Drug Dosage Optimisation Using AI for Healthcare Company

Business Goals

• Personalize drug dosage.
• Prevent cases of drug toxicity.
• Find out why some patients don’t respond to the medicine.
• Optimize medication spending.

Challenge

• Years of treatment history according to the unified protocol revealed that some patients experienced toxic effects from an excessive amount of the drug. In contrast, others developed no therapeutic effect regardless of dosage.
• Fortunately, the customer has been carefully recording medications and corresponding patients’ responses in the form of blood biochemistry for years.

Results

• Biochemical factors of drug resistivity have been determined, described, and quantified.
• During 30 days of clinical testing of the system, 12 cases of drug poisoning have been prevented; 3 cases of drug resistance have been identified.
• Drug dosage was either lowered or canceled, saving the substance and decreasing medical spending.

Implementation Details

• The history of medicine usage was analyzed.
• Patients were stratified into high, moderate, and no drug susceptibility groups by exposing biochemical drug response patterns.
• Systems of early detection of drug resistance and toxicity have been developed. In the detection case, the drug administration is immediately canceled.