Data Science Partnership

Through our collaboration with ConcertAI, a market leader for RWD and enterprise AI technology solutions for precision oncology, we have access to ConcertAI use-case engineered RWD products and enable their use across key disease areas of the Janssen Oncology portfolio. Together, these data sets provide an integrated and holistic view of the patient journey with greater clinical depth to support translational sciences, clinical study design and RWD applications for regulatory submissions.

Through our collaboration with HealthVerity, we are accessing their Identity, Privacy, Governance and Exchange (IPGE) platform, the largest linked real-world data (RWD) ecosystem in the U.S. This platform enables organizations to connect and directly access one of the largest de-identified and privacy-compliant linked real-world datasets of 330 million U.S. patients across a broad network of data sources, including medical and pharmacy claims, electronic health records (EHR), labs and consumer data.

We have collaborated on more than 50 projects with nference, a leading biomedical AI startup, since 2018, for pre-clinical target identification, lifecycle management for late-stage assets, and real-world evidence. Janssen and nference have recently expanded projects to the clinical domain. Projects have included leveraging patient data to develop ECG-based algorithms for early detection of pulmonary hypertension and characterizing clinical care in patients converting from intravenous to subcutaneous medicine for multiple myeloma.

We are collaborating with Tempus, a leader in AI and precision medicine, to develop a predictive machine learning (ML)-based model to improve enrollment in biomarker-driven clinical trials in the oncology portfolio. Together, we are using large multimodal datasets in oncology to build and deploy AI-enabled diagnostics that rapidly accelerate the drug development process, increasing probability of success and reducing the overall cost.

As part of ongoing work to build better medicines for patients, we have entered into two separate agreements with Datavant to link RWD and clinical data sources. Under the first agreement, we are integrating disparate data sets to create rich, longitudinal real-world and clinical datasets to better understand both therapeutics and the holistic patient journey. In the second agreement, Janssen is offering guidance and insights to Datavant’s strategy in relation to new product and service offerings, including efforts to link clinical trial data to real-world evidence to enhance clinical trial execution.

Our collaboration with Iterative Scopes has the potential to help speed study recruitment and enhance our understanding of inflammatory bowel disease (IBD) overall. Iterative Scopes uses AI and computer vision to assess endoscopy recordings, and our partnership enables us to accelerate the development of therapeutics that have the potential to transform patient lives.

In early 2021, we co-led a Series C investment in Paige AI, a global leader in digital diagnostics focused on providing AI tools that will enable faster and more accurate diagnosis and patient treatment decisions to be made. This investment expands on our development of AI-based capabilities both within and outside of oncology and the delivery of these capabilities to laboratories and clinicians globally.

Through our collaboration with VisualDx, a web-based clinical decision support (CDS) company, we can reduce racial and other forms of bias in the clinical decision-making process. Using a new VisualDx application programming interface (API), we can bring CDS into applications that enhance diagnostic accuracy and improve health outcomes, particularly for traditionally marginalized patient populations.

In 2020, Johnson & Johnson completed a Series B1 investment in Aetion, a woman-led healthcare technology company specializing in the analysis of RWD to enable the next generation of decision-ready evidence for regulatory, policy and pricing decisions. The Aetion Evidence Platform® is scientifically validated software for performing regulatory-grade analytics at scale and was selected by the U.S. Food and Drug Administration (FDA) to help establish novel approaches to drug approval and safety processes, including to inform the agency’s response to the COVID-19 pandemic. Our team uses Aetion's technology and services to inform critical decisions and help guide product development.

By partnering with Domino Data Lab and NVIDIA, we accelerated the speed of deep learning models, in some cases as much as 10 times faster, to diagnose and characterize cancer cells through whole-slide image analysis more quickly and accurately. Based on early results, it’s anticipated that one model will generate a 4X increase in the number of patients who can be screened as positive for eligibility in clinical trials.

The Digital Medicine Society (DiMe) partnered with our team, AbbVie, Novartis, Pfizer and UCB to make nocturnal scratch an endpoint for atopic dermatitis. Atopic dermatitis, also known as eczema, can lead to nighttime itches and scratching, which impacts the quality of a patient's sleep. Recent studies have outlined wearable sensors’ role in helping to track and monitor the condition digitally. This initiative is a way to help reduce time and cost in research and development of new therapies.

We partnered with the Abdul Latif Jameel Clinic (Jameel Clinic) for Machine Learning in Health at the Massachusetts Institute of Technology (MIT) for the development and application of artificial intelligence and machine learning capabilities to advance drug discovery and development. Specifically, this would span the diagnosis of disease, development of treatments, prediction of treatment response, development of novel biomarkers, clinical trial optimization and medical imaging, among other projects.

Janssen R&D is a founding industry member of Our Future Health, which will collect information from up to 5 million adult volunteers across the UK, to create one of the most detailed pictures we’ve ever had of people’s health. Researchers will be able to use this information to identify new ways to prevent, detect and treat disease, ultimately bringing us one step closer to our goal of changing the trajectory of healthcare.