In any industry where data is a major component for compliance (e.g., Biotechnology/Pharmaceutical), regulators need to efficiently review and process the submitted data. To achieve these goals, many regulators have established data standards. However, as regulation and the number of standards increase, so does the time and effort it takes to develop, manage, and distribute standards in a way that results in the benefits intended. Implementation of these standards is often burdensome and expensive for industry due to impact on existing business processes. As a result, organizations typically perform duplicate work to convert data to standardized formats after the fact for regulatory purposes. This inefficient approach results in longer cycle times, higher costs, and lower quality data.
Data standards alone are not enough to overcome these issues. Only through Semantic Interoperability can regulatory agencies and industry achieve benefits from these standards. By binding systems to robust common domain terminology produced by standards development organizations (SDOs), industry can more efficiently implement end-to-end data lifecycle processes.
Over the last decade, the amount and complexity of clinical study data has significantly increased. The Clinical Data Interchange Standards Consortium (CDISC) has developed several clinical data standards to increase patient safety, data quality, and enable more efficient regulatory reviews, and regulators globally are moving towards requiring data to be submitted in these standard formats, This is driving BioPharma and supporting companies to seek out tools for implementing the standards in a more automated way in order to achieve regulatory standards compliance and improve overall business efficiency.
To effectively implement standards and be able to better manage change, data must be defined more broadly, but managed more granularly. Data should no longer be defined for a single system or use, but more broadly by industry level standards to facilitate reusability of the data. More granular management doesn’t mean managing data any differently, but requires additionally managing data about the data, or metadata. This facilitates lifecycle management for the data and enables flexibility in the clinical development process.
To achieve data lifecycle management and process flexibility, the recommended technology is a metadata repository (MDR) that supports the implementation of standards and their use to develop and manage operational and study level metadata. Ideally it will have a flexible metamodel definition framework that easily accommodates new metadata standards, and a standards governance process that facilitates impact analysis and inheritance of changes.
Akana’s Semantics Manager is built upon an industry-leading repository and governance platform. It enables SDOs to develop, obtain and incorporate reviewer input, manage, and distribute metadata standards more efficiently, and helps industry to implement standards faster and more effectively while automating and improving business processes.
Semantics Manager has been chosen by the Clinical Data Interchange Standards Consortium (CDISC) to power its Shared Health And Clinical Research Electronic (SHARE) Library project. CDISC SHARE will provide a global electronic repository for developing, integrating and accessing CDISC metadata standards for clinical research in electronic format.