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Strategies for successful Integrated Summary of Efficacy and Safety (ISS/ISE) submissions

Preparing for regulatory submissions by integrating safety and efficacy data from multiple clinical studies is a complex process. Sponsors contend with challenges including inconsistent data formats, legacy datasets and limited resources. Alongside this are the continuously evolving global regulatory requirements which can contribute to commercialisation delays.

Overcoming these barriers to deliver high quality submissions packages requires deep regulatory knowledge underpinned by technical expertise. In this blog we outline some strategies for preparing effective submissions for integrated summary of safety and efficacy (ISS and ISE). We look at the potential risks and benefits of each approach and provide some recommendations to ensure that your study’s ISS and ISE address the regulatory requirements and avoid potential pitfalls.

Method 1: Analysis Dataset Model (ADaM) only integration using study SDTM and/or legacy tabulation data

In this approach, data relevant for the ISS/ISE are directly integrated from the individual study-level study data tabulation model (SDTM) or legacy tabulation data into the ISS/ISE ADaM database. Harmonisations on study-level codelists as well as up-versioning on WHODrug and MedDRA dictionaries are applied onto the ADaM level during this process to ensure the consolidated data is comparable and adheres to regulatory requirements. 

Method 1 benefits 

  • A balanced approach ensures the traceability of work from tabulation source data while saving time through the harmonisation and integration of data into the ISS/ISE analysis database.

Method 1 risks

  • Inevitably this method requires reprogramming of endpoints, variables and derivations already programmed at a study level.
  • This approach may also require more time for creation and validation as the complexity grows with the harmonisation need of the study-level tabulation data. 

Method 2: ADaM only integration using study ADaM and/or legacy analysis data

This approach works well for analysing studies that were implemented with an integration submission strategy already in place and where they are also very similar in their design. In other words where they have used consistent controlled terminology and variable definitions across the studies to be included clinical trials. The process is effectively the same as the previous method (including MedDRA/WHODrug upversioning), but here data from the various studies’ ADaM and legacy analysis data feed directly into the combined ISS/ISE ADaM database instead of using the study-level tabulation data. 

Method 2 benefits 

  • This method enables the fastest creation of the ISS/ISE ADaM database, ideal when the integration was already preplanned in the individual studies and therefore consistent terminologies and dataset structures were ensured from the start.

Method 2 risks 

  • This approach has less flexibility in cases where the ISS/ISE is intended to include endpoints that are not covered by the study-level ADaM/analysis databases already. In such a case, SDTM/tabulation data will need to be integrated subsequently requiring more time. 

Method 3: SDTM and ADaM integration using study SDTM and/or legacy tabulation data

This method aims to first create a dedicated integrated database (IDB) on the SDTM level, ensuring that the study-level SDTM/legacy tabulation data is stored in a unified and harmonised fashion, which then functions as the basis to construct the ISS/ISE ADaM database. 

The SDTM IDB created here can also be further expanded in the future with new/other studies within the same compound. It also offers the added flexibility that it can be reused for other ISS/ISE analyses. For example, if for the same product two different indications are pursued the same SDTM IDB can be used to cover two separate indication-specific ISS/ISE ADaM databases.

Method 3 benefits 

  • Greater traceability and flexibility is possible following this approach.
  • The review of SDTM datasets is simplified by their availability in a single integrated SDTM dataset per domain. For example, a reviewer could review information of a specific single study by filtering an integrated SDTM domain by STUDYID.
  • The SDTM IDB can be reused or further expanded for future analyses needs.
  • Separates the complexity of harmonising the incoming data from the complexity of creating the ISS/ISE analysis, simplifying an otherwise difficult project into easier manageable chunks.
  • This is especially noticeable when including a number of legacy studies that have extensive harmonisation requirements.
  • The integrated SDTM datasets provide a single input source for the ADaM programming. This eases maintenance, clarifies the programs and provides traceability.

