Global trade tensions and changing pricing policies create significant challenges for manufacturers as they strive to maintain product availability on retailer shelves. According to Christy Christian, senior director of industry at Kinaxis, these disruptions are not entirely new, but the pace and unpredictability of change has intensified. Manufacturers now face a rapidly changing landscape in which tariffs can change overnight (from metals to paper to other key materials), making it difficult to maintain stable, long-term supply chain strategies.
A key issue is the extensive and globally distributed nature of modern supply chains. Many companies source components or raw materials from regions far from where final products are assembled, causing delays and reducing flexibility to respond to sudden pricing changes. The cascading effects of these disruptions extend to first, second and third tier suppliers, amplifying bottlenecks and vulnerabilities.
Traditionally, companies mitigate supply chain risks by creating inventory reserves. However, in today’s financial climate, organizations are less willing or able to tie up capital in excess inventory. Maintaining large inventories directly impacts free cash flow, which remains a top priority for many manufacturers. This constraint leaves supply chains with limited room to maneuver and little margin for error in the event of disruptions.
As a result, businesses must find ways to optimize and adapt their networks under increasingly complex conditions. Agility, both in planning and execution, has become essential. Businesses must quickly update their sourcing strategies, reallocate inventory, and pivot operations in response to pricing changes or supplier closures. However, the challenge is to ensure that adjustments occur quickly enough to avoid the arrival of excess raw materials after market conditions change. In today’s volatile global environment, the ability to dynamically balance inventory, cash flow and supply flexibility defines supply chain resilience.
Christian also comments on the hurdles that typically arise when moving from manual spreadsheets to AI-based orchestration in the healthcare supply chain, the reliability of AI-based demand forecasts in the face of unpredictable events; how supply chain modernization directly affects the affordability and accessibility of over-the-counter medicines; and more.
Additionally, in traditional pharmaceutical manufacturing, organizations often had to make trade-offs between speed and compliance. As production increased, it became increasingly difficult to maintain consistent quality and prepare for audits, leaving many companies unprepared when regulatory inspections arose. Hari Kiran Chereddi, CEO of HRV Pharma, explains that its new operating model fundamentally changes this dynamic by digitally orchestrating processes across all partner facilities. Each location connects to a unified digital infrastructure that enforces standard operating procedures, quality metrics and documentation standards in real time. This centralized system automatically tracks and validates each process deviation and corrective or preventive action, ensuring continued alignment with regulatory expectations.
The result is a significantly more efficient regulatory pathway, as organizations using this model have achieved 30% faster regulatory review cycles. Submission dossiers, such as Master Drug Dossiers for active ingredients, are pre-validated by an AI engine, allowing companies to embark on regulatory review with confidence and significantly reducing the risk of deficiencies.
A transcript of their conversation with PC can be found below.
PC: How reliable are AI-based demand forecasts in the face of unpredictable events? Additionally, what role does AI play in transforming supplier management, compliance validation, and production forecasting within a global pharmaceutical network?
Christian: I really think it depends on the stability of the product, because if it’s predictable and stable enough, that data will be pretty clear. You’re going to have the anomalies from these disturbances, which you can remove. I think where you’re going to struggle to take advantage of it is something sporadic or project based where it’s really a seesaw type of demand, it’s going to be a challenge in that regard, because is it the structure of the product, or is it a disruption?
Even leveraging that on fairly stable products, it would take up a significant portion of their portfolio, so they could actually leverage that, apply human creativity and subjectivity to it, and be much quicker in decision making. Again, it’s about getting people out of the mentality that we have to have everything or we can’t have anything. It’s crawling, walking, running. What can we do today to free up time and make decisions faster while we work on other things that don’t necessarily fit the current model.
Kiran Chereddi: Speed and compliance were always trade-offs. The more you increase production, the more difficult it becomes to maintain quality, or even prepare for audits. Usually a lot of people would look at it and say, “oh, you know what the FDA is at my door, and I have something to do tomorrow morning.” I don’t know how ready I am.
What we saw is that our model is actually able to break this phenomenon, by orchestrating some of these things. Each partner facility connects to our digital infrastructure, which enforces standard operating procedures, quality metrics and document templates, in real time. This means that every process deviation, or every corrective and preventive action, is tracked and validated through it. So what happens then?
What we saw was a 30% faster regulatory review cycle. What happens is, from the time the master drug dossier is ready — especially with the active ingredient — to the time the submissions are there, everything is pre-validated by the AI engine that’s there.
We have seen faster vendor onboarding. We’ve seen 15-20% faster vendor onboarding. This is something that we are in the process of defining and ensuring that the standard operating procedures are more robust at this point, and getting to a point where there are absolutely no compliance gaps. And for this reason, quality control is something that is done constantly and not a posteriori. And then with that, for us today, the virtual model has actually given us global reach, but the AI layer is what gives us the precision if I may, as well as the regulatory precision panel that’s there. Many people have seen this sign in the formulation area, but many have not seen it in the active ingredient area.