The Challenge of Grid

By CIOinsight

IT and Pharmaceutical Data: Finding Needles in Haystacks

Knowledge management is still an elusive concept for many CIOs, but not in the pharmaceutical industry, where collaboration and high-speed data discovery is key to future profit. Daniel E. Klingler, Ph.D., as CIO and senior vice president of Information and Knowledge Management for the Worldwide Medicines Group at Bristol-Myers Squibb, oversees all of the business processes that are part of the company's pharmaceutical business. Klingler has responsibility for developing, delivering and supporting all of the applications that are used within the pharmaceutical area, including scientific R&D. CIO Insight spoke with him recently about the role of IT in the drug business—and how good project management rules can help speed results.

In the pharmaceutical industry, time is money—and the race to future profit will be won by companies that can use IT to sift through data faster, and shorten time to market. In that sense, pharma is leading the way when it comes to thinking up new ways to use KM to bolster the bottom line. How do you see your role in this arena?

The businesses challenges we face in pharmaceuticals are becoming more numerous, more complex and much tougher. When I came to Bristol-Myers about four and a half years ago, I kept hammering home the point that the pharma business today demanded three things: changes in the way people worked, changes in the processes that they used, and changes in the technology needed to support it all.

As a result, we've launched a fairly large number of large and complex business change initiatives. I don't want to call them information technology initiatives because they're really business change initiatives, integrating people, integrating data, integrating processes across geographies and assumptions.

Historically, most people in IT—unless they came out of formal engineering backgrounds—tend to learn their project and program management skills on the job. There's still a fair amount of management-by-the-seat-of-your-pants going on in that regard, when people get thrown into big projects.

When I first came here, I initiated formal, quarterly portfolio reviews of all of the major projects that are in our IT portfolio. In reviewing these, we spent an awful lot of time assessing how our projects were being managed, what risks are involved and the challenges that any project faces. We also ask ourselves what are we doing to minimize those risks, and so forth.

About two years ago during one of these portfolio reviews, there was a groundswell of complaint from the staff, that they were being constantly moved around on new projects. We'd have large groups of people being brought together to work on projects, and we lacked a common vocabulary, we lacked a common framework for working together. We somehow needed a grounding in project management that we all could share and identify with, and that we could all put into place.

So there was an appeal, in essence, from the staff. There was a recognition on the part of my management team that if we were going to deliver some of these large and influential initiatives, whether in R&D, manufacturing, or sales and marketing, that we needed to have more sophisticated and standardized IT project management process tools.

Consider the drug discovery area, where the ideas for potential new drugs come forward. We have a large number of biologists and chemists who work to take ideas for new drugs from the idea stage to at least the point where we can evaluate whether we think those potential molecules are going to be safe and effective in humans and, thus, could at some point go into human testing.

Historically, drug discovery has been kind of a cottage industry. Lots and lots of people and lots and lots of labs are doing lots and lots of different things, generating a lot of information in notebooks. But there are so many different kinds of information that are used to develop an effective drug, that nobody has ever really had a view to any of that.

The biologists see their own data, the chemists see their own chemical tests. People who are involved in toxicity testing see their own data. People who are involved in the pharmacokinetic testing see their own data. And there hasn't, in essence, been any way of integrating or aggregating that information so that effective decisions could be made about which compounds to bring forward and which not.

Well, that kind of cottage-industry approach was okay when we had people working in labs developing maybe one new compound a week. But with the massive sort of high-throughput chemical generation and screening technologies that are in place right now, we can craft 10,000 new molecules a week, 100,000 new molecules a month, and the volume of data is just overwhelming. So we put a set of technologies in place working very, very closely with our colleagues in drug discovery to standardize a number of aspects of the drug discovery process. We wanted to make sure that the people who are working on that process understand their roles, and then integrate all of that data. Anyone who is involved in the process has full visibility to all of the data necessary to support the development of these potential drugs.

?So whether it's a chemist, whether it's a biologist, whether it's a laboratory manager, whether it's a clinician, they all have access to all of this data fully integrated. So when someone says, "I need to know about the performance of a particular molecule," all of that information is aggregated and there are decision-making tools that support decisions about whether to take that potential drug into further testing.

