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International Clinical Trials
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Risk-based monitoring (RBM) is primarily discussed by large life
sciences organisations and CROs as they continue to implement this
methodology. However, there is still a significant segment of the
industry that has not yet transitioned to RBM – most notably, small to
mid-sized companies. Some of the key reasons for this delay include the
following perceptions and outlooks:
- RBM is complex and difficult to execute
- The model is nascent and continues to undergo changes
- Internal expertise is unavailable to modify the necessary business processes
- Fear of failure with a ‘wait and watch’ approach • Delayed technology buying decisions: ‘build’ versus ‘buy’
- Change management challenges within organisations
For
organisations wishing to progress towards RBM adoption, an important
question is whether the RBM model followed by large businesses will be a
good fit for everyone. Today’s RBM system has evolved from a base of
traditional data management processes – which works reasonably well in
full-service CROs, where RBM becomes an extension and modification of
data management processes and repurposing of organisational staff to
implement it. Smaller companies generally lack dedicated resources and
expertise to develop and adopt RBM. In the absence of a nimble alternate
model for executing RBM, this has led to the perception that its
implementation is complex and difficult to introduce to smaller
businesses. However, there is an alternative approach that is simple and
implementable, with minimal change management barriers.
So,
what does it actually take for smaller organisations to readily embrace
RBM? Below is a step-by-step outline that can help lead to successful
RBM adoption. This approach is divided into three segments: process,
technology and people.
Process Aspects
The first step in working towards RBM adoption is to get the process right. It is crucial to consider the following aspects:
Risk Prioritisation and Developing a Risk Plan
The
key objective of risk planning is to not only identify risk, but also
its mitigation by effectively planning and objectively monitoring it
without being elaborate and convoluted. There are two major aspects to
consider during risk planning:
- Pursue risks that matter and
prioritise them. TransCelerate has formulated a risk assessment and
categorisation guiding tool for the industry (1). The intent is to use
this approach for continued risk planning in a clinical programme;
however, all of this can translate into a very extensive risk outline,
with multiple categories posing challenges for actionable planning
- A
lighter starting point for risk planning is to focus on processes
linked to the successful scientific and ethical objectives of a study,
and then propose risks that can affect the final outcome. A shorter, but
critical list is then created from which those that really matter can
be distilled into a risk plan and prioritised, based on probability and
impact. This will help teams to focus on the highest need risks to be
mitigated
- Once prioritised risks have been listed, the top 10
risks in the order of priority (higher degree of probability and impact)
need to be selected. These should be discussed within a team that is
comprised of both scientific and medical personnel – including clinical
operations, data management and statistical leads – which can assist in
crystallising robust mitigation plans and dependencies between different
functions to holistically monitor such risks in an aligned manner
In
this way, risks can be added to the plan, prioritised and mitigated on
an ongoing basis. It is acknowledged that risk planning as a process is
relatively new to the clinical research industry, but external support
can be utilised on an as-needed basis if such resources are not
available within an organisation. The final output is a cross-functional
derived integrated quality risk management plan (IQRMP) with proposed
mitigation steps.
Transforming Risk Planning into a Data Monitoring Plan
The outcome of risk planning generally provides the following answers pertaining to risk:
- What is the risk?
- Why is it important?
- When can it occur?
A
data monitoring plan helps in clearly articulating and setting the
foundation for monitoring risks using data points. It addresses the
question of which data points will be reviewed, how exactly the risks
will be monitored, how frequently they need to be observed, when an
alert should be raised and the basis for escalation. The plan would also
define data thresholds where applicable, such as when and if data
outliers need to trigger alerts. Thus, a data monitoring plan links the
risks into definitive data components and processes for manual review or
automated signalling for systematic, consistent and scalable review.
Finally, it is recommended that a data monitoring plan broadly cover
site and subject level risks – along with other monitoring aspects as
desired by the study – and be aligned with the site monitoring plan (see
full PDF for Figure 1).
Monitoring Risk
The
traditional monitoring model is not optimal, as the process is
vulnerable to the subjective skill and experience of the site monitor.
This is further compounded when ad hoc issues are discovered and managed
during monitoring activities, which leads to more workload and less
productive time on-site. This has been circumvented in the RBM approach
by a combination of centralised data and on-site monitoring:
Clinical Intelligence Through Centralised Monitoring
The
RBM approach lays focus on prioritising and reviewing subject data and
processes that are linked to scientific and ethical outcomes in an
objective and standardised manner. The central monitors can proactively
identify issues or non-congruence in activities by reviewing subject and
site data; this ensures that data quality is consistent, and decreases
downstream surprises during audits or interim analysis. Site monitoring
visits (SMVs) can also be rationalised better and objectively based on
data. On an ongoing basis, there will be insights compiled by central
monitors, which will be available to site monitors to review – bearing
in mind they could vary from simple insights to pattern recognition in
data.
On-Site Monitoring
In the RBM model, efforts
required during an SMV will be dependent on the understanding and
performance of a site from a quality and risk perspective. The modified
process will be as follows:
- Utilise the insights and reports provided from central monitoring
- Perform
source data verification (SDV) on subjects where data non-congruence or
scientific queries have been noted in the central monitoring report.
