Trends for 2019: from global studies to digital therapeutics

The most technically advanced life sciences businesses know that in today’s world, digital innovation and platform hyper-connectivity are no longer a luxury. Technological innovations in clinical trials are increasingly necessary for enabling drug development.

Life sciences as an industry has an enormous opportunity to improve efficiency and cut costs, whilst extending the scope of its research and improving patient and clinical experiences. This is happening as industry leaders leverage the latest digital trends such as data science, artificial intelligence (AI), risk-based monitoring and analytics and machine learning to enhance, streamline and de-risk the drug development process.

Technology is catapulting clinical trials into a 'new era' as technology breakthroughs bring new opportunities to an industry that has traditionally experienced certain constraints when it comes to innovation given the tough but necessary regulatory boundaries. New platforms are improving the efficiency and productivity of clinical trials, delivering novel outcomes, increased patient engagement, and reduced patient burden.

So, what does Medidata think will be the growing trends in the world of life sciences, pharma and healthcare for 2019?

Patient scarcity, a move towards more personalised and value-based medicine, an increased focus on rare diseases, as well as rising operating costs are all driving the move towards the globalisation of clinical trials. Moving beyond the US, UK and other developed markets, we expect to see clinical research organisations and pharma companies look to other regions across the globe for their trials with the expectation that they will be able to benefit from a wider source of potential patients, lower operating costs and ultimately accelerate their treatments to market.

Almost half of clinical trials currently take place outside of the US, as emerging countries heavily invest in healthcare and life sciences infrastructure. Testing and approval is now also set on a global path, which serves both drug developers and diverse patient populations.

According to industry analysts’ forecasts for the global market, developed countries are projected to account for about 66.8% of trials by 2020, down from 76% today; whereas the emerging countries combined are projected to account for 25.2%, up from 15.7%.

The increasing trend toward conducting clinical trials outside the US is an important consideration in improving their efficiency. The number of patients enrolled in trials is decreasing in the US and increasing abroad.

The applicability of foreign trials results depends on the disease being studied and the state of current clinical practice in that area, but, overall, many agree that globalisation is a positive trend, as if a large trial requires enrolling thousands of patients, for example, selecting trial sites outside of the US can result in hundreds of millions of dollars in savings as well as far more rapid patient sourcing.

Clinical research organisations are continuing to see the importance of reducing patient burden during trials, as well as wanting to make trials and treatments accessible to as many patients as possible. As a result, virtual trials that allow patients to record data remotely, often from the comfort of their own homes, will increase in number.

This will be facilitated by the advancement of new technologies, such as wearable monitoring devices, and the wider use of smartphones to record and transmit patient data remotely, in real time, as well as more sophisticated anomaly and compliance tracking software to ensure the reliability of this data.

For children, being able to take part in trials from their own home becomes particularly beneficial, as it allows them to feel more comfortable during what can be a challenging and often scary time.

With built-in location tracking systems, the technology to run medical apps and the ability to empower those who live great distances from their nearest hospital, the smartphone is perfectly positioned to accelerate the advancement of virtual trials.

Additionally, the way virtual trial data is being recorded and transmitted has been proven to be reliable and clinically meaningful, making it a very viable option for pharmaceutical industry researchers.

As improving the patient experience increasingly becomes a strategic goal for life sciences businesses, it will be necessary for certain individuals take responsibility and a leading role in ensuring this mindset is driven across the board.

Improving patient experience is no longer just “nice to do”; organisations simply won’t survive in the current market if they don’t make it a strategic priority. The increasing need for patient satisfaction is creating a related need for new leadership roles, as senior executives realise the need to "operationalise" the patient experience mission. An exceptional patient experience has to offer safe care, a good experience, transparency, patient understanding, efficient payment and more, and life sciences organisations won’t underestimate their role in delivering this.

The chief patient experience officer is a role likely to become more prominent in 2019. Perhaps a continuation of the corporate journey from chief digital officer, this new role is seen as someone who is responsible for overseeing all the different aspects of a trial; from protocol design, selecting the patients, how to operate the trial and how patients are followed up with, to minimise patient drop-out and ensure the reliability and validity of trials.

The value of diversity has become almost a cliché in the world, but the fact remains that representation of minorities and individuals with disability in many areas of the life sciences industry still lags the representation of these groups in the general population.

Diversity is becoming critical to the success and ultimately, the quality of any organisation, and diversity in life sciences is key to innovation in an economy that increasingly demands it. For the life sciences industry globally to continue its success, diversity and inclusion cannot be just another initiative. It must be the backbone of company policy from the top down and reflected in recruitment, retention and promotion strategies.

This is particularly important when considering patient diversity; recruiting a range of patients into a trial will require more diverse representatives from life sciences to help build trust and communications into those communities.

2019 and beyond will see a related drive towards encouraging those from minority groups to take part in clinical trials.

Part of the challenge is that, in developed markets, often these minority groups might be found in low income areas where clinicians lack the resources to run the kind of patient engagement programmes needed to bring new communities into the trial process. Where there isn’t a history of participation in a community, it takes significantly more resources to educate people on the benefits, risks, protocols and processes of a trial.

The benefits of having a more diverse trial are not only an increased patient pool size, but as we start to explore rarer diseases, we understand that they in fact only affect a small proportion of the population, a proportion that frequently aren’t middle-class Caucasians.

New technologies such as wearable devices, remote monitoring, and virtual clinical visits are already helping to fulfil the goal of making clinical trials more patient-focused. Social media is also offering increased opportunities for patient engagement.

AI has already established a small but growing presence in the life sciences industry, starting with drug discovery and development and now in emerging applications across the product life cycle. While the life sciences industry is full of data-rich processes, AI is only just beginning to be applied to gather, manage and intelligently use all the structured and unstructured data in the domain.

For 2019 and beyond, AI has the biggest potential to support the analysis of the vast amounts of patient data, helping clinicians and healthcare workers to spend more time with their patients, ultimately improving the human touch. The key applications for AI, machine learning and big data analytics in pharma will include, in the year ahead:

• Data curation and ingestion – streamlining the 700+ ways we record gender in clinical trials, for example
• Accelerating biomarker discovery – as machine learning groups genomic profiles at the patient level and helps us understand the causes of disease and adverse effects
• Outlier identification through big data analytics will accelerate approvals with regulatory bodies
• Synthetic control arms created through analytics will reduce the need for placebo arms in trials

Today, pharma companies are sitting on a huge pile of data. Due to the competitive operating environment and strict regulatory compliance standards, this data is hidden behind a firewall and is sealed from the rest of the world. In 2019 and beyond, big data analytics will continue to combine different data sources and bring to light new relationships and insights which might otherwise have been left unknown.

Last but by no means least, machine learning will increasingly become a great tool for pharma R&D, if the most advanced data infrastructures are in place, the right questions are asked, important goals are set, and enough data training is provided. If all these conditions are met, trained machine learning models will exponentially speed up the R&D process.

Digital therapeutics are already emerging as a treatment option for certain mental health diseases, including alcohol addiction, via everything from digital therapists to the gamification of addiction management. As the life sciences industry continues to exploit the potential of new technologies, digital therapeutics will become increasingly more integrated into traditional drug therapies.

For many chronic conditions the drug therapy is centred on disease management, which requires real-time monitoring and use of therapies. Connected monitors for factors such as blood sugar, for example, could support with a more automated process for insulin delivery, reducing the risk of hypo or hyper-glycemia incidents and reducing the need for as many home/or site visits, or emergency admissions. We expect to see more innovations in this category in the year ahead.