HMNC Brain Health is a clinical-stage biopharmaceutical company revolutionising Precision Psychiatry through its AI-powered platform, focusing on addressing Treatment-Resistant Depression (TRD) and Major Depressive Disorder (MDD).
Their approach integrates genomics, psychiatry, and analytics to develop novel, targeted treatments for mental health disorders with increased treatment efficacy. Currently, HMNC is running three programmes: Ketabon, Nelivabon, and Cortibon.
In 2023, HMNC reached out to IMed Consultancy for support with preparing the necessary documentation for the Cortibon clinical trials starting in the United Kingdom and ensuring compliance with UK regulatory requirements. IMed came highly recommended by their EU consultancy, revealing their good standing among peers. In addition to this, IMed Consultancy’s expertise in AI-based devices was an important benefit. IMed’s team has, in fact, extensive experience in navigating the complexities of innovative and multi-faceted devices – spanning software, AI, and novel technologies – and in bringing those lifesaving and life-enhancing products to market. Not an easy task, as regulatory bodies are currently grappling with the complexities of evaluating and approving AI-based medical devices, and regulations are rapidly evolving as a consequence.
The Cortibon programme represents an effort by HMNC to address a critical unmet need in the treatment of depression. Through precision psychiatry, HMNC tailors treatments to individual patients, enhancing efficacy. By employing AI-based genetic selection tools, the programme accurately identifies patients with a dysregulated stress axis, making them ideal candidates for targeted therapies. Historically, pinpointing patients whose depression results from an altered stress response – affecting about one-third of those with depression – has been challenging. The Cortibon programme uniquely addresses this by integrating a novel therapeutic approach with a precision diagnostic tool, offering a promising solution to this critical challenge.
Over the course of a year, IMed supported HMNC in preparing the necessary documentation for clinical trial submissions. IMed provided HMNC with clear advice on the documentation required, helping them to meet all necessary standards before the trial’s initiation. Their ability to quickly integrate into HMNC’s operations allowed them to respond efficiently to any challenges, enabling the team to stay on track for the planned start of the trials.
“IMed’s expertise and fast response will be critical in getting our Cortibon programme’s clinical trial off the ground. Their pragmatic approach and deep understanding of the regulatory process, as well as their attention to detail, insightfulness, and versatility, made them an invaluable partner in this journey. Not all regulatory consultants are able to tailor their work based on the maturity of the product, but IMed was clearly experienced in supporting innovation at different stages of development. It was a pleasure working with them!” confirms Annet Glas, Associate Director Clinical Development, HMNC Brain Health.
IMed Consultancy’s focused support has enabled HMNC Brain Health to prepare for the successful initiation of the Cortibon clinical trials in the UK. With the necessary documentation in place and the trials ready to proceed, HMNC is on track to introduce a new class of treatment for depression. Once the trials are successfully completed, the potential exists for expanding the Cortibon programme into additional markets beyond the UK, where HMNC plans to rely on IMed’s expertise whenever possible.
“Working with HMNC on the Cortibon programme has been an incredibly rewarding experience. Their innovation in precision psychiatry combined with our regulatory expertise created a smooth pathway for the trials. We’re excited to see this programme take off and make a real difference for patients,” concludes Jonathan Ripley, Managing Director, IMed Consultancy.
[1] IMed Consultancy, Digital Dilemmas: Regulatory challenges for Artificial Intelligence and Machine Learning in medical devices and digital health products
