Labeling of pharmaceutical products is a complex and dynamic process requiring organizations to assemble information from multiple sources, consistently provide accurate information, comply with changing global regulatory guidelines, while ensuring that products are launched at the right time across markets. Generic authoring and content management applications that are tweaked to manage labeling content and life cycle operations are unable to achieve desired levels of effectiveness and efficiencies, resulting in wasted resources and high costs of compliance. Outsourcing to third parties further adds to project management overheads.
Indegene's Intelligent Labels empowers global pharma enterprises to modernize their enterprise-wide labeling data and operations and transform the way labels are generated, contextualized, and published for consumption by patients and HCPs. Custom-built for global life sciences enterprises and augmented by AI and advanced analytics, Intelligent Labels drive content effectiveness, operational efficiency, and regulatory compliance across label life cycles.
Organizations use multiple siloed applications to manage label life cycles - like MS Word/SCA tools, document management systems, workflow management systems, regulatory intelligence management systems, submissions management systems- causing operational inefficiencies. Intelligent Labels eliminates the need to use disparate bespoke applications with complex integration pathways. Using a single enterprise solution, Intelligent labels, pharma organizations can manage label life cycles end-to-end, including content consolidation, structuring, authoring, reviews, workflows, and regulatory submission tracking. The SaaS-based solution can be easily plugged into an enterprise's existing technology ecosystem and scaled up or down depending on business needs.
Product labels source data from multiple documents including clinical study reports, core data sheets, safety documents and investigator's brochures. Sifting through these documents for relevant and most current content is mostly handled manually and is a cumbersome process. Intelligent Labels simplifies the process with accelerated onboarding, machine-led deconstruction and classification of the source content universe into a central repository of structured and reusable data components. The components can be interlinked across documents basis organizational content standard operating procedures, thereby simplifying content tracing, reuse, and change management. Using Intelligent Labels, subject matter experts are able to free up time from redundant data sifting and consolidation activities and invest their expertise on more strategic labeling tasks.
Traditional MS word/SCA tools for label authoring are highly dependent on human expertise to ensure content accuracy and consistency, resulting in oversights, multiple review iterations, and long content cycles. Intelligent Labels provides users with an Assisted Authoring Studio, enabling them with intelligent utilities like automated first drafts and updates, SOP-based content recommendations, cognitive component search, rich-text editors, predictive patient-friendly language generation for PIL, collaborative reviews, and many more, ensuring content quality and shorter content cycles. Enterprises are able to achieve consistent delivery of accurate product information to customers and healthcare professionals in significantly shorter times.
Global pharma operations present an inherent requirement to orchestrate and comply with standard operating procedures across departments and markets. Any deviations from standards can lead to unplanned queries from health authorities, subsequent content iterations and delays. Intelligent Labels enables automated tracking and management of deviations from defined operating procedures. Proactive management of subsequent responses to queries from health authorities and follow-up until closure is made much simpler using intuitive alerts and dashboards.
Labeling content standards can vary across regulators from different geographies. Product-related information across multiple downstream documents are expected to be consistent yet compliant with multi-geographic requirements. Constantly evolving regulatory standards add to the challenge as they warrant migration of all existing labels to new standards. Inbuilt template and style-guide management capabilities in Intelligent Labels enable labeling teams to centrally define market-specific requirements and activate automated workflows for intelligent laying of content in respective standards. Automated checks across upstream and downstream labels ensure harmonization of labels, common classes within labels and also help assess impact of deviations. Tools are made available for easy modification or creation of new templates to accommodate new guidelines, and seamless migration of existing labels to new standards.
Toggling between authoring, regulatory intelligence and submission tracking tools for product labels increases the probabilities of human oversights, missed submission deadlines, and longer regulatory approval cycles by a considerable extent. This can cost pharma enterprises with longer time to procure marketing authorizations in the product patent period and therefore lost revenues.
With Intelligent Labels, organizations can consolidate the entire label lifecycle onto a single platform, including regulatory intelligence and submissions handling. Built-in with functionalities like content syndication, milestone tracking dashboards, optimized submission planning, and HA feedback lifecycle management, the platform enables enterprises achieve efficiencies in regulatory approval management and therefore faster time to market with new products.
Health authorities across the globe have been working towards refining their guidance for distribution of product information to achieve industry-wide standardization, enhance interoperability and ensure timely delivery of accurate information to regulators, health care professionals and consumers. Some of these regulations include SPL/SPM, e-labeling, ePI , and Dynamic Dossier in the Cloud Evolving regulations warrant organizations to have flexible systems that can accommodate the changes rather than having to invest in new technologies and systems with every change.
Intelligent Labels-based content is digital in nature, making the incremental effort to adhere to newer standards minimal. Delivered on a SaaS infrastructure, any incremental changes required can be easily applied on the platform, providing organizations with the flexibility to scale up or down basis business and regulatory requirements.
Intelligent Labels empowers labeling teams with continuous insights that enable efficiency improvements. Out-of-the-box analytical dashboards provide intelligence around content-reuse, adherence to standard operating procedures, content harmonization, and content lifecycle milestones.
Content cycle times reduced by more than 30%
Assisted authoring and collaborative reviews achieving more than 40% enhancements in resource productivities
More than 30% cost savings on content iterations
99% content accuracy with reusable components, deviation checks, and content comparator tools
Flexible architecture that allows seamless migration to new regulations
Simplified enterprise-level management of label life cycles
Proactive tracking and management of label content and timeline compliance across markets
Intelligent content authoring (ICA) involves creation of a fully indexed knowledge base derived from source documents, and helps ensure faster time-to-agency, faster time-to-market, and exceptionally high gains in productivity and efficiency in developing medical content.
E-labels will mitigate a lot of challenges that are inherent to physical labels. When augmented with AI solutions and a robust content management system, e-labeling can be seamlessly implemented across business units and markets.
Sian Ratcliffe, Head of Medical Writing, from Pfizer and Tarun Mathur, Chief Technology Officer, from Indegene discuss how, at Pfizer, content generated throughout the drug development lifecycle is managed using medically trained machine intelligence to accelerate authoring and updating of clinical and regulatory documents.
