AI in healthcare

One of our clients, a leading pharmaceutical company, wanted to anticipate elements of their medical communication by developing a tool that could help detect week signals in text databases.

As a first step, Alcimed determined the use cases that enabled the definition of specifications.

Our team then collected, cleaned, and structured the data, before developing natural language processing (NLP) algorithms to visually highlight the weak signals analyzed by the tool.

One of our clients, a dermatology laboratory, wanted to define their strategic roadmap in cancer prevention. To do so, they wanted to organize a board of experts in order to:

• Reflect on building a consensus around the place of AI tools in improving skin cancer diagnoses
• Identify the means for promoting the usage of such a tool amongst healthcare professionals

We supported our client in organizing and leading this board, and particularly in the definition and selection of the profiles of participants, whether from medical (dermatologists) or technical (AI researchers) backgrounds.

One of our clients, a world leader in providing technical solutions, wanted to reinforce their position in the healthcare sector.

To do so, they wanted to better understand the issues related to AI-based analysis of images in order to identify the opportunities in this market, the main players present, the needs and expectations of clients, and to thereby find a unique and differentiating position that responds to the segment’s expectations.

To do so, Alcimed first characterized the market of AI-based medical image analysis by mapping out the key challenges and analyzing the market’s value chain. Afterward, our team identified the market’s value sources and analyzed two major use cases.

Finally, we established recommendations for whether or not our client should become involved in this segment of the market.

One of our clients, a leading pharmaceutical company, wanted to explore the potential for external patient data from the United States and Germany for an artificial intelligence initiative in the diabetes field.

As a first step, Alcimed provided an understanding of the primary owners of public and private data in the concerned countries. These owners were then classified by our team in terms of volume, quality, relevance and accessibility of data.

Based on these criteria, we prioritized certain data owners as potential partners for our client and, together with our client, co-defined a primary strategy for acquisition of data for this specific study.

Alcimed worked with an institutional player to define a global roadmap and identify partners in line with the company’s AI and machine learning (ML) ambitions for its R&D activities, in terms of application needs and used technologies.

Based on an internal investigation and interviews, we conducted an in-depth analysis to enrich our client’s initial mapping of internal needs and AI/ML applications, and provided a first level of characterization based on key criteria (feasibility, data availability, complexity of implementation, maturity, cost, etc.) to then prioritize use cases and their solutions. We collaborated closely to delineate short-term, mid-term, and long-term activities aligned with our client’s ambitions. Based on these defined activities, we conducted additional research to assess the relevance of potential partners (based on adequacy with envisaged solutions, adaptability, experience, etc.).

In the end, we conducted a thorough assessment to gain better insights into our client’s internal needs, particularly focusing on the demand for more sophisticated tools. Through this process, we developed a clear roadmap outlining the implementation steps for specific tools, supplemented with recommendations on potential partners.

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.

One of our clients, a global medical devices player, wanted to test the market receptivity with regards to a solution they developed based on artificial intelligence and supporting the decision-making of anaesthesiologists regarding patients in coma.

Our team first assessed the strengths and weaknesses of the solution by setting up tests and by engaging with potential users in 9 Northern European countries. We also identified measures on how to overcome the identified barriers were equally identified.

After these steps, our team conducted a market sizing to assess the number of potential users and patients to benefit from this solution. Finally, we supported our client in understanding and navigating the purchasing process for such a solution.

Our team supported an international pharmaceutical stakeholder in selecting a new AI tool to improve their knowledge management. Documents and data being stored on various platform, information retrieval was identified as a major hurdle in their activities.

To help our client, we first conducted internal interviews to identify the main pain points and challenges associated with knowledge management. Existing solutions were then mapped, characterized and prioritized.

Based on the investigation, we suggested an approach that would solve their current challenge, by leveraging previous unused functions of their current platforms, and with the integration of a new AI solution supplier.

One of our clients, a leader in the medical device industry, was searching for a competent partner in programming artificial intelligence applications for digital pathology, with the objective to extend its product offering.

To do so, our team conducted a global scouting of innovative AI providers, which were notably analysed in terms of technological maturity, business maturity and their network strength.

Based of our work, a selection of prioritized providers was approached to explore opportunities of collaboration with our client.