As the societal transformation imposed by COVID-19 starts to become considered normal, daily life has changed and businesses in many sectors are adapting. The paradigm shift has been perhaps most profound in healthcare, where staff in primary, secondary and tertiary care, as well as those in research, have had to deal with immense challenges.
One of the undoubted bright spots during a difficult 18 months has been the success of the vaccine program. In particular, the development of a new set of protocols around the use of Real World Evidence (RWE) has been encouraging and has provided an additional source of data. Apps such as Zoe have become commonly used for tracking COVID, and the Phase 4, post-marketing authorisation data collection exercise is ongoing and of immense importance to our understanding of how immunity wanes over time and is boosted by additional injections.
The broader acceptance of RWE had already started prior to the pandemic. In April 2019, the United States (US) National Institutes of Health (NIH) and the National Science Foundation (NSF) held a workshop where they invited experts in clinical trials, digital technology and digital analytics to discuss strategies to implement the use of digital technologies while considering the challenges that might arise. The NIH also made “pragmatic trials” – which include the use of digital technologies – a priority. The call was made to integrate digital technologies without losing the rigour of the Randomised Controlled Trial as the gold standard by which a drug product, device or other intervention is assessed for efficacy or safety.
In the UK, the Medicines and Healthcare Regulatory Agency (MHRA) has acknowledged the role that RWE plays and recently set up the Innovative Licensing and Approvals Pathway. There is also a recognition that technology has a role to play in their vision for the Future of UK Clinical Research. The 5 key themes underpinning the MHRA’s vision for clinical research in the UK are:
clinical research embedded in the NHS
patient-centred research
streamlined, efficient and innovative research
research enabled by data and digital tools
a sustainable and supported research workforce
Further, the MHRA write:
“We can create a truly digitally-enabled and future-ready clinical research environment. This will act as a vital enabler to deliver faster, more efficient and more innovative clinical research – which increases access and brings new gene sequencing, cell-based therapies, precision medicines, digital tools and artificial intelligence to bear to tackle the NHS’s most pressing healthcare challenges.”
What is Real World Evidence (RWE)? The FDA defines RWE as the evidence that is derived from routinely collected administrative data sources related to the patient’s health status and/or the delivery of healthcare. RWD can come from multiple sources, including:
Electronic health records (EHRs)
Claims and billing activities
Product and disease registries
Patient-generated data including in home-use settings
Data gathered from other sources that can inform on health status, such as mobile devices
As opposed to the highly controlled RCT, RWE reflects the patient’s lived experience and as a result concerns the measurement of effectiveness rather than efficacy and as such starts to relate more directly to the concerns of the patient. One of our mantras at Alta Flora is that the patient is only ever concerned with two “outcomes” – a) Quality of Life and b) Quantity of Life. In this sense, RWE appears to be more aligned with patients concerns rather than researchers’ specific questions. The RCT has had its own criticisms as a measurement methodology. Only 7% of drugs from Phase 1 make it to patients and there are valid concerns about the cost, length and in some cases ethics of RCTs.
The “randomising” and “blinding” that happens is something that will need to be replicated in whatever clinical trials are developed in the future in order to persuade those who are most sceptical about the effects of bias and confounding factors. However, the idea of the clinical trial is changing as personalised medicine starts to dictate that cause and effect is understood at the level of the individual rather than in cohorts with particular inclusion / exclusion criteria. As Artificial Intelligence and Big Data start to permeate the clinical trial industry, “in silico” trials will leverage software solutions and data from previous trials to develop new types of clinical trials. Goldman Sachs estimate that 15% of drug development costs could be removed through better use of technology, and as Big Tech becomes more deeply involved in healthcare, some trials simply won’t need to involve humans at all, utilising “synthetic” control arms
Thus the RCT remains “an analog tool in a digital world”, and while it serves a purpose, the realities of post-pandemic healthcare mean that we need to (and CAN) achieve exponentially more without a corresponding increase in costs and resources. Technology will play a crucial role, and to get anywhere near addressing the inadequacies in the system, we need Moore’s law to apply, rather than the current situation where US healthcare spending doubles every 13 years and the recent increase in NHS spending means that little is left for the rest of social care.
Decentralised clinical trials
At a recent NIHR Life Science event in London, a prominent topic of conversation was decentralisation. No longer were multiple trial sites appropriate for patients to travel to in a lockdown; the trial had to be taken into the patient’s home through the use of mobile technology, wearables and devices. Workflows were re-imagined, with consent forms and follow-up appointments handled digitally.
Decentralised Clinical Trials (DCTs) are a hot opportunity, with market growth segment forecast from $2.5B currently to $10B by 2026. DCTs involve the use of technology to improve the recruitment process in terms of speed of onboarding, diversity of population and retention rates through the trial. Technology also opens up new sources of data such as wearables and digital biomarkers.
Examples of standard digital endpoints are measurements for heart rate, while examples of novel digital endpoints include measurements for the appearance, heat, or pallor of skin, or composite endpoints, such as the synergistic combination of heart rate and movement intensity. To determine the efficacy and safety of an investigational medical product in the future, novel digital endpoints may complement standard endpoints, both because of their predictive capabilities and their feasibility of inclusion in DCTs.
