COMMENTARY
Common pitfalls in oncology drug applications aiming for conditional
marketing authorization.
Sinan B. Sarac1, Peter Kiely1,
Simona Stankeviciute1, Jorge
Camarero2, and
Amy McKee1
1Parexel International
2 MSD Spain
Corresponding author: Sinan B. Sarac,
sinan.sarac@parexel.com
Parexel Denmark, Agern Alle 5A, Hoersholm, Denmark
Tel: +45 60628757
Keywords: drug development, rare disease, precision medicine
Abstract
Early approval mechanisms, such as conditional approval in the EU, have
been used extensively to provide timely access to therapeutic
innovations to cancer patients with unmet medical needs.
While based on promising early evidence, such approvals are challenging
from many perspectives due to the lack of comprehensive data. The
limitation typically relates to data that demonstrates clinical benefit
via particular endpoints and is only acceptable when the early evidence
is particularly convincing to assume that the benefits of early access
are greater than the potential harms.
This paper describes the requirements for conditional approval and
reviews common pitfalls in oncology, such as misunderstandings about the
strength of evidence from exploratory trials and secondary analyses,
lack of planning, and opportunities to improve communication.
Thereafter, we present a framework (“EDGE”) on how to improve the
submission and evaluation of drug applications for conditional approval
in the EU.
Introduction
Conditional marketing authorizations (CMA) in the EU and accelerated
approvals (AA) in the USA have been set up as regulatory mechanisms to
bring promising drugs to patients with unmet medical needs. The
mechanisms originated in the 1990s in the USA based on the promise of
early endpoints that were likely to predict a clinical outcome, namely
viral load for antiretrovirals. These mechanisms have been implemented
in different regions over the years with small variations but the
emphasis on likely surrogate endpoints for early approval and the need
for confirmatory evidence is still considered the cornerstone of these
approvals.
To date, in the EU, more than 70 drugs have been approved by the CMA
pathway across different therapeutic areas, and of these 24 have been
converted to full approval based on the submission of comprehensive data
post-approval (1). This pathway allows early approval when the
benefit-risk (B/R) balance is deemed positive in situations of unmet
medical need, yet the clinical data are not comprehensive. The marketing
authorization holder must then comply with conducting studies
post-approval to ensure the dossier becomes comprehensive within agreed
timelines. CMAs are particularly controversial, as they bring together
the potential greatest opportunities for patients with unmet medical
needs but also the greatest challenges for other stakeholders in the
health system due to the limited evidence. While non-exhaustive evidence
may still be compatible with regulatory approval considering the
patients’ needs, this may be insufficient for other decisions such as
pricing and reimbursement.
In this perspective, we briefly introduce the criteria for conditional
approval, discuss common pitfalls, and provide suggestions from
experience on how to avoid them, drawing from examples of new cancer
drug applications submitted to the European Medicines Agency (EMA).
Understanding the requirements for conditional
approval
CMAs are intended for treating, preventing, or diagnosing seriously
debilitating or life-threatening diseases, including orphan medicines
and public health emergency medicines. CMAs may be granted based on less
comprehensive clinical data under certain conditions (2, 3), namely, 1)
a positive benefit-risk balance; 2) comprehensive data will be provided
post-approval; 3) an unmet medical need; and 4) a benefit to public
health of the immediate availability.
Concerning the first condition referring to the positive B/R balance,
some note an apparent contradiction between a “proven” positive B/R
balance on one hand, and the need for confirmation on the other. In
practice, this means that for a CMA, “proof” of positive benefit-risk
at time of approval can be claimed albeit relying more strongly on
assumptions, and that confirmation post-approval refers to the need to
verify strong assumptions, so that eventually, in an agreed timeframe,
the uncertainty is reduced to the level of a “standard” approval.
“Comprehensive” clinical data is defined as scientific standards of
evidence that are necessary for full approval (e.g., control of
statistical error concerning endpoints that measure clinical benefit).
There is often confusion that a CMA based on a non-randomized controlled
trial will systematically require an RCT in the approved indication.
Although this may often be the case, the design of studies (prospective,
observational, indication, endpoints, etc.) will depend on the
objectives, i.e., the evidence required to address the uncertainties
according to conventional scientific standards and will be considered on
a case-by-case basis, as occurs with any other standard authorization
granted in the EU.
