Why Trust Is the Biggest Barrier to Supply Chain Transparency

Pharmaceutical supply chains have long been designed primarily for regulatory compliance rather than speed or adaptability, often resulting in rigid, slow-moving operations. According to Hari Kiran Chereddi, CEO of HRV Pharma, that model is rapidly changing as the industry adopts intelligent technologies that make supply chains more responsive, connected, and patient-focused.

At the core of this transformation is AI-enabled orchestration. Instead of relying on monthly or quarterly reviews, modern systems now connect quality, manufacturing, regulatory, and operational data in real-time. This continuous visibility allows organizations to predict deviations before they escalate, automatically trigger corrective actions, and even pre-validate documentation ahead of audits. The result is faster decision-making, stronger compliance, and improved patient safety, while also supporting commercial performance.

A second major shift is the way data is shared and aligned across the ecosystem. Manufacturers, contract manufacturing organizations, logistics providers, and regulators are increasingly operating on interconnected platforms, enabling better coordination and faster response to disruptions. This level of interoperability reduces silos and ensures that critical information flows seamlessly across partners, accelerating execution and reducing risk.

Kiran Chereddi also highlights the growing role of federated learning in AI orchestration. This approach allows multiple manufacturing sites to train and benefit from shared AI models without centralizing sensitive or proprietary data. By preserving data privacy while still enabling collective intelligence, federated learning helps scale innovation across global networks.

Together, these pillars—AI-driven orchestration, ecosystem-wide data connectivity, and federated learning—are moving pharmaceutical supply chains away from static pipelines toward adaptive, self-correcting systems. The ultimate objective is to ensure that medicines reach patients faster and more safely, while maintaining rigorous compliance and unlocking greater operational speed and resilience across the industry.

He also comments on how an asset-light, fully virtual model can improve regulatory speed and manufacturing quality compared to traditional API production frameworks; the challenges than remain in ensuring transparency, audit readiness, and long-term scalability across a decentralized supply chain; and much more.

A transcript of his conversation with PC can be found below.

PC: As the industry increasingly adopts digital and data-driven models, what challenges remain in ensuring transparency, audit readiness, and long-term scalability across a decentralized supply chain?

Kiran Chereddi: It's funny how you asked that. In fact, I actually was talking to a bunch of college kids at one of the Indian Institute of Technologies in India a few weeks ago. There I was telling them, saying, guys, today's biggest challenge in this whole landscape is not technology, it's the trust, and for me, the decentralized network has a good part and also a bad part, where everybody says, oh, this is decentralized. I want visibility.

They say, I don't want to lose control of my data. And then people get very touchy about my data can kind of situation. What we tell people is that we actually work on federated intelligence, where we say data stays where it is generated, and only the insights actually move on. That's where we actually give that comfort to these people. That way, the intellectual property security is about creating a single version of truth that everyone in the system is actually able to see, and whereby what's happening is that the audit readiness is something that is automatically built in, where from batch release to a corrective, preventive action closure, all this is automatically logged in, timestamped, and you can't play around it, so the moment the auditors are there, the data is automatically organized.

Data is already available, but from there, we tried it with one plant, two plants, three plants. Today, we have more than 15 plants which have good manufacturing practices, US FDA approvals. Now we're actually going ahead and putting the whole digital twins of each of the partners. How is it that we can allow this scale without adding the compliance complexity that's coming in?

For us, the transparency isn't just about the dashboard that you see, because a lot of people think it's like a Salesforce dashboard, and you see everything is green. For me, it's about, how is it that AI and data help in one way, but culture and compliance mindset is something that keeps it continually sustainable, and that's something the more you keep doing or repeating some of these things, it's not a new invention. It's about how you create the movement.

How are you able to design some of these things? How are you able to get these things out? How is it that the whole trail moves through the unified network, ensuring everything is in compliance? So that's what we've been able to see. The model was a pipe dream a few years ago, but now, with the revenues and plants on the platform, here we are.