You could call this stuff knowledge management. In essence, it supports the way that drug discovery as a discipline is done, which is about managing knowledge. It's about having a full set of analytical capabilities in place so that we can look at this information appropriately.

Increasingly, IT is becoming mission-critical in drug discovery.

Well, that's certainly true in R&D. At the end of a research and development project, the outcome of any project is really information, and what we do in R&D is process and sift through and analyze massive amounts of information.

Also, the genomics revolution has been on the one hand a real boon to our business but, on the other hand, it has been a tremendous challenge because what used to be a kind of cottage industry has become highly systematized simply because of the volumes of data that we are generating. One of our challenges is to make sure we're building data warehouses and not data landfills. Given the volume of information that we're having to deal with right now, you could not do research and development in this industry without massive investments in information and technology.


' Data Boom">

Pharmaceuticals' Data Boom

Just how much more data volume are we talking about in terms of what systems today are handling versus what they're going to be asked to be handling tomorrow?

Probably a simple thing to do would be to talk about how many individual molecules historically have been synthesized and tested by companies and how many are being synthesized and tested today, and how many will be synthesized and tested in the future.

When I first entered this industry, in the early 1980s, a good-size pharmaceutical company would bring out hundreds of compounds, maybe a few thousand compounds from their drug discovery laboratories every year and test them.

Five years ago, that number—for a company that was doing extremely well—might have been 10,000. Today, companies are synthesizing and testing 10,000 in a day, hundreds of thousands a month. The issue we had then, but have now even more critically, is this: How do you find the needle in a haystack when you're dealing with those kinds of numbers?

We've gone from a scenario in which maybe you're dealing with hundreds of these sorts of research efforts and data points, most of which were in laboratory notebooks, to now being able, easily, to fill a terabyte of storage every couple of months with the amount of information that we're generating simply from our drug discovery efforts.

Data warehousing really got its start in our company primarily in the sales area because we have bought a lot of sales data from various sources, and we also generate a lot of data internally from the interactions our sales representatives have with customers and with physicians. But we are at the point now where the data warehouses that we have in place in R&D far exceed in size the storehouses we have to deal with in the sales and marketing arena. That's because of the advent of combinatorial chemistry techniques, the high throughput screening that we do, and the genomics and proteomics testing that we're doing.

There are companies out there now that are coming up with ways to use information technology to help sift through complexity.

You can't scale the people fast enough to keep up with the growing demands for information. Server management is one example. Storage management is another one that's a huge challenge for us because, again, you know, I talked about the data mining, data warehouse, data landfill analogy. We were filling mass storage at a rate that was faster than, frankly, our people could maintain it unless we were using the kinds of IT tools that we spoke about.

Where the complexity management is still very, very difficult is more around complexity of business processes and mapping of those processes, optimizing those processes, and then implementing technology to support those processes. That's where it still falls in many cases to groups of subject matter experts, in some cases with butcher paper on the walls of conference rooms to figure out what are the best processes to use. That's where we bring a lot of our own subject matter experts to bear. But yes, we're looking at those kinds of tools, but more in the back-end infrastructure area.

Another thing that we're doing that is proving very interesting is looking at a number of algorithms, especially in the research area. If we could apply them, it would have great value to us in speeding new drugs to market and also in allowing us to identify potential advantages of liabilities of some of the compounds that we want to develop. I'm talking mostly around molecular modeling, chemical simulation, biological simulation kind of work.

But the problem that we have is that even with supercomputers, many of those kind of algorithms can run for weeks if not months. What we have done recently in our drug discovery area is to begin to implement what we call grid computing, which lets us take massively parallelizable problems, break them into relatively small pieces, distribute those pieces to hundreds if not thousands of personal computers, and use idle cycles on those personal computers to do the kinds of simulations that ordinarily would have been done on a supercomputer.

If you think about it, we've got incredible amounts of CPU capacity in our PCs, yet most of the time PCs just sit there, and the fans run but they don't do much. What we've done is take a huge amount of that personal computing capacity without intruding on what people are doing at their desktops or benchtops, and we're harnessing that to tackle some of what has historically been, frankly, unsolvable problems, because of the computational load.

