Data management
of technology in some trials and helped to accelerate the adoption of technologies that were already on the adoption curve.” Yet, after years of relatively gradual technological adoption, the change from 2020 was rapid. One 2021 survey found that 87% of respondents (a mix of biopharma companies and CROs) were running decentralised trials, in which patients, rather than travelling to trial sites and hospitals, record their own data, often through wearable monitoring devices, which is then sent automatically to a central database. Consent forms, too, are completed digitally rather than on paper. Before the pandemic, only 28% were running decentralised trials. What is equally striking is that 95% said they planned to increase the use of decentralised trials within the next 24 months.
“We now know the tools exist and it’s exciting to see trends moving towards more hybrid and decentralisation, because it gives people more options for treatment and we are able to reach more patients”
Michael Rosenblatt
Some of these technological changes have obvious benefits. “The ability to sign a consent form remotely, or for a patient to fill in a journal on an iPad or their computer makes things significantly easier,” says Rosenblatt. Some of Roche’s CRO partners are now using eConsent and electronic patient-reported outcomes (ePRO), and some are deploying and managing devices such as iPads and wearables. A move to decentralisation is not necessarily straightforward. Rosenblatt points out that the changes “have added a layer of complexity to managing the trials” and that it is “important to strike the right balance between patient convenience and sponsor coordination that will ensure the rigour of the clinical trial is maintained”. The feasibility of running a decentralised trial, he adds, “depends on the medicine, the types of assessments that need to be performed and the logistics of all parties involved – patients, investigators, sponsors, institutions – to facilitate a decentralised trial. We now know the tools exist and it’s exciting to see trends moving towards more hybrid and decentralisation, because it gives people more options for treatment and we are able to reach more patients.”
One of the challenges, says Horneck, is the “great cultural gap between Europe and the US.” Germany in particular “is very averse to having too many things online – the German culture sees the
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patient-physician relation as something very important”. He thinks it unlikely, in Europe at least, that the sector will move to “fully decentralised trials, where we don’t even have a clinic any more, where patients register online, get those drugs shipped and monitor themselves”.
Machine learning will be “critical” Horneck believes a hybrid model will become more and more prevalent: “If you’re an outpatient and in the past would have gone to your clinic every week for clinical assessment, it might be that you will only go every four weeks and in between have a video conference with your doctor or will have something like a wearable device which monitors your primary disease. Or you get your drugs shipped to your home, or even have a study nurse who comes to your home and administers a drug to you – these are things that might come more and more.”
Despite the barriers, the advantages of the hybrid model are so clear that it is difficult to see the industry returning to the older way of doing things. Not only can more patients be recruited using this method, but it is easier to recruit a more diverse group. The problem of patient drop-out or patients not turning up to appointments is likely to diminish. The use of a wearable device to collect data about blood pressure or heartrate is not only more efficient than requiring a patient to have those measurements taken by a clinician, it is likely to produce more accurate and consistent results.
It seems inevitable, too, that technology adoption will extend beyond tools that streamline the collection of data and the organisation of information. Rosenblatt believes that artificial intelligence and machine learning “will play a critical role in shaping healthcare and future health systems”. These technologies, he argues, “have the potential to augment and accelerate drug development, and transform outcomes for patients”. Machine learning, he points out, will enable pharma companies to “obtain and interpret data from clinical trials faster and more efficiently and to optimise trials by more quickly writing appropriate protocols”. If Horneck and Rosenblatt are right, and technology is increasingly playing a more significant role in the success of a trial, then it is likely to become a more important consideration when sponsors are choosing a CRO. A CRO with the ability to run a trial that is more effective at recruiting and retaining patients, better at collecting and recording accurate data and more efficient at providing results will inevitably make it a more attractive prospect for sponsors. ●
Clinical Trials Insight /
www.worldpharmaceuticals.net
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