Over the past decade, technology has played a pioneering role in driving biopharmaceutical innovation and created significant disruption in the regulatory environment. The regulatory aspects of Chemistry, Manufacturing, and Control (CMC) are evolving rapidly with advancements such as analytics, automation, robotics, and blockchain, becoming mainstream in strategic and operational functions.
Automated Regulatory Equals Scrutinized Compliance
One of the many revolutionizing technologies – intelligent automation – has now become an inseparable part of several business functions. From lowering costs to simplifying data gathering between different systems, automation presents numerous opportunities to enhance quality and efficiency. Technologies in artificial intelligence (AI) such as machine learning (ML) and natural language processing (NLP) take over manual, repetitive, and time-consuming tasks to achieve self-evolving, automated systems with rapid outcomes. Let us take a look at a couple of scenarios where technology could potentially disrupt the traditional regulatory process.
Handling Data Silos
Due to the prevailing non-interoperable legacy enterprise systems, regulatory teams across the world, face issues such as inconsistent and incomplete data filing. It is cumbersome to ascertain if the organization is using the latest documentation process, especially when users across the globe are using disparate systems, leading to inconsistent filings and submission errors. This is where the power of automation and AI can be leveraged effectively, to conceptualize and create an intelligent web-based system with access to all artifacts. This web-based system accounts for a ‘single source of truth’ that can provide consistent and complete data through a central repository for all types of documents. Further, automated processing and AI improves customer service, increases productivity, helps groups meet compliance requirements, and lowers costs.
Automating Regulatory CMC data
With the traditional regulatory approach, it is difficult to collate, process, analyze, archive, and exchange data effectively and ensure cost efficiency. This can result in delayed submissions leading to late approvals for drugs. If regulatory CMC data is not managed effectively, pharmaceutical companies become vulnerable to the risk of non-compliance, which when coupled with issues in data integrity, can lead to application rejection and degradation of the organization’s reputation. In order to overcome these challenges, pharmaceutical companies need to analyze the existing regulatory process workflows, identify operational and technological gaps, and adopt automation techniques. A centralized repository with automated responses to health authority (HA) questions coupled with AI-driven extraction engine for reading and interpreting HA query responses is a good example of automation in this scenario. Every time a new HA query enters the system, the AI-enabled smart search engine will be able to search the internal repository for the right response to questions with the help of reference data. This also enables the re-use of data, brings speed to response authoring and compilation, and reduces overall cycle time for faster approvals.
Effective Regulatory Automation
Irrespective of the fact that technology can benefit pharmaceutical companies, regulatory CMC and operations teams need to assess the real need for automation and the ways it can improve process efficiencies. To begin with, specific process automation requirements can be defined by:
1. Mapping the entire end-to-end processes
2. Identifying process steps that can be automated
3. Leveraging appropriate criteria to understand the logic for automation, maturity of process and business value, and availability of data
The target model for automation can be defined with the help of the aforementioned steps following the evaluation process. For effective management of regulatory automation, organizations must pay attention to the following aspects:
Intelligent operations: Pushes data-driven models through smart alerts and workflows.
Technology simplification: Enables programs focused on process automation and rationalization, and makes the technology landscape smarter, scalable, and future ready.
Data repositories: Implement databases and invest in development capabilities in advanced analytics. Improve data quality and accuracy by adopting standard approaches and allied technologies.
AI and cognitive: Leveraging AI technologies to convert information from structured and unstructured sources into knowledge and actionable insights.
The Way Forward
Considering the limited scope for change in regulatory procedures, the pharmaceutical industry needs to focus on automating the approaches that can propel business momentum without impacting the desired outcome. While automation will result in significant time savings for regulatory development and compliance teams, it also ensures better data reliability. Furthermore, it allows the possibility of analyzing data in more meaningful ways by connecting different data sources and conducting data crosschecks.
It is evident that regulatory process automation will spur the current process and act as a catalyst for the existing tools in obtaining desired outcomes, accelerating regulatory submissions, and expediting product approval processes.