Artificial Intelligence (AI) could lead to an era of precision medicine tailored to each individual.
AI involves the use of computer systems to analyze data and produce meaningful results. Many companies are now beginning to integrate AI in order to analyze large amounts of data – often referred to as ‘big data’ – from various sources, including clinical trials and open data resources. As their name suggests, some AI platforms are ‘intelligent’, i.e., they learn as they analyze increasing quantities of data. This is called ‘machine learning’. In theory, machine learning should lead to a more accurate and reliable system as time goes by.
The intention is to use AI to identify patterns in data and can be applied to many different areas of healthcare, from helping doctors decide which medicines could be most effective for their patients to identifying the most suitable individuals for a specific clinical trial based on their medical history.
The overall aim of using AI is to create a faster, more reliable health system that delivers personalized treatment (also referred to as ‘precision medicine’) schemes for each individual patient. The current model of treating a large population with a specific condition with a singular ‘gold standard’ treatment does not always work due to the differences between individuals. Instead, research performed by AI programs can link specific people with specific treatments based on their individual conditions including their genetics, stage of disease or past treatment.
The concept of integrating AI into healthcare is still in its earliest stages, although the number of companies using the platform is growing exponentially year on year, creating a cross-disciplinary environment where technology companies, healthcare providers and the pharmaceutical industry combine their expertise and work together to advance the technology.
So far, those companies involved in developing and applying AI are producing some very promising results.