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Artificial Intelligence Trends in Healthcare

Over the past many years, the application and uptake of Artificial Intelligence (AI) has accelerated across technology verticals, and even in daily lives. While AI is not new, the convergence of various advances, including widespread developments in computing power and increasing volumes of data being generated, are leading to a renewed interest in AI. There is a considerable amount of public and private interest, and accompanied investment that are driving research in AI.


Unlike other sectors, AI still has seen very modest adoption in healthcare. However, there is a clear urgency and prospects for uptake of AI in healthcare. If managed properly, AI will lead to automation of routine tasks and processes, freeing up the doctors and the scientists to tackle the bigger challenges in healthcare, and more importantly, focus on patient care.

AI for new drug discovery

Bringing a new pharmaceutical drug to market takes about 12 years, involving billions in R&D expenditures. A lot of that investment fails, as nine out of ten candidate therapies fail somewhere between phase I trials and regulatory approval. As a result, pharma companies are now seeking more efficient means for this process and machine learning is emerging as one potential solution.

The last decade was marked by a wave of new R&D collaborations between key biopharma players and AI-driven companies, primarily startups. The interest in AI-driven solutions for early stage drug discovery is increasing among biopharma companies with a potential market volume anticipated around $10B by 2024 (including AI-based medical imaging, diagnostics, AI assistants, drug discovery, and genomics).

FDA greenlighting medical apps

The U.S. Federal Drug Administration (FDA) released its draft guidance regarding a newer, skyrocketing segment of the medical device industry—that of Software as a Medical Device (SaMD). The guidance means to address the emergence of thousands of stand-alone, health-oriented software apps that fall into a gray area in terms of regulation.

The guidance defines SaMD as “software intended to be used for one or more medical purposes without being part of a hardware medical device.” More specifically, SaMD is a medical device that:

  • Includes mobile apps and in-vitro diagnostic (IVD) medical devices.

  • Can run on general purpose (non-medical purpose) computing platforms, such as a smartphone, tablet, or PC.

  • May be used in combination or interfaced with other products, including medical devices, other SaMDs, and general-purpose software.

The 'Artificial Intelligence Trends in Healthcare' deep dive report from Hammerkopf is available here.


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