The criterion about unmet medical requires that there are no available
treatments or that the drug will bring a major therapeutic advantage
over existing therapies. What is often not realized, is that the latter
is a bigger hurdle and has been met either when some type of superiority
over existing treatments could be shown or, arguably, when it could be
justified that the new drug was a significant new addition to a range of
available treatments (i.e., adding a non-redundant treatment to thearmamentarium , typically, a treatment with a new mechanism of
action that is not adversely affected by prior existing treatments and
does not adversely affect subsequent existing treatments, in situations
where patients ultimately run out of treatment options).
Two other criteria for CMA are often given less attention, namely that
regulators need to conclude that early approval is beneficial from a
public health perspective compared to waiting for more comprehensive
evidence before approval and that confirmatory studies must be feasible
and timely provided by the marketing authorization holder. These are
complex criteria to establish, as they need to consider both the
consequences of CMA under different scenarios and that aspects of
clinical trial conduct are often difficult to predict, e.g., difficulty
recruiting due to competing trials or new treatment options.
Lastly, it is important to recall that while there are specific criteria
for conditional approvals to be fulfilled, all the remaining
requirements still apply. A piece of general advice is that to cope with
uncertainty in some parts of the dossier, it is advisable to minimize
uncertainties elsewhere to reduce the overall uncertainty (e.g., it is
imperative that the data obtained are of the highest quality,
particularly concerning the accuracy, lack of bias, precision (4).
Moreover, while providing clear information on the conditional nature of
the authorizations is a requirement, there is an opportunity to optimize
effective communication beyond the standard statements in the summary of
product characteristics, to provide exhaustive and continuously
up-to-date information about the remaining uncertainties and how they
are being addressed to patients and healthcare professionals.
Conditional approval is not a way to rescue “negative”
studies.
Developers may consider promising results from post hoc analyses
of failed confirmatory studies as convincing for a CMA. For example, a
drug application was submitted for malignant gastrointestinal stromal
tumor (GIST) based on an exploratory analysis of the secondary endpoint
overall survival (HR: 0.29; 95% CI: 0.10; 0.85; p-value: 0.016) from a
randomized clinical trial (RCT) that observed no difference on the
primary endpoint progression-free survival (5). This was considered
insufficient for conditional approval due to uncertainties about the
efficacy and lack of statistical power to test the hypothesis. A
negative result in the overall population may also weigh against the
credibility of findings in small subgroups, regardless of the scientific
hypotheses. In this respect, a well-planned exploratory study showing a
strong signal based on a sound hypothesis may be more convincing than
the same signal observed in a subgroup analysis of a negative trial.
More generally, attention to the development plan is needed to ensure
generating as strong as possible corroborating evidence to support any
assumptions. For instance, there is a need to apply as rigorous
“confirmatory” approaches as possible, such as the intention-to-treat
principle, and scrutinize the magnitude and quality of effects (e.g.,
consistency across subgroups and endpoints, analysis sets,
dose-response) and outside the study (e.g., pharmacological evidence and
rationale, non-clinical evidence, other clinical studies) (4). Careful
planning will also allow to optimize the timing and nature of
confirmatory studies and may increase the likelihood of meeting the
requirements for conditional approval.
While early approval strategies based on outstanding results may work
for frequent or rare diseases alike, a common misconception is that for
rare diseases it may be acceptable to lower evidentiary standards for
approval since adequately sized randomized controlled studies are
difficult to conduct. Rather, the emphasis is on using methods to
increase the efficiency of the design and analysis of clinical studies
(4).
Conditional approval is best when it occurs late in ongoing
development.
In oncology, companies typically justify applications for CMA by
claiming that frequent and durable objective response from
non-randomized controlled trials is a predictor of beneficial effects on
clinical endpoints like overall survival and quality of life. Timely
confirmation is crucial given the generally poor surrogacy of response
rate, unless results are so convincing that surrogacy becomes
self-evident. Depending on the uncertainties and how they are
communicated, there may be a narrow time window for conducting
randomized controlled trials following approval, especially due to the
perceived lack of equipoise post-approval. This is an important risk
since the failure of timely completion of confirmatory trials may lead
to revocation of the authorization. A recommended approach is to time
conditional approval to occur after confirmatory studies are well
underway (6). For example, for the first CMA granted in the EU, the
final analysis of the ongoing confirmatory trial was expected
approximately one year after submission, and the recruitment had been
completed before approval (7).
