Pharma factories are leaving capacity on the table — and this AI partnership wants to fix that
Two Canadian companies just announced a partnership that could change how pharmaceutical manufacturers plan their production. On March 17, 2026, OPTEL and Kaster Technologies revealed a commercial agreement to bring AI-powered production planning to drug manufacturers worldwide. The promise is straightforward: increase production capacity by up to 20% without spending a dollar on new equipment.
That is a significant claim in an industry where capacity constraints directly affect drug availability.
Why pharmaceutical manufacturing planning is still surprisingly old-fashioned
Most people assume that drug manufacturing, one of the most regulated industries on earth, runs on cutting-edge technology. The reality is more complicated. Many pharmaceutical facilities still rely on rigid ERP systems and spreadsheets to plan their production schedules. These tools work reasonably well in stable conditions. However, pharmaceutical manufacturing is rarely stable.
Equipment goes offline for cleaning. Quality control checks take longer than expected. Staff availability shifts. Regulatory constraints under Good Manufacturing Practices add another layer of complexity. When any of these variables change, a production schedule built on a spreadsheet can collapse within 48 hours. Teams end up in reactive firefighting mode, scrambling to reschedule instead of producing. Valuable capacity sits idle as a result.
This planning-to-execution gap is the problem OPTEL and Kaster Technologies are targeting together.
What each company brings to the table
OPTEL is not a newcomer. Founded in 1989 and headquartered in Quebec City, the company has spent over 30 years building track-and-trace and vision inspection systems for the life sciences industry. It tracks billions of products annually for leading pharmaceutical brands and operates across North America, Europe, Asia-Pacific, Germany, Ireland, India, and Brazil. Its strength is real-time manufacturing data. It knows what is actually happening on the factory floor at any given moment.
Kaster Technologies brings the intelligence layer on top of that data. Its AI-powered planning engine takes the real-time operational picture that OPTEL provides and uses it to build production schedules that reflect actual constraints rather than theoretical ones. When equipment availability changes or a cleaning cycle runs long, the system adjusts the schedule automatically rather than waiting for a human to notice the problem and respond.
Together, the two companies are closing the gap between what a plan says should happen and what is actually possible on any given day.
The results from a real facility make the case better than any pitch deck
The partnership is not purely theoretical. According to the press release, the combined solution has already been deployed at one of Canada’s largest sterile injectable manufacturing sites. Sterile injectable manufacturing is one of the most demanding pharmaceutical production environments in existence. Contamination risks are high, regulatory scrutiny is intense, and scheduling errors have direct consequences for product availability.
The results demonstrated measurable gains in production capacity, workflow efficiency, and schedule stability, all without additional capital investment. For pharmaceutical executives weighing this kind of solution, the sterile injectable case study is the most important line in the entire announcement. It means the technology has been tested in a genuinely difficult environment and performed.
According to McKinsey’s analysis of pharmaceutical operations, the industry consistently underutilises existing manufacturing capacity, with many facilities running at 60 to 70% of theoretical output due to planning inefficiencies. A 20% capacity improvement through better scheduling alone would represent a substantial commercial benefit for any mid-to-large pharmaceutical manufacturer.
Why this matters beyond just one partnership announcement
The pharmaceutical industry is under real pressure to produce more with the same resources. Drug demand is rising globally, driven by ageing populations, expanded access to medicines in developing markets, and the ongoing build-out of biologics and specialty drug manufacturing capacity. At the same time, building new pharmaceutical facilities is expensive, time-consuming, and heavily regulated.
The International Federation of Pharmaceutical Manufacturers and Associations has highlighted operational efficiency as one of the primary levers available to manufacturers facing capacity constraints without the capital for new facilities. AI-driven production planning fits directly into that strategy.
OPTEL’s global footprint also means this solution can scale quickly. Pharmaceutical manufacturers in Europe and Asia-Pacific, not just North America, can access the combined OPTEL and Kaster platform alongside existing automation, inspection, and track-and-trace systems. That integration capability is a significant commercial advantage over standalone planning software that requires separate implementation.
The solution will be demonstrated publicly at INTERPHEX in New York from April 21 to 23, which gives manufacturers a direct opportunity to see it in action before committing.
Sources
- McKinsey — Digital Manufacturing in Biopharma
- International Federation of Pharmaceutical Manufacturers and Associations — Manufacturing
- OPTEL Group — Official Press Release via PRNewswire
Editorial disclosure
This article is based on a press release issued by OPTEL Group and has been editorially expanded. It covers a commercial partnership between OPTEL and Kaster Technologies in the pharmaceutical manufacturing technology sector. Market context is sourced from McKinsey and the International Federation of Pharmaceutical Manufacturers and Associations. Commentary reflects the author’s own assessment. The information provided on this website is for informational and educational purposes only. Our content is derived strictly from verified online sources to ensure accuracy and objectivity. This analysis does not constitute financial, investment, or professional advice. Readers are encouraged to consult with qualified professionals before making decisions based on this information. For more information, please see our full DISCLAIMER.
