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Infusing Artificial Intelligence into the Pharmaceutical Supply Chain

Jan. 21, 2020
Slowly but surely, the pharmaceutical sector is becoming the next testing ground for companies looking to use AI to help digitalize their global supply chains.

Slowly but surely, the pharmaceutical sector is becoming the next testing ground for companies looking to use AI to help digitalize their global supply chains.

Examples of artificial intelligence’s value to healthcare is already coming to life in the form of new drugs, new cures, and new ways to diagnose conditions. And while AI hasn’t exactly made its footprint in the pharmaceutical supply chain yet, its time could be coming soon.  

An area of computer science that emphasizes the creation of intelligent machines that work and react like humans in relation to activities like speech recognition, learning, planning, and problem solving, AI holds great potential in the pharma supply chain.

In recent years we’ve seen an acquisition spree with some of the largest pharmaceutical companies snapping up biotech start-ups, investing in state-of-the-art AI solutions, and hiring in-house data scientists to work alongside, well, scientists,” Rich Quelch writes in Leveraging AI in the pharmaceutical supply chain.

“Yet, technology in the pharma supply chain that connects the lab to the marketplace is lagging, with investment instead being prioritized towards the discovery, development, and marketing of products,” Quelch continues.

A Silver Bullet

Calling artificial intelligence the “silver bullet” for smarter pharmaceutical supply chains, Quelch says companies are under these pressures—all of which can be addressed with some level of AI:

  1. Environmental pressures. Regulators are imposing stricter environmental controls across the design, manufacture, and transportation of pharma products to help curb carbon emissions and reduce plastic and water waste.
  2. A new wave of medicines. Complex biologic drugs and gene therapies are becoming increasingly popular but throw up huge challenges for manufacturing and distribution networks due to their sensitivity and short lifecycles.
  3. Demographic shifts. Populations around the world are ageing and so is the prevalence of associated chronic diseases such as diabetes, cardiovascular disease, cancer, and dementia.
  4. Falsification. The criminal market for falsified medicine is worth over $200 billion per year, making the protection of medicine quality and safety a priority, including the development of tamper-proof packaging technologies.
  5. Demand from emerging markets. To unlock the potential of developing regions such as the BRIC economies (Brazil, Russia, India, and China), pharma needs to invest in and implement truly global supply chains.

“AI could hold the key to overcoming these pressing challenges,” Quelch writes, “and help keep the industry be one step ahead of future ones too.”

Tracking Products Around the Globe

Quelch isn’t alone in his assertion that AI would do wonders for the pharma supply chain. In “The Pharmaceutical Industry and the Digital Supply Chain, Datex Corp. points out that the implementation of The Drug Supply Chain Security Act (DSCSA) has pushed companies to transition from complex, traditional pharmaceutical supply chains to digital ones.  

“By executing on the DSCSA vision,” Datex points out, “a system of electronic drug product traceability will improve the speed and accuracy of track and trace, saving the lives of patients across America.” Tools like predictive analytics, big data, and AI will all help make that happen.

For example, Datex says a large wholesaler implemented AI-driven cloud software and uses it to collect data from across its enterprise including at multiple subsidiaries and storage facilities.

“This is used to track hundreds of thousands of pharma product SKUs which are distributed to customers,” it states.

Transforming the Pharma Supply Chain

According to Datex, AI shows the promise of being able to transform pharmaceutical supply chains though its ability to process vast volumes of data and provide intelligent insight and recommendations. “Using machine learning algorithms,” it notes, “AI is capable of learning and refining information in real time, even as it crawls data sets from internal and external sources.”

And, thanks to its robust cognitive automation abilities, AI can also be applied to examine and improve processes across the supply chain, including supply and demand forecasting, manufacturing performance, assessments of supplier reliability, and inventory optimization.

“As the pharmaceutical sector continues to evolve, companies can no longer afford to resist implementing digital technologies and tools,” Datex concludes. “The pharmaceutical companies seeking strategic advantage are finding many new ways to leverage digital solutions, and will stand a better chance of staying competitive and agile in this constantly evolving landscape.”

About the Author

Bridget McCrea | Contributing Writer | Supply Chain Connect

Bridget McCrea is a freelance writer who covers business and technology for various publications.

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