Application Of Deep Learning into Drug discovery

Drug discovery and development is considered to be a tedious process, often consuming a significant amount of time and resources. On an average, it costs USD 2.5 billion to bring a new drug to the market. For big pharmaceutical companies, this average is around USD 4 billion and has been shown to go as high as USD 11 billion. Designing a new drug that binds to any specific target requires a large amount of time, as well as computing power. In many ways, deep learning algorithms are being developed to accelerate this process. It is anticipated that digital solutions for drug discovery may save significant time and capital.

In the proof-of-concept I show how you can use deep learning in Drug discovery. Take a look at the app here

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