Integrating clinical data with data obtained from DCTs (i.e. real-world settings) may also add additional context between remote and in-person clinical interactions. As data can be streamed from devices rather than periodically collected, technology offers the potential for enhanced patient safety monitoring, as well as a much more granular picture of changes in patient symptomatology. The Ecological Momentary Assessment framework offers potential in pain and mental health conditions and is something we have looked at in the design of our app, Eva. This move to “always on healthcare” focused on prevention rather than “healthcare only when sick” focused on treatment is one of the biggest shifts to advance Quality of Life for millions around the world and is where our technology can inform longevity research.
A key challenge in clinical research, highlighted In our conversations with customers (primarily academic researchers and pharmaceutical producers), centres on patient retention. Technological advances offer multiple opportunities for enhancing retention in DCTs, and methods by which a patient can be encouraged or incentivised to contribute data and remain part of the trial. There are many questions for regulators and researchers to answer around the appropriate and valid use of financial incentives and gamification mechanics in digital products. Many researchers are also determining the primary outcomes of DCTs, particularly in a way that regulators are comfortable with, and the explosion in data means that big data processing is required. Finally, the question of standards is critical, with FHIR and CDISC playing a role in defining data models, standards for portability, interoperability and quality.
Health care and clinical research policies are evolving simultaneously across multiple jurisdictions and countries to support the broad inclusion and recognition of digital endpoints in all therapeutic areas by regulatory agencies. At Alta Flora we foster improvements in real-time data analysis by integrating outputs of digital endpoints and clinical data derived from multiple sources with AI/ML. There is a “jigsaw puzzle” of data that needs to be assembled to allow a more comprehensive and holistic understanding of the health status of individual patients..
There are a series of different means by which digital technologies can be used with different trial methodologies
Adaptive clinical trials enable the trial design to be altered in the course of the research.
Pre-planned changes that an Adaptive Design may permit include, but are not limited to:
refining the sample size
abandoning treatments or doses
changing the allocation ratio of patients to trial arms
identifying patients most likely to benefit and focusing recruitment efforts on them
stopping the whole trial at an early stage for success or lack of efficacy
This iterative approach to dosing is much more appropriate for certain drugs (e.g. medical cannabis, where the patient has to “dial in” to his or her optimum medicine) and in certain conditions (e.g. childhood epilepsy, where parents often tweak the dose and time of medication)
Schwartz and Lellouch were the first to use the word “pragmatic” in relation to clinical trials in 1967. They defined a pragmatic trial as a trial designed to help choose between care options, as opposed to an explanatory trial which is used to test causal research hypotheses, for example about biological processes.
About 30 years later Roland and Torgerson made the distinction between these two types of trial in a slightly different way, explaining that explanatory trials evaluate efficacy, the effect of treatment in ideal conditions and pragmatic trials evaluate effectiveness, the effect of treatment in routine clinical practice.
In the twenty-first century it has been recognised that there is, in fact, a spectrum of trials with very exploratory trials at one end and very pragmatic trials at the other end.
In an era of personalised medicine, the N=1 clinical trial focuses on how a medicine will be assessed for an individual. There are examples where the RCT is either impractical or unethical – for example, in some palliative care scenarios, RCTs fail because of the inability to recruit and retain sufficient numbers of subjects to achieve necessary sample size requirements. As a result of the lack of RCTs with subset analyses which are relevant, RCTs have failed to inform drug selection for an individual patient requiring palliative care. There are a number of methodological issues which N=1 trials can minimise through smart blinding in crossovers, combining multiple N=1 trials together, and looking at constructing RCTs based on the N=1 data that is gathered.
Other data collection efforts in healthcare
Observational studies are studies where the “researcher observes the individual without intervention or manipulation.” Alta Flora is undertaking an observational study with MGC Pharma of children with epilepsy and the data collected will inform the design of an RCT. There is a lower bar for ethics approval needed for these types of studies as they are generally recognised to be less sensitive than trials.
Registries are a database of persons containing a clearly defined set of health and demographic data collected for a specific public health purpose. Registries are being established across Europe for the purpose of collecting data on medical cannabis.In the UK, the Sapphire UK medical registry and Drug Science’s Project Twenty21 are probably the best known, while the NHS has also announced the creation of its own registry. Across Europe, similar methods of data capture have been mandated at the national level, from the Danish Pilot Program launched 3 years ago to the recent national trials for up to 3000 patients launched in France.
The key takeaway from all this flux in the world of healthcare data is that there are huge opportunities to improve how we conceive of healthcare and wellbeing. At Alta Flora, we aim to combine decentralised, networked, always-on data collection with deep empathy for the patient in order to transform clinical research. Most patients aren’t told about their own results, updated on the overall trial progression or told how their participation may help the lives of others: the culture of the clinical trial is something that digital technology must transform too.
