Keeping An Eye And Ear On Patients’ Needs: Where AI Meets Supply Chain

11 August 2021 | Wednesday | News

The healthcare supply chain ensures that patients get the medicines they need when they need them. Is artificial intelligence set to revolutionize this increasingly complex process?

“We want every patient to be able to get the medicines they need when they need them,” says Teresa Rodó, Merck Head of Global Healthcare Operations.

“This is our number one priority,” adds Markus Koehler, Head of Supply Network Operations. “Everything we do in our Healthcare business ultimately comes back to the patient. The patient is the priority and that’s also true when it comes to our supply chain.”

It’s common to read about new medical treatments in the news and the fascinating research which has led to their development. What you’re less likely to hear about are the complex processes involved in ensuring that medicines, both new and established, reach patients when they need them


Given that the volume of medicines used globally now stands at 4.5 trillion doses, with more than 50% of people taking more than one daily dose of medicines [1], healthcare supply chain management is clearly vital to our everyday lives.  

It’s an incredibly complex process, usually involving several independent stakeholders – manufacturers, wholesalers, hospitals, healthcare providers, group purchasing organizations, and many regulatory agencies.

“The supply chain of our medicines serves 90 million patients worldwide across 160 countries,” says Alessandro De Luca, our Healthcare Chief Information Officer. “We want to be able to react faster to accelerating changes in demand that we see across the healthcare industry.”

A certain level of automation is already a feature of most supply chain models, with complex algorithms predicting demand and aiding forecasting. However, in recent years these systems have still required human intervention. But with artificial intelligence (AI) and machine learning becoming more accessible, there is now an opportunity to create a system that is entirely “self-driven.”

“Within our Healthcare supply chain, we’ve embarked on artificial intelligence and machine learning to optimize our response to the demand for our medicines,” explains Koehler.

This move towards greater automation also comes in response to the changing world of healthcare and increased digitization in our daily lives. The healthcare sector is witnessing drastic change in the way goods and services are delivered. Key drivers include a move away from treating shorter episodes of illness towards a greater focus on longer-term wellness and prevention, as well as the changing expectations of patients and consumers.

“Health is becoming more connected,” says De Luca. “New technologies are emerging that allow patients to order nonemergency medications directly from their computers and phones. New patterns in medicine distribution are also emerging as a result.” The recent pandemic has further strengthened application of digitally and data-generated tasks.

“Consumers are beginning to expect personalized health products and services,” adds Koehler. “That will also mean there needs to be more flexibility and responsiveness in the supply chain.”




These technological and social trends are behind our ambition to create a “self-driving” healthcare supply chain. One where production and distribution adapt automatically to meet changing demand.

“With the help of machine learning, deep learning, and neuronal networks, we will be able to use our data in an advanced manner to ultimately increase the accuracy of our forecasting and to enable real-time decision-making in order to react to last-minute changes in demands,” notes Michelangelo Canzoneri, Global Head of Digital and Data for Healthcare. “A digital pharmaceutical supply chain provides real-time data to increase full transparency to visualize and analyze the end-to-end performance along the entire supply value chain, which includes all analytical testing steps, the manufacturing and packaging of the drug and its distribution.”

“Our aim is to leverage digital solutions across our entire value chain to improve the lives of patients,” says De Luca. “In the supply area, our first step was the creation of a supply chain control tower. This descriptive element brought all the Healthcare business supply chain data together in a single digital dashboard, providing a centralized, real-time view of its end-to-end supply chain operations”.
“This helped us to boost service levels from very good to almost perfect," stresses Koehler.

Now, four years on, we’re making extensive use of AI, machine learning, sensors, and analytics to automate large parts of our manufacturing and logistics processes. We’ve partnered with a range of technology companies, notably Aera Technology Inc, a specialist in cognitive automation, as well as Tracelink, an expert in serialization and data analytics. These partnerships are helping us to pull together a suite of tools to accurately predict demand and ensure adapted production and supply.

The digital supply chain will notably decrease our inventory and synchronize seamlessly with our specific drug cycle times. The visibility and use of all these data and the underlying information across the entire supply chain will further the optimization of our inventory, minimize excesses and shortages and reduce overall and specific drug cycle times.

“The new systems mean we’re better able to mitigate supply shortages, predict spikes in demand, and bottlenecks,” says De Luca. “Initially, this approach was piloted with our portfolio of fertility medicines, but now we’ve expanded the program to incorporate our whole Healthcare portfolio.”

“The self-driving operations aspires to eliminate waste – and allow an optimized use of material, personnel or energy,” notes Koehler. “Ultimately that helps us ensure that our patients receive the drugs they need when they need them.”

It’s important to emphasize, however, that increasing automation has never been about cutting jobs. Instead, we are upskilling people who used to work purely in supply or demand planning and augmenting their ability to analyze operational situations and make quick and data-based decisions.

“We believe there are other places where human intervention can add value, rather than needing them to carry out trivial operational tasks or data crunching that a computer can inevitably do better,” says De Luca.

“We’ve also created a digital supply chain academy to retrain our planners to become supply chain architects and build their data science knowledge,” highlights Koehler. “We’re enhancing the value of these roles, taking them from planning to providing business insight that could change the trend of the supply chain or influence where we go to market.”

This work to create a self-driving automated supply chain is now gaining recognition in the wider business community.

“We were recently featured in Gartner’s 2020 ‘Future of the Supply Chain’ Executive Report [2],” explains De Luca. “It identifies our work as a key case study in driving digitization and hyperautomation in the supply chain.”


As we become increasingly digitally connected and medicine becomes more personalized, it seems almost inevitable that the future of the supply chain is increasingly digital. But will it also be completely automated?

Canzoneri is confident in this vision. “I believe that automation and advanced capabilities in digitization and data such as machine and deep learning will be the only way to meet changing patient demands,” he says. “Personalized medicine, online prescribing, more personal health trackers and sensors – these will all place the patient at the heart of the supply chain. We will need increasingly intelligent systems to meet these more complex demands.”


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