Adapt the level/percentage of SDV based on the output of central
monitoring, as well as process checks during SMV at the site
The
focus of monitoring will shift to deriving maximum value of being on
site by evaluating study conduct processes at the site. This will
include aspects like relationship management (with primary investigator
and study staff), understanding the subject pathway followed for
conducting study procedures, and assessing logical checks to what is
being recorded in source documents. Hence, the expectation from a
monitor – on an ongoing basis, and before a SMV – is a comprehensive
understanding of safety risks or issues with trial subjects, as well as
areas of focus for quality enhancement. All of these lead to the site
monitor focusing on high-value activities.
Technology Enablement of Process
Technology
needs to effectively enable RBM implementation. Small and mid-tier
organisations in particular need nimble and easily configurable
solutions to allow a smooth execution of the above processes (see full
PDF for Figure 2).
Risk Planning
TransCelerate has
created and shared the Microsoft Excel® based risk assessment and
categorisation tool, which is derived from programmatic risk evaluation.
Realistically, small and mid-size organisations tend to focus on a
study-to-study basis, and every trial is considered by the team to be
special in its own right. A dynamic, yet simple web tool – which can
easily be configured to desired risk categories and enable
documentation, assessment and planning for risk mitigation – is ideal.
This helps in sharing information across company silos, creating a
growing knowledge repository which can then be reused.
Smart Data Capture Systems that Enable RBM
Electronic
case report forms (eCRFs) should offer an optimal way to dynamically
manage field relationships. For example, if there are leading data
points in an eCRF that need to be linked to an endpoint, the system
should be able to readily link the field to the endpoint. The opposite
is also applicable: if there are leading questions within a study that
suggest a particular endpoint matter is unnecessary, the system should
be able to hide or disable a field. This aids in decreasing data entry
errors, while simultaneously lessening the risk of creating conflicting
data. It represents an important step in accurate monitoring, as
conflicting data may result in improper risk assessments.
The
ability to create custom edit checks to flag endpoints based on specific
data characteristics is also of great importance. This includes the
capacity to identify data, such as out-of-range, high or low categories.
Flags can then be associated with the characteristic that may be a
cause for concern. Doing so aids in accurate patient safety risk
analysis and drives appropriate actions.
Ongoing Data-Centred Monitoring
Critical
data points linked to a central monitoring plan can be reviewed through
standard data reports, such as operational data model XML and others.
These insights help in manual review when the number of data points,
volume of data and extent of correlations are small. However, in typical
Phase 2, 3 and late phase studies, where the data and scope for review
are more comprehensive, such an approach could mean manual, laborious
and error-prone processes. This can be mitigated by using meaningful
data visualisations. A system that can provide uncluttered and
user-friendly visualisation for analysis, while at the same time helping
to solve the end user question of ‘so what?’ works best for small and
mid-tier organisations.
The personnel performing reviews should
follow the central monitoring plan, which stipulates what needs to be
evaluated. Additionally, the ability to define thresholds on certain
parameters in a simplistic manner (data outliers more than 1.5 times of
normal or desired range, for instance) is key. Advanced alerts can
subsequently be configured at a later point in time.
Tracking Observation and Actions
Following
data review, its findings and outcomes should be recorded. If there are
issues for which action is required immediately, as a part of the
routine telephonic call or during SMV, the same needs to be assigned and
tracked until the problem is solved. Maintaining all of these in a
simple and configurable system ensures that the audit trail for review
of subjects, as well as action taken by respective team members, is
recorded and available.
People Executing Process through Technology
Implementing RBM further requires the following two major skillsets from staff:
Risk Planning
The
cornerstone for successfully adopting RBM begins with robust risk
planning. Experience in risk planning and managing clinical trials,
along with the acumen of forecasting risks, is critical – therefore, the
study team leader, or equivalent, should possess this knowledge and
ability. If such a skillset is not available within an organisation,
seeking external help from specialised companies or consultants is
beneficial. Such a resource should be able to review the protocol and
suggest recommendations regarding study risks; they should also be able
to work with different functional teams to develop a holistic mitigation
plan and an effective IQRMP.
Centralised Clinical Data Review
This
is a relatively new activity within the industry; the current standard
approach is to repurpose staff (normally site monitors or data managers)
to carry out this key role. These groups all have skills that allow
them to understand the clinical and monitoring context that enables
accurate data review. However, there are a few factors that merit
consideration:
- The reviewer needs to remain independent in
their view of the subject’s progress and site performance, without being
weighed by positive or negative bias of the clinical operations team or
site
- Analysing data through an in-depth review of correlations, trends and patterns requires an analytic skillset
If
no suitable individuals can be recruited in-house, they can be found by
either working with data management organisations equipped with central
monitoring, or other niche providers who can offer centralised data
monitoring on a pre-agreed scope. These partners should have procedures
in place that seamlessly blend with clinical operations and data
management of the organisation.
Bridging the Gap
To
conclude, adopting RBM does not need to be complex and overbearing. It
can be achieved by employing a combination of selective process
upgrades, applying offthe- shelf nimble and effective technologies, and
utilising people who can effectively plan and monitor for risks.
It
is time to bring science back into the effective management and
monitoring of clinical studies. Small and mid-sized organisations have
the opportunity to move up the value chain and leverage their operating
flexibility to bridge the RBM implementation divide within the clinical
trials industry.
Reference
1. Visit: www.transceleratebiopharmainc.com
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