Accenture - Redefining Regulatory through Intelligent Automation
The day-to-day lives of most Regulatory professionals are abundant with digital connectivity, where different devices, platforms and apps all communicate seamlessly to create an automated experience. Want a car
to come and collect you where you are? Uber can do that and give you all the relevant information you need with the click of a button. For many of those same professionals, however, the experience of their Regulatory
working environment doesn’t reflect the same ease of use… but that could be about to change.
In our report, Intelligent Life Sciences: Redefining Regulatory through Intelligent Automation, we explore the rapidly growing potential and impact of Intelligent Automation in Regulatory. We found that by embracing new technologies and a change of mindset, automation can help Regulatory professionals rebuild their strategic influence in life science organisations and get back to what brought them to the industry in the first place: helping bring products to patients faster.
A new wave of intelligent tools and techniques is revitalising Regulatory. Some life sciences companies are ready to jump on board and gain efficiencies. Others may find themselves barely able to stay afloat.
The tools and techniques include analytics, robotic process automation (RPA) and artificial intelligence (AI) methodologies such as machine learning and natural language processing.
Their value comes through partnership with technology collaborators and innovators who are painting a more nuanced portrait of human health that regulators will need to see. The tsunami of Regulatory data floating around organisations includes registration data, research and product data and health authority correspondence.
The goal of Intelligent Automation is to make data work for Regulatory professionals, not the other way around. With a new toolkit and skill set, Regulatory professionals can rebuild their strategic influence in life science organisations.
They will return to what gets them out of bed in the morning, shaping research and development for the benefit of patients.
This is Regulatory redefined.
It’s how the Intelligent Enterprise will dictate future growth in life sciences.
Most people in Regulatory Affairs chose the profession to help patients.
Not because they love data entry.
Yet many are awash in a sea of data, and swimming against the tide.
There is a better way.
However, according to Accenture research, most organisations are still struggling to understand and assure the basic “truth” of the data they use and exchange with others.
The Accenture Technology Vision survey found just one-third of 103 life sciences executives have high confidence in their data and validate them extensively. One in four executives said they validate data sources to some extent and believe there is a lot more they need to do to ensure data quality.
There is greater urgency now because their companies will need more real-time and near real-time data to drive critical business decisions.
To confirm data veracity and increase confidence, Regulatory needs to change the way people collect, curate, interpret and apply data for submissions.
In the future, the Intelligent Enterprise will follow these 4 steps to make this change:
Utilise cloud-based solutions with global access that facilitates one repository with a single source of truth and eliminates the use of local file sharing and servers. Integrate applications across the end-to-end value chain eradicating data entry duplication.
Apply data standardisation and master data management to define the right granular level of data for storage. Implement robust data governance and management to maintain data quality and integrity. Ensure traceability of data evolution, as well as end-to-end transparency of submission status and its components.
Use readily available data to drive business decisions and optimise operations. Apply analytics to past submission data to recommend future submission content plans and pre-empt and mitigate health authority (HA) questions.
Use stored data to intelligently create submission documents. Limit documents full of free text fields and subjectivity to adopt a more digitised approach, where document templates can be compiled automatically from available data. Make real-time data accessible to the consumers of the information when and where it’s needed. Manufacturing scheduling can be optimised, and batch release decisions more informed. Healthcare practitioners can get the most up-to-date product information at their fingertips. Some companies have taken a few of these steps. Others are a long way off. By failing to embrace the opportunities offered by new technologies, they have no way to unlock true data value.
Confirming data veracity is necessary for realising the full benefits of AI. The low confidence in data revealed by the Accenture Technology Vision may explain why the survey also found that 85 percent of life sciences executives say that AI is advancing faster than their organisation’s pace of adoption.
There is a clear imperative to accelerate progress. Over the next few years, life sciences companies must be ready to manage increases in the volume and complexity of new products coming to market.
The industry's late-stage pipeline is forecast to be sustained at a minimum of 40 New Molecular Entity approvals annually over the next five years.
The opportunity for introducing and growing Intelligent Automation in Regulatory has never been greater; and the need, never more relevant.
Here are some common use cases, showing how Intelligent Automation is changing the game:
Regulatory Requirements & Content Plans
Problem. Maintaining data on submission requirements is a constant challenge. As a result, market requirements gathering is often repeated for each submission, leading to longer lead-times. Additionally, insights gained from HA feedback are not incorporated into submissions, reducing first- time submission approval accuracy.
