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Pharma and biotech companies collect about 10x more data than other industries. With so much data available, how do biotech companies know where to begin when it comes to implementing AI and ML? These are some of the most common use cases for machine learning in biotechnology. Newer fields like AI or ML may not be as applicable to your business right now, but keep these in mind if you have plans to grow or pivot in the future. Building a data platform that can scale with your company should include data storage, data ingestion, and a data discovery and visualization layer.