38 - AI: Welcome to the machine

Global events of recent years have underlined how critical global pharmaceutical supply chains are in preventing shortages and ensuring the commercial viability of new treatments.

But it’s not just about preparing for the next disaster. Everyday operational failures, which can result in defective, wasted and recalled drugs, also threaten the availability, and increase the cost, of life-saving drugs and vaccines.

Losses due to problems in temperature-controlled logistics cost the industry an estimated $35bn every year, and lack of visibility and automation in an increasingly complex supply chain are usually the culprits. As the biologics market grows, life sciences companies are looking to strengthen their supply networks with advanced analytics.

Applying AI and machine learning to large amounts of data can reduce uncertainty and improve decision-making, including forecasting. In our hyper-connected world, we’re seeing what might once have been termed black swan events become grey swans – still rare and potentially disruptive but more predictable because of analytics.

As well as transforming research, including the success of clinical trials, advanced analytics are improving supply chain operations too – mitigating the risk of unplanned machine downtime or a break in the temperature-controlled cold chain.

Teams can, for instance, use sensor data to proactively predict when machines and systems will require maintenance, and identify any deviations in GMP (good manufacturing practice) at the earliest opportunity.

Lack of data isn’t usually a problem in pharmaceuticals – if anything, companies have so much of it that they’re in danger of overburdening their stakeholders with constant alerts that aren’t always actionable.

Yet applying advanced analytics to cold chain allows operators to continually monitor numerous variables such as temperature, tilt and vibration in a much smarter way to maintain the viability of biologics and minimise waste.

Because of the difficulties around storage and transportation, analytics can also be used to target supply in different regions, incorporating external factors such as weather conditions and the prevalence of influenza outbreaks, or triggering alerts when stocks are low. Moreover, intelligent cold chain tracking gives operators the agility to respond swiftly to the ever-changing regulatory and security requirements in biologics transportation.

There have been some major steps forward in this area over the past few years. SAS has worked with life sciences organisations to enable them to access real-time intelligence via IoT (internet of things) sensors fitted to freezers, for example.

This flawless stream of data allows operators to monitor the variables that could impact cold chain integrity, and therefore predict the stability of biologics to ensure efficacy and patient safety, and reduce waste.

Greater certainty in cold chain logistics is helping to address bigger humanitarian challenges too, like equitable access to vaccines and treatments for people in remote rural communities.

Without advanced analytics, supply chains are more likely to break down because decision-makers don’t have the evidence they need to pivot quickly out of trouble – whether that be a global event, the emergence of a competitor or demand for new treatments.

There are many more questions that analytics can answer, from how long it takes for a biologic to spoil after a power failure, right down to whether a driver should stop for lunch or wait until after delivery.

A genuine black swan, by definition, will catch anyone off-guard but the impact of a grey swan event is likely to be far worse for those whose decisions aren’t based on real-time analytics.

Welcome to the machine

Step change