3 things that will change medicine in 2018

Digital technologies and big data tools are changing every aspect of how companies operate, across myriad industries. Healthcare is no exception. We are on the verge of a digital revolution across every aspect of the sector, from the lab bench to the patient’s bedside.

This presents a significant opportunity to drive the next wave of medical innovation. We can meet our patients in the digital world, to provide them with new, improved and more holistic solutions that not only lead to better outcomes, but help reduce the burden of illness.

Digital solutions can democratize the research process for new medicines by helping us reach previously underserved and understudied groups of people. Digital technology will also improve how we capture and analyze data. One of the most valuable assets we have at our fingertips, data gives us a deeper understanding of patient needs. Ultimately, we can bring new and better medicines to patients who need them.

Three emerging technologies will drive the next wave of urgently-needed medical innovation:

1. Internet of things. Data from smart devices can give us critical real-world context and deepen our understanding beyond conventional R&D approaches. For example, wearables and sensors can capture robust, real-time data about patients’ quality of life, enabling us to understand disease progression and the impact of our treatments better.

At Novartis, we are already using sensor technologies to quantify disease progression in multiple sclerosis patients for clinical trial research. Through the ASSESS MS system, we can track measures such as walking speed, balance and movement of patients. Current methods for measuring physical disability in MS can produce inconsistent results, and it can be hard to track small changes in disability. By training a computer program to evaluate people with MS like an expert neurologist, ASSESS MS aims to provide consistent and reliable data that can potentially better support clinical decisions, improve the efficiency of clinical trials and make expert neurological assessments available all over the world.

2. AI and machine learning. These technologies are revolutionizing the way we can interrogate data, leading to a faster clinical trials process. They enable us to understand data sets more deeply, so that we can better identify new insights from our decades of clinical trial experience. All this data is complementary to information collected by conventional R&D approaches. It can help drug makers develop new medicines more quickly, smartly and cheaply than traditional models.

For example, in partnership with Quantum Black, Novartis developed a program called Nerve Live. It combines data on clinical trial operations from multiple internal systems, applying machine learning and advanced analytics to predict and monitor trial enrolment, trial cost and trial quality. This enables us to increase automation, maximize efficiency and make data-driven decisions. Our work in this area has already delivered a 10-15% reduction in patient enrolment times in pilot trials.

3. Emerging data platforms. Unprecedented computing power and advances in data management systems allow us to store, organize and optimize data for analysis and insight generation. By integrating our vast resources from current, future and historic clinical trials into data lakes - virtual warehouses holding immense amounts of raw data in their native form - we can embrace emerging technologies and trends to drive deep insights.

We are also exploring tech companies’ powerful data processing capabilities to conduct Real Time Data Analysis on clinical trial datasets. These often run to petabytes worth of data and can take weeks to analyze using traditional methods. Quantum computing could allow large-scale processing of highly complex clinical and biological data. If applied to develop medicine design and target selection, this could accelerate our ability to do in silico research. Blockchain also holds great promise for the healthcare industry, in addressing current challenges like interoperability of data systems and data security.

Incorporating emerging technologies into everyday processes will be challenging. But it is clear that digital technologies and data science have incredible potential for medical innovation. We must blend the technology industry’s culture with the pharmaceutical industry’s expertise. A huge part of this involves encouraging the broader health-tech ecosystem, including start-ups and academic institutions, to collaborate.

We must work hard to inspire the next generation of talent to pursue this critical area. Everyone in the healthcare ecosystem should understand the full potential of digital health. The companies that will prove most successful in the future are those that see this transformation as an opportunity, rather than as an insurmountable challenge.

Let’s leverage the full power of digital and data to develop medicines for the people that need them the most.