My Experience at University College London’s Great Ormond Street Institute of Child Health Developing a Rapid Gene Panel for Autoinflammation in a LIMS-less Environment.
Introduction
In this webinar titled “Development and Clinical Application of a Rapid Gene Panel for Autoinflammation,” I had the opportunity to share my insights and experiences regarding the challenges faced while developing diagnostic assays for autoinflammatory diseases. In this webinar and blog post, I provide a detailed account of my research at Great Ormond Street Hospital, highlighting how LIMS software could have significantly improved workflow efficiency.
My Background
My name is Dr. Dara McCreary, and I currently work as a business analyst at Sapio Sciences. However, in my past life, I held roles as a research fellow at University College London’s Great Ormond Street Institute of Child Health. My educational background includes an undergraduate degree in Cell Molecular Biology, a master’s degree in Regenerative Medicine, and a Ph.D. in Medical Science. At Great Ormond Street, I collaborated with a team of researchers and clinicians to develop assays for diagnosing patients with neuroinflammation within the neurology and rheumatology department.
Research Aims
One of the key focuses of our research was to develop a test tailored explicitly for urgent cases with potential life and limb-threatening implications. We aimed to diagnose patients with known genetic autoinflammatory diseases that could benefit from rapid diagnosis and the availability of possible treatment options. Initially, our research aimed to provide results within two weeks of the request, and we also aimed to ensure the transferability of the developed assays to other institutes or departments. However, we encountered several challenges during the project, particularly regarding communication, collaboration, and resource management.
Life in a LIMS-less Environment
We faced numerous difficulties without Laboratory Information Management System (LIMS) software: collaborating with team members became increasingly challenging, especially during the COVID-19 pandemic when limited lab access was allowed. Communication relied on sending pictures or screenshots of the machine runs over email or other digital platforms, often leading to delays in obtaining feedback and opinions from colleagues. Furthermore, issues surrounding stock and equipment availability, time management, and potential errors emerged as significant hurdles in our workflow.
The Rapid Autoinflammation Panel (RAP)
Our previous research focused on a neuroinflammation-targeted panel, which aimed to identify disease-causing mutations in children with neuroinflammatory disorders. While the panel showed promising diagnostic impact, the time it took to return results remained a concern. To address this, we developed a rapid autoinflammation panel (RAP) to provide results within 24 to 48 hours for patients with severe organ or life-threatening diseases. We strived to ensure that our approach could be easily transferred to other labs and departments, enabling timely treatment decisions.
From Rapid to Rocket Speed
The potential benefits of utilizing Sapio Sciences’ LIMS platform would have been tremendous. The software offered valuable features such as built-in collaboration and chat functions, notification systems, end-to-end reagent consumable management, and integration with genomic tools. These features would have significantly enhanced our workflow efficiency, reducing the need for multiple communication channels and simplifying data management. The web-based interface allowed 24/7 access to protocols, facilitating project planning and ensuring seamless coordination. Ultimately, implementing LIMS software would have saved time, reduced stress, and improved overall productivity and accuracy in our research endeavors.
Conclusion
There is a critical role for efficient laboratory management systems in expediting research progress and facilitating the delivery of life-saving treatments.
Adopting Sapio’s LIMS could have solved numerous issues that could have significantly enhanced our study. Potential advantages include improved collaboration among team members, real-time notifications for efficient communication, streamlined stock management, easy accessibility to results, reduced stress levels, time-saving capabilities, increased productivity, and minimized errors.
As we sit on the verge of an artificial intelligence revolution, maybe we’ll be aiming for “warp-speed” panels soon.
