December 2023 • PharmaTimes Magazine • 30-31
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Mind craft
The technology that is shaping brain tumour studies
Patients living with severe or rare diseases face many challenges, but accessing novel therapeutics through clinical research should not be one of them.
International Brain Tumour Awareness Week presented a timely opportunity to consider how the clinical trials industry navigates research into notoriously difficult-to-study indications, such as brain tumours.
For example, in recurrent glioblastoma, a type of brain tumour, registrational studies investigating new potential treatments have a high failure rate, even in cases where there has been positive early-stage data.
This is incredibly difficult for a patient population whose existing standard of care is poor. With glioblastomas making up nearly half of all primary brain tumours, this is a significant patient population that is being underserved by a lack of effective treatments.
Part of this shortage of treatment lies in the difficulty in designing effective trials for complex conditions.
For these indications, patient recruitment comes as a particular challenge, due to the time pressure to recruit as quickly as possible.
There are also the ethical implications of recruiting for a control arm involving conditions where there may not be effective treatments available – as is the case for recurrent glioblastoma patients.
Synthetic control arms (SCAs) use patient-level data from historical trials, offering data sets that give valuable information about a disease, indication or treatment.
This technology allows for a significant reduction in the number of prospectively randomised patients assigned to the control arm, thus reducing enrolment challenges, and decreasing patient drop-out due to the improved access to investigational medicines.
The enhanced recruitment and retention of recurrent glioblastoma patients promotes higher rates of trial completion, in doing so driving scientific research into brain tumours, and hopefully enabling the development of more innovative therapies.
This is all without compromising the scientific interpretability of trial results.
SCA beats
SCAs use patient-level data such as electronic health records, patient registries and historical trial data to create a comparator arm within a clinical trial. Data collection follows a rigorous process, characterised by formulaic extraction and cleaning to ensure robust results.
The data collected enables an ‘apples-to-apples’ comparison between the outcomes of patients in the investigational arm and the outcomes of the synthetic control group, providing researchers with a fair comparison between the two groups.
Ultimately, clarity emerges on where improvements – seen in patients – are due to the investigational therapy.
Multiple case studies comparing SCA outcome predictions to ‘gold-standard’ randomised control trials have successfully demonstrated the technology’s credibility.
Design for life
As with other severe diseases, many recurrent glioblastoma patients turn to clinical trials in search of an investigational therapy due to the inadequate standard of care and an overall survival of around eight months.
Early-stage recurrent glioblastoma trials have historically been single arm due to the unethical nature of assigning terminally ill patients to ineffective standard-of-care treatments.
These trials, however, are notoriously difficult to interpret because there is no point of reference. One ramification of this is that many products that have success in the phase 2 setting fail once they get to the pivotal phase 3 stage.
‘SCAs use patient-level data from historical trials, offering data sets that give valuable information about a disease, indication or treatment’
This is a bad outcome for everyone – time, money, and resources have been spent by pharmaceutical companies and regulatory bodies, and there’s no benefit to patients.
In comparison, randomised control trials give patients a 50% chance of being assigned to the control arm and therefore receiving the same, inadequate standard-of-care therapy that they hoped to avoid.
The possibility of not receiving the investigational treatment can be difficult for patients and their families and ultimately can put them off participating in a clinical trial.
Therefore, the major advantage of building in an SCA to a recurrent glioblastoma trial is the ability to significantly reduce the number of patients assigned to the control arm, meaning that more patients get access to experimental medicines.
One recent example saw the use of a synthetic control arm reduce the number of patients on placebo from 150 to just 50.
As such, SCAs have been well-received by patients, their families, and the clinicians treating them due to the increased access to innovative new therapies.
Fast-forward
Many randomised recurrent glioblastoma trials are unsuccessful because the trials themselves cannot be completed.
This often occurs because patients do not enrol in the first place or because patients drop out of the trial when they learn they have been assigned to the standard-of-care treatment.
Not having an effective clinical trial process means that potentially groundbreaking experimental medicines are not being tested effectively and therefore do not have sufficient data to make it to market.
The potential of SCAs to help run effective clinical trials is key to ensuring that trials can be run to completion and provides the opportunity for pioneering drugs to be fairly assessed while accelerating the drug development process.
Therefore, SCAs have also been well received by scientists whose research in a difficult-to-study indication is able to progress with the help of this technology.
SCAs also play a role in identifying ineffective treatments. Adding SCAs in early trials can allow better decisions to be made around drug efficacy, meaning that inadequate therapies can be discontinued earlier on.
Not only would this ultimately accelerate the approvals of promising novel therapeutics, but it could also save pharmaceutical organisations and regulators the time and money associated with registrational trials that fail in later stages.
Final analysis
As SCAs continue to gain traction within the industry, it is important to consider the challenges that inevitably come with such innovations.
A key issue is finding appropriate data from relevant patients and, given the amount of historical trial data that is needed to create SCAs, this can be particularly challenging within rare disease research.
This means that, while SCAs are becoming more and more established in indications such as recurrent glioblastoma, in some disease areas, more historical data is required to build out synthetic control arms.
There is certainly more to come in the SCA space across different disease areas. Indeed, it is exciting to see growing interest from pharmaceutical companies, with some even setting up dedicated teams tasked with incorporating SCAs into trial design, underlining their faith in the future capabilities of this technology.
For patients living with brain tumours, this means greater investment in the technology that will open up access to studies’ treatment options, while also contributing to the advancement of clinical research.
Ruthie Davi is SVP, Integrated Evidence at Medidata AI and Elizabeth Lamont VP, Clinical Development at Medidata. Go to medidata.com
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