Facebook
  1. Home
  2. Insights
  3. Blog
  4. How data intelligence tools are enhancing signal detection methods

How data intelligence tools are enhancing signal detection methods

Advancements in intelligence tools such as ICON’s Signet help overcome challenges with data volume, complexity and completeness to accurately and rapidly detect safety signals to ensure patient safety throughout the drug’s lifecycle.

Safety monitoring and signal detection is a critical component to drug development and meaningful therapeutic progression, ensuring that the drugs, devices and therapies remain safe and effective. Effective signal detection requires rich data to be collected, integrated, analysed and validated from a myriad of sources and occurs both during clinical development and post-marketing environments. 

The ever-deepening pools of data across the product lifecycle pose unique challenges, but advancements in technological capacity and data methods are supporting an industry-wide push towards more proactive signal detection. Business intelligence solutions coupled with artificial intelligence (AI) capabilities are tackling the challenges associated with vast dataset integration with intuitive solutions from end to end. 

 

Efficiencies for early signal detection

Early signal detection in clinical trials protects the patient population, mitigates risk to public health by identifying potential safety issues and informs regulatory and authorisation decisions. However, as clinical trial sizes grow and become more complex, safety monitoring must encompass larger and more heterogenous patient populations, meaning larger, richer and more varied datasets. A business intelligence tool offers a central platform for the analysis of this data. Centralising updated preclinical and clinical data into an intuitive interface can allow for early signal detection, identify safety issues sooner or uncover additional endpoints for consideration. It also has implications for cost-savings during the development lifecycle by identifying safety issues and enabling intervention that could result in costly potential failures.i

 

Agile regulatory and reporting 

Global trials are also confronted with varied regulatory requirements across different countries. An agile, robust intelligence tool can support compliance efforts with advanced reporting capabilities, ensuring regular reporting is complete, accurate and compliant to avoid regulatory hold-ups and costly delays. For example, ad-hoc analysis capabilities built into ICON’s Signet tool allow for custom report generation on demand, even outside of reporting schedules set by regulators. Increasing levels of detail can be visualised and downloaded or exported in multiple formats with detailed summaries to reflect the specific reporting needs. Even outside of regulatory reporting, the effectiveness of pharmacovigilance safety surveillance hinges on the ability to communicate important information quickly and with clarity. 

 

AI automation for efficiency

Automating the cleaning and transformation of the raw data via intelligent tools streamlines workflows and leads to timelier and more efficient detection of case-level and higher-order aggregate signals. This is especially useful for post-marketing data that comes from a multitude of sources and is not structured the same way as clinical data, with more variation in data completeness and coding between multiple sources. 

Additional challenges in data heterogenicity, relative completeness, complexity and volume necessitate further processing before it can be appropriately analysed. Manual approaches to cleaning, transforming and integrating the breadth of available data are burdensome, time consuming and prone to processing errors. AI built into some business intelligence tools, like Signet, allow for automated review of aggregated data that replaces the manual data input and analysis, minimising the burden on human analysts and reducing time and resource burdens while decreasing risks to patients’ lives. 

 

Continuity from pre-clinical through post-marketing 

Clinical and post-marketing signal detection efforts can be undertaken as separate projects, however, there are benefits to using a single data integration tool to link insights across both. The high-quality, validated data collected and analysed in pre-marketing clinical settings is important to understanding and even anticipating safety signals in post-marketing. By using one business intelligence tool, sponsors are guaranteed more continuity in their safety monitoring between the two stages, avoiding the potential for losing data in a transition and ensuring that all the knowledge and insight captured in clinical monitoring is preserved as a foundation for post-marketing monitoring and analysis. 

 

More data, deeper insights

Incorporating more patient data across a wider range of the drug lifecycle creates the possibility of generating deeper insights – if appropriately managed, maintained, visualised and analysed. Intelligence tools like Signet are built to ingest, integrate and review wider ranges of granular and aggregated data for rapid, precise analysis. The capacity to generate real-time data visualisation enables analysts to drill down into the data, assessing various components such as gender, age, country, etc.  

Increasing levels of detail can be layered or isolated and incorporated into custom visualisations, allowing analysts to examine novel reconfigurations of the near real-time data or toggle through various cohorts to better identify trends and areas of interest. This technology facilitates deeper assessments of continuously updated data at previously impossible speeds. 

 

Proactive approaches to signal detection

With the exponential expansion of data and the reciprocal advancements in business intelligence tools to efficiently engage that data, signal detection methods have made significant strides. We are now able to generate a more holistic view of the safety data throughout the drug’s lifecycle and detect signals faster than ever before, aided by AI analysis and automation and broader data management solutions. Leveraging leading technologies like Signet allow for faster and more accurate identification of risks – and we can even begin to predict them. As the industry continues to drive innovation in safety monitoring through the integration of Big Data, next-generation business intelligence tools and AI capabilities, the potential for pharmacovigilance expands from reactive toward proactive approaches. 

Contact us to learn more about how Signet’s cutting-edge solutions can support your pharmacovigilance program. 

References:

iYao B, Zhu L, Jiang Q, Xia HA. Safety monitoring in clinical trials. Pharmaceutics. 2013 Jan 17;5(1):94-106. doi: 10.3390/pharmaceutics5010094. PMID: 24300399; PMCID: PMC3834937.

In this section

Connect with us