The technology industry continues to be a hotbed of patent innovation. Activity is driven by the increasing volume and complexity of genomic information, necessitating faster and more accurate analysis for research, clinical diagnostics, and personalized medicine, and growing importance of technologies such as deep learning models, natural language processing, and generative models. In the last three years alone, there have been over 4.1 million patents filed and granted in the technology industry, according to GlobalData’s report on Artificial intelligence in technology: AI in genome analysis. Buy the report here.
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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 stabilizing 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.
190+ innovations will shape the technology industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the technology industry using innovation intensity models built on over 1.5 million patents, there are 190+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, deep reinforcement learning, finite element simulation, and GenAI for design are disruptive technologies that are in the early stages of application and should be tracked closely. AI in EHR, intelligent predictive maintenance, and forward inferencing are some of the accelerating innovation areas, where adoption has been steadily increasing.
Innovation S-curve for artificial intelligence in the technology industry
AI in genome analysis is a key innovation area in artificial intelligence
AI in genome analysis involves employing artificial intelligence techniques and algorithms to scrutinize genomic data. This encompasses the management and interpretation of extensive genomic datasets to extract insights into various genetic facets, including identifying disease-associated mutations, predicting treatment responses, and comprehending molecular pathways.
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 650+ companies, spanning technology vendors, established technology companies, and up-and-coming start-ups engaged in the development and application of AI in genome analysis.
Key players in AI in genome analysis – a disruptive innovation in the technology industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to AI in genome analysis
Source: GlobalData Patent Analytics
Among the companies innovating in AI in genome analysis, Caris MPI is one of the leading patents filers. The company’s patents are aimed at techniques and systems for conducting molecular assessments of diseases, including cancer. In certain implementations, this molecular profiling can serve to pinpoint potential treatments for a disease, even those not originally recognized or anticipated as viable options for that specific condition. The other prominent patent filers in the space include BioNTech and Congenica.
In terms of application diversity, Expanse Bioinformatics leads the pack, while BioNTech and Biodesix stood in the second and third positions, respectively. By means of geographical reach, GenomSys held the top position, followed by Expanse Bioinformatics and BostonGene.
The integration of AI in genome analysis expedites the processing and interpretation of vast genomic datasets, enabling researchers and clinicians to extract valuable insights with unprecedented speed and accuracy. It accelerates the pace of genomic research and facilitates the identification of genetic variations associated with diseases, paving the way for more effective diagnostics and personalized treatment strategies.
To further understand the key themes and technologies disrupting the technology industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI).
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
