The biopharmaceutical sector is utilizing technologies and develop substantial disruption in the regulatory environment.
FREMONT, CA: Technology plays a groundbreaking role in driving biopharmaceutical development over the past decade and has produced substantial disruption in the regulatory environment. With advancements including analytics, automation, robotics, and blockchain, the regulatory aspects of Chemistry, Manufacturing, and Control (CMC) are changing rapidly, becoming common in strategic and operational functions.
Automated Regulatory Equals Scrutinized Compliance
Intelligent automation, one of several revolutionizing innovations, has become an inseparable part of various business functions. Automation provides multiple opportunities to increase quality and performance, from reducing costs to simplifying data collection across different systems.
In order to accomplish self-evolving, automated systems with rapid performance, artificial intelligence (AI) technologies like machine learning (ML) and natural language processing (NLP) take over manual, repetitive, and time-consuming activities.
Handling Data Silos
Regulatory teams worldwide face challenges like inconsistent and incomplete data filing due to the existing non-interoperable legacy business structures. It is difficult to decide whether the organization utilizes the best documentation process, mainly when users worldwide use different systems, resulting in conflicting filings and errors in the submission.
Check This Out: Top Artificial Intelligence Companies
This is where it is possible to effectively harness the power of automation and AI to conceptualize and construct an intelligent web-based framework with access to every object. The web-based framework accounts for a 'single source of reality' that can offer all sorts of records with clear and complete data with a central repository.
Automating Regulatory CMC data
It is difficult to efficiently collate, store, interpret, archive, and share data and maintain cost efficiency with the conventional regulatory method. It may result in delayed applications that lead to late drug approvals. Suppose regulatory CMC data is not completely controlled. In that case, pharmaceutical companies are likely to be at risk of non-compliance, which can contribute to application denial and loss of the company's credibility when combined with data integrity problems.
Pharmaceutical companies need to evaluate the current workflows of the regulatory process, recognize organizational and technical gaps, and implement automation strategies to address these challenges. In this case, a centralized repository of automated health authority (HA) responses combined with an AI-driven extraction engine for reading and decoding HA query responses is a good example of automation. The AI-enabled smart search engine will be able to search the internal repository for the right answer to questions with reference data assistance any time a new HA query enters the system.