Artificial Intelligence (AI) technologies are being developed at lightning speed, but they need a fuel source before they can offer insight or value. In the healthcare industry, the fuel is patient medical data. Where other industries may leverage data with relative immunity, the healthcare industry is governed by strict regulatory standards like HIPAA. Personally identifiable information (PII) cannot be shared without consent, making anonymized or sanitized data one of the only reliable, real-world sources of medical data and evidence for pharmaceutical organizations.

Real-World Data (RWD) and Real-World Evidence (RWE) are integral in proving the legitimacy of results from clinical studies.^[1] Furthermore, RWD and RWE hold huge potential in the context of drug development—delivering insight around disease risk, identification of optimal patient treatment pathways, monitoring adherence to treatment plans, and understanding patient behavior.^[2]

The healthcare industry generated over 2,314 exabytes of new data in 2020.^[3] This data consists of both structured and unstructured data which often resides in IT siloes, making it difficult to extract insight across the entire healthcare continuum. Recent surveys within the biopharma industry have revealed that 80% of pharmaceutical companies plan to use, or are using, AI or Big Data to improve performance.^[4] Furthermore, 65% feel that they do not have sufficient RWD capabilities to generate the RWE needed. This evidence is extremely valuable^[5]in the development of AI innovations, delivering improvements in quality of care, efficiency of care, and accelerated time to market within pharmaceutical organizations.

Emerging digital technologies offer great opportunities for biopharma

A review of these statistics raises important questions. Emerging digital technologies offer great opportunities for biopharma, transforming the identification of patient cohorts, improving operating models, and integrating AI into workflows that could improve patient care. As the pharmaceutical industry accelerates its adoption of these technologies, organizations like GE Healthcare are well-positioned to assist healthcare providers in adopting AI strategies to get more done, at pace, without sacrificing on quality. Additionally, the pharmaceutical industry can leverage AI when conducting clinical studies. Traditionally, clinical trials have had to rely on one-off clinical studies, which are then validated with statistics averaged across the target patient cohort. These studies do not accurately depict the diversity of patient populations, and, as a result, struggle to deliver compelling RWE. With RWD services through GE Healthcare’s Edison^TM Digital Pharma Solutions, you can move away from “the average” approach to “the individual” approach by including a more diverse range of medical cases in your studies. This increases the breadth and depth of your reference datasets, extracting more insight with greater accuracy and a wider scope.

Overcoming the existing technical challenges in biopharma

With access to the right patient data, the next hurdle is overcoming the existing technical challenges in biopharma. Included in the primary challenges is a lack of data integration. AI technologies can ingest data from both structured and unstructured data sources. This data can be used to train AI / ML models, with ETL pipelines ensuring the data is transmitted efficiently and effectively.

Edison^TM Digital Pharma Solutions can help you access large quantities of quality-assured Real-World Data. These datasets are provided in highly compatible formats and assist with identifying more targeted patient cohorts. Our solutions can help you advance your AI strategy by leveraging innovations that:

Identify “hot-spots” of patient cohorts with Real World Data and sources that are HIPAA and GDPR compliant
Develop pharmaceutical algorithms with the Edison™ Ecosystem
Leverage the Edison™ HealthLink to deploy your solution, where you need it in the care continuum
Provide compliant digital image management
Access imaging data quickly through existing healthcare PACS and VNA infrastructure

We are a single trusted source for vendor agnostic imaging data and AI services, driving efficiency through AI innovation.

[1] https://link.springer.com/article/10.1007/s41649-019-00095-1

[2] https://md.catapult.org.uk/application-of-ai-and-data-science-to-extract-value-from-real-world-data-rwd/

[3] https://www.statista.com/statistics/1037970/global-healthcare-data-volume/

[4] ICONplc.com/digital

[5] McKinsey/GE Healthcare study, September 2020

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