Abstract
Organ-on-a-chip technology, often referred to as OOAC, represents a revolutionary paradigm in biomedical engineering and research. It is a sophisticated microfluidic system that replicates the structure, function, and microenvironment of human organs on a miniature scale. The aim is to create a platform for studying organ-level physiology and pathology outside the human body, providing a more accurate and ethical alternative to traditional methods that often rely on animal testing. Furthermore, the ongoing progress in artificial intelligence (AI) brings additional enhancements to the design and data processing capabilities of OOACs. In this chapter, we explore the opportunities and obstacles entailed in the integration of OOACs and AI. In summary, the evolution of OOAC technology and its eventual synergy with AI have the potential to disrupt the current landscape of drug evaluation, presenting a promising path forward.
TopIntroduction
Artificial intelligence (AI) encompasses the development of computer systems that replicate human-like intellectual processes, including reasoning, meaning discovery, generalization, and learning from past experiences (Datta et al., 2019) (Hashimoto et al., 2020). It refers to the simulation of human intelligence in machines. These systems aim to accomplish goals without the need for explicit programming for each specific task (Barua et al., 2023). Defining AI remains a matter of ongoing debate, with various proposed criteria for intelligence failing to provide a universally satisfying definition (Amisha et al., 2019). This uncertainty has given rise to the well-known saying that “AI is whatever challenges remain.” It involves the development of computer systems that can perform tasks typically requiring human intelligence, such as problem-solving, learning, reasoning, and understanding natural language (Barua et al., 2023). AI technologies include machine learning, deep learning, natural language processing, and computer vision, among others (Fanelli et al., 2020). As an illustration, tasks like optical character recognition and translation are no longer categorized as “artificial intelligence” due to their now routine and ubiquitous application. Artificial Intelligence is a transformative force in biomedical engineering, revolutionizing diagnosis, disease management, drug development, genomics, and surgical procedures (Barua et al., 2022). Its impact is far-reaching, offering more precise, personalized, and efficient healthcare solutions (Yu et al., 2018). While challenges and ethical considerations exist, the potential benefits are immense, and AI continues to reshape the landscape of biomedical engineering, bringing us closer to a future with improved healthcare and outcomes for all (Jiang et al., 2017) (Datta et al., 2023).
Figure 1.
The creation of object-oriented analog and digital communication (OOAC) devices
Key Terms in this Chapter
3D Bioprinting: Basically, it is an innovative technology that constructs three-dimensional biological structures by layering living cells, biomaterials, and growth factors. It has transformative potential in regenerative medicine, tissue engineering, and drug testing, offering precise control and customization for creating functional human tissues and organs.
OOAC: Organ-on-a-Chip (OOAC) technology involves microscale devices that mimic human organ functions, revolutionizing drug testing, disease modeling, and biomedical research by offering an ethical alternative to traditional methods.
Artificial Intelligence: AI, or Artificial Intelligence, involves creating computer systems that simulate human intelligence, enabling machines to perform tasks such as learning, reasoning, and problem-solving without explicit programming.
Biomedical Engineering: Basically, it combines principles of engineering and biology to develop technologies and solutions that improve healthcare. It encompasses medical device design, tissue engineering, and healthcare system optimization.
In Vitro: An in vitro model refers to experiments or studies conducted outside a living organism in a controlled laboratory setting. These models use cells, tissues, or biological components to simulate physiological or pathological processes, serving as valuable tools in drug testing, disease research, toxicology, and biomedical investigations.