Source: TechTarget
Drug discovery, drug manufacturing, targeted clinical trials and personalized healthcare — these are just some of the areas in which the pharmaceutical industry has implemented AI. AI enables a future in which we have more targeted, more personalized, faster and better overall healthcare.
Because the pharmaceutical industry has so much access to data, there are many potential applications for machine learning and AI.
AI helps with disease identification and drug discovery
Companies are using AI in pharma to research and develop diagnostics and therapeutic treatments. AI combined with big data and analytics is helping to detect and prevent illness before it happens. AI tools can also mine patient data and combine that with machine learning to identify patterns that could indicate potential health issues. In fact, clinical trials and research are showing that AI systems are just as helpful, if not more so, than traditional medical practices in detecting early signs of illnesses such as diabetes or Alzheimer’s disease.
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.