A medical evidence network for clinical and imaging data, Life Image recently announced a strategic partnership with Graticule, a firm providing data subscriptions and advisory services.
The partnership brings together Life Image’s network includes more than 1,500 US hospitals, 150,000 providers and 58,000 global clinics, and Graticule’s advisory services and technology solutions.
To further discuss the partnership, its goals and next steps, Outsourcing-Pharma (OSP) caught up with Life Image CEO and President, Matthew Michela (MM), and Dan Housman (DH), the founder and CTO Graticule.
OSP: What historical challenges does the partnership look to address?
MM: For decades, biopharma has relied primarily upon structured data found in claims, pharmacy, lab and, more recently, EHR data to accomplish research goals. However, that data has clear elements of bias given that it was largely created to facilitate medical payment or authorization for payment rather than clinical decision-making by providers.
Even though these data types have limited clinical value, decades of standardization of claims systems, billing codes, lab systems, and pharmacy management platforms made this data available at scale.
Therefore, the industry’s reliance on these types of data has been extensive. It is also becoming clear that the results of analyses based on these data types are not adequate for research today as biopharma solutions become more complex, more precise, and targeted.
As the types of available data explode, the ability to include other types of data in research grows, and as computational power becomes more available, richer data and real world evidence (RWE) is seen as necessary to meaningfully demonstrate outcomes.
OSP: What will each company bring to the table?
DH: Both companies recognize the significant unmet need in health care to learn from data already being produced by patient care that is stored in imaging data sets. It is challenging to focus on two markets at the same time.
In the case of Real World Imaging, health systems need reliable data exchange and workflow around imaging while life sciences companies require data sets with sufficient scale and quality to answer key questions.
By working together, Life Image can focus on making a great point of care application and engage primarily with health systems, while Graticule can focus on making great real world data assets and engage primarily with life sciences companies as clients.
OSP: What is the goal?
MM: Clinical trials can last as long as seven years and cost up to $1.5bn, and a growing number of those activities reaches a successful conclusion but then requires extensive post-market evaluation and occasionally experiences recall.
One reason for requiring this continuous monitoring or the placement of additional restrictions on marketing is because the study data itself is suspected to have not been fully representative of the diversity or currency of the broader healthcare population.
Simply, despite the cost and duration of large trials, the risk is that the original study cohort produced a safe and effective result, but when released into the real world of diverse patients, the product acts differently.
Ultimately, our common goal is to help mature the industry’s use of advanced data to provide better study results and accelerate the development or label expansion of biopharma solutions, all while reducing the development cycle – which saves lives – and cost of R&D.
Given the complexities of life sciences, the industry needs more dynamic clinical data and access to therapeutic endpoints to understand disease progression and comparative effectiveness.
OSP: How will the companies work to achieve these goals?
DH: We share a vision that we can create a better patient experience by accelerating the creation of systems to unlock the value in imaging data.
We can achieve many goals by doing this including identifying new biomarkers, increasing the number of patients able to leverage experimental therapies through clinical trials, improving quality that leads to better patient outcomes, and faster identification of rare diseases.
A prototypical vision for the value of the business partnership is to allow a life sciences company to use machine learning across a large number of imaging studies and related de-identified medical records sourced through Life Image and curated by Graticule to find a novel way to classify the rare disease risk based on reading the patient's history.
Once it has been validated by a larger data set also sourced by Life Image and curated by Graticule the algorithm can be used to score large numbers of cases. The algorithm is then run on a large archive such as a PACS system or VNA to score patients who may have the rare disease.
Patients who are identified with high risk can be engaged the next time they interact with the health system because physicians will see an alert in their EHR or be notified by an administrator verbally that the patient has a high probability or risk for the disorder.
This encounter leads to a prospective test to confirm or rule out the diagnosis of the rare disease and then treatment by the available pharmacological treatments.