Identifying Compounds
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Instead of throwing darts at the wall and hoping to land on an eventual hit—an expensive and inefficient process—pharmaceutical companies can leverage Deep Learning techniques to not only cull through literature and journal publications but also to pre-screen for the most effective potential compounds to prioritize their time.
There are software solutions that allow researchers to view sequence alignments and disease data alongside objective findings.
Benefits for the company
Bringing the efficiency into the drug development process can help companies in saving time and money.
Feasability
High
Type of expertise/ AI domain
Natural Language Processing
Internal data required
Different Protein interaction, genomic data, bio- markers etc
The estimated cost for drug development by U.S. biopharmaceutical companies is nearly $ 1 billion per drug.