Adnan Jamil of Deloitte sets out specific recommendations and emerging leading practices as Life Sciences organisations assess what’s needed from next-generation regulatory information management (RIM) systems, both to comply with the latest regulatory requirements and drive greater operational efficiency and strategic intelligence.
Life Sciences industry regulators have become increasingly focused on data-driven processes as a means of managing marketing authorisation submissions. Potential associated benefits to companies themselves include improved decision-making; optimised health authority interactions; increased regulatory intelligence; and streamlined data exchange between business functions.
But this requires that regulatory information management system (RIMS) upgrades are approached holistically. Common issues, and appropriate recommendations, can be broken down into system challenges, process challenges, and matters of data governance, as discussed below.
System challenges
Although the transition from document-centric information delivery and management to a data-first environment is not entirely a technology issue, technology will form the foundation through which everyday order, consistent format and structure, data quality, and status visibility are maintained and improved.
Many companies have realised now that there will never be a definitive point in time when all the new requirements are set in stone, and that a more agile methodology is more appropriate to enable flexibility.
Yet this can bring its own challenges as teams adapt to the new way of working, including:
- The need to develop an agile mindset around RIM systems upgrade.
Adopting a mindset of refining requirements in subsequent system/project iterations can be difficult to adapt as companies have been used to implementations with pre-known parameters, even though regulators themselves are embracing an agile approach to development and implementation of new requirements and ways for the industry to interact with their systems.
- Gaps in existing data captured within central RIM systems.
Up to now, companies have had the flexibility to define the data and processes based on their own requirements. Yet, where such efforts have happened without specific response to regulatory requirements, there are likely to be gaps in that data. Technology teams will need to work with the relevant business stakeholders to work out how best to address these.
- Data collection efforts required for upcoming regulations.
In addition to getting existing data in order, technology and functional teams will need to establish new/additional data fields that must now be populated, under EU IDMP for instance. This has implications not just for the upgrade of RIM systems, but also for the collection and entry of the data within the applicable data model field/object, with appropriate links to existing records.
- The need to transform existing data to the new standard fields as the data model is updated.
Although software vendors may provide out-of-the-box tools to support data loading and transformation efforts, these won’t automatically deliver the data transformation. Appropriate knowledge and preparatory work is essential to ensure that all data in the updated RIMS system is reliable, correct and compliant.
- Establishing and embedding the culture and approach around data quality management.
To ensure that the data referred to in future for all aspects of regulatory exchanges, operational checks, and strategic decision-making is dependable, companies must establish formal parameters for reviewing all of this. These should include validation rules within the RIMS, and frequent data quality audits.
- Existing reports will need to be assessed based on the system upgrade.
Since the existing fields might be modified during the RIM system upgrade, the current reports used by business users will need to be assessed for any impact to business continuity. Review of existing report specifications should be treated as part of the upgrade project to facilitate business continuity post go-live.
- Existing systems integrations will need to be reviewed.
Any existing system integrations will need to be assessed based on the RIM system upgrade, for the potential impact on upstream/downstream systems. The upgrade might mean that existing data is not available in the same location going forward, so an assessment and advanced precautions will need to be taken to ensure that upgrade doesn’t impact business continuity.
- Decisions will be required about legacy data/product information management.
In populating upgraded RIM systems, teams will need to make decisions about where to draw the line with the data being transformed and managed on an ongoing basis. For inactive registrations, archiving may suffice.
Process challenges
However powerful the new system, the scope for transformation will be limited unless associated business processes are optimised to take advantage of a continuous flow of good-quality, standardized product and registration data. This starts with ensuring that the new/updated system works better for everyone.
- Integration of business & system processes.
With increased dependence on and requirements for regulated data, RIMS is finally gaining traction as the facilitator and enabler of the regulatory function. But in reality business processes will need to be (re-)modelled, as it is better not to pursue customisation – in the interests of maintaining simplicity through standardisation.
Setting up a process framework using a (Business) Process Architecture methodology allows a clear overview of all of the process steps, increasing everyone’s understanding of relationships and dependencies between specific processes, while also making it possible to drill down into more detailed process steps as needed.
- Change in system functionality.
Inevitably the addition of new data-based capabilities, e.g. in preparation for EU IDMP compliance, will require the adaptation of business and system processes. Numerous updates and changes to documentation can be a laborious and inefficient process if done manually. Considerable duplication of documentation can exist across functional subdivisions, too. Having one harmonised master can substantially reduce the update effort and associated user training.
Data governance challenges
To date, Life Sciences companies have struggled with setting up proper data governance measures. Unless these are addressed, they risk compromising the potential of their RIM systems and process optimisation. Challenges include:
- Data roles (including data owner, data stewards) to date not being clearly defined. By now, a governing body and associated process should exist to assign roles and responsibilities.
- Data definitions, business rules, and data quality requirements and metrics need to be established. A unit dedicated to this will speed all of this up.
- The need for central coordination of controlled vocabularies, organisation records, substance information, and specific product identifiers.
Recommendations
With so many considerations, Life Sciences organisations can become ‘stuck’ in knowing how best to proceed, especially when they want to achieve key milestones within an acceptable timeframe.
Emerging leading practice suggests:
- Multiple business stakeholders being involved and have a detailed understanding of the intended data model, as well as the target system and business processes.
- Establishing a data governance body with defined roles and remits.
- Business reporting, using data in the RIM system (both for regulatory compliance and process checks/efficiency), being provided for in its own right – by region, timeline, etc.
- Remediation of existing data within the RIMS to ensure it is reliable, complies with upcoming regulations, and can be trusted as a definitive source of truth.
- Clear and proactive communication about regulatory expectations to end users. This also requires appropriate training.
Summary
Although the demands of data-based RIM transformation can seem overwhelming, the rewards are potentially unlimited – provided companies act now.
Cultivating an organisational culture that recognises the value of good data and fosters the right environment to drive this is crucial. Then it becomes a matter of simply scoping and planning technology initiatives with an understanding that projects will need to be incremental and additive.
Keeping in mind that the end goals go beyond compliance for its own sake will help keep initiatives all-inclusive and continuously evolving, while ensuring maximum returns.
Process-wise, as long as improvements are supported by effective change management, there is an opportunity for extensive modernisation of the product lifecycle – ultimately leading to more affordable and accessible offerings for patients.
About the authors
Adnan Jamil is a Manager at Iperion, a Deloitte business. He has 10 years of experience within the Life Sciences industry, focusing mainly on Regulatory Information Management. Adnan’s expertise spans the assessment, definition and implementation of processes, technology, organisational, and data changes in small, medium and large pharmaceutical companies.
