Tech injection

31 August 2020

Technology is having a huge impact across all industries, and pharma must keep pace to avoid being left behind. Digitisation offers huge potential for improving patient engagement, coordinating data from different sources and improving decision-making. Lynette Erb speaks to Dr Yuri Martina, senior vice-president for development at Gr√ľnenthal, about how to utilise it most effectively.

Digitisation means converting objects and information into computer-readable formats, and it is, quite literally, transforming the world around us. In the trials space, it already covers a broad scope of technologies, from patient-based reporting and real-time tracking via implants and sensors, to connected drug delivery devices.

Still, there are opportunities for the pharmaceutical industry to make more of our appetite for tech. In R&D generally, and in clinical trials in particular, there is huge potential for digitisation to improve patient outcomes and speed up development timelines by implementing AI for data analysis.

Dr Yuri Martina, senior vice-president for development at Grünenthal, says digitisation offers the opportunity to harness data to provide more efficient therapies more quickly, thus helping to safely service unmet patient needs.“Digitisation brings the opportunity to collate real-time data, identify safety trends and intervene in a more timely manner,” he says. “As a consequence, it also helps speed up the development of new drugs for patients.”

Indeed, across the full scope of medical trials, digitisation and data optimisation can provide improved patient insights and clinical understanding.

“When it comes to trial phases, I believe digitisation has a different role at different stages,” Martina continues. “It becomes increasingly important in the conduct of trials as you increase their scope and site locations from phase-I to phase-III. Digitisation plays a key role in data handling, as well as in how we use this data across specific development programmes to learn and gain insights.”

That said, Martina stresses the need for a realistic approach. On their own, more computers producing more data are not a force for good. Rather, digitisation is a way of aiding studies that still require sound design and implementation.

“I do not share the view that digitisation by its nature helps to design better or more patient-centric study protocols,” he says. “Digitisation provides you with a set of tools that can aid the study design and conduct. However, to design better protocols, we need to focus on the principles of quality by design. At Grünenthal, we have now started on-site protocol simulations to ensure our protocols are mindful of both patients’ and investigators’ needs. Digitisation provides us with the tools to aid all when it is done in respect of these objectives.”

But it’s with AI that Martina predicts digitisation will have the most significant and far-reaching impact, especially in the field of predictive analytics. Continuous monitoring – made possible by technologies such as device connectivity, wearables and implants – has the potential to increase both the amount of data and the quality of data collected. That means the resulting data sets are larger, and the analysis required to understand them is more complex than ever before.

The time saving that one study found direct data capture systems could achieve over manual entry from medical records.
Error rate when manually entering medical records.
International Journal of Medical Informatics

“AI gives us the capacity to elaborate on and process a huge amount of data in a very short time,” says Martina. “I see a big advantage in terms of the integration of information from different functions and sources. This is something that, in the past, required a lot of time. But with AI, it can be done very quickly and achieve goals beyond what could be done in the past.”

In this way, AI will lead to a move away from descriptive analytics based on historical data, and towards predictive analytics, helping drive better, more informed decision-making throughout the clinical trial landscape.

Clear as the potential might be, pharmaceutical companies are lagging well behind their big tech counterparts. More collaboration between them could help close the gap, but Martina is suspicious about the pharmaceutical sector’s commitment to implementing digitisation quickly enough to keep up with how fast the technology is developing.

“We have heard much about this transformation, but from my perspective, we have still seen little in terms of real applications,” he says. “Some consolidated technologies – e-diaries for example – are now implemented routinely, but these technologies have been around for five or more years. Some more advanced applications – such as wearables and remote monitoring – have only been minimally implemented. I believe we have been too conservative and really need to step up. The big tech companies are leading and the potential of some of these technologies is limitless.”

Pharma in need of a boost

With that in mind, Grünenthal is now investing heavily in an effort to put itself at the forefront of digital innovation, and to engage with tech companies to learn from their experiences, both inside and outside the medical sphere.

Such humility is important too, because digitisation brings a host of new challenges. Moving from clinical trials designed, recorded and analysed on paper to a fully digital environment raises serious privacy and data protection concerns, while the avalanche of data digitisation means trials will need to be highly targeted in their design to remain relevant.

“The biggest challenge is the investment needed considering this is exploratory data, and that navigation of a large amount of collected data is required,” says Martina. “This is why a well-defined plan is key to securing investment, and also ensuring the maximum is obtained from the collected data.

“First of all, companies will need to invest in mapping or cataloguing their data. They need to understand what, where and how data is collected in different functions. Then they will need to define how and what they want to achieve with this data. Investments will be substantial and might include a trial-and-error process. I don’t think companies should be shy in moving forward in this respect if they want to capitalise on the advantages of having such data integration and digitisation.”

That investment also needs to extend to attracting the talent needed to manage and guide the move towards tech-driven research. Digitisation is transforming not just the way clinical trials are developed and managed, but also the skill sets of those running them. Clinical trials teams, like R&D teams generally, need to adapt as technology changes: data specialists, mathematicians and software engineers are becoming instrumental in developing and analysing R&D outcomes.

“Digitisation has changed team structures, adding new capabilities to the mix, to the tasks and to the way we provide oversight,” says Martina. “But I don’t believe data science skills and medical/scientific skills are necessarily mutually exclusive. These both need to be present to achieve the maximum advantage from digitisation. We are not talking about replacing skills, but rather adding them to the mix.”

This cross-pollination of ideas and technologies across industries requires more collaboration with the research institutes, biotechs and start-ups that are currently pioneering digital tech solutions. Martina says pharmaceutical companies will need to increase the concentration of investment and resources to reap the benefits of these partnerships.

And while heavy regulation has often been cited as a major hurdle to the digitisation of the clinical trials, Martina disagrees. “I personally – having spoken with the FDA and other agencies – feel the real obstacle is the industry itself. Rightly, we are a highly regulated industry, and this has driven us somehow to be very conservative when it comes to the implementation of the new technologies that are driving digitisation.”

Martina believes pharmaceutical companies need to commit more resources to testing emerging tech in the medical sphere. In fact, he says this is the best way to actually prove to regulators – and to others in the industry – that digital technologies hold the key to improvements in patient outcomes.

“We need more trials with wearables. We need to correlate data to approved end points and prove to the regulators that these new digital end points can be as good, or better, markers for efficacy,” he concludes. “The new E6R2 and E8R1 ICH GCP regulations already capture significant points on new technologies and how we should use this to avoid the errors of the past. We, in the pharmaceutical industry, need to move forward more courageously and boldly to try and implement some of them.”

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