ML & AI in the Pharmaceutical Industry: Where the Biggest Gains Lie

Use Cases & Projects Lynn Heidmann

After a century of rapid progress in the development of new medications, the discovery of new drugs has slowed significantly, and the process of developing new pharmaceuticals has become more and more expensive. But advances in data science — particularly in the areas of deep learning and artificial intelligence (AI) — are fit to fundamentally shift the industry, which means opportunity is ripe for the taking for those enterprises willing to dive in.

pharmaceuticals

For a look at the state of the industry and how data science is already starting to make an impact (plus what the future holds), take a look at the white paper How Machine Learning is Transforming the Pharmaceutical Industry.

Top Areas of Impact

  1. R&D: For drug companies, there is major incentive to reduce R&D spending, both to free up funds for additional ventures as well as to be able to offer lower prices for their products. Use cases range from using data science to identify patients for clinical trials, identifying chemical compounds, more advanced computational biochemistry, and more.
  2. Supply Chain: Identifying the most efficient supply system will become even more important as drugs are increasingly customized to small populations of patients with certain genetic profiles.
  3. Manufacturing: Drug companies are increasingly able to ensure consistent quality standards with the use of advanced analytics.
  4. ...and much more! Like, for example, prescription optimization:

 

You May Also Like

Dataiku Solutions: How They Work and How to Use Them

Read More

5 New Dataiku Features to Streamline Your RAG Pipelines

Read More

Taming LLM Outputs: Your Guide to Structured Text Generation

Read More

From Vision to Value: Visual GenAI in Dataiku

Read More