Method 3 risks

  • This process ultimately takes the most time. If there is no intention to reuse the SDTMs for future submissions, or the to-be-included data requires little harmonisation effort and is not from a lot of different studies, the cost of following this approach quickly can become too high for the benefits it brings. In those cases, Methods 1 or 2 would be the better choice.

Method suitability at a glance

ADaM-only integration strategy

Method 1 or 2 suitable if:

SDTM and ADaM integration strategy

Method 3 suitable if:

  • All ISS and ISE analyses and resulting TFLs can be generated based only on integrated ADaMs
  • Only few of the input studies are not CDISC compliant
  • Method 2 can be followed only in situations where the analysis definitions of individual studies is consistent with that on 
    integrated analysis plan
  • Combination of studies with CDISC vs. non-CDISC compliant SDTM-level datasets
  • Intent to reuse the SDTM IDB for future submissions (e.g. different indications)
  • High need of harmonisation due to differences in source studies

 

 

Recommendations and considerations

Before determining which approach is most appropriate the sponsor or CRO should conduct an initial review and gap analysis of individual study data and documentation. The results of this initial review can be all that is needed to determine if the to-be-selected approach should consider the creation of an SDTM IDB first or can directly skip to the ISS/ISE analysis.

Generally speaking, four areas are critical when planning an ISS/ISE strategy: timelines, data quality, ensuring traceability, and roles and responsibilities.

Timelines

  • Preplanning from the early stages is advisable to avoid missing data or artefacts at start-up
  • For biologics license applications (BLAs), the FDA does not require integration, however they still do recommend it
  • The latest when an integration strategy is selected, a gaps analysis should be conducted
  • Discussions with the regulatory agency should be carried out early on, or at the phase 2 meeting
  • A follow-up second discussion can take place at the pre-NDA meeting
  • Time should be planned for upcoding medical dictionaries and involving the sponsor medical team in developing the ISS/ISE

Data quality

  • To minimise the risk of inconsistencies within or across study data individual study data and scale of work should be evaluated
  • It needs to be determined if single-study CDISC conversion is required for studies in legacy format or if these can stand on their own
  • Medical terminology needs to be upcoded to MedDRA and WHODrug standards
  • Both ISS and ISE should include effects and risks in subpopulations 

Ensuring traceability

  • Data integrity should be ensured by verifying integrated counts against individual studies, if applicable and required
  • The integrated statistical analysis plan (SAP) should be started after the phase 2 study SAP is final
  • This SAP should include details of the studies that are to be pooled in the SAP, specifics on how the treatments will be grouped and should also include mock shells
  • If legacy study data is converted to SDTM, the conversion strategy should be documented in the cSDRG (study or SDTM IDB level) or ISS/ISE ADRG 

Roles and responsibilities

  • Clearly defined roles and responsibilities are essential to avoid late changes based on regulatory consultation or after hand off
  • If using a CRO, the different roles and responsibilities for both CRO and sponsor should be agreed
  • Submission timelines, including regulatory consultations should be transparent and clearly outlined 

Preplanning and partnership are key to successful submissions

As with all regulatory requirements, preparation is a prerequisite for success. Early planning, identifying the appropriate integration method and conducting a gaps analysis can mitigate many of the risks associated with ISS and ISE submissions. However, with constrained timelines and inexperienced staff it can be difficult to assign the necessary resources. Partnering with an experienced CRO will streamline the transformation of data from multiple, complex studies into a submission-ready deliverable, without allocating additional inhouse resources. Through tried and tested work structures, open communication and collaboration, ICON ensures that sponsors meet regulatory expectations and CDISC standards. Our support continues after submission when a dedicated rapid response team is available to support post-submission queries and time-sensitive requests. 

Partner with ICON to transform your data into submission-ready deliverables that meet global expectations and move your program forward.

Contact us today or visit www.ICONplc.com/biostats to learn more. 

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