Challenges for biomarkers
Challenges for biomarkers in medicines development
As the use of biomarkers in pharmaceutical research grows, companies face new technical and regulatory challenges. The field as a whole also faces several ethical challenges. These are summarised below.
Technical challenges
- Biomarkers used in clinical trials must be validated (‘qualified’): is there scientific evidence in place to say that the biomarker test used is sufficiently accurate, reliable, sensitive and specific? Companies developing new biomarkers will have to collect all this data for each biomarker.
- Is the biomarker a valid measure: for example, if it is to be used to predict how severe a disease may get, is there enough evidence of this ‘predictive ability’? In other words, has it been shown to predict severity enough times before?
- Sample collection and processing methods (e.g. for biopsies or blood samples) must be consistent. The results of biomarker tests can be affected by variations in the way samples are handled. This could invalidate the results of a trial.
- The IT systems used for data management and data analysis must be robust and fast to cope with the amount of data generated. All biomarker measurements must be correctly linked with individual patients.
- Where the use of a companion diagnostic is required for a new medicine to be prescribed, a new platform or kit for testing patients in the clinic may need to be developed. It will usually need to be available for use during the large confirmatory trials of the medicine (Phase III), and it must also be validated. Validation must include data to show that the diagnostic is accurate and clinically useful.
Regulatory challenges
The regulation of medicines is
evolving, especially relating to the use of novel methods such as biomarkers.
A good definition of biomarker for clinical trial purposes
is the following one, already formulated by Temple, in 1999: A biomarker is a
laboratory or physical sign that is used in therapeutic trials as a substitute
for a clinically meaningful endpoint. The endpoint is a direct measure of how a patient
feels, functions, or survives and that is expected to predict the effect of the
therapy.
- The development of the disease.
- A treatment intervention with an important clinical endpoint.
- They can be measured earlier, more easily or frequently and with higher precision.
- They may be less affected by other treatments, reduce the size of samples required and allow researchers to make faster decisions.
- There are important ethical advantages in diseases with poor prognosis.
This is the reason why
surrogate endpoints (if validated) are often used in ‘fast-track’ or ‘accelerated’
approval procedures. They will assist the development and speed up the review
of new medicines that are intended to treat serious or life-threatening
conditions and/or demonstrate the potential to deal with unmet medical
conditions. In ‘accelerated’ procedures however, post-marketing data is
required to ‘verify and describe the medicine’s clinical benefit’. Post-marketing data is
also required to resolve remaining uncertainty as to the relation of the
surrogate endpoint (upon which approval was based) to clinical benefit, or the
observed clinical benefit to ultimate outcomes.
- Normal biologic processes - how things work within the body;
- Pathogenic processes - how a disease develops, or;
- Pharmacological responses to a therapeutic intervention - how the body responds to the use of a medicine or other therapy.
It should be directly related
to clinical outcomes.
For regulatory purposes,
surrogate endpoints represent only a ‘sub-set’ of biomarkers. A biomarker can
be called a surrogate endpoint if it is expected to predict clinical benefit
(or harm, or lack of benefit or harm) based on epidemiologic, therapeutic, pathophysiologic
or other scientific evidence. Just having a good ‘correlation’ does not make a
good surrogate endpoint. As an example, an increase in something called
‘prostate specific antigen’ (PSA) is correlated with prostate cancer, in other
words, people who have prostate cancer often also have higher levels of
PSA. However, it is unreliable as a surrogate endpoint. This is because
levels of PSA may be reduced when the patient is treated for prostate cancer,
but there is no effect on the long term outcome of the disease.
A strong example is in the
development of antiretroviral medicines for HIV and AIDS. Levels of ‘CD4 lymphocytes’ and changes in ‘HIV-RNA’ plasma levels can now be used as surrogate
endpoints. Previously, studies would have been based on hard clinical endpoints
such as progression of the HIV infection to AIDS and/or patient survival.
Biomarkers are also being used
in the development of medicines that are targeted to a specific sub-population
of patients. A medicine that is only going to be prescribed to a small
sub-population of patients can be labelled by the European Medicines Agency (EMA) as an ‘orphan’ medicine. Such products are given benefits
when they are authorised, such as ‘market exclusivity’. This means that other
companies will not be authorised to market a similar medicine or ‘generic’ for
10 years. The EMA is receiving an increasing number of requests for orphan
designation for new medicines. This has resulted in the EMA building up
considerable experience in assessing the potential benefits and limitations of
biomarker use for regulatory purposes.
Medicines developers are being
encouraged to engage with regulators at an early stage when they
are considering using novel biomarkers. Developers of novel biomarkers can
submit their plans to use the biomarkers to the EMA. They can present the
scientific evidence they have collected to validate specific biomarkers, so
that the EMA’s Committee for Medicinal
Products for Human Use (CHMP) can give an opinion on their use.
Validating biomarkers to meet
regulatory standards can be complex and expensive. This is especially
challenging if a biomarker is to be used as a surrogate endpoint. In this case,
a dedicated clinical trial is required that is designed to test the link
between the biomarker and the clinical endpoint.
Finally, in the EU, medicines and diagnostics are regulated differently.
Licensing a medicine and its companion diagnostic together adds an extra layer
of complexity to the approval process.
Ethical challenges
Ethical issues
that arise associated with handling of personal medical data, in biomarker research are those linked to the storage and use of tissue samples.
In addition, wider concerns have been raised about the impact of
targeted medicine (which is largely based on biomarker research). For example,
as targeted treatments only bring benefits to the sub-population of patients
that respond to them, who will make sure that medicines are developed for those
who fall outside of this sub-population?