Advancing Pharmaceutical Quality through Integrated Digital Systems and Collaborative Scientific Innovation

PharmTech recently spoke with Saharsh Davuluri, Vice Chairman and Managing Director, Neuland Labs, to get his perspective on trends that shaped pharmaceutical development and manufacturing in 2025 and where things are headed in 2026. In this part 2 of our three-part interview, Davuluri explores a digital transformation within the API manufacturing sector. He observes that while the API industry has historically been slower to automate than other chemical sectors, a new paradigm is emerging through the adoption of AI-based tools and digital workflows. He notes Merck’s Synthia tool for route synthesis and equipping a new R&D campus with advanced parallel synthesis equipment to better mimic plant-scale production.

Davuluri’s ultimate vision is a fully paperless manufacturing environment driven by electronic batch records and a manufacturing execution system, which ensures complete traceability and product quality. Davuluri highlights the practical impact of these advancements for the workforce, stating: "This is real, and this is something that's going to make life a lot easier for process chemists who are looking at making scalable processes when it comes to manufacturing."

Central to this transformation is a shift attracting and retaining scientific talent through fostering a "knowledge hub" in which scientists collaborate on innovative processes for new chemical entities. Unlike traditional roles that may feel academic, scientists in such an atmosphere are encouraged to go into the plants to oversee scale-ups, allowing them to see their designs evolve into actual medicine for patients. This focus on high-level expertise marks a significant departure from traditional industry models. Davuluri explains, "We are living in a world where it's no longer about labor arbitrage; it's about knowledge arbitrage."

Access Part 1 and Part 3 of this interview!

Transcript

Editor's note: This transcript is a lightly edited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.

We are starting to see that there is a clear trend in using digital tools and AI for process development and scale up, but especially when it comes to API process development, scale up and manufacturing. What we are seeing is adaptation of AI-based tools. I think there's a Merck tool called Synthia that Neuland’s been using now; helps us, you know, identify the most appropriate route of synthesis for making an API.

That's a tool that we've been using now for quite some time and, right now, Neuland's in the process of building a new R&D campus in Hyderabad. As part of our plan, we intend to equip all our labs with these parallel synthesis equipment called Mya 4 by this company called Radleys.

The idea would be to use Synthia as an AI tool for coming up with the right process and then use these automated synthesizers at lab scale, which actually do a fantastic job of mimicking plant scale manufacturing, and then use eLab notebooks to capture all the data from these modern lab equipments and essentially give us a fully prepared recipe with no human intervention, which is kind of locked and loaded to plug into a manufacturing execution system, or an MES, at plant scale. This is real, and this is something that's going to make life a lot easier for process chemists who are looking at making scalable processes.

When it comes to manufacturing, I think there's a lot of interesting developments. You know, the API manufacturing sector has not automated or modernized as much as the other industries like chemical manufacturing has. It's time to kind of make some moves over there. So we are starting to see a better adoption of DCS systems in our manufacturing environment.

You know, our vision for Neuland would be to eventually move into a paperless environment where we would have a manufacturing execution system coming out of our ERP telling us what's the recipe, and then, you know, actually plug it in and get the entire manufacturing done through electronic batch records so we don't have any paper and there's complete traceability and the ability to kind of assure the quality of the product for the patients. I think some of these will take time, but I think there is a clear crystallization of how these tools can really help us start embracing modernization for API manufacturing.

There's always dearth of talent. And I think in light of these technological advancements, it's very important to figure out ways in which you can not only attract, but retain top talent, especially on the scientific side… try to create an ecosystem that nurtures scientific talent, try to create a knowledge hub where, you know, there's a lot of scientific learning other than just kind of, you know, the grind of delivering projects and getting stuff done. There's a lot of community-based scientific discussions, and we have a very interesting mix of scientists. Most of them are Indian, because we are based in India, but a lot of them are trained in different parts of the world, and therefore they approach science from a different perspective.

And we have a very open culture where we not only look at protecting IP, but within the framework of IP sensitivity, we also encourage this talent pool to exchange ideas on what might be an interesting way to crack a problem. A big part of what we do as a CDMO business, we spend a lot of time working with innovators, hand in hand, trying to develop novel, innovative processes for new chemical entities. And a big outcome of doing creative work over there is that our scientists get to put their names on patents, although these patents are attributable and owned by our customers, which is the, the pharmaceutical companies, the names of the authors are very frequently the scientists working at Neuland who have contributed to that IP. And that creates a very high level of attraction, especially in an industry, in an area, like India. There's a lot of generics business and, therefore, it creates an additional motivation.

The other thing I would say is, you know, there's a lot of emphasis on successful scale up and delivering product to the patient because Neuland is… you know, 90% of the work we do is commercial manufacturing, and therefore when a scientist wants to come and work for Neuland, they recognize that they are actually coming and working for a company that is likely to put a pill in the hands of a patient and not necessarily just doing work in the lab, which might seem academic at times.

So the ability for a scientist to go stand in the plant and oversee a scale up, that's something that does not happen in a lot of organizations. But we have started to encourage our scientists to go into the plants, oversee campaigns, learn from the engineering groups, learn from the manufacturing groups on how their process that they have designed is performing in the plant scale.

That is a unique exposure, which also stimulates a lot of scientists, and that's also something that helps us attract the right kind of talent. We are living in a world where it's no longer about labor arbitrage. it's about knowledge arbitrage. And we cannot operate in the old paradigm where… Neuland is located in India, which is a developing economy and therefore there are these labor arbitrage opportunities. I think that does not work anymore and therefore, you know, trying to get to a paradigm of knowledge arbitrage.