The use of biomarkers and adaptive design is now more common in early phase clinical trials with a reputation for improving flexibility and accuracy, but many still believe that they may be not right for their processes. What potential benefits do they have, and what are their limitations? How compatible are they to be used together? What changes need to be made so we can overcome some of the challenges?
We explored these questions with clinical trial experts, some of whom will be speaking in a new stream dedicated to early clinical development at Clinical Trials Europe (Barcelona, 19-21 Nov). They were keen to offer their perspective on where biomarkers and adaptive trial designs currently stand.
Staffan Dahlgren, Unit Manager Phase-I, Karolinska Trial Alliance
The benefits: For me the biggest benefit in both biomarkers and adaptive design is the possibility of an early efficacy-/safety read-out and decision-making for the future of the project.
The challenges: The challenge regarding biomarkers is related to biological relevance of the biomarker, to the development of the disease, and relating to adapting design that this adds complexity in the planning of the conduct of the trial.
Peter Van Der Ark, Clinical Research Manager, Neuroscience Experimental Medicine at Janssen
Adaptive design: It proved not to be very practical. In practice it was hard to look into the future and so how, where and to what extent adaptations were required. We write our protocols with flexibility which is more practical.
Biomarkers: They are still common practice and I think we will use them in the future. We are rather successful in using biomarkers for target engagement. But in neuroscience, biomarkers for outcome (change in disease severity) is still speculative.
James O’Loan, Consultant Pharmacist, Doctor4U
Adaptive design: Introducing adaptive design is intended to increase the efficiency of clinical trials. Adaptive design trials are often more flexible allowing for modifications throughout the trial which makes better use of resources such as time, money, and the number of participants.
By adapting the trial throughout the course depending on outcomes, saves time and money, and increases the probability of a successful trial. Using adaptive design in early phase trials may speed up the process so that treatment becomes available on the market quicker. It is beneficial to use adaptive design in all trial phases, however, the earlier it is used the more efficient the overall trial will be. This allows for better preparation and decision making which reduces any risks to patients and is therefore more ethical.
However, there are some practical challenges and concerns about adaptive design in clinical trials. Adaptive designs can be more complex and require more intensive planning. If adaptive designs aren’t used correctly it may produce biased results and compromise the validity of the trial. There is lots of confusion around the definition of adaptive design and there are many types of adaptive design. Although it’s more flexible, it can be more complicated.
Efficient and accurate electronic data collection is needed to constantly collect results as the trial is adapted. As part of the careful planning of adaptive design trials, a simulation of the trial may be created to overcome any potential challenges along the way.
Biomarkers are crucial in clinical trials, as in order to measure the effects of drugs, we need to measure the effect on biomarkers. Biomarkers are anything that can be measured to see if a medicine or treatment is working, for instance this could be blood pressure or blood count etc. Results from biomarkers can indicate whether or not the treatment being tested is helping the patient. Using biomarkers in early phase trials allows us to find out quickly if a treatment is working, and if there is no improvement in the patient’s condition or it is made worse, the trial can be stopped and another treatment may be tested.
Biomarkers can also add more value to the treatment being trialled. Trialling those patients who are likely to respond to the treatment based on biomarker measurements, increases the probability of a successful trial and increases its value.
Dr Kristy Draper, Global Trial Leader - EPAD PoC, University of Edinburgh
The benefits: One of the benefits of using biomarkers along with an adaptive design in early phase trials is the potential to identify and select participants who may be more likely to respond to specific treatments and through interim monitoring adapt the trial towards selection of the most suitable subpopulation. Depending on the biomarker and drug being tested, the adaptation may take the form of narrowing down the patient population to exclude those without or with low levels of the biomarker, or vice versa, expanding a biomarker positive subpopulation to include those with lower levels.
The challenges: One of the challenges of this in early phase trials is there may be a limited understanding of the biomarker specificity and sensitivity, which can make it difficult to define the appropriate biomarker cut-off for inclusion/exclusion. In the field of Alzheimer’s disease we need a greater understanding of the disease and the specificity and sensitivity of its biomarkers in order to set suitable cut-offs.
Ross P Walton BSc, MSc, PhD, Co-founder, Board of Directors, A-IR Clinical Research Ltd
The benefits: Biomarkers are invaluable tools for the rapid definition of disease progression status, in addition they can also be used to determine the likelihood of a given individual responding positively to a specific treatment approach. Historically, biomarkers were restricted to a single indicative gene or protein, however as understanding of more complex disease and the heterogeneity within populations has developed, the concept of a biomarker within a particular disease has expanded to encapsulate a network of readouts including genes, soluble mediators and cells.
The challenges in measuring such biomarkers include access to specific locations where they may only be present, stability overtime and through processing and assessment and the complexity of science required to accurately measure them. In addressing these challenges successfully, we require the use of thoughtful study design, incorporating novel sampling approaches and rigorous scientific expertise to enable meaningful data.
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