, a safety database is an excellent tool to track, report, and maintain the product safety profile for the life of the drug, biologic, or device.