Decolonising clinical research
Movements around the world such as Black Lives Matter and MeToo are drawing attention to structural racism and social injustices. Across every level of society, discussions on Diversity, Equity and Inclusion have become more prominent over the last few years, and in particular in healthcare research, that diversity and inclusion is something that needs to be addressed. The NIHR in the UK has launched the INCLUDE roadmap to address issues in UK research, and have defined the following groups as marginalised or under represented:
Groups by Demographic Factors (Age, Sex, Ethnicity, Education)
Age extremes (e.g. under 18 and over 75)
Women of childbearing age
Black, Asian and Ethnic Minorities (BAME)
Male/female sex (depending on trial context)
LGBTQ/ sexual orientation
Educational disadvantage
Groups by Social and Economic Factors
People in full time employment
Socio-economically disadvantaged/ unemployed/ low income
Military veterans
People in alternative residential circumstances (e.g. migrants, asylum seekers, care homes, prison populations, traveller communities, the homeless and those of no fixed abode)
People living in remote areas
Religious minorities
Carers
Language barriers
Digital exclusion/disadvantage
People who do not attend regular medical appointments
People in multiple excluded categories
Socially marginalised people
Stigmatised populations
Looked after children
Groups by Health Status
Mental health conditions
People who lack capacity to consent for themselves
Cognitive impairment
Learning disability
People with addictions
Pregnant women
People with multiple health conditions
Physical disabilities
Visually/ hearing impaired
Too severely ill
Smokers
Obesity
Groups by Disease Specific Factors
Rare diseases and genetic disease sub-types
People in cancer trials with brain metastases
Historically, clinical trials have not included the above groups. Black Americans represented only 2.5% and 4% of enrollees in trials involving cardiology or cancer immunotherapy. The National Institute for Health Research (NIHR) analysed the ethnicity data provided by a total of 622,978 participants taking part in studies across the UK and found that only 5.8% of the vaccine study participants were from an ethnic minority. It is incumbent upon the next generation of researchers to address this historic injustice.
We aim to boost the participation of these under-represented groups in clinical trials through the use of technology and data. In our work at Project Twenty21, we have helped the Drug Science team understand the value of digital patient acquisition, with the enhanced targeting that digital platforms can deliver. This profiling will ultimately, over time, help us to rebalance the composition of the clinical trial to be reflective of the marginalised groups above. But the imbalance goes beyond trial participation. Earlier this month, Nature magazine announced its focus on Diversity, Equity and Inclusion, and noted that there are racial disparities in those being funded for clinical research. We need to ensure BAME researchers get the funding needed to make the research community representative of society more broadly.
At a global level, similar imbalances need to be addressed. Here is a map of Phase III trials taking place in each continent from clinicaltrials.gov:
In India we see a population of 805,000 per trial, whereas in North America that number is 21,000. Those numbers exemplify the global imbalance in clinical research, and that is despite India being the global production centre for generic drugs! Those generics are perfect candidates for being repurposed for other diseases, but the prohibitive cost of doing research – and the low margin nature of the generics business – means that this research isn’t being done when it could be.
Destigmatising medicines
Alta Flora began life in 2018 with a plan to produce medical cannabis for patients. As we realised that the nature of the deep personalisation required to ensure cannabinoid therapies modulate the Endocannabinoid System as needed, our focus moved to the data needed to validate and personalise these cannabinoid medicines. Medical cannabis has been a niche area of medicine but is breaking out as more and more doctors learn about the Endocannabinoid System and hear testimonials from patients who have seen their lives transformed by this medicine. Medical cannabis also suffers from being a stigmatised medicine; a complex medicine to analyse; a challenging medicine to understand; and a medicine which sits outside the traditional profit formula for Big Pharma.
As a result, researchers, academics and researchers in the medical cannabis industry are innovating and establishing alternative frameworks for developing the evidence base around safety and efficacy of medical cannabis. Registries are being established across Europe, with Project Twenty21 the most prominent in the UK, and RWE is where most of the activity has been focused thus far.
Many psychedelics – such as psilocybin, DMT, MDMA and ketamine – are drugs which face similar issues to the ones we were addressing in medical cannabis. Common to both cannabis and psychedelics was that gathering cost-effective RWE was critical to addressing all these issues, and that there is an astonishingly high degree of engagement from communities of patients and others who wish to see these medicines integrated into mainstream healthcare provision. It’s our view that the lack of content provided by researchers to these communities pre-, during and post- trial is a missed opportunity, and something that we will remedy in the studies where our platform is used.
So in addition to our focus on underrepresented and marginalized groups of people, our focus is on those medicines which have been historically stigmatised and under researched – natural medicines in general, with cannabis and psychedelics in particular. But we know that our tools and technologies will only be taken seriously by the medical establishment if we adhere to the same “regulator-grade” evidence and frameworks as is needed for the marketing authorisation of traditional pharmaceuticals.
In order to broaden access to these medicines there is much work to be done. There are companies like GW Pharmaceuticals and Compass Pathways who have taken fairly traditional approaches in order to generate “regulator-grade” evidence. They have undertaken great work and have been rewarded in the financial markets. In a post-pandemic healthcare industry, however, new measurement methodologies are being developed; Alta Flora is playing a role in building the infrastructure required for these new medicines to play a role in improving quality of life. We welcome those who are interested in our work to get in touch.
Published November 29, 2021
By Gavin Sathianathan