Computer-assisted drug development is a result of artificial intelligence (AI). The extensive use of machine learning, particularly deep learning, in a variety of scientific areas, as well as developments in computing hardware and software, are all contributing to this growth. Artificial intelligence machine intelligence, as opposed to natural intelligence created by animals such as humans, is known as (AI). AI is the study of “intelligent agents,” or systems that understand their surroundings and take actions that increase their chances of attaining their objectives. The many sub-fields of Ai technologies are based on specific aims and the application of certain techniques.
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Thinking, information processing, planning, learning, speech recognition, sensing, and the ability to move and manipulate objects are all conventional AI research aims. General intelligence is one of the field’s long-term aims (the ability to solve any problem). RNNs, such as Boltzmann constants and Hopfield networks are closed-loop networks with the ability to memorize and store information. CNN’s are a kind of dynamic system with local connections that are used in image and video processing, biological system modeling, complex brain function processing, pattern recognition, and advanced signal processing. According to(NCBI) Several tools based on the networks that form the core architecture of AI systems have been developed.
End-User
- Pharmaceutical and Biotechnology Companies
- Contract Research Organizations
- Research Centres and Academic
- Government Institutes
Applications of Artificial Intelligence in Drug Discovery:
- Immuno-Oncology
- Neurodegenerative Diseases
- Cardiovascular Disease
- Metabolic Diseases