Altarum’s subsidiary, KAI Research, Inc., uses clinical trial data standards experts to enhance study efficiency and timely submissions.  Our experts understand a wide range of industry data standards and apply them to the needs of individual studies. The skill at supporting and working with such a range of data standards maximizes the ability to meet clients’ goals. KAI can collaborate with clients to ensure that the appropriate standard is implemented from the beginning. For existing studies that do not adhere to a specific standard, we leverage knowledge, tools, and experience to transform metadata and produce deliverables that conform to an industry-wide or sponsor-specific standard.

The overall deliverable is a submission database that FDA reviewers can use to easily confirm study analyses. This gives regulatory agencies confidence in the submission with fewer queries and an expedited review so that the drug may go to market sooner.

The KAI team has been involved in the creation of the industry-wide CDISC data standards and continues to participate in the CDISC organization.  KAI can design studies to support the current CDISC standard, a future version, or legacy versions as project needs dictate. These tools allow for submission databases that are consistent across each study and compliant with FDA standards and expectations.

Our clinical data warehouse repository provides for the construction and maintenance of a centralized data repository; integration of data from multiple data sources, including CROs and other external data vendors; and distribution of data to multiple output channels. Output channels include standard data models in CDISC standards and reports facilitating study submission activities. The solution provides an environment that takes into account the specific FDA regulatory requirements for 21 CRF Part 11 software systems. KAI offers the following data warehousing services:

  • Conversion of legacy data into CDISC study data tabulation model-compliant datasets in SAS or XML format, and
  • Data warehouse design and conversion.