Express Pharma

AI and ML hold answers for Indian pharma’s logistics challenges

Rahul Vishwakarma, Co-founder and CEO, Mate Labs, asserts that deploying Artificial Intelligence (AI) and Machine Learning (ML) at scale can make the pharma industry more agile

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There hasn’t been a more complex challenge to the pharmaceutical industry in recent times as the COVID-19 pandemic. While concerns like batch losses, replenishment issues and lower yield plagued the pharma supply chain even pre-pandemic, the virus exacerbated the demand fluctuations in the sector. Thanks to the extreme challenges the industry has had to overcome during this pandemic, it has simply become impossible to rely upon traditional predictive systems. Ever since, Indian pharma has been increasingly turning to data, Artificial Intelligence (AI) and Machine Learning (ML) to improve its production efficiency, inventory management and the processes of replenishment.

Leveraging AI and ML to optimise capabilities

While the industry has begun leveraging AI and ML to optimise its capabilities, only when they are deployed at scale can they make the sector more agile. Data analytics is based on past events, but predictive analytics takes it notches ahead by drawing patterns, verifying assumptions and using ML algorithms to create and adapt to a model that yields the most accurate results. This method of predictive thinking allows the pharma industry’s supply chains to take a pro-active approach than a reactive one, allowing them to forecast demand more precisely. Even during unforeseen events and disruptions such as this pandemic, the industry can reduce its response time through accurate forecasting.

Owing to the gaps in infrastructure, logistics and cold chain management pose severe challenges to the pharma sector. That coupled with a lack of clear visibility and rising demands made it extremely challenging for the industry during the pandemic to forecas