Gunjan Aggarwal has been appointed Head of Data & Analytics at Averitas Pharma, the U.S. subsidiary of Grünenthal GmbH, announced in a LinkedIn post.
Aggarwal has held senior roles in consulting and in-house analytics functions. At Novartis, she was Executive Director of Data Capabilities & Marketing Data Solutions, responsible for commercial data platforms and marketing analytics frameworks. Her earlier career included work in predictive modeling, patient segmentation, and digital health strategy. She has also published and presented on methods to integrate data into decision-making processes, particularly in commercial operations and healthcare marketing analytics.
Data and Analytics in Pain Management
Averitas Pharma was established in the United States in 2018 following its acquisition by Grünenthal, a German pharmaceutical company with a long-standing focus on pain research. The company is responsible for the U.S. commercialization of QUTENZA®, an 8% capsaicin topical patch indicated for neuropathic pain conditions, including postherpetic neuralgia and diabetic peripheral neuropathy. The treatment is part of Grünenthal’s broader portfolio strategy to expand non-opioid options for chronic pain.
In addition to its current indications, Averitas has overseen late-stage clinical development of QUTENZA® for other neuropathic pain settings. Earlier this year, the company completed patient recruitment for a Phase III trial assessing the treatment in post-surgical neuropathic pain. As in many therapeutic areas, advancing such programs requires not only clinical trial data but also real-world evidence and health economics analysis. These inputs help establish the value of therapies in discussions with regulators, payers, and providers.
Analytics plays a central role in connecting trial outcomes with broader measures of patient benefit. By bringing together clinical data, electronic health records, insurance claims, and patient-reported outcomes, companies are able to build a fuller evidence base. In fields like pain management, where variability in patient response is high, these datasets are critical for both regulatory submissions and post-market evaluation.
Grünenthal is also leveraging artificial intelligence and machine learning to enhance pain management strategies. The company uses AI-driven analytics to pinpoint cells responsible for chronic pain, focusing on targeted interventions and improving treatment precision. Additionally, Grünenthal is collaborating with RWTH Aachen University Hospital on the Bio²Treat project, which integrates biometric and biological data from multiple sources, including smart devices, to develop innovative approaches for neuropathic pain. This comprehensive, AI-enabled approach helps guide clinical development and evidence generation, linking patient outcomes to regulatory and commercial priorities .
Building Evidence for Non-Opioid Therapies
For Averitas, establishing a dedicated leadership role in data and analytics comes at a time when Grünenthal is investing heavily in non-opioid pain solutions. Qutenza® is already approved for certain neuropathic pain conditions, and the company has pursued additional trials to expand its use in post-surgical pain. With these initiatives, the demand for real-world evidence has become more pronounced.
Unlike large pharmaceutical corporations with broad internal infrastructures, smaller organizations such as Averitas must integrate data functions across clinical, regulatory, and commercial domains. This creates both challenges and opportunities. A leaner structure allows for faster alignment, but it also requires leadership that can ensure consistency and credibility across different stakeholders.
Regulators and payers are now placing greater weight on information that goes beyond traditional clinical trial outcomes. Cost-effectiveness analyses, long-term patient outcomes, and real-world usage patterns are increasingly part of the evidence packages submitted in support of reimbursement and approval. Building systems to capture and analyze these data streams has become an essential requirement for companies developing chronic pain therapies.
In this context, Aggarwal’s role is expected to focus on unifying disparate data flows into frameworks that can withstand external scrutiny while also guiding internal decision-making. Her background in enterprise-scale data strategy suggests a focus on integrating evidence that connects patient outcomes with regulatory and commercial priorities.
