The modern biomedicine and health industry is one of the most vibrant, innovative, breakthrough, and challenging industries since the 21st century. With the wave of technology, the integration of artificial intelligence (AI) and the biomedicine and health industry has started a new era of AI biopharmaceutical industry. As early as 2019, Accenture predicted that the big health industry of AI will develop rapidly with a compound growth rate of 40%, and the future will be the golden decade of AI biopharmaceutical and health industry. Nowadays, the AI biomedicine and health industry has entered a new stage of reform. Under the drive of artificial intelligence and data, life sciences, biomedicine, genetic engineering, and human health have moved from isolation and closed-loop to open and collaborative development, achieving faster, more accurate, safer, more economical, and more inclusive industry innovation.

The AI biomedicine and health industry’s evolution into 2024 is characterized by significant reforms and advancements in ten key subfields:

1AI Drug R&D

Professor George Fitzgerald Smoot from the University of California, Berkeley, a 2006 Nobel Prize winner, predicted in his 2019 speech “Exploring the unlimited possibilities of life sciences and artificial intelligence” that by 2026, big data and machine learning in the field of medicine and pharmaceuticals would bring an amazing value of 150 billion dollars each year. AI has already played a role in automated screening, accelerated drug design, virtual high-throughput screening, chip modeling, and even later medical simulations and toxicity analysis. The ultimate goal is to shorten drug development time and reduce costs.

2、AI Medical Devices (Medical Robots)

The combination of medical devices and AI is the earliest and most widely used in the biopharmaceutical industry, also known as medical robots. At present, AI medical devices have shown characteristics of high-tech integration, miniaturization, and intelligent precision, capable of independent judgment and adaptation to environmental changes, changing traditional medical modes and improving the quality of life for patients.

3、AI Medical Imaging

Dependent on image recognition and deep learning technology, according to the clinical diagnostic path, the image recognition technology is applied to the perceptual link to process and analyze unstructured image data, extract useful information, input large amounts of clinical image data and diagnostic experience into the AI model, train it to form an algorithm model, perform intelligent inference of imaging diagnosis, and output personalized diagnosis and treatment judgment results. Currently, there are mainly three types of imaging diagnoses: 1) lesion recognition and labeling, 2) automatic delineation and adaptive radiotherapy of the target area, 3) three-dimensional reconstruction of images.

4、AI Precision Medicine

Precision medicine is a new medical model that provides customized treatment solutions based on personal genomic information, and combines individual habits and living environment to carry out personalized precision treatment and improve disease prevention and treatment effects. Precision medicine currently mainly includes gene sequencing, cell immunotherapy, and gene editing.

5、AI Telemedicine

Also known as Internet medicine, by adopting remote communication technologies, holographic image technologies, modern electronic technologies, and computer multimedia technologies to leverage the advantage of large-scale medical centers in terms of technologies and equipment, telemedicine provides medical information and services for those in areas with inferior medical conditions or special environments. The inclusion of AI in telemedicine enhances efficiency and quality throughout.

6、AI Hospital Management

AI hospital management covers the management of various functions of hospitals in medical care, teaching, and scientific research activities. By planning, organizing, coordinating, and controlling various resources, it aims to maximize the medical utility.

7、AI Health Management

The application of artificial intelligence technology in health management specific scenarios, usually closely related to Internet medicine, is considered as a deepening development stage of Internet medicine. At present, AI health management mainly applies health risk identification, virtual nurses, mental health, mobile medical care, wearable devices and other health management areas.

8、AI Medical Payment Systems

At present, relevant organizations in this field primarily operate on medical insurance payments, commercial insurance payments, medical installments, and payment tools.

9、AI Elderly Care

The AI elderly care system is targeting for home-bound elderly, communities and elderly care institutions with networks of sensors and information platforms. On this basis, it provides real-time, efficient, low-cost, Internet of Things-based, interconnected, intelligent elderly care services.

10、AI Public Health

The machine learning and predictive analysis capabilities of artificial intelligence are used in the field of public health, and can systematically analyze a large amount of data and identify patterns that are difficult or impossible for humans to discern. Such AI technology is used to predict future health outcomes, allocate resources effectively, and develop more targeted intervention measures.

AI in the bio-pharmaceutical industry holds great promise. The rapid update and iteration of technologies have led to significant breakthroughs in disease treatment by stem cells and tissue engineering. Genomics and big data technologies are leading precision medicine. Immunity, stem cells are bringing about disruptive biological treatments. Synthetic biology and gene editing have taken the ‘regulation of life’ to a new height. AI and bio-pharmaceuticals are mutually beneficial, and the vast amount of data accumulated in the drug field are accelerating the discovery of new drugs by AI. Capital has already started this industrial innovation engine. In 2020, the global AI bio-pharmaceutical industry accounted for 18.9% of the entire AI industry (2020 AI medical investment and financing report), and it is predicted that it will account for over 20% by 2025. University education also needs to meet the industry demand. Many famous schools in Europe and America cover “Artificial Intelligence + X” disciplines, their future technological implications are richer enhancing the unlimited potential for development.