Solution. Submission contents are suggested using analytics and AI, which analyses past submission activity and previous HA interactions.
Benefits
Reduced time and effort with submission preparation
Increased consistency of filings
Improved right-first-time filing accuracy and fewer HA questions
Health Authority Correspondence Processing
Problem. Timely recording of submission approval dates or tracking of HA questions can be challenging when information received by affiliates needs deciphering and translating before being entered into Regulatory systems.
Solution. AI tools can translate and decipher letters without the need for local affiliate intervention and automatically enter information in Regulatory Information Management systems for stakeholders to act upon.
Same day entry of submission approvals and HA question tasks
Reduction in effort equating to a $1mil saving per 10,000 submissions
Increased compliance and regainedsystem confidence
Label Authoring and Tracking
Problem. Managing and providing traceability of the roll out of global label updates is onerous based on language nuances, implementation considerations and replicated data terms across multiple documents. Leading to a high risk of product label inconsistencies.
Solution. AI tools can take the complexity out of mapping global-to-local terms and provide end-to-end traceability.
Reduced effort of reviews and hand-offs to multiple affiliates
Increased speed in getting updated information to patients
Improved compliance with a single source of registered information
Automation is needed to support the data interoperability revolution in healthcare, as science, technology and regulation all advance and converge to change how and where patients’ health and wellness needs are met.
The Accenture Technology Vision survey found 99 percent of life sciences executives expect the volume of data exchanged with their ecosystem partners to increase over the next two years.
These higher levels of data exchange put more pressure on Regulatory organisations that want to adopt automation. No partnership is going to work well unless Regulatory first gets its own house in order. A good foundation is possible by following a few fundamentals.
Accenture recommends that all automation projects are:
Business-outcome orientated: Solutions must be business-focused, rather than simply automating a task or a function. Successful automation programs often start with an overhaul and redesign of old processes, or invention of new ones.
Human-centered: While eliminating repetitive tasks, Intelligent Automation should put people at the center of its service organisation, augmenting the workforce by applying machines so that people can focus on higher-value analysis, decision-making, and innovation.
Technology-rich: Intelligent Automation solutions will often leverage multiple technologies, including open-source ones, from a broad ecosystem. Intelligent Automation needs to be integrated into the broader architecture of data sources and applications.
No matter how thoughtfully designed, however, there are common management pitfalls that could derail automation implementation projects.
Here are a few traps to avoid:
1. Software Engineering Principles Violated Many automation initiatives are carried out in silos leading to multiple overlapping objectives, resulting in chaotic programs.
2. Disconnect between IT and Business Businesses that make ad hoc implementations of RPA without aligning to the overall IT strategy lead to post-implementation support challenges and fall outs.
3. HR Management Lack of communication on how the workforce will be re-purposed post automation implementation can lead to internal unrest and possible attrition.
4. Change Control Ineffectively managing the communication of the implementation and its impact without proper change control and management.
5. Responsible Automation One key consideration missed in most automation initiatives: what are the ethical and legal implications when tasks are automated? Who is accountable and responsible for outcomes?
Becoming an Intelligent Regulatory function is not always smooth sailing.
Accenture has charted the typical journey a company takes to become an Intelligent Enterprise (see graphic).
There are headwinds to face. Yet clients that mature from the basic stage to achieve Intelligent Enterprise status reap quantifiable gains. Based on Intelligent Automation projects that Accenture have delivered globally, it is estimated that companies that reach maturity can realise increased value ranging from 40 percent to 50 percent efficiency saving through a carefully managed disruptive transformation program.
Efficiency gains made by industries that have reached maturity prove this journey is worth the effort.
To sum up the Accenture vision, we recall a voice from the past.
This concept still resonates.
Applying Intelligent Automation adds efficiencies and impacts on top of traditional improvement levers such as ‘centralise’, ‘standardise’ and ‘optimise’. Accenture is helping life science companies to realise disruptive benefits that are above and beyond the tangible gains of cost, quality and productivity improvements.
With Intelligent Automation, Regulatory may experience:
It’s a brave new world in Regulatory Affairs.
The life science organisation that matures into an Intelligent Enterprise will sail with confidence toward the horizon.
Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. We combine unmatched experience and specialised capabilities across more than 40 industries — powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. With 509,000 people serving clients in more than 120 countries, Accenture brings continuous innovation to help clients improve their performance and create lasting value across their enterprises.
European Regulatory Lead Accenture Life Sciences kim.brownrigg@accenture.com
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