The Challenge of Grid


The Challenge of Grid Computing

Your look toward grid computing is intriguing. Down the road, how does Bristol-Myers Squibb hope to tackle this?

We have partnered with a firm called Platform Computing, and we are using their software and then customizing some of our own scientific algorithms internally to run on their software. So this is not something we're doing solely on our own.

There also are a number of different firms—some large like IBM, some that are small venture capital funded firms—that we are talking with about how we can make use of some of this kind of technology. But so far we're dealing with one particular vendor, and we're customizing a lot of our own analysis algorithms to take advantage of the technology.

One other term that's tossed about freely these days is the real-time enterprise. How does that impact Bristol-Myers Squibb?

Well, I guess we don't talk about it very much, but we do sort of assume we live it. In different parts of our business, there are different time scales. For instance, on the one hand, drug development is a very lengthy process. Historically, it's taken on the order of 12 years from the time that a drug is a concept in someone's mind's eye in a laboratory to the point where that drug is actually available to patients. We are decreasing those time lines significantly, but within that there's a lot of almost real-time work that has to go on in terms of the way we manage the trials that we do, in terms of the way that we manage our chemical processes.

If you talk about what are the critical success factors for companies within the pharma industry, I think that there are really two. One is innovation, and the other is process excellence, and process excellence is embedded with dimensions of speed, quality, time, and so forth.

It's been made very clear by the marketplace and by regulatory agencies worldwide that developing the fifth, tenth, or twentieth look-alike compound to something that is already on the market is not going to be the wave of the future, that they would be something that people are not going to be willing to pay for, governments are not going to be willing to pay for, HMOs are not going to be willing to reimburse for drugs unless they are truly novel and address an unmet medical need.

So one of the major challenges that every pharmaceutical company has is the challenge of innovation, and that comes back to excellence in research and development.

The second challenge, as I said, is the process excellence challenge, because people have to be fast, they've got to be nimble, and we have to be able to do more and more of this kind of work at lower and lower unit cost. In many ways what is happening in the pharma industry right now with some of the consolidations is that people are looking for critical mass. People are looking at the number of critical trials that have to be done.

The amount of work that's got to go on in drug discovery in order to support this kind of innovation can only be done with larger numbers of people, with larger facilities, with larger budgets. So the challenge is going to be how do we, as an industry, lower the unit costs while still supporting the kind of innovation that we need in order to bring novel new drugs to market?

Are Mergers the Answer


Are Mergers the Answer?

Is this necessarily a merger strategy or do you think companies can do it alone?

Well, the funny thing is if you ask 10 companies, you'll get 10 different answers. I'm not convinced that scale is the answer. Strictly from a financial standpoint, if you go back over the last 10 or 15 years and look at whether companies that have merged have returned greater value to their shareholders than those that have remained independent, I think the data would say that the companies that have remained independent are at least as financially viable, if not more so than the ones that merged.

Now there's a bit of a chicken-and-an-egg situation there, because in some cases the companies that merged probably merged because there was some sort of inherent financial weakness. But mergers clearly have not been a panacea. You can't point at all the mergers that have been done and say, "Well, gee, this has been the answer to whatever the challenges are for the pharmaceutical industry."

I'm also not convinced that mergers in and of themselves are an aid to innovation. In some ways, the bigger organizations are harder to manage than smaller ones and less nimble than smaller ones. So I think one of the challenges is this: How can you use technology to give the kind of scope and scale that perhaps you would also get through a merger, but retain the kind of nimbleness that some smaller companies have?

And your answer?

My answer is that smaller is better. Bigger helps in some situations, but companies that attempt to remain independent, I think, are going to be the winners.

You take the view that project management can help speed time to market.

One of the erroneous views that is held is that if you put all this project management discipline in place, somehow you're going to slow projects down.

I disagree. The one thing I have to do is make sure I'm doing the right things, and that's what portfolio management is about. The other thing I have to do is make sure I'm doing them right, and that's what project management is about. And by doing the job right, in fact, we are able to deliver more quickly.

