If you know the money and time needed to bring a new drug to market, you know. If you don’t: welcome to the club! This decade-plus process is exorbitant; much of it spent developing and delivering clinical trials. It is also an expensive gamble, with 93 per cent of all candidate drugs failing to pass the clinical trial phase.
However, COVID-19 and the rapid development of novel mRNA vaccines showed that a more effective and efficient drug development pathway is possible. The challenge now is to adopt the lessons to help rapidly develop new treatments and technologies to tackle other common and life-threatening diseases – from diabetes, heart and respiratory diseases, to tuberculosis, cancer and dementia.
Some this requires regulatory change, but just as critical is the role of new and innovative technology.
An inefficient system
The economic and social cost of COVID-19 was immense, but in many ways, it was not extraordinary. Looking around the world, there are a whole raft of diseases that exert huge health and cost burdens year in, year out.
Take dementia. In 2020, this was responsible for 11.5 per cent of all deaths in the UK (second to COVID-19 at 12.1 per cent) and represented a total societal burden of $1.3 trillion to the global economy in 2019. This burden is projected to increase to almost $3 trillion by 2030.
The same year, tuberculosis, malaria and HIV together accounted for almost 3 million deaths, highlighting the magnitude of the challenge we face in health.
Yet – by varying degrees and for different reasons – all of these are solvable. However, one issue that is common to all of the potential solutions is making the clinical trials system more efficient. Reforming this would not only bring down that cost – and improve timelines – but it would give us far more opportunities to tackle these health grand challenges.
This inefficiency falls into three categories: logistics, markets and strategy.
For the first, patient recruitment is a huge challenge. In the US, it delays around 80 per cent of trials, while 35 per cent of trials fail altogether. Diversity is also a problem that leads to underrepresentation and sub-optimal treatment. Around 76 per cent of nearly 300,000 participants in clinical trials globally in 2020 were white. Just 11 per cent were Asian and only 7 per cent were black. And - as would be expected - admin is another ill. Researchers running clinical trials often have to manage time-consuming tasks, alongside managing data across multiple systems and sites, which can lead to incompatibilities, inconsistencies, redundancies or gaps in patient data.
Centralisation is another issue as trials are often only available at medical centres and frequently require face-to-face visits, incurring burdens on both patients and researchers. This effect has been accelerated by Covid-19, which has seen a decrease in patient willingness to attend clinical settings.
For markets, some of the main concerns include: competition, as the industry is still largely dominated by a relatively small number of large incumbents; data-sharing, as this has huge value even beyond original study; as well as risk-sharing across private and public organisations, particularly high-risk or complex challenges.
Lastly, on strategy, two critical areas are prioritisation of research resources to efficiently and effectively address gaps in medical evidence and alignment with clinical practice and coordination at a global level with more research spanning regulatory jurisdictions.
Technological solutions
Despite these challenges, there is reason for hope. Technological solutions are emerging to make drug discovery and clinical trials more intelligent, more efficient and more effective, enabling new drugs to come to market sooner, without compromising patient safety or increasing costs.
AI
Central to this future is AI.
As has been well-documented, AI provides potentially game-changing potential to revolutionise not only drug discovery, but the trials process too. Companies like Isomorphic Laboratories and BenevolentAI are seeking to identify new targets and design novel candidates, while others such as Owkin and AiCure are using machine-learning to predict the clinical outcomes of candidate drugs before they enter human trials. There are then those such as Trial.ai, who are working on “smart protocols” for clinical trials, which can help avoid costly delays caused by poor design.
Open-source platforms like DQueST are also using AI to simplify eligibility questionnaires for trials listed on ClinicalTrials.gov (a website enabling people to sign up to participate in clinical trials) to make it easier for prospective participants to understand if they are suitable candidates.
Management Systems and Real-World Evidence
Major tech players are also moving into the clinical-trial business, bringing to bear their vast computing power and economies of scale. Hyperscale cloud-infrastructure and data-management platforms like Oracle’s Clinical One are unifying clinical-trials data held across multiple sites on to a single platform that also links to patients’ Electronic Health Records.
In the future, connecting such platforms to complete national-level health-data infrastructure offers the potential to massively accelerate the identification of suitable trial participants, while also collecting real world evidence on patients after a trial has ended.
Smaller-scale start-ups are attempting similar things in an attempt to disrupt the industry. TrialSpark, for example, utilises automation and data to simplify logistics, processes and outsource clinical-trial appointments to local doctors’ offices in the US. Its platform can reportedly significantly decrease trials timelines and speeding up the timeframe in which new drugs are developed, as well as improving accessibility for participants.
Decentralised trials
Through remote virtual trials, technology is also trying to tackle issues of accessibility. The RELIEVE IBS-D study is one example of this. After Covid-19 interrupted participant recruitment, it pivoted to digital to recruit and monitor participants. A single virtual site recruited 67 per cent faster than all 28 sites using a traditional approach.
Others such as Huma and Medable have also developed similar virtual platforms, while Protas, led by Sir Martin Landray, who previously ran the world’s largest decentralised COVID-19 clinical trials (RECOVERY), is designing and delivering large-scale, global, randomised and decentralised clinical trials.
Wearable technology is also emerging as a vital component of decentralised platforms. For example, smart watches can be used to collect continuous longitudinal data on patients’ vital signs, such as heart rate, body temperature and sleeping patterns, to remotely monitor patient responses to treatment regimes. They can also provide helpful reminders to patients on when to take medication. In the UK, the NHS is using wearables for remote-monitoring purposes, providing smartwatches to more than 120,000 patients suffering with Parkinson’s disease.
Move fast and make things
All in all, there is significant potential to begin to fix inefficiencies that plague the system. But in order to realise this potential governments needs to move faster.
Central to this is building the digital infrastructure that is not only critical for the future of health, but which also connects to clinical-trial management systems to improve speed and effectiveness. This will also be crucial for reducing search costs and finding more eligible patients. Cracking data-sharing and consent regimes is going to be fundamental to this, and to the benefits it brings in terms of real-world evidence and more.
Second, is the need to be innovative in drug discovery and trials, bringing in the benefits of AI and cloud to build transformative new platforms. Equal is the need to be creative with new commercial and regulatory models to foster discovery of new treatments. This will differ by markets; although the data available to the NHS should put the UK in a unique position to build a health-industrial complex. But globally, we are on the precipice of a new era of medicine where single-dose, curative treatments (such as gene and cell therapies), digital therapeutics and other breakthroughs will become increasingly available. We just need to get better at scaling them and making the accessible.
Third, is greater support for decentralised, global clinical trials. In particular, the UK could take a lead on this through sharing national databases of ongoing trials and creating Trusted Research Environments which provide anonymised patient data to approved researchers from around the world.
This is a critical challenge. Recent advancements in technology – from AI and cloud infrastructure to telemedicine platforms and EHRs – offer the opportunity to radically accelerate and improve candidate drug development, speed up and diversify patient enrolment, and make clinical trials drastically more efficient, providing solutions to many of the most significant challenges faced by the life-sciences industry.
It is one of those issues that when you know, you know how much better the system could be – and how technology it central to improving it. It will take leadership to disrupt it; but the technology is there and so is a significant prize. Better health, reduced burden of disease and improved economic outcomes. For countries who want to be at the forefront of the biotech revolution, this is a good place to begin.