Nautilus.ai

A biotechnology stakeholder developed a new solution for diagnostics in oncology. They identified the analysis of the results as a remaining bottleneck in the diagnostic process, and wanted to offer a solution at this step of the value chain.

To help our clients, we developed a dashboard, that would convert simple questions into actionable insights. With our client’s input, as well as the insights of potential future users, we developed a dashboard that used state-of-the-art natural language processing (NLP), to create meaningful graphs and extracted statistical parameters from the complicated underlying data.

Our project enabled our client to get an insightful dashboard while guaranteeing data protection and avoiding hallucination from the generative AI model.

Alcimed supported a biotechnological start-up in developing an AI-powered dashboard for interpreting experimental results, transforming user queries into informative graphs for intuitive data analysis.

We conducted thorough research to identify the most suitable tools for platform development, including libraries and existing open-source projects, and then developed and tested the solution’s backend to ensure functionality and reliability. We crafted the graphical elements of the dashboard, aligning them with the client’s graphic charter for cohesive branding and user experience.

In the end, our team developed a useful interface that allowed to enhance our client’s R&D processes, offering valuable insights in a user-friendly format. This interface was not only intended to serve internal purposes but also to showcase a visually appealing aspect, impressing potential investors and clients and leaving a lasting impression.

Alcimed worked with a top pharmaceutical client to develop a comprehensive process and project management product-specific tool to plan and prioritize actions at the right timing to efficiently launch multiple products on hematology in a short timeframe.

At first, our team defined a clear vision of what the tool should be, key parameters, required data, and future use cases, including format, information granularity, and outputs desired. We then proceeded to define a set of operational activities (e.g. segmentation and targeting strategy, environmental field campaign, product availability, etc.) for the launch of a product to be implemented in the tool. For each activity, all the relevant steps for the launch of the product, the process evolution criteria, and associated decision processes were characterized and implemented in the final version of the tool.

In the end, we built a product-specific project management tool to optimize the process of the launch of several products within a short period. The intuitive and easy-to-use tool provided a clear visualization of the potential bottlenecks, teams’ planning, and the different activities details (“to-do lists”), enabling our client to sequence and optimize their product launches.

Alcimed supported a major healthcare industry player in modeling a business case to evaluate the opportunity for launching a new oncology product in 6 key markets over the next 15 years.

Our team collected epidemiology information and data on the usage rates of different health products that are available or under development to create a model of the evolution of the market size and the market shares in the concerned geographies.

We could thereby predict the future performances of a new health product launch thanks to time series analysis techniques.

Alcimed worked with a top French wine association to build their alcohol consumption monitoring platform to track and analyze the major trends on global, European, and national scales regarding the consumption of alcoholic beverages and societal indicators, with the objective to launch education and prevention initiatives.

To do so, our team first consolidated the global, European, and national data available on approximately 60 different alcohol consumption and societal indicators. We then analyzed and compared the data sets to build an optimal, sustainable data architecture within Power BI, followed by the design and configuration of relevant visualizations related to responsible consumption, to ensure an easy and effective interpretation of the insights (e.g., global alcohol consumption and sales evolution, French consumption frequency, etc.). In addition, our team built queries to clarify knowledge of alcoholic beverage consumption such as consumption rate, alcohol-related mortality, alcohol dependency rate, and more.

In the end, we developed for our client a one-stop monitoring platform, consolidating over 50 different data sources into a single interactive visualization tool, performing all operations end-to-end (data collection and consolidation, data transformation, data visualization in dashboards, and cross-query generation to identify correlations) to ultimately highlight the key takeaways, offering easy sharing of content, in any layout (presentation, print, and online access) facilitating the clients development of education and prevention initiatives aimed at the general public and professionals regarding health and prevention issues.

Alcimed’s team of Data scientists has set up a machine learning model to conduct an unsupervised analysis of the topics mentioned on Twitter in connection with the American Congress on Diabetes, ADA2021, as well as Twitter user communities communicating on this topic.

Our analysis, published in our Data use case 2, makes it possible to highlight 2 communities concerned mainly by different topics with the visualization of networked data.