Real-world evidence (RWE) is becoming increasingly important in driving pharmaceutical innovations, as it helps researchers to understand the settings in which a drug, medical device, or other treatment is applied, such as innovation, care patterns, and disease burden in populations.
Through the systematic analysis of real-world data (RWD), RWE can support clinical trial evidence, particularly in rare diseases where patient recruitment is difficult, because it generates information from different sources and different contexts. RWE is currently finding increasing acceptance in such areas as:
With the acquisition of Panalgo, Norstella took another big step forward in different ways that are already beginning to take shape. As a result, Norstella is better positioned to address the trend towards using RWE and RWD in health care decision-making.
Panalgo offers software, access to data, expert analytic services, and combinations of them for health care analytics. Its Instant Health Data (IHD) software platform seeks to eliminate complex programming, thus making both data analysis and the conversion of data into insights more streamlined.
IHD users can convert a wide range of data sources in its data model, including administrative claims, electronic health records (EHRs), and registry data, then iterate research questions. These sources range from database analyses to supplement cost-effectiveness or cost-utility models, to the real-world comparative effectiveness of different treatment options. Key features include:
The associated IHD Cloud extends the platform into the cloud via Amazon Web Services. Erik Maul, senior director of RWE partnerships at Panalgo, describes it as a single pane of glass solution, centralizing data, and technology to drive meaningful RWE in a dedicated environment customized to each client s needs.
IHD Cloud is designed to deal with some of the key challenges of RWE generation, such as:
The company, which was founded in 1996 as Boston Health Economics, was renamed Panalgo in 2022 by combining pan, the Greek word for all , with algo, short for algorithms. Since then, according to Dr. Meg Richards, executive director of strategic solutions and consulting services at Panalgo, it has greatly expanded its services.
“Now, instead of just a software-as-a-service (SaaS) analytics platform, we offer data on demand along with analytic and consulting support to clients to conduct all the analyses they wish, from something as simple as characterizing burden of disease to something as complicated as modeling a disease trajectory over time,” she says.
Panalgo’s analytics services range from evidence for health economics and outcomes research (HEOR), RWE, epidemiology, regulatory, and market access needs, handling everything from study design and feasibility testing to protocol writing, study management, interpretation, reporting, and publication.
IHD has been used to expedite responses to all the major regulatory agencies, generating regulatory-grade evidence, such as external control arms, RWE for label expansion, and post-marketing safety surveillance. Panalgo states that the platform is 85% faster than traditional programming methods in these applications.
In addition, the company has a service component. Clients can hire a highly qualified analyst on a retainer basis to embed in their organization for project work or to carry out rapid project work to provide a quick answer to a given question.
“It’s like a four-legged stool now: the analytics platform, data on demand, embedded analysis support, and our consulting line,” Richards says. In August 2024, Panalgo hired Allison Petrilla to head this team, who can write protocols and clinical summary reports or help with research dissemination, such as abstracts for congresses and manuscripts.
Panalgo’s roots in HEOR mean that its client base is strongest among those who have successfully completed a Phase I trial, adds Panalgo’s research director Dr. Michael Munsell. “They’re already thinking about market access, but also about the cost for treatment and how it weighs against the outcomes in certain patient populations,” he says.
“This information is generally not collected in clinical trials but is necessary for payers to make informed coverage decisions. This puts us in the RWE arena, meaning our clients are typically using data that are not collected for a specific hypothesis.”
Clients rely on Panalgo’s capabilities for generating cost estimates, safety signals, and other findings that are challenging and expensive to collect prospectively. “If a client has a full study that they want to do from start to finish, we can work alongside them for the entire process, or just support portions of it. Whether they need access to data, support analyzing it, or publishing their findings, we’re there with the full spectrum of capabilities,” Munsell says.
“Some clients, usually small and mid-sized biopharmas, have neither data nor any analytics platform, and they need Panalgo to advise them on what data to interrogate. We have data available on demand that we can make available quickly and easily,” says Richards.
“We also have some partnerships where we can’t make the data available on demand, but we can streamline access to it. We can offer clients both the data source and a way to interrogate those data that is rapid, secure, and transparent, and has been validated many times over.”
“Prior to starting a clinical trial design, certain companies may want to get a general understanding of how many patients have this specific disease, their characteristics, and outcomes on current treatments. This information could help inform trial design,” Munsell adds. The data are also useful for insurers in calculating the true cost of a disease.
With this documentation, an audit trail is generated, which supports regulatory submissions and dissemination. This, according to Richards, is becoming more important as authorities increasingly require complete documentation of the data source and the methods used in analysis, and the platform itself.
“Panalgo’s platform also makes it possible to structure data in a way that streamlines the interrogation of those data and pursuant evidence generation. You can swap in and out different data sources because they look the same within the platform. It’s like a web interface that does all the dragging, dropping, and clicking without programming. The same person who designed the study can also do it without knowing how to program,” says Munsell.
The most obvious synergies Panalgo has within the Norstella Group are with MMIT, because of the overlap between HEOR and market access. Using IHD, claims, EHR, and lab data can be bridged to MMIT s formulary data, enabling users to characterize the patient journey and access to treatments more fully.
Many members of the team are already supporting work on data analysis of bridged formulary data and claims in order to characterize barriers to access. In one project, they are working with a large pharma company on biologics for ulcerative colitis, covering such issues as formulary strategies, utilization, management, prior authorization, and step therapy. Another involves the very hot topic of glucagon-like peptide (GLP)-1 agonists for Type 2 diabetes and obesity.
Nonetheless, Richards and Munsell can also see opportunities for Panalgo to work with Citeline and Evaluate in the future. For instance, it is possible for aspects of clinical trial planning, such as locating patients and sites and/or assisting with diversity and inclusion in recruitment, to be informed by analyses in IHD.
“Panalgo can easily do this with Citeline’s rich data sources around product development. I think, in time, because RWE spans across the whole drug development pipeline, there’s potential with each of [the Norstella companies],” Munsell adds.
Panalgo has formed various partnerships with other companies who can enhance its offerings. These include data vendors like TriNetX and COTA. The most recent, signed in June 2024, is with Atropos, a generative artificial intelligence (genAI) company.
Using the Atropos system could make it possible to ask a question about clinical care and have an answer within 24 hours. Atropos also has its own data, which will be made available in IHD, while Panalgo is going to make their data available to Atropos. The Atropos offering will also be complementary to Panalgo’s data science module, which employs ML and AI.
Another new service of note is NorstellaLinQ, which is described as the first and only fully integrated data asset combining RWD and Norstella s proprietary intelligence. It will combine RWD, including open and closed claims, lab results, and EHRs, with Norstella s proprietary forecasting, clinical, regulatory, payer, and commercial intelligence data. Clinical operations, clinical trials, brand, HEOR and epidemiology, commercial, and market access teams are all potential users.
Until now, Munsell notes, much of the available data have not been connected and doing so has been laborious. For example, insurance claims will yield information about diabetes patients adherence to a treatment but will not say anything about how their hemoglobin A1C levels are behaving in your relation to that.
“For a long time, we’ve had the ability to link some clinical data with the administrative claims data to give you a granular view of a smaller sample. That’s been helpful for outcomes research,” he says.
“NorstellaLinQ is taking that even further where we have all these data sets and you’re not going to have a patient that is necessarily matched to all of them. But for specific questions, you have more flexibility and fewer assumptions about the patient. It’s broadening the view of the patient you’re trying to represent, and you can choose which linkage and what datasets are best for your given research question.”
Research Director | Panalgo
Executive Director of Strategic Solutions and Consulting Services | Panalgo
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