Using human-centered design to understand market feasibility and user needs for an early-stage clinical gut microbiome AI-based analysis platform

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"Microorganisms are invisible to the human eye, but they run our world. A well-balanced community of gut microorganisms is critical in the context of human health, and disturbances are often associated with disease. Metagenomic approaches allow the assessment of microbial communities by directly sequencing and analysing all species present in a sample.For these approaches to become a general practice in a clinical setting, it is critical for clinicians to be able to digest the large amount of data generated and translate it into actionable insights. By understanding important metagenomic outputs, clinicians can implement ways to bring the gut microbiotic population back to normal levels through drug treatments, probiotics, and changes in diet and lifestyle.Lifebit has created a fully functional and accurate backend pipeline which allows users to input their raw metagenomic sequencing data in order to determine 1) which microorganisms are present, 2) their levels and 3) their biological function. Our overall goal is to bring this pipeline to market, however, we need to further understand the context-specific needs of potential users.Since metagenomics analyses involve huge amounts of data that is useful in the clinical context, we need to understand how to enable clinicians without extensive computational training to manipulate and analyse the data. Therefore, an intuitive and understandable UI that meets their needs is a crucial component for the success of the product.This feasibility study will allow us to make informed choices about the design needed to make this pipeline useful to clinicians that are either using, or need to use, metagenomics analysis to advance their patients' health. Specifically, our key objectives for this study are to:* Understand the market for the pipeline,* Understand what users need in the context of clinical metagenomics, and* Identify how tailored design and front-end features could address user needs.To accomplish these key objectives, we will use human-centered design (HCD) processes and methods. The main area of focus is HCD for the design of clinical AI-powered metagenomics software. The combination of metagenomics and machine learning for clinical microbial analysis has not been explored, rendering our efforts innovative. Furthermore, design patterns for this type of software are not yet established, so the design for UI and data visualisations will include novel approaches. Finally, using HCD to validate assumptions is not common for the development of life science software, making the project itself innovative in this design context."