But the more important thing is that we deliver within budget, and even more important than that, in an industry like ours that is heavily regulated, is that we deliver with the appropriate measure of quality. If we deliver a system or business capability and it is somehow flawed or it somehow does not stand up to regulatory scrutiny, we simply cannot use it. And so what this effort was about was not just to address the time dimension but the cost and quality dimensions as well.

We went out and did an RFP and looked at a number of project management service providers. We partnered with a group internally that is really our internal training organization for Bristol-Meyers Squibb called the Productivity Development Center. We worked with Boston University to create lectures delivered by several of us Bristol-Meyers Squibb executives that became part of the management training course itself, so that we're delivering this course in a way that meets our needs. I and some of my colleagues go into the course, do sessions on negotiation, risk management, conflict management—all of which are part of effective project management.

We have now been through five training sessions, and we will have about 120 people who have gone through this training. And what we have done is target this toward people in our information technology and information management organizations who have significant project management or program management responsibilities.

As a result, we've built a whole cadre of people who have the same set of techniques, who have the same vocabulary, who have the same set of forms and processes that they follow for project management, so it has given us a tremendous amount of flexibility as well in terms of moving people around and knowing that they're going to be effective when they hit the ground.

How much of this kind of thinking was initiated during the days of Y2K? Project management offices set up to tackle that problem are, in many cases, being used to bring more discipline to projects of all kinds.

What I'm talking about certainly builds on that. What I think we were struggling with as a firm is that we didn't have just one flavor of program or project management. We were a little like Hallmark cards, you know, we had one of these for every occasion. And what we needed to do was standardize some of the good work that had been inside. It's always easier to go through that standardization process if you're bringing people in from the outside who are experts in the process and who bring instant credibility.

Now we have quarterly portfolio reviews, and we measure whether projects are on budget, whether projects are delivering on time, and then we have quality standards and quality reviews. Every single project that we do has a budget that is funded by a business area, and if the perception is that they are not getting value for that investment, they simply stop making it.

One of the sort of secondary criteria for success for the work that we are doing is that our business colleagues have been willing to fund projects much more aggressively and at much higher levels than before. And the reason they're willing to do that is because, first, IT works in close partnership with the business and, second, we make the commitment to the business side in terms of the timeframe in which we'll deliver, the cost at which we will deliver, and the quality of our delivery, and we meet or exceed those targets.

And as long as we continue to meet or exceed those commitments, what we find is people are willing to make investments. If we weren't doing those kinds of things, they wouldn't make those investments.

If you're doing your projects on time and on budget and the quality is good, what's the significance of that competitively? Does that mean you can get new drugs to market quicker?

Sure. Every major initiative that we have under way right now has a set of business metrics associated with it that deal with one or all of the following: They deal with capacity, meaning how many drugs can we discover and develop simultaneously with our budgets in the work force we have available to us; speed, meaning how long does it take us to identify new compounds that perhaps we want to take into testing, how long does it take us to take those drugs all the way through human testing and then to file them with regulatory agencies; and then the third is quality—are we bringing forward potential new drugs that are going to be of sufficient quality that they're going to, in essence, meet a significant unmet medical need and, thus, hopefully be financially advantageous to us as well?

Every major initiative that we're working on now has its own set of business metrics associated with it. Now, because these are relatively complex, relatively large, multigeographic, multifunctional initiatives in many cases, they are not going to be successful unless we're dealing with the three dimensions of people—meaning, are we organized correctly to deliver that business value, do people have the right skills to deliver that business value, and are they trained appropriately in the processes that they use in order to deliver that business value.

Next is process, meaning, do we have a well-defined and standardized set of activities that support the process, whether it's drug discovery, drug development, manufacturing, what our sales people do in the field? And then when those processes are codified, do we have a set of technologies that support the efficient and effective execution of those processes?

By making sure we are delivering the technology on budget, on schedule, with the right level of quality, then we contribute to the realization of those business objectives. We have some thoroughly aggressive objectives in terms of reduction of cycle time in our clinical development area, increase in capacity of our research groups and effectiveness of our sales force out in the field. Again, everything we do has to support those business objectives.

But the only way those things could happen is if we were putting the technology in place that made those processes executable and enabled the people to work the way they need to work.

This article was originally published on 10-23-2002