Pressed by the COVID-19 crisis, life sciences companies have pointed their spotlight toward regulatory performance. Given the need to petition health authorities for variations to registrations and clinical protocols, as well as opportunities for Emergency Use Authorizations (EUAs), life sciences companies are placing new burdens on their regulatory teams. A global regulatory process transformation was taking place even before COVID-19, with a focus on adopting global regulatory information management (RIM), reducing operational complexity and continuously improving speed and quality.
To inform industry about the evolving maturity of regulatory capabilities, Gens & Associates conducts a biennial survey tracking industry performance, technology trends and key drivers of change for regulatory divisions. The 2020 World Class RIM Study
, conducted between February and April, focused on the question “Is industry at a performance tipping point?” According to Managing Partner Steve Gens, the results clearly found the answer is “Yes.” Given the COVID 19 crisis, he expects acceleration of digitization and streamlining of global regulatory processes. He said the survey will remain open until the fall since many companies were impacted by the crisis. In addition, a COVID-19 impact pulse survey will be released this fall.
Survey results show that RIM has become an enterprise asset. As companies modernize this capability, they are connecting to key areas of the enterprise with safety/pharmacovigilance, change control/enterprise resource planning and label/artwork management as the value priorities. This connectivity brings a new wave of automation and analytic possibilities.
Support from regulatory intelligence
Registration and life cycle maintenance activities can be better supported by improved application of regulatory intelligence (RI), said Grant Thornton Life Sciences Regulatory and Quality Leader Pat Shafer
. According to Shafer, many of his clients estimate that their regulatory professionals spend 30% to 50% of their time looking for information. This alone is reason for commitment to transformation. Add the fact that expectations of health authorities are not sufficiently defined by requirements subscriptions, and it’s easy to see why companies are looking to exploit the wealth of information embedded in health authority meeting minutes, approval letters and responses to questions. Companies are also exploring other sources — leveraging knowledge management to retain on-the-ground experience and analytics to extract metadata from RIM systems to inform resource planning and approval forecasting.
The other challenge is deployment of information. Too often, RI output is in the form of a newsletter or blast email, and not readily available when needed. Leading companies embed the intelligence in automated workflow and document templates to ensure the requirements are reflected in the regulatory product.
The RIM system is also the primary source for regulatory performance analytics. RIM systems track planning and execution of submission development. As RIM systems become integrated with document management and content development systems, leveraging the metadata can provide valuable insights into how long it takes to develop, review and approve content.
Rather than just looking at historical performance, you can drive (and continuously improve) performance by monitoring activities in real time to identify constraints. You can then proactively break logjams to make sure submissions stay on track.
Mastering change control and variation management
Manufacturing changes — such as the supply chain adjustments made necessary by COVID-19 — may require submissions to health authorities. Depending on the change being made, these submissions could be simply notification to regulatory bodies of the change at the end of the year in an annual report. For some changes, health authority approval may be required prior to implementing the change. Managing supplements and variations related to manufacturing changes is one of the greatest challenges that regulatory teams face. Performing the regulatory impact assessment for the change control process is time consuming and can delay manufacturing changes for months, sometimes over a year, especially where agency approvals are required. Additionally, health authority rules related to such changes vary by region and country and many country-specific submissions may be required to implement the change globally.
The challenge in many companies is compounded by manual, disjointed processes and systems across quality, manufacturing and regulatory. It is time- and resource-intensive to understand the impact of the change and what submissions need to be filed in which markets while navigating siloed quality management and regulatory processes and systems. The lack of integration, combined with the no easy access to the right data, opens the door to delays, rework and compliance risk. For example, over time, approved product registrations can fall out of sync with manufacturing processes and procedures if the appropriate agency approvals are not obtained. As a result, firms can be subject to fines and other penalties if this discrepancy is discovered in an audit.
Companies are looking at ways to streamline change control management to more tightly integrate processes across quality, manufacturing and regulatory, as well as to provide more reliable, easy-to-access data to support the impact assessment and variation filing process.
The data within more modern RIM systems that include submissions document management, combined with regulatory intelligence and an integrated QMS, makes it possible for stakeholders to understand the regulatory impacts of a change. The data can help identify the submissions, and submissions content and approvals needed in each country. The figure below highlights the multiple decision points critical to advancing the manufacturing change agenda, as well as the systems that support those decisions.
The RIM system also supports change implementation. By leveraging submission and approval dates, the system informs the manufacturing teams about the time typically taken by different health authorities to review and approve variations. This allows for more precise implementation planning.
