Health Industry

The healthcare industry is facing very strong pressures, related to the health issues of our time, as well as an exponential growth of data that is critical to value. It is also subject to requirements and increasingly strong regulatory constraints. The digital transition, this process of digitization of laboratories consisting of transforming analog information into a digital format, is one of the major levers for facing these challenges. We can distinguish the issues that concern laboratories in particular: 

• Implementation of an electronic laboratory notebook and migration of existing
• Inventory management and inventory of products and reagents used within the  laboratory
• Implementation of a LIMS (Laboratory Information Management System)
• Management of molecular drawings
• Implementation of data visualization tools, true accelerators
• Automation of measurement and test data analysis
• Peak analysis

Beyond the day-to-day activity within laboratories, healthcare stakeholders must also be concerned with the industrial logic associated with monitoring and publishing:

• Bibliographic acquisition and management
• Scientific article writing and publication
• Scientific communication
• Speaking and media 
• Scientific and technological watch in innovation projects

This overhaul of the tools and information system also concerns everything related to Studies:

• Biostatistics
• Survival analyses
• Clinical trial management

Operational efficiency stems from an approach that falls under the engineering professions:

• The implementation of experimental designs
• The optimization of quality and manufacturing processes

Recent developments in software technology and Artificial Intelligence are revolutionizing quantitative analysis

• Simplifying the implementation of the most sophisticated statistical methods
• The use of techniques related to Data Sciences and Machine Learning
• The rise of technologies available in Open Source
• Reporting methodology and visualization
• Data methodology and analysis
• Software development methodology
• Scientific and medical data analysis
• Use of biostatistics
• Conducting survival analysis
• Conducting Surveys

Finally, the changes also affect the use of methods related to quantitative analysis.

• Analysis of unstructured and qualitative data.
• Automated interview transcription