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Can Automation Reduce Non-Compliance In Pharma Industry?

By CIOReview | Thursday, November 26, 2020

FREMONT, CA: Considering the limited chance for change in the regulatory landscape, the pharmaceutical industry needs to adopt automation that can drive business momentum without impacting the result.

In bringing new medicines to market, pharmaceutical companies create thousands of documents that need to be recorded, reviewed, and managed promptly. With strict regulations in place to ensure that all medicines are efficient and safe, meeting pharma regulatory compliance is essential. Process automation technology can help pharmaceutical firms boost productivity and collaboration while meeting all their regulatory requirements. Here is how.

Due to the prevailing non-interoperable legacy enterprise systems, pharma regulatory teams worldwide face issues like inconsistent and incomplete data filing. It is daunting to ascertain if the organization uses the advanced documentation process, especially when users are using disparate systems, leading to inconsistent filings and submission mistakes. This is where automation's potential can be harnessed effectively, to conceptualize and create an intelligent system with access to all data. This system accounts for a single source of truth that can offer consistent and complete data through a single repository for all documents. Automation also improves customer service, increases productivity, helps firms meet compliance requirements, and lowers costs.

With the legacy regulatory approach, it is difficult to effectively collate, process, analyze, archive, and exchange data and ensure cost-efficiency. This can result in late submissions leading to delayed approvals for drugs. If regulatory data is not managed effectively, pharmaceutical companies become vulnerable to the risk of non-compliance, which, when combined with issues in data integrity, can lead to rejection of application and degradation of the firm's reputation. To overcome these challenges, pharmaceutical companies need to analyze the existing regulatory process workflows, identify operational gaps, and adopt automation tools.

A centralized repository with automated responses to health authority questions coupled with an AI-driven extraction system for reading and interpreting query responses is a good example of automation in this context. Every time a query enters the system, the AI-powered smart search engine will be able to search the internal repository for the right response with reference data. This also lets the re-use of data, brings speed to response authoring and compilation, and reduces overall cycle time for faster regulatory approvals