Everyone wants real-world evidence, and they want answers quickly, so having the capability to turn data around
quickly is important.”
As the demands on real-world data teams continue to grow, with more data sources, more stakeholders, and more pressure to deliver trusted evidence faster, the tools supporting that work need to evolve just as quickly. We spoke with Chris Harvey, VP of RWD Product and Offering Management at Norstella, Panalgo’s parent company, to explore how IHD is meeting that moment, from cloud deployment and machine learning integration to smarter code list curation.
Q: How is IHD helping our clients generate better insights from complex healthcare data, and how does it stand out from our competitors?
A: Clients use IHD to accelerate and scale evidence generation by empowering both technical and non-technical users to work more efficiently with RWD. We know our clients need data they can trust, and to customize project designs to the bespoke needs of individual use cases, and IHD helps them do that.
Over the years, we added automated documentation and transparency features to IHD. This allows clients to consume insights-as-a-service from our experts, recognizing some teams just want the answers and to understand them but not build out the teams to do the work. And we added integrated programming and advanced modeling capabilities for teams that wanted to do more of their complex work in IHD.
As we began working with over 30 real-world data vendors in the industry, teams started coming to us with a different kind of question. Not just how do I use this data, but what data should I even be using and can we get data on demand from Panalgo? So we’ve enabled data vendors independent from us to use IHD to bring their data to customers faster, whether pre-loaded in IHD or available to their consulting teams. Last year we activated IHD in the cloud to deploy IHD in other environments rather than requiring the data to be sent to us.
And now, our focus is on continuing to meet our client asks, from validated phenotypes available on demand as code lists, enhancements to our AI agents, modernized and customizable dashboards and visualizations, and more ways to query data in its native format.
Q: Tell me more about client-hosted IHD Cloud. What advantages does this offer to pharma companies?
A: Some of our pharma clients are licensing more data sources than ever before and are investing heavily in internal cloud infrastructures to host and use that data. At some point it reaches an inflection point where efficiency becomes much higher if you can leverage our platform inside the same cloud ecosystem where your data already lives.
So we built IHD to be available in client-hosted clouds, where IHD is deployed into the client environment, control is given to your team in terms of data sources you bring in and access. Unlimited seats are granted across your organization, and there’s the ability to scale more data without additional cost. This became the true enterprise version of IHD.
At the same time, clients are increasingly working with data vendors where that data simply can’t leave its location. We can deploy our software inside those environments and make it accessible through a consistent web interface, regardless of where the data sits.
Q: What can our clients do to leverage machine learning to improve their project planning and execution?
A: IHD Model Studio helps them leverage machine learning by bringing advanced predictive models into healthcare-specific workflows. There are so many use cases, from identifying data-driven patient characteristics and stratification variables at the design stage, to discovering key drivers of treatment, progression, and cost outcomes. It also helps identify key patient profiles with unmet needs and identify hidden patient populations earlier. Importantly, IHD Model Studio is built specifically for healthcare data, a key advantage over general machine learning tools.
Q: For real-world data teams, selecting the right code lists can be a challenge. How does our partnership with Navidence solve that?
A: Every project starts with defining how patients get selected, and teams can spend weeks curating codes. While IHD provides great features to share and standardize codes, definitions can drift across studies and teams unless organizations are very intentional in how they standardize them. Our partnership with Navidence allows them to do that. It’s helping our clients minimize manual code curation, backing every definition with published references, and harmonizing definitions across studies and teams, which ultimately helps them define diseases and therapies consistently and accurately.
Contact us to find out how IHD can help you fuel a better understanding of the patient journey.