Artificial Intelligence in In-vitro Diagnostics

The study focused on exploring advancements in the interpretation of In Vitro Diagnostic (IVD) test results, particularly those correlated with emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Neural Networks. It identified key technologies poised to impact future result interpretation and highlighted opportunities offered by AI-based solutions in the IVD sector. Additionally, the study examined adjacent technologies like telemedicine that could enhance result interpretation and identified available products that can be utilized in the IVD of autoimmune diseases.

Client Background:

The client is a big player in the biotech industry, as well as a leading provider of in-vitro diagnostics (IVD), and is also a global supplier of innovative solutions across major disease areas.

Engagement Objective:

The objective of the study was to provide developments in the interpretation of IVD test results correlated with advancements in AI, ML, and other similar/ adjacent technological areas.

The study includes:

• Identification of technologies such as AI, ML, Neural Networks, and others that will have an impact on result interpretation in the future.
• Identification of the opportunities offered by AI-based technologies in IVD.
• Adjacent technologies (Telemedicine) that would improve the interpretation of results.
• Identification of available products that can be used in IVD of autoimmune diseases

Outcome Snapshot

Client Impact:

The study provided insights on challenges and solutions on which the market players are working i.e., implementation of ML or AI for In-vitro Diagnostics of neurodegenerative, inflammable, allergic diseases, and others. Furthermore, the study helped the client understand the competitors strategies’ such as mergers and collaborations, patent activity, product portfolios, etc.
A detailed bibliographic summary, including company profiling and solutions, geographical patent filing distribution, and technical focus, also helped gain a better perspective on the domain.