How AI is revolutionizing the healthcare and life sciences industry 

Use of artificial intelligence (AI), including applications such as machine learning (ML), where AI software is trained to form its own decision-making criteria based on previous examples of a particular task in life sciences has the potential to transform how we better human health and conduct medical research. According to the Artificial Intelligence Report 2023 prepared by Stanford University in 2022, medical and healthcare was the AI focus area with the most investment with $6.1 billion. 

To better understand the potential for how AI can revolutionize the life sciences industry, let’s first explore the concept of AI. 

What is AI? A definitional treatment 

AI is a term that most of us are now familiar with, but its interpretation is extremely varied. At a high level, the term “artificial intelligence” encompasses the use of technology to perform tasks typically associated only with human beings, such as learning and decision making. This can be seen anywhere from “strong AI” or Artificial General Intelligence (AGI), which is where a machine could have intelligence equivalent to a human, to “weak AI,” the version we are most familiar with, from voice assistants and driverless cars, where software is trained to perform focused and specific tasks.    

According to the AI Act, EU regulatory framework for AI - 2021, AI is defined as "software that is developed with techniques and approaches that can generate outputs such as content, predictions, recommendations, or decisions influencing the environments they interact with." Annex I of the act outlines approaches such as ML, explicit logic-based approaches as well as more general statistical techniques. 

The current U.S. Food and Drug Administration (FDA) definition of AI describes it as the “science and engineering of making intelligent machines, especially intelligent computer programs.” Wherein, AI can use different techniques, including models based on statistical analysis of data, expert systems that primarily rely on if-then statements, and ML. The FDA also states that ML is a subset technique of AI that can be used to design and train software algorithms to learn from and act on data. Software developers can use ML to create an algorithm that is ‘locked’ so that its function does not change, or ‘adaptive’ so its behavior can change over time based on new data.  

What does AI mean in medical technology (medtech) and in pharmaceutical terms? 

Given the significant expenditure associated with drug development and delivery for burgeoning global populations, it is unsurprising that AI is sought as a tool to increase productivity and efficiency in healthcare. We must go back to 1995 to find the first ML technology approved by the FDA. Since then, more than 500 medical devices have gained 510k status aiding image analysis and diagnosis of diseases such as cancer with AI led software devices. These devices seek to optimize delivery of surgery and post-operative care for orthopedic patients receiving an implant such as an artificial hip.