Source: Pharma Phorum
Machine learning is widely predicted to make drug discovery and patient diagnosis quicker, cheaper and more effective in the future, and signs of this can already be seen.
Nearly 70 years ago, artificial intelligence researchers at New Hampshire’s Dartmouth College discussed building machines that could sense, reason and think like people — a concept known as ‘general AI’. But their plans were destined to remain in the land of science fiction for quite some time.
However, in the last decade the rapid growth in computer-processing power, the availability of large data sets and the development of advanced algorithms have driven major improvements in machine learning.
This article highlights the scope for developing therapeutics with new innovative, alternative approaches. The current trillion dollars pharmaceutical industry is in peril where the current drug development pipeline is slow, inefficient and incapable of being extended to multi-combination drug therapies as well as minimally focused on prevention. The complex modeling of diseases and biological functions has been limited because of the inability to integrate large scale molecular pathways.
Watch this Video to understand how recent advances provide breakthrough technology for doing scalable modeling of complex molecular systems to dramatically accelerate drug discovery and development.