Frost Radar –Which Best Practices Drive Growth in Digital Pathology?
A benchmarking system to spark companies to action—innovation that fuels new deal flow and growth pipelines
Overview
Digital pathology potentially is a high-growth industry. Relatively low penetration is increasing because of the impact of AI and machine learning (ML) algorithms and platforms that are improving the outcomes of clinical and research applications, reducing the time pathologists spend on diagnosis and prognosis.
Digital solutions’ high cost is a crucial concern in diagnostic labs. Companies are addressing this by providing pathology-as-a-service, pay-per-slide scan, and storage-as-a-service models. This eliminates upfront investments and offers regular updates, maintenance, scalability, and flexibility.
Competitive intensity is increasing, especially in the image analysis segment, with the entry of start-ups. Players are under pressure to create unique, competitive products. With the emergence of new AI technologies, more new image analysis and reporting solutions are expected to emerge.
An opportunity exists for the emergence of companies that can acquire new technologies and software for data management and interpretation services that are expensive for other institutions. The number of companies offering outsourced digital pathology services to laboratories or hospitals that do not have the digital technologies or tools to analyze samples has increased.
- How can digital pathology companies capitalize on the increasing adoption of AI and ML algorithms to drive growth in clinical and research applications?
- How can pathology-as-a-service, pay-per-slide scan, and storage-as-a-service models help address cost concerns in diagnostic labs and create new growth avenues?
- How can your team capitalize on opportunities to acquire new technologies and software for data management and interpretation services in the digital pathology industry to drive growth?
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