Life Image Represents the Only Company Providing Large, Heterogeneous, De-Identified and Linkable Imaging Data Sets that Integrate to Longitudinal Clinical Outcomes
NEWTON, Mass.–(BUSINESS WIRE)–Life Image, the world’s largest medical evidence network for clinical and imaging data, today announced the launch of its new Real World Imaging (RWI™) offering to respond to researcher needs for maturing insights and accelerating drug development decisions. With its digital platform that is powered by industry-leading interoperability standards, Life Image specializes in ‘living’ or evolving data sets of novel imaging that’s linkable to other clinical information. Life Image’s RWI™ will also be used to train artificial intelligence (AI) models demanding deeper accuracy and sensitivity across diverse data sets.
Life Image’s RWI™ ‘living’ data sets represent hundreds of thousands of patients, tens of millions of images and hundreds of thousands of associated reports and studies categorized by more than 25 anatomical parts including head, lung, breast, chest and more. This heterogeneous and continuously growing data represents an expanding variety of demographics, temporal data, linked longitudinal records and virtually every global manufacturer across all modalities.
Imaging data, especially for Real World Evidence (RWE), has historically been difficult, if not impossible, to access, retrieve, view, de-identify and normalize at-scale, even though it provides clinically material insights for a growing number of therapies. Since 2008, Life Image has been the market leader using common interoperability standards to solve the many technical, procedural and structural barriers that have effectively segregated imaging data into unconnected data silos.
“The time has finally arrived that imaging can be utilized as an effective part of the RWE process by eliminating manual processing and compliance errors, providing access to large heterogeneous data sets, and doing so at the speed of the internet,” said Matthew A. Michela, CEO and President, Life Image. “With RWI™, Life Image is expanding its focus on helping researchers and innovators capture the full potential of RWE by providing ‘living’ data sets that grow and become even more meaningful over time. This makes it possible to answer questions as they arise as opposed to answering one question in a limited manner retrospectively, such as carefully controlled clinical trials. The potential benefits are innumerable for patients, payers, population health initiatives, artificial intelligence, and drug and device development.”
RWE is now a global mandate for drug development and pharmacovigilance from the Food and Drug Administration (FDA) in the U.S. as well as regulatory agencies in Europe. RWE supports the process of establishing better arguments across the drug development lifecycle by using clinical, operational, administrative, social and patient-reported outcome information gathered from sources that capture this data at the time of the patient care transaction, as opposed to historical methods of data collection from a controlled clinical trial setting.
Common sources of Real World Data (RWD) such as labs, pharmacy, EHR and medical claims data unfortunately have limited ability to meaningfully capture a patient’s clinical circumstances. Biases exist in these sources of data, especially in oncology and cardiology, due to the type of data being collected (e.g. claims or billing codes) or due to limited access to sources of this data (reinforcing homogeneity). These challenges often result in inaccurate representations of the patient’s or population’s actual condition or the impact of a treatment. Enhancing this type of data with imaging and unstructured data sets elevates the ability to validate the effectiveness of research and statistical models, accelerating the ability to improve protocols and patient outcomes.
In addition to RWI™ data, Life Image also provides value-added services to researchers and innovators including end-to-end management for de-identification, data curation and linking across medical claims, EHR, genetics and other phenotypical commercial and public data assets.
