The whitepaper, ‘The Role of Digital Health in Immuno-oncology Therapy Development and Adoption’ from BrightInsight, highlights the many ways in which digital can realise and accelerate the impact of innovative immuno-oncology (IO) therapies.
It says that the growth in treatment options is making it more difficult for oncologists to match patients to the right therapy – but there are many ways in which digital tools can help address this by leveraging data.
“Increasing the accuracy of patient matching – by getting the right patient the right therapy and maximising adherence – could have greater impact on clinical outcomes than more primary innovation with new therapies,” the authors point out.
Companion digital diagnostics and clinician support tools – aided by predictive AI algorithms – can help doctors sort through data and decide which IO medicines will work best for a particular patient, ultimately allowing for more precision treatment.
And after a patient has been matched to a treatment, data gathered from companion apps and remote monitoring tools such as wearables can optimise outcomes, both through assessing how well a treatment is working and by flagging potential adverse events.
Digitally monitoring a patient’s body temperature, for example, can help physicians predict and mitigate cytokine release syndrome (CRS) in CAR-T patients, an early indication of which is fever.
But with increasingly large volumes of data on IO drugs and cancer patients being generated every year, it is becoming more difficult for stakeholders to parse out insights that are actionable and valuable.
This, too, is an area where digital can make life much easier for pharma companies and clinicians.
“All of these datasets are incomplete and disconnected,” says BrightInsight’s chief commercial officer, David Matthews. “None of it is coming together in one simple way for clinicians making treatment decisions.
“Digital infrastructure, combined with informatics and predictive sciences, offers us an opportunity to bring that disparate data together and get the most out of it.”
One issue is that many health IT systems and biopharma companies run on proprietary software that does not integrate well with others, while data silos exist between biopharma and diagnostic companies.
The whitepaper therefore recommends that companies invest in a common underlying digital infrastructure that enables interoperability and integration across systems.
“A regulated digital health platform enables transferring, processing, and analysing data to support therapy development, making the data more accessible,” it says.
Remote monitoring and the real-world data it produces can also address another major challenge with IO drugs – their costs.
IO therapies often have price tags in the range of hundreds of thousands of dollars, and therefore manufacturers are increasingly being asked to show unequivocally improved outcomes in real-world data to continue and expand reimbursement from payers.
“With digital, you can measure how well immuno-oncology drugs are working in a real-world setting in a more reliable way,” Matthews says. “If you can demonstrate who gets the most benefit out of a particular therapy, payers may be more likely to reimburse these treatments.
“This enables pharma to take advantage of reimbursement trends that favour outpatient over inpatient treatment, as well as a trend towards value-based care systems in which payers only reimburse drugs that are demonstrably effective.”
Digital can also improve access by making clinical trials more accessible to more patients, the whitepaper adds.
Clinical trial enrolment is an expensive and time-consuming process, and currently only 8.1% of oncology patients participate in clinical studies.
The whitepaper notes that AI can assist in the patient matching process by structuring patient records for ClinicalTrials.gov and comparing inclusion and exclusion criteria. Meanwhile, in-depth protocols reduce rejection rates by applying machine learning to pre-screen information against protocols.
From there, remote monitoring can enable more home-based treatment and participation, allowing for patients with more limited resources and difficulties in travelling to participate in studies.
“These applications of digital health have the potential to significantly reduce the costs associated with clinical trials, increase patient enrolment and expand clinical trial coverage,” the whitepaper says.
Matthews says that these benefits of digital tools are already clear to IO manufacturers – and that the question isn’t “whether” they should adopt them, but “when and how”.
“Over the next five years digital is going to become essential to the clinical and brand strategy for every type of therapy, and digital will be considered from the outset of IO drug discovery, through to clinical trials and commercial launch.”
Matthews says a key decision these companies need to make early on is what to build in-house and what to build in partnership with dedicated digital organisations.
“Digital is such a massive undertaking, and it can present many challenges to a pharma company that does it all by themselves.
“We see pharma companies going further and faster by partnering rather than trying to build solutions entirely in-house.”
Through this, he says, companies can bring in a common digital health data infrastructure that will underlie every digital solution they create, allowing them to build regulated solutions more quickly
Using a common platform for every digital tool can also pre-empt issues with “app overload,” Matthews says.
“If all these digital tools that pharma creates are not interconnected – e.g., there’s a different app for each treatment or each stage of the patient journey – we run the risk of patient and clinician fatigue.
“That problem becomes even more pertinent in combination IO treatments, when there might be different tools for each drug in the combination.
And if that underlying infrastructure has regulatory considerations built in, Matthews says, it can help minimise the time and administrative burdens associated with regulatory approval.
“Getting regulatory approval for a digital device can be a huge endeavour; there’s a massive volume of accreditations and certifications that are necessary just to begin building these tools.
“In cases where a digital tool is actually making a clinical decision based on the measurement – such as a temperature sensor warning of the risk of CRS – regulatory bodies will want to be heavily involved and have a lot of oversight on what is produced.
“Because of that, we strongly encourage companies to think about the regulated nature of their digital endeavours or digital ambitions from the very beginning.”
Beyond this, he says that the biggest remaining barrier to ensuring widespread adoption of digital tools in immuno-oncology is awareness among doctors and patients.
“Likewise, the purpose of these tools for patients is not to make their life revolve around a treatment plan, but to enable them to have a better life because their treatment is managed more effectively through digital.
“The awareness piece has to focus on how digital can demonstrably make the lives of patients and clinicians better from an experience and outcomes perspective.”
Asked what he hopes people can take away from the whitepaper, he says that companies working in immuno-oncology should recognise that digital transformation is already happening, whether or not they are ready for it.
“We have ample evidence to show that it’s valuable and may improve outcomes – so the question then becomes, what is pharma going to do about it?
“The best answer is to get involved and provide digital solutions, apps, connected devices, and algorithms to the patients and clinicians who are using immuno-oncology treatments in order to generate the best possible outcomes.”
To read the full whitepaper, ‘The Role of Digital Health in Immuno-oncology Therapy Development and Adoption’, visit BrightInsight’s website.
David Matthews, PhD, has 15 years of experience in pharmaceuticals, medical technology, and medical research. Before joining BrightInsight, David was a partner in the Healthcare, Commercial, and Corporate Finance & Strategy Practices at Boston Consulting Group (BCG), where he helped lead the West Coast Medical Technology business. He was selected as an Ambassador to BCG’s internal thinktank, the Henderson Institute, where he designed and published on new economic models for biopharma products, including building the Netflix model for curative therapies. Prior to his time at BCG, David was a computational neuroscientist, with more than 20 publications and conference proceedings across machine learning, bioinformatics, brain imaging, neuroanatomy, and health economics. David holds a PhD in Computational Neurobiology from The University of California, San Diego and the Salk Institute, where he was a National Science Foundation (NSF) Research Fellow and NSF Center for Theoretical Biological Physics Fellow; and a Bachelor with honors in Molecular Biology, and minors in Bioengineering and Neuroscience, from Princeton University.
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