When confirmatory trials are ongoing, applicant companies have sometimes
offered informal ‘previews’ of the results to regulators to support
early approval. Such practices need to be managed carefully due to
several issues, such as the risk of damaging trial integrity, increased
type I error, and lack of transparency of the decision. Following
standard practices, whenever considering interim data from confirmatory
studies during the review, applicant companies or any other evaluator
are required to apply formal statistical approaches and beware of undue
disclosure that may compromise trial integrity.
Superior response is not necessarily a
“major” advantage.
Establishing that an increase in response rate is a “major”
therapeutic advantage compared to available treatments is challenging,
even in randomized controlled trials, due to poor surrogacy for
time-to-event endpoints, e.g., overall survival. This highlights the
fact that conditional approval is more challenging if there are
available treatments with proven effects in terms of meaningful clinical
outcomes.
For example, a higher complete response rate was observed for a drug
submitted for conditional approval in acute leukemia compared to the
historical control (18.3%; 95% CI: 11.6, 26.9 v. 7.0%; 95% CI: 1.5,
11.9). However, in the context of the study employing indirect
comparisons and a non-validated surrogate endpoint, the results were not
considered convincing enough to establish a therapeutic advantage (8).
One successful example, although with diverging views, is based on much
higher activity in terms of complete response when used in combination
compared to the historical control (40% v. 11%), and a different
safety profile and clinical use in the treatment of lymphoma (9).
An additional aspect often overlooked, albeit referring to the framework
of EU orphan medicinal product designation and not of marketing
authorization, is that meeting the criterion of “major” therapeutic
advantage does not automatically constitute a “significant benefit”
from the point of view of the criteria for maintenance of orphan
designation. “Significant benefit” may have more stringent and
specific data requirements for demonstrating improved, broader, or
otherwise different beneficial effects compared to the authorized
products (10). For example, in the case of teclistamab, a “major
therapeutic advantage” was accepted for the CMA based on the product
offering an alternative therapeutic option whereas for maintenance of
orphan designation, it was highlighted that a demonstration of the
product’s equivalence in terms of efficacy, safety and benefit/risk
balance would likely be needed to confirm “significant benefit” (11,
12).
Non-randomized is not necessarily
non-comprehensive (and vice
versa )
There is often a misunderstanding that if the submission is based on
single-arm trials then the outcome, if favorable, must be a CMA. Or that
a CMA requires an RCT to be converted to standard approval. This
misunderstanding is based on the wrong focus given to the study design
rather than the uncertainty and objectives of different studies.
While a commitment to conduct an RCT is practically always necessary
when there is a need to confirm an effect on time-related endpoints like
overall survival, if the approval was based on single-arm trials, it is
possible that on occasion, for example, RCTs conducted in other
populations or with slightly different treatment characteristics (e.g.,
different dose or combination), coupled with reasonable assumptions and
extrapolations, still provide sufficient confirmatory evidence.
Sometimes uncertainties about reliability or generalizability may be
addressed without RCTs, for example through external comparisons using
observational studies, or larger non-randomized cohorts to replicate
results (e.g., a condition for larotrectinib, approved in a
histology-independent indication, was to further confirm the
histology-independent effect of larotrectinib in a pooled analysis of a
non-randomized “basket” trial with increased sample size) (13).
Ultimately, to design post-marketing studies, the real question is not
if the drug developer completed an RCT or not pre-approval but how the
existing uncertainties (regardless of the design of submitted studies)
can be addressed and minimized to an acceptable level, using any
suitable design and taking into account available data, reasonable
assumptions and extrapolations.
Communicate, inform,
describe.
Conditional authorizations are arguably one of the most important
decisions to communicate effectively to patients and doctors, not only
for reasons of transparency and accountability but also to better inform
clinical decisions. The main tool to inform healthcare professionals is
the summary of product characteristics, which is a short document that
follows a rigid format. Currently, CMAs are flagged in a short paragraph
in the product information, alerting to the fact that confirmatory data
is expected.
More extensive educational material for both health professionals and
patients could be developed in the form of educational material. This
would help manage any risks that doctors and patients may not be
well-informed about the uncertainties associated with CMAs. Educational
material can be fine-tuned to the relevant population and uncertainties
and provide useful information to support clinical decision aids.
Patient preference data and quantitative benefit-risk assessment may
also highlight situations of heterogeneous preferences where careful
clinical decisions are needed based on individual preferences (14).
Lastly, up-to-date information can be provided on an ongoing basis about
remaining uncertainties and the available data to address them, as they
emerge.
