An AI-Pharma Transport Collaboration
How artificial intelligence tools are helping to optimize the pharmaceutical transport process.
Logistics play a very important role in the pharmaceutical industry, as the activities involved are highly sensitive to time and quality control. It involves delivering drugs to the right place, at the right time, in a safe and secure manner, and at a competitive operational cost. Given this crucial nature of activities, drug shipping faces multiple challenges, including the requirement of temperature-controlled transportation, regulatory compliance, difficulties in demand forecasting, and the need for timely deliveries.1
In recent years, many companies have introduced software and artificial intelligence (AI)-driven innovations to help the pharmaceutical logistics industry by addressing these gaps and loopholes. With such advancements, AI has emerged as a key tool to overcome the above challenges and, in turn, optimize pharmaceutical shipping and delivery processes.2
Partnering with 3PLs for deliveries
Pharmaceutical logistics can be complicated due to the multiple challenges discussed above, but any product shortages due to human errors or delays in delivery can lead to compromised patient safety. As a result, many large pharmaceutical companies have started to rely on third-party logistics (3PLs) providers for managing transportation, warehousing, and quality control of their products. Many large 3PLs, such as Maersk, DHL, UPS Healthcare, and FedEx offer specialized services, including temperature-controlled delivery and regulatory compliance, which are vital for safe and efficient distribution of pharmaceutical products.
AI: Streamlining pharma logistics by filling the gaps
In recent times, AI has become the talk of the town for its potential applications in every sector, including logistics. When it comes to pharma logistics, software and AI-driven innovations are transforming operations and helping in overcoming challenges in the following six pivotal ways:
1. Dynamic route planning. Pharmaceutical shipments often face various on-road hurdles like traffic, weather changes, natural disasters, or geopolitical factors that could potentially lead to delays in deliveries. Such delays not only affect the schedules but also pose a risk to the efficacy of pharmaceuticals. In such a scenario, AI has emerged as a solution to tackle these challenges by optimizing shipping routes that analyze real-time traffic, weather conditions, and historical data.2 This approach helps in ensuring timely delivery of shipments, while minimizing the risks of degradation of pharmaceutical products during transit.2 An example for this can be Maersk, which uses AI to dynamically plan shipping routes by evaluating traffic, weather patterns, ocean currents, and other factors.3
2. Real-time tracking. Pharmaceuticals are required in every region of the world; as a result, pharmaceutical deliveries often span thousands of miles. This makes tracking of shipments a very complex task. However, AI technologies have now made real-time tracking of delivery vehicles possible, and are able to provide up-to-date status information to all concerned stakeholders. This approach not only increases transparency but also keeps customers informed about any potential delays, so that they can make required decisions accordingly.2 One example is FedEx, which uses AI for predicting potential delivery delays based on weather conditions and traffic, and keeps customers notified of these factors in real-time.
3. Cost efficiency optimization. Apart from optimizing the operations, AI can also help in reducing delivery management costs for the suppliers. It can decrease fuel costs with the help of dynamic route planning, can reduce labor costs with the help of automation, and can lower vehicle maintenance expenses by optimizing driving patterns and using predictive analytics. All these savings allow businesses to allocate these resources to other important tasks and long-term goals.4
4. Advanced temperature reporting. As discussed earlier, temperature control during transit is critical for maintaining the efficacy of pharmaceuticals. AI-powered internet of things (IoT) devices can be very helpful in this space. These devices continuously monitor the temperature and humidity levels of the shipment during transit. Such an approach saves time, as the drivers don’t need to frequently stop and inspect the goods. In case of any temperature fluctuations, the team is instantly notified about the deviation.2 For example, DHL SmarTrucking—a service officed in India—uses IoT-enabled sensors to provide real-time temperature tracking of shipments to their customers.5
5. Regulatory compliance monitoring. Regulatory compliance and audits are an integral part of pharmaceutical logistics since quality assurance is required at every step. AI can help in maintaining compliance by ensuring that transit regulations are followed at all times. It can continuously monitor the temperature data and compare it with industry standards to make sure that everything is under control. Moreover, it can notify the team in case of any deviations and potential risks to shipment, so that they can take corrective actions on time. One example of this is Kuehne + Nagel, who utilizes its "KN PharmaChain" solution to guarantee compliance with the strict transportation regulations governing pharmaceutical products in order to provide a standardized logistics service.6
6. Predictive analytics: By using predictive analytics on historical data, AI can predict future market trends, such as peak demands and seasonal demands. This information can help suppliers prepare for unexpected demand via surges or dips in the market, allowing them to manage number of vehicles and delivery intervals accordingly.4 Additionally, AI can use real-time data from IoT sensors on vehicles to assess vehicle health and identify any potential failures. This approach can reduce unexpected failures and minimize downtime, eventually optimizing the operations.2 For example, UPS uses sensors in its trucks to generate important information such as tire pressure, engine temperature, freight weight, etc. and use it to predict maintenance needs of the vehicles.7,8
We look forward to seeing how innovations in this sector continue to be brought to light in the years to come. Will other forms of technology emerge?
Society will have to wait and see.
About the Author
Purav Gandhi is the CEO of Healthark Insights.
References
1. Tan, J. A Complete Guide to Shipping Pharmaceuticals. MGS IceStorm. August 16, 2022. https://mgsicestorm.com/shipping-pharmaceuticals/
2. Singh, J. Pharmaceutical Cold Chain Logistics in the Age of Artificial Intelligence. Pharmaceutical Commerce. October 3, 2024. https://www.pharmaceuticalcommerce.com/view/pharmaceutical-cold-chain-logistics-artificial-intelligence
3. AI in Transportation and Logistics: Use Cases, Benefits, and Examples. Travancore Analytics. August 21, 2024. https://www.travancoreanalytics.com/ai-in-transportation-and-logistics/
4. How AI-Powered Delivery Management is Shaping the Future of Logistics. FarEye; #creator. October 8, 2024. https://fareye.com/resources/blogs/ai-delivery-management
5. Data: The Differentiator in Logistics Transport. DHL. https://www.dhl.com/content/dam/dhl/global/dhl-supply-chain/documents/pdf/SC_Insights%20Article_The%20differentiator%20in%20logistics%20transport_EN.pdf
6. KN PharmaChain for Road Transport. Kuehne + Nagel. https://us.kuehne-nagel.com/en/-/services/pharma-healthcare-logistics/road-transport
7. UPS Premier: Priority Shipping for Healthcare Products. UPS Healthcare. https://www.ups.com/us/en/healthcare/solutions/ups-premier.page
8. Filipsson, F. How UPS Uses AI to Predict Maintenance Needs for Its Delivery Fleet. Redress Compliance. January 26, 2025. https://redresscompliance.com/how-ups-uses-ai-to-predict-maintenance-needs-for-its-delivery-fleet/
