The Future of Computational Biochemistry


Computational biochemistry allows drug-makers to cut out a significant portion of the test tube experiments. Instead, a computer simulates the protein and tests all of its atomic interactions. That analysis will yield a far conscise list of leads that researchers can take to the next stage of testing

Benefits for the company

Deep learning truly has revolutionized drug discovery, as it can factor in everything from possible toxicity risks to new applications for existing drugs, which subsequently are saved the expense of a Stage 1 trial.



Type of expertise/ AI domain

Deep Learning

Internal data required

Different Protein interaction, genomic data, bio- markers etc

One Response

  1. Recent experimental techniques (including parallel synthesis of drug-like compounds) has drastically increased the amount of available data for deep learning models. This makes such models adept at bioactivity and synthesis predictions, in addition to molecular design and biological image analysis.

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