Computer Vision Models to Decipher Drug Efficacy & Authenticity

About The Client

A US based fortune 100 healthcare company that offers solutions in the pharmaceutical, insurance, care provider, and retail space.

Challenge

We had set out to achieve two main challenges; an efficient method to flag counterfeit drugs, and the second to assess the efficacy of expired medication.

Solution

We were able to develop a working prototype of computer vision-based machine learning models to decipher drug efficacy & authenticity.

Assessed and created machine learning models to achieve a confidence rate of 84% when looking at drug identification.

Tailored respective models to highlight the correct drug potency for both expired and non-expired medication.

Leveraged difference aspects of Ramen spectrometry to for drug efficacy and authenticity

Results

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Achieved a confidence rate of 84%+ with our models

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40% less costly when assessing drug efficacy & authenticity

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5X increase in operation efficiency within pharmaceutical workflows