Interview with Bob Di Scipio, Aegis Analytical

Aegis Analytical Corp. ( publishes manufacturing process optimization software for the life sciences industry. The company's solution helps biopharmaceutical firms monitor federal compliance matters, supply chain issues, production costs and product quality. Headquartered in Lafayette, Colo., Aegis is a late-stage, privately funded enterprise. Its backers include 3i Ventures, Future Capital AG, Lafayette Equity Fund, Merck Capital Ventures and Skyland Capital.

To learn more about Aegis, Techrockies recently spoke with its president and chief executive, Robert M. "Bob" Di Scipio.

Your Web site frequently uses the term "discoverant" when describing your software solution. Could you elaborate on what that term means?

Bob Di Scipio: Our approach to data management is to put users in command of the access of data. People that are charged with making the data actionable—those doing analysis and statistical work on it—are typically disconnected from their data sources. They usually rely on IT personnel to help them retrieve data from repositories.

What we’ve created is a way to get to the data through a roadmap that’s very familiar to users, and it’s been created with the manufacturing process in mind.

What’s familiar about your interface?

Bob Di Scipio: Users are able to simply point and click on process steps and retrieve the data that relates to the process step that they want to investigate. And, with another click of the mouse, they can quickly move into statistical functions. So, you have one holistic environment for both data access and data analytics and aggregation.

How does your solution change or improve upon the status quo?

Bob Di Scipio: The current situation is that, in a manufacturing environment, you have different data silos, or repositories, from various vendors. You have manufacturing execution systems, ERP [enterprise resource planning], data warehouses and data historians, and they may come from companies like SAP, Oracle, Rockwell Automation, Werum, OSIsoft, Aspentech—all of which have done a great job of helping capture pertinent data.

The issue is that, when you want to analyze the root cause of an outcome or a process, sometimes you need to look at data that spans from the raw materials part of the process to maybe a fill finish—the terminus—of the process. The data that you need to analyze is in different silos, and those silos were created by different vendors.

Until now, there has not been a cohesive, unified view of all the data. What we try to do is provide a sort of Switzerland-like approach so that we can integrate and provide access to all the data, from whatever vendor, from whatever source and from whatever data type. There are many different data types, and they can be difficult to correlate.

Is this a SaaS-based solution we’re talking about?

Bob Di Scipio: We’re a client-server technology. We can publish results to the Web, but our product is one environment, one desktop, that allows you to get to the data and perform the analysis from any of these data sources.

Our software is not customized, but the views of data that someone might want to see are a custom process. In other words, if someone’s got SAP and Oracle, that might be one set of views, and if someone’s got SAP, Oracle, Rockwell and Aspentech, they might have more data and they might need to see more process steps.

It depends on the complexity of their process and what they need to do their jobs. Ultimately, what we do is create roadmaps to data that might include 300 critical data points and or more than 7,000.

Where you at right now as far as funding?

Bob Di Scipio: Almost $30 million has gone into the company. I came on board about three years ago and actually invested some of my own money along with the venture fund of Sanofi-Aventis, a large Parisian-German biotech company.

We’ve essentially doubled our revenue the last couple of years, and we’re at the point now where, in order to meet customer expectations and accelerate product growth, we need to add more resources. So we’re looking for approximately $5 million in funding to expand sales efforts and so forth.

Even so, we were cash-flow positive in 2007.

What round of funding would this latest round represent?

Bob Di Scipio: This company has been around for nearly 10 years, so this is late-stage funding.

Up to now, we developed a product and had it vetted, tested and installed. Now, it’s being improved upon. We’re actually in our fourth generation of the software.

It’s a very long sales cycle, but once we get in, we’re very sticky.


Bob Di Scipio: A lot of these companies thought they could solve their problems with established vendors, and, in most circumstances, they’ve tried many other product offerings from other vendors.

Now, those companies are coming around to us and saying, “You know, we still can’t get to the data. We still can’t correlate the data the way we want and we’re trying to leverage the return from these prior investments we’ve made in data collection, but they’re focused on the collection piece, not so much the immediate access and aggregation.”

And your product delivers those?

Bob Di Scipio: Yes, but only when you want it. It’s a read-only format and we’re focusing on the life science base right now. We’re also looking at the chemical and food and beverage industries.

In the life science base, you have to be careful not to replicate source data. You want to make sure that there’s data integrity. We employ a read-only access so only the data that’s needed at that time is copied.

You’re basically looking at a flexible, ad-hoc investigational exercise and only selecting the data that you need for analysis at that time. [The data] can then be stored, revised and published.

A lot of companies use that data as the basis for their annual product reviews. In the pharmaceutical industry, you basically have to do an annual report on every product, and several companies have reported that, after using our tool throughout the year, they’ve cut down the cost and the time of doing annual product reports by 95 percent.

You keep referring to the pharmaceutical industry. Is that your base?

Bob Di Scipio: We’ve got many of the top life science companies in the world [as clients]. We have Eli Lilly, Baxter, Abbott, Genzyme, Biogen and a number of other life science companies. Some of them have just started with us this year and are in a pilot phase. Others that just started this year have already purchased additional licenses, and several are in rollout.

So is the biopharmaceutical sector becoming your niche?

Bob Di Scipio: I would say the reason we’ve been a differentiator in life science is that, if you manufacture in the life sciences, you need to fully characterize the nature of each process that you’re running across the enterprise, so you need a granularity about the data and you need an understanding of the physics, biology and chemistry that’s going on within a bioreactor or on a production line.

By its very nature, ERP is not designed to provide that particular characterization of a process. It’s not designed to make the data immediately actionable. It’s more designed for data capture as opposed to providing a contextual understanding behind the data.

Essentially, what our users are doing is looking for the root cause of outcomes. Business intelligence dashboards provide a descriptive analysis. They’re designed to show what is going on. But if you need to look further and ascertain the “why?”, then you need to conduct an investigational analysis, as we call it.

Would your technology lend itself to other verticals?

Bob Di Scipio: Yes, we can take this [technology] to other places. Essentially, the software is applicable to other verticals where you have process variability and data is collected and then reviewed to determine the root cause of variability. In fact, we’ve had inquiries from chemical companies, food and beverage companies and steel producers that have had trouble managing their data.

Basically, anywhere that data management and process variability come together, that’s an opportunity for Aegis’ discoverant software.