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Use Cases :

● Drug Discovery & Development- Drug discovery can be competitive and expensive. AI tools can identify patterns in large datasets and solve challenges related to complicated biological networks. Precision medicine or next-generation sequencing helps in the faster discovery of drugs and provide tailored medication for individual patients. It can assist in studying diseases, drug repurposing; and biomarker identification and suggesting drug compositions ideal for such diseases. ML technologies possess the ability to process and analyze massive amounts of data quickly, they can help quicken the diagnosis process as well. It can also help identify the right amount of dosage.

● Prediction and Prevention- AI tools can help develop cures for diseases like Alzheimer’s and Parkinson’s and other rare diseases. ML tools can help monitor and forecast outbreak of epidemics. Machine learning tools are capable of predicting a patient’s response to possible drug treatments by understanding relationships among factors affecting the results

● Manufacturing and Marketing- AI in manufacturing improves efficiency and faster production of life saving drugs. It can study previous marketing campaigns and allow companies to design campaigns

● Efficient processes- AI tools can monitor quality control, shorten design time, reduce materials waste, improve production reuse.

With the world moving towards Data driven technologies, the importance of AI and ML in the Pharmaceutical industry is bound to enhance productivity, efficiency and revenue.

Blogs by Yashi