Early approval as part of a comprehensive development
strategy
For products falling within the scope of CMA, advocating the pursuit of
early approval within a comprehensive developmental framework is
pivotal. This is in line with the principles of “adaptive licensing”,
seeking to maximize the positive impact of new drugs on public health by
combining timely access for patients with prospectively planned
iterative phases of evidence gathering to reduce uncertainties (15).
The key elements of a comprehensive evidence-generation plan consist of
timing of studies and assessments; diagnosing gaps and uncertainties;
guidance about decision rules and adaptations; and engagement with
stakeholders and decision makers (“EDGE”, see Figure 1).
Initiating this process should be the careful design of an, focusing on
generating and assessing available evidence at submission and subsequent
milestones, as well as acquiring knowledge on drug utilization, and
monitoring. The primary objective of the plan is to describe expected
evidence and uncertainties at each time point, which is crucial for
benefit and risk assessment, and managing uncertainties. Special
attention should be devoted to the timing of conditional approval and
the design, conduct, and feasibility of the confirmatory trial(s).
At each milestone, the plan should describe the expected evidence gaps,
strength of evidence, and uncertainties, such as internal and external
validity, heterogeneity in response, and selection bias. When expected
gaps are identified, it is important to assess the impact on the B/R
balance and propose strategies to address uncertainties (e.g., further
analyses of data; further studies; communication; other risk
minimization measures).
The plan should describe prospectively defined decision rules about key
aspects of development (e.g., use of external comparator studies,
evidence thresholds for early submission) should be pre-specified as
much as possible, to allow assessment and advice about chosen strategies
including study adaptations or submission timelines. The plan should
include analyses addressing scenarios when some of the planned studies
do not deliver expected evidence or if the studies are delayed.
Engaging stakeholders throughout the design of studies and relevant
stages of development should be standard practice and is particularly
important for early approval. Scientific and regulatory advice should be
sought about the adequacy of the evidence-generation plan, aiming to
address expected uncertainties in a timely way. Advice should be sought
in parallel with other stakeholders and decision-makers (e.g.,
regulators from different regions, patients, health professionals, and
health technology assessors), striving for efficiency of evidence
generation whenever possible. Communication should be an integral part
of the overall planning, making use of all available tools, including
educational material to ensure informed clinical decisions, informing
patients and doctors about uncertainties and how they are being
addressed.
The plan, gap analysis, and advice should be regularly updated during
the development.
Figure 1. Key elements of a comprehensive evidence-generation
plan to describe iterative phases of evidence gathering and regulatory
assessment (“EDGE”).
Summary
Common pitfalls in CMA submissions highlight the need for a switch from
a framework where unexpected findings from exploratory data are rushed
for a regulatory decision to a planned strategy for the early generation
of convincing evidence within a comprehensive confirmatory strategy and
transparent communication.
Extensive consultation of different decision-makers in the system, along
the lines of EMA-FDA parallel scientific advice and Joint Parallel
EMA/HTA (Health Technology Assessment) scientific advice procedures,
provide a great opportunity for ensuring that the evidence generation
fulfills the needs of different stakeholders as efficiently as possible.
A thorough discussion on what uncertainties need to be addressed and
what can be accepted will play a vital role in the final decision on
whether a drug should be approved or not. Understanding the limitations
of a given dossier, such as validity, reliability, internal and external
consistency, missing data, precision, etc., and assessing what is
acceptable and what is not, will greatly reduce the unpredictability of
such submissions.
It is imperative to understand that the required evidence can vary over
time for a given indication, as more and more knowledge and data
accumulate. With this, it is important to emphasize that drug developers
must understand the changing regulatory landscape, recent trends, and
approvals. Repeated advice may be needed to address the evolving
scenarios and requirements.
Companies and regulators need to make an extra effort to justify and
communicate what is expected in terms of clinical benefit, the data and
assumptions that form the basis of their deliberations, and any
remaining uncertainties and coping mechanisms making use of the vast
toolbox of communication means at their disposal. This will inform
clinical and other decisions.
What uncertainties concerning CMA can or cannot be accepted from
different perspectives? This is what matters in the end. By avoiding
common pitfalls and by careful planning, developers can support timely
and comprehensive evidence generation to address unmet medical needs and
inform decisions.
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FIGURE LEGENDS
Figure 1, Key elements of a comprehensive evidence-generation
plan to describe iterative phases of evidence gathering and regulatory
assessment (“EDGE”)
SUPPLEMENTARY MATERIALS