Enhancing regulatory performance with advanced technology and AI
As shown in the change control example and echoed in the Gens survey results, companies are looking to further enhance speed to market while maintaining or improving compliance by enabling more efficient hand-offs with touch point areas. This is essential because of the volume of information is exchanged among Regulatory and other departments across the enterprise.
The shift back toward structured data submissions such as identification of medicinal products (IDMP) has led to an increased focus on leveraging regulatory data to make processes more efficient. COVID-19 has shown life sciences leaders how they can rapidly innovate and make transformational changes to more quickly benefit patients. Taking these factors into account, there are many opportunities to make these interactions between functional areas more efficient, e.g.:
- Management of manufacturing changes to gain significant efficiencies and reduce compliance risk
- Artwork management and end-to-end labeling to cut costs while increasing compliance
- Streamlining hand-offs with Clinical and Safety departments to minimize redundant entry of protocol data across systems and simplify — including relevant trial master file and adverse events documents in regulatory submissions
- Integration of portfolio, application and submission planning processes and systems
Making the most of advanced technology and artificial intelligence (AI) can help further cut costs and streamline processes. Companies are actively seeking to understand how they can apply intelligent automation to regulatory activities and how they can benefit. “Robotic process automation [RPA] and various AI technologies,” said Cary Smithson
, Grant Thornton director of Digital Transformation and Management in Life Sciences, “can be used to automate document quality checks for submission readiness to reduce time to prepare agency submissions.”
A best-practices approach is prioritizing problem areas and resolving them by matching them up with the appropriate technology.
Step 1. Identify process inefficiencies and non-value-added tasks across the functional areas.
A key concept is to avoid automating inefficient processes. Simplify processes where possible prior to applying automation. For high-volume, repetitive tasks such as transferring data from forms to RIM, consider RPA. For more cognitive tasks, such as identifying regulatory intelligence or IDMP data from documents, consider machine learning or natural language processing (NLP).
Step 2. Define the future process and requirements, and agree on terminology and data structures, or map to a common structure across units.
Define how you’d like the future process to work, with an eye on available technologies but without getting bogged down in selecting specific tools. Where possible, leverage industry standard data models and reference models, such as the DIA RIM Reference Model, to avoid reinventing the wheel and more easily interoperate with other organizations and health authorities. This step establishes the foundation for easier process and system integration. Cross-functional process integration has been a long-standing pain point, and resolving these barriers is now a top priority, according to the Gens survey.
Step 3. Select technology solutions and implement the new process and system capabilities.
Applying RPA and cognitive technologies is no different from implementing more established technologies. The software development life cycle should be followed, including testing, training and organizational change management.
Intelligent automation comprises several kinds of technologies — from basic tools like RPA (which can be likened to an advanced Excel macro because it blindly follows steps and rules) to more advanced AI-like machine learning and NLP that can read language and learns based on data obtained and defined parameters. Different problems are best suited to each type of tool or a set of tools chained together.
To date, RPA has yielded some benefits to industry, and firms are earlier in their exploration of other intelligent automation tools, e.g., NLP and natural language generation, which can be used to generate new submission documents from a sample document, relevant metadata and sample text. Active industry groups are focused on driving regulatory innovation and use of technology.
The COVID-19 crisis has prompted a bolus of regulatory activity. Some practices (such as the volume of EUAs) will fade as the crisis eases. Others that provide lasting value to the industry will endure.
The volume of EUAs is unprecedented, with over 100 issued by the FDA in multiple areas including diagnostics and medical devices. More will be coming with the addition of therapeutics and vaccines. Rapid review and approval increase risks, and the industry has seen some of EUAs rescinded when real-world evidence demonstrates concerns regarding safety or efficacy. FDA Commissioner Stephen Hahn
has indicated that the agency will continue — and will perhaps increase — reliance on post-market evidence to support more rapid reviews.
The short- and long-term regulatory practices put into place due to the current crisis reflect the overall transformational changes. The ecosystem needs to move with greater speed and less risk. Lessons we can draw are to better manage intelligence and that data is key to speed, operational efficiency and compliance.
For more information and insights, register to replay Regulatory implications for the Life Sciences industry: Strategies to build a confident tomorrow
Leader, Business Consulting, Life Sciences
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Leader, Regulatory and Quality, Life Sciences
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Director, Digital Transformation and Management, Life Sciences
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