History of AI discuss Briefly?
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AI is set to transform chemical synthesis, providing opportunities to shorten one of the longest steps in the drug discovery process: getting new medicines to patients faster.
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When we are experiencing minor problems – such as an ache or pain – or have a more serious illness, most of us will rely on medicines to help us get better. But how many of us are aware of the huge amount of research that goes into the drugs we take?
Developing a new drug is a long and expensive process. It costs an estimated $2.6 billion and takes up to 12 years to take a drug through to regulatory approval [1].
The overwhelming majority of today’s pharmaceuticals are ‘small molecule’ compounds, composed of a few hundred atoms or less. Between 2010 and 2017, 76% of new drugs approved by the US Food and Drug Administration (FDA) were small molecules [2]. Due to their extra-small size, these drugs are more likely to get inside cells to reach their targets in the body compared to larger biological therapies.
This unimaginably diverse group of compounds share little in common except for their size and the fact they’re made from synthetic chemical reactions. A prominent example is aspirin, which is one of the oldest and most used medicines in the world – and many of the newest, most cutting-edge drugs for treating illnesses such as cancer, autoimmune diseases and depression, are also small molecules. And there are currently many more being developed to prevent and treat different conditions.
At the heart of small molecule drug discovery is chemical synthesis, which involves medicinal chemists creating brand new molecules through a complex, step-by-step process. Despite decades of research this is still a long, laborious procedure – and is a key bottleneck for advancing new medicines to the clinic.
But recent advances in AI-based software offer unprecedented new opportunities to help speed up this stage of drug discovery and get effective drugs to patients, faster.