Developing new medicines is not for the faint-hearted! On average, it takes about a decade of research with an expenditure that amasses US$2.6 billion to shepherd an experimental drug from lab to market.
The field of artificial intelligence and machine learning (AI/ ML) has witnessed sharp upturns, particularly concerning deep learning (DL) methods that are pillared with the availability of big data. Biomedical data is humongous and becoming increasingly available in ML-ready digital formats, it is now possible to deploy AI/ML algorithms to support healthcare research and services. However, within the larger healthcare ecosystem, biopharmaceutical companies, in particular, have been criticized for the skyrocket pricing of prescription drugs. Artificial Intelligence and Machine learning have the power to improve drug discovery and medical research which may reduce drug prices in the long-term.
Out of the total drug discovery done only about 5 per cent of experimental drugs make it to market!
This paves way for drug makers and pharma companies to invest hugely in artificial intelligence and machine learning with the hope that these technologies will make the drug discovery process faster and cheaper.
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