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Introduction of Artificial Intelligence in Life Sciences
The advancement of AI can be observed in pharmaceuticals and drug industry as well. On an average, this process takes 10-15 years, with ultimately only 12% of drugs in the clinical trial is approved by the U.S. Food and Drug Administration (FDA).
On the whole, 22.7% of all global research and development spending in 2017 was in the healthcare industry and secondly, 23.1% was spent in the computing and electronics industry. As enterprises consume a lot of time on researching and development of the products, Artificial Intelligence can help in reducing this time.
AI Startups in Life Sciences
A number of forward-looking venture capital enterprises and investors have predicted AI startups in life sciences. Many of the AI in pharma and biotech are in the drug discovery phase. AI can remarkably reduce the time of discovering new drugs which amount to real cost savings.
AI can be used in drug discovery and development in plenty of ways:
• Organic synthesis and design
• Scoring synthetic complexity
• Automation of molecule design
• Predicting organic reaction outcomes
• Computer-aided synthesis
• Computer-assisted retrosynthesis based on molecular similarity
• Predict drug performance in testing
• Discover off-label use
• Predict toxicity prior to clinical trials
• Personalized medicine
○ For Instance, startup Atomwise develop AI systems using deep learning algorithms and supercomputers for drug discovery. Its AtomNet solution enables 10 to 20 billion chemical compounds daily thereby reducing the time of discovery from years to weeks.
○ Palo Alto-based AI biopharmaceutical twoXAR provides an AI-driven drug discovery platform to identify in vivo testing with predictive technology.
○ Insilico Medicine is an AI startup which uses generative adversarial networks (GANs) for aging research, new molecule drug discovery, biomarker development.
○ London-based Benevolent AI aims to deploy AI not only to a specific development but across the entire R&D process.
AI investments by three major Global Pharmaceutical Giants:
1) Johnson & Johnson has an incubator called JLABS. It's resident startups with AI technology.
2) GNS, precision medicine company announced a collaboration with Roche subsidiary Gene tech to discover and validate new oncology drugs.
3) IBM Watson Health for Drug Discovery is an AI that incorporates data from four million patents, 25 million Medline abstracts and over a million full-text medical journal articles that are updated regularly. Pfizer is teaming up with IBM Watson Health for Drug discovery, to assist in immuno-oncological research and development.
Pfizer and XtalPi are coming together to combine quantum mechanics and AI machine-based learning to predict the pharmaceutical properties of molecular compounds for drug discovery and development.
Recent developments in AI drug discovery solutions is noted in one of the top institutions. A Stanford research team came up with a drug discovery called "one-shot learning" that greatly reduces the amount of data required to identify new drugs.
Industries like Pharmaceuticals and Biotech are spending approximately $75 billion in research and development annually. Startups and corporate enterprises are hugely investing in AI technology in order to shorten drug development time, be competitive and stay feasible in the future.
You may life: Using Technology to Simplify the Drug Development Journey
By Xavier Flinois, President, PAREXEL Informatics