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DataRobot awarded prestigious status

"AWS Machine Learning Competency"

Drug Delivery Optimization

DataRobot helps optimize supply chain delivery processes by predicting which orders can likely to be consolidated.



Why DataRobot

Factors that help predict whether a given drug order can be consolidated are very heterogeneous: time, drug characteristics, geographical information, doctor characteristics, etc. DataRobot’s algorithms and feature engineering naturally handle these complex datasets to generate the most accurate predictive models in minutes.

  • Reduce delivery costs on millions of drugs without affecting quality of service
  • Without manual intervention, turn an expensive process into a smart and more efficient one
  • Leverage powerful supply chain predictive optimization without statistics or coding experts


Pharmaceutical firms spend significant money on producing and shipping drug samples to medical practitioners in an effort to acquire new adopters. To avoid unnecessary costs, the delivery and supply chain processes must be optimized using models based on real-time requests.


Using DataRobot model automation and historical drug delivery data, a business analyst can build a model that accurately predicts whether a given drug sample order could be consolidated with another upcoming order to the same location or department. You can then minimize shipping costs on those orders predicted to be consolidated by retaining them for a few days at the warehouse.


  • Reduce the cost of acquiring new customers by consolidating drug sample shipments
  • Provide an automated and efficient delivery service

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