Strength in Numbers: How Data Science is Unlocking Innovation, and Transforming the Way We Prevent, Treat and Cure Disease
When most people hear the term 'data science,' they probably think of people sitting at their laptops feverishly crunching numbers using fancy formulas with massive spreadsheets and data visualizations. And, in fairness, that is part of the average day in the life of a data scientist.
But the real magic is in what we're able to do with those numbers. Thanks to tremendous advancements in data science, including in areas like machine learning, artificial intelligence (AI), real-world evidence, digital health and computing power, our ability to collect, analyze and understand data to deliver better insights and outcomes has become more sophisticated and impactful than ever.
Data science is changing the game across all industries – from digitally-native companies like rideshare apps to the likes of financial services companies, and increasingly, in the healthcare space. In recent years, the use of and investment in data science within healthcare has grown exponentially. The biopharmaceutical industry is uniquely positioned to lead the way in data science, given our deep understanding of diseases, regulatory systems, data privacy and – most critically of all – people with serious illnesses.
In pharmaceutical research and development (R&D), the potential – from drug discovery through development and beyond – is immense. Data science is generating insights to help us better understand and define the diseases we're tackling. It is helping us more effectively determine which compounds in our libraries show the most promise and assess their safety profiles, enabling us to bring the best ones into clinical development. It is helping us design and execute better and more efficient clinical trials. And it is helping us determine which medicines are best suited for which patients and enable earlier detection and treatment of disease, leading in general to much better outcomes for those with progressive diseases.
So, how does this impact materialize in real life?
At the Janssen Pharmaceutical Companies of Johnson & Johnson, we're using machine learning to accelerate the development of a novel vaccine candidate for E. coli infections – which are becoming increasingly resistant to common antibiotics. We're using AI to identify patients likely to have rare, difficult-to-detect diseases, like pulmonary arterial hypertension (PAH), based on echocardiograms – tests routinely performed early in the patient journey. AI helps us analyze histopathology slide images from people with bladder cancer to detect mutations that may make them more likely to respond to new medicines in clinical development and facilitate recruitment into clinical trials for potentially lifesaving therapies. And we've developed an AI-enabled platform that will enable us to leverage real-world data (RWD), together with a randomized controlled trial, to advance the clinical development of an adjunctive treatment for major depressive disorder with insomnia symptoms.
Data science has also played a critical role in the development of COVID-19 vaccines. Early in the pandemic, we were able to gather accurate and comprehensive data sets and use advanced analytics to understand how COVID-19 was spreading worldwide, where it would likely peak next and where the potential for viral mutations would be highest. These predictions proved remarkably accurate and enabled us to place clinical trial sites in 'hot spots' where participants would be more likely to have exposure to COVID-19 – meaning we could more quickly determine the efficacy of vaccines. This significantly accelerated data collection efforts and shortened the vaccine development timeline, all while generating efficacy data across multiple COVID-19 variants of interest.
Beyond this, data science has helped us quickly analyze real-world evidence for COVID-19 vaccines, enabling timely, data-driven public health decision-making during the pandemic, including the FDA's Emergency Use Authorization of the Johnson & Johnson booster. Most recently, data science has been used to develop large, rigorous real-world studies on the durability of COVID-19 vaccines in the U.S. – results that are critical for informing real-time clinical and policy decisions.
At Janssen R&D, we have more than 100 data science projects spanning our drug development portfolio, led by our innovators who are, or are quickly trained to become, 'bilingual' in both medical science and data science. Beyond pharmaceutical R&D, Johnson & Johnson is leveraging data science to advance both R&D and access efforts across our entire global organization – including in our medical device and consumer portfolios.
Our company has a bold ambition to change the trajectory of healthcare and a clear vision of the transformational innovation – and the impact – that we want to deliver for patients and communities. We are advancing progress through our own efforts, but also in partnership with other leaders in this space – including data science and digital health start-ups, entrepreneurs, leading technology players and academic collaborators. Our ultimate goal is to bring the best data science talent together to tackle the world's toughest health challenges.
How – and how quickly – we can collectively unlock the power of data science to continue transforming healthcare and delivering for patients has the potential to be one of the most consequential and defining opportunities of our time. So, the question is: how bold and disruptive are we willing to be?
Our take at Janssen? It's time to go big in data science. Learn more about how we're leveraging data science to change the trajectory of human health.
March 9, 2022