Now more than ever, largely due to COVID-19, Pharmaceutical Research & Development has an amazing opportunity to dissolve the public perception of ‘Big Bad Pharma’. How can we seize this opportunity and demonstrate that our goal has been and always will be to bring novel treatments to patients faster? I believe transforming clinical trials into personalised engagement experiences while leveraging digital technologies is a critical path forward, but how we leverage those technologies is even more critical.
Who doesn’t love a personalised experience? Retail, banking, streaming services and many other industries have established a phenomenal precedent for personalised experiences, all centred around the notion of customer-centricity. Customer-centricity is why I’m addicted to monitoring my fitness progress on apps like Map My Run and why Amazon parcels are constantly being delivered to my front door. Patient-centricity, similarly to customer-centricity, is a concept that has been around for a while. In my opinion, the primary difference between the two is that while other industries have truly grasped and engaged with customer-centricity, the term ‘patient-centricity’ has felt more like a trend rather than a true practice until very recently. In my last blog post (‘The Pharma Bubble’), I said ‘Pharma does not own drug development…we enable it and partner with patients to drive it’. Fortunately, the evolution of patient-centricity is full of promise as we are now recognising the power of this partnership. We’re working towards empowering patients to own their clinical trial experience and it’s about time because what’s more personal than health?
For us digital innovators seeking to improve clinical trial data quality, one of our biggest challenges is bi-directionality. How do we improve clinical trial data quality and arm clinical trial teams with the ability to explore outcomes, but also empower patients to be and feel like the centre of everything we do? How do we personalise their experience?
I’m thrilled that mobile health (mHealth) and real-world data (RWD) are becoming primary facilitators for effectuating patient-centricity. However, as an industry with a hunger for data plus more data, we have a tendency at times to forget that patients are not just data points. Impersonal data-driven assumptions are certainly essential, but we must hear their voices authentically to give the best trial experience for optimised trial outcomes and improved health outcomes.
So how do we make that shift towards viewing and utilising data and digital technologies as mechanisms to actively listen to people’s wants and needs authentically and truly adopt patient-centricity? Let’s talk about trial design for a moment. Several aspects of a clinical trial are unpredictable; therefore, we need all the robust data we can get to ensure we design a protocol that leads to predictable study delivery within timelines and within budget. Recruiting patients is often the most unpredictable step as well as the most critical, which is why patient involvement in designing a study is pertinent for a successful outcome. The industry as a whole has made considerable improvements to ensure we engage with patients at the earliest stages of program and protocol design in the last 5 years. However, in my view, study design optimisation activities are still often disproportionately focussed on using RWD to model cost and time variants, rather than listening to what works for the patient on a personal level. ‘But we love data!’ I hear you say. Well, I’m with you there. So why don’t we convert what we hear directly from the patient about their personal inclinations, circumstances, drivers and unmet needs into quantifiable data? We all love data, but true patient centricity recognises the need to make data more about the person.
A human-centred approach to data and quantification of human measures will allow us to design and conduct research with a sensitivity that perhaps has been missing in the past. I’ve said before that people are more than just patients. They have families, they have jobs, they have social lives, they have responsibilities, they’re part of a community. A very topical example is cultural sensitivities towards certain groups and subpopulations, which of course resonates strongly with me. Racial and ethnic minorities are considerably less likely than our white counterparts to be included in research, even when certain health conditions disproportionately affect our communities. Fortunately, many emerging innovations show huge potential to address some of the inequalities in clinical research, specifically mHealth which covers wearable sensors, mobile devices and other online or digital services which may be more basic in nature (e.g., social media). The broad accessibility of these tools could inherently enable more inclusive study participation. Of course, this sounds promising, but without the authenticity of actively listening to the human experiences, there is actually a risk of discriminatory profiling or ‘targeting’ ethnic minorities for clinical trials, which is anything but sensitive and less about personalisation. Personalisation means understanding what someone wants and needs and translating that into measurable evidence to improve and enhance their lives.
Our comprehension of patient-centricity is evolving. As we realise it’s more than just a moment and no longer just a trend, the practice of it is critical. As standard practice in digital innovation, we must develop and enhance technologies through the lens of the patients. Whether it’s solutions that put patients at the heart of trial design to improve the likelihood of enrolment, or conceptualising different humanised methods for consenting and recruiting patients; it’s all about making it more personal because what’s more personal than health?
References:
Neuer, A. Patient Centricity and Virtualizing Technologies in a COVID-19 World. SCRS White Paper. 2020. Available at https://vertassets.blob.core.windows.net/download/7e2fa92c/7e2fa92c-e04f-49df-8fd5-f924349e9575/patient_centricity_white_paper_w_scrs__dec_20_.pdf. Accessed February 19, 2021.
Covington, M.T. Digital health Innovation: The Predictive Impact of Curated Real-World Data In Times Of Change. Clinical Leader. 2020. Availavble at https://www.clinicalleader.com/doc/digital-health-innovation-the-predictive-impact-of-curated-real-world-data-in-times-of-change-0001. Accessed February 19, 2021.
Morgan, C. Redefinig Clinical Strategy With Scenario Planning. Clinical Leader. 2021. Available at https://www.clinicalleader.com/doc/redefining-clinical-strategy-with-scenario-planning-0001?vm_tId=2276198&vm_nId=63747&user=9f389338-46b5-4822-a7a6-ccdd597034fc&gdpr=1&vm_alias=Redefining%20Clinical%20Strategy%20With%20Scenario%20Planning&utm_source=mkt_CLNCL&utm_medium=email&utm_campaign=CLNCL_02-11-2021-Oracle&utm_term=9f389338-46b5-4822-a7a6-ccdd597034fc&utm_content=Redefining%20Clinical%20Strategy%20With%20Scenario%20Planning&mkt_tok=eyJpIjoiTUdJMk56Y3pabVppTldNeiIsInQiOiJwclNsVnRzU1RNZlg4czRBRGc1UStua1BOUjlXdGIrMEF5dXlPcER5aGxQbUdmWXB0OXVOMEMwSEFGTmtFbG1pKzNSdHYxdGY4cmkzOXZwTGlHb2ViVHNYV1k3NU54Z1dTZ2V6Y3dDUjJHVkJMTTZKSXVPVEhwK2JVOVdBek1tZCJ9. Accessed February 19, 2021.
Cleary, M. How mHealth Technology is Revolutionizing Clinical Research. Value and Outcomes Spotlight. 2018. Available at https://www.ispor.org/docs/default-source/publications/value-outcomes-spotlight/september-october-2018/ispor-vos-october-2018-toc-mhealth.pdf?sfvrsn=5822a619_2. Accessed February 19, 2021.
Callier, S. and Fullerton. S.M. Diversity and Inclusion in Unregulated mHealth Research: Addressing the Risks. Journal of Law, Medicine & Ethics. 2020. Available at https://journals.sagepub.com/doi/10.1177/1073110520917036. Accessed February 19, 2021.
Chen, J., Mullins, C.D., Novak, P., and Thomas, S.B. Personalized Strategies to Activate and Empower Patients in Health Care and Reduce Health Disparities. Health Education & Behaviour. 2015. Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681678/. Accessed February 19, 2021.
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