Scroll through LinkedIn and you'll see plenty of posts singing the praises of Process Analytical Technology (PAT) — the benefits, the productivity boosts, the data-driven insights. And, they're absolutely right. PAT has become a cornerstone of innovation and efficiency in pharma manufacturing.
But here’s what’s often left unsaid: most of these success stories come from Big Pharma.
Large pharmaceutical companies typically have the capital, infrastructure, and talent to implement robust PAT systems. Many of them use a combination of strategies: a traditional PAT setup supported by backup analytical labs, or increasingly, a hybrid model that blends PAT with mechanistic modeling. The latter is gaining traction and proving to be extremely effective.
Some organizations are even pushing boundaries by relying solely on mechanistic modeling without real-time physical measurement (a bold move), and in my view, a high-risk strategy. Skipping direct measurement in favor of purely theoretical models might offer cost savings, but it compromises process visibility and control.
The Challenge for Smaller Players
While these advances are exciting, they highlight a growing divide in the industry.
Smaller pharma companies and CDMOs (Contract Development and Manufacturing Organizations) often don’t have PAT teams, or even a PAT process, in place. And that’s not just an oversight; it’s a symptom of deeper challenges:
- High upfront costs:PAT requires specialized equipment, infrastructure, and training.
- Ongoing maintenance:Once a model is built, it needs continuous validation and updates, which adds to the long-term cost.
- Expertise gap:Recruiting and retaining PAT talent can be a major barrier for smaller organizations.
As a result, these companies are falling behind, unable to access the same level of process insight and optimization that their larger peers enjoy.
Moving Forward
If the industry is serious about digital transformation and continuous manufacturing, we need to address this gap. That might mean:
- Developing cost-effective, scalable PAT solutions for smaller companies.
- Creating shared infrastructure models, perhaps led by CDMOs or regional hubs.
- Investing in training and support to build the necessary expertise outside of Big Pharma.
The future of pharmaceutical manufacturing shouldn’t be reserved for those with the deepest pockets. We need a more inclusive, accessible approach to PAT — one that brings innovation to the entire industry, not just the top tier.