Home » Clinical Trials » How digital devices are changing the clinical trial landscape

Andrew Greenberg

Managing Director, NA Digital Health Lead, Life Sciences

Alex Simmonds

Digital Clinical Lead, Accenture Life Sciences

Changes to the digital trial space are being driven by technological advances that present an increased role for patients.

New technologies and devices are enabling a shift from traditional clinical trial formats to decentralised studies with patients and their experience at the core of research.

In tandem with this, a new generation of digital-friendly physicians and Principal Investigators (PIs) are embracing the remote approach which industry experts believe could enhance the development of drugs and therapies and lead to more personalised and precision medicine.

Use of remote monitoring devices on studies enables clinical trial participants to provide insights into their physical outcomes and patient experiences all the time, not just while they’re in the clinic.

However, Andrew Greenberg, Managing Director, NA Digital Health Lead, Life Sciences at Accenture believes the critical patient-physician contact in clinical trials is still of value.

Rather than purely decentralised trials (DCT), he sees a future of an NPT (near-patient-trials) model, one that changes the focus from the standard academic medical centre (AMC) model to meeting the patient where they are, regardless of location.

From medical centre to patient-centric

COVID-19 social-distancing requirements have accelerated this move to decentralisation, along with patient reluctance to receive treatment in traditional care settings.

But Greenberg, suggests the shift away from traditional, site-based, clinical trials began prior to the pandemic.

He says: “Five years ago we recognised digital was going to have an impact in the space, so we reconfigured our business to become more digital and bring about digital enablement across the board in R&D, and particularly in clinical studies.”

Initial “promise” turned into reality in 2018-19 with the “maturation of digital technologies” and a new generation of PIs who were keen to move on from the traditional academic medical centre model and embrace the digital future. Regulators and pharma companies were also expressing interest.

By 2020, there was increasing interest in decentralised clinical trials when COVID-19 struck. Since this transition was already well under way, it gained even greater momentum.

Interfaces and databases

Accenture, a global professional services company with a range of strategy, consulting, technology and operational service offerings in the clinical trial space, has evolved technologies to keep pace with this and help R&D organisations transform trials by improving the patient experience and transitioning to digitally enabled platforms.

These innovations have the ability to significantly impact nearly every part of the trials process including study design, site selection and monitoring, participant recruitment and retention, data collection and analysis.

Greenberg continues: “We have been helping clients understand what patient centricity and digitisation of patients really means, what it means for patient flow, follow up, enrolment and informed consent. It puts patients at the centre.”

Digital approach

The challenge, however, is how to retain site-based platforms in partnership with the DCT approach.

Accenture’s technologies keep the PI in place with the trial elements available through a novel platform.

As digital data collection generates huge amounts of data requiring analysis and interpretation, Accenture has worked with pharma companies to build systems to handle this efficiently while minimising patient burden and supporting other key performance indicators.

Other novel approaches include designing virtual clinical trials that use synthetic control arms, he says, and utilising patient data differently with smart algorithmic and artificial intelligence-based approaches to model trial outcomes before commencing human studies, increasing the possibility of success with the study.

AI and machine learning can be used to pick up patterns and trends that would not be visible with human review or with conventional analytic tools – especially where unstructured or continuous time series data is involved – and technologies like RPA (robotic processing automation) are further digitising the system “to bring about a transformative change in the end-to-end clinical trial.”

Data-driven and nearer to the patient, trials of the future will harness the power of digital to become less manual, more efficient, and yield higher quality data.

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