Artificial intelligence innovation: leading companies in clinical data modelling for the medical device industry 

The medical devices industry continues to be a hotbed of innovation, with activity driven by increased need for homecare, preventative treatments, early diagnosis, reducing patient recovery times and improving outcomes, as well as a growing importance in technologies such as machine learning, augmented reality, 5G and digitalisation. In the last three years alone, there have been over 450,000 patents filed and granted in the medical devices industry, according to GlobalData’s report on Artificial Intelligence in Medical Devices: Clinical data modelling. 

However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity. 

Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have. 

150+ innovations will shape the medical devices industry.

According to GlobalData’s Technology Foresights, which plots the S-curve for the medical devices industry using innovation intensity models built on over 550,000 patents, there are 150+ innovation areas that will shape the future of the industry. 

Within the emerging innovation stage, AI-assisted radiology, motion artefact analysis, and treatment evaluation models are disruptive technologies that are in the early stages of application and should be tracked closely. MRI image smoothing, AI-assisted EHR/EMR and AI-assisted CT imaging are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are computer-assisted surgeries and 3D endoscopy which are now well established in the industry. 

A clinical data model is a framework that extracts various health metrics from electronic health records and integrates that with the tasks associated with a patient care plan, which creates a data model using methods such as AI, machine learning or deep learning.

GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies.  According to GlobalData, there are 20+ companies, spanning technology vendors, established medical devices companies, and up-and-coming start-ups engaged in the development and application of clinical data modelling. 

‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.

‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’. 

Heartflow is one of the leading patent filers in the field of clinical data models. Some other key patent filers in the field include Zimmer Biomet, Thermo Fisher Scientific and Fresenius. 

In terms of application diversity, Zimmer Biomet leads the pack, followed by Heartflow and Fresenius. By means of geographic reach, Estee Lauder Companies held the top position, followed by Medaware and Restech.

As AI becomes more prevalent, one can expect it to be increasingly integrated into clinical data models, allowing the consideration of Big Data sets, bringing a step change in the accuracy of the models, and resulting in improved patient outcomes, reduced hospital readmission rates and improved disease prevention strategies. 

To further understand the key themes and technologies disrupting the medical devices industry, access GlobalData’s latest thematic research report on Medical Devices.