David Stauffer (PhD '89), Chemical Biologist, Data Scientist, and IT Consultant

The massive scientific, administrative, and business effort to bring pharmaceutical drugs to market presents unique challenges in information technology and data science. Biological research itself has become extraordinarily data-intensive over the past two decades, and the successful execution of drug discovery requires expertise in both life sciences and data sciences. Enter Dave Stauffer, who, as a consultant for CGI, works with companies to establish the most robust IT systems in support of their pharmaceutical research efforts. As he emphasizes in the discussion below, although he no longer works as a bench scientist, his area of expertise requires a fluency in chemistry and biology so that science objectives can be computationally supported. It is a vital component of the pipeline from basic science to life-saving medicines.

From his initial interests in medicine as an undergraduate at Penn State, Stauffer became fully invested in fundamental research in chemistry as a member of Dennis Dougherty's lab at Caltech. Both generationally and scientifically, Stauffer became part of Caltech's revolutionary contributions in the creation of chemical biology, a discrete field that can be understood as the application of a chemist's ability to manipulate molecules in order to explore biological phenomena. Following a postdoctoral appointment at Columbia, Stauffer's strongest opportunities were in industry, and he developed his nascent interests in computer systems. Reflecting on his Caltech education, Stauffer connects the Institute culture of problem-solving and the art of achieving the impossible, with his record of providing important consulting in support of major pharmaceutical companies.

DAVID ZIERLER: This is David Zierler, Director of the Caltech Heritage Project. It is Friday, October 20, 2023. It is great to be here with Dr. David Stauffer. Dave, it's great to be with you. Thank you so much for joining me.

DAVID STAUFFER: Thanks for inviting me. This should be fun.

ZIERLER: To start, please tell me any titles and institutional affiliations you currently have.

STAUFFER: I am a Senior Consultant with CGI. CGI's an acronym that formerly stood for Consultants to Government and Industry.

ZIERLER: What kinds of things does CGI do?

STAUFFER: CGI has consultants all around the globe, and I would say we are involved in all manner of industries. We've got different markets that we serve. I know we're strong with financial services, we're strong with government services. My particular involvement is more on the life sciences side of things. Prior to being employed by CGI, I was with a smaller company called Paragon, and when Paragon merged with CGI about five years ago, I was part of that merger. And I've been involved in pharma IT as a consultant/business analyst for about 12 years now.

ZIERLER: Who are some of CGI's clients? Are you working both in a government and private industry space?

STAUFFER: I'm just in the private industry space, the commercial space, as they call it. The clients are any of the big pharma that you might know about, whether it's Pfizer, GSK, or Merck. I've worked on projects with many different large pharma. I would say that we're fairly active across the pharmaceutical industry, at least in terms of the branch of CGI that I'm most familiar with.

IT Consulting in the World of Drug Discovery

ZIERLER: What kinds of expertise do you bring to these partnerships? When you're a consultant for industry, what are they looking for from you?

STAUFFER: Mainly, I would say, CGI is mainly IT consulting, a lot of strategic consulting. What they're looking for from me is help with managing the data related to discovery, related to commercialization and manufacturing. That data can be related to chemistry, related to biology, related to all of the processes that it takes a pharmaceutical company to go from identifying candidates for therapies to characterizing them, clinical trials, bringing them to the manufacturing shop floor in order to take your drug and make it ready to sell to patients.

ZIERLER: Do you get to be a scientist at all in this role? Have you transferred to data science or even systems engineering? How is your Caltech experience and expertise relevant in what you're doing now?

STAUFFER: That's a great question. I'm not a bench scientist in the sense that I'm not the chemist, biochemist, or biologist who is trying to discover or otherwise optimize the manufacturer of small molecule drugs for biologics or vaccines. I've kind of jumped over to the IT side of things. But where my Caltech background comes in, particularly in Dennis Dougherty's lab, I was in the lab, making molecules with Dennis, but there were others in his group that were doing computing. This was 30-plus years ago, so the computing back then was a lot different than what you could do today. I would say the arc of my career has taken a lot of the different things I've learned from Caltech and allowed me to bring them forward to different aspects of my career. Mainly, I see myself as something of a translator for science and IT. Scientists in the lab are trying to find new therapies or optimize the production of those therapies, and I'm able to help them understand what IT tools are available to serve them. And when it comes to building IT tools, I know who the people are that are going to be using them and what their requirements are. That's kind of placed me in the role of business analyst, to use a generic term. I can help the scientists communicate with those who are going to be building the systems, mainly IT systems.

ZIERLER: Have you always been a computer guy, a data guy? Or is that sort of a pivot after graduate school?

STAUFFER: I think that was something that started in graduate school. Perhaps, it might've started earlier. It's kind of run in parallel. My experience as an undergraduate was mainly focused on hands-on work in the lab as a bench chemist. Similarly, when I was at Caltech, my graduate project was oriented to what we could characterize with molecules synthesized in the lab. As a post-doc, I was also doing laboratory stuff. But running in parallel, there's been, "Hey, do you know how to use these computer systems or computational chemistry tools?" My first job after my post-doc was for a small company called CAChe Scientific, and they had some really cool technology for visualizing molecules in three dimensions. And that was appealing to research chemists, and so they needed to learn how to use these tools. "How am I going to do computational chemistry and 3D visualization of molecules?" I was part of a team that was introducing those tools to biotech, pharma, sometimes even agri-chem, anywhere in discovery and where seeing what your molecules look like can be of value.

ZIERLER: What have been some of the most important technological advances, ranging from computation to instrumentation, even machine learning and artificial intelligence, that really influence what you're doing today?

STAUFFER: I'm not sure of any particular technological advances that have influenced the direction that I've gone. I've done a lot of work with sort of the high-end workstations 25, 30 years ago. In terms of technological advances, being able to take what were really specialist tools and have those become more commonly available, I think that's been a benefit to science. Although, while that was happening, I was moving from computational chemistry into information systems more generally, the management of chemistry and biology data related to drug discovery. And so, going from the standalone workstation systems to more of a client-server architecture. Those server-based systems became powerful enough to connect over networks to a larger number of users so that you didn't have necessarily only the power user–I thought of myself as a power user, and in talking to power users, I was also talking to more scientists who don't routinely go to a computational chemistry workstation and say, "I want to understand how to dock molecules."

The tools did evolve so that, from a client-server standpoint, managing data became something that the bench chemist could do on their own. Rather than computational chemistry, it's, "Hey, I'm making a series of molecules. I need to share what I'm doing from my bench, whether it's through an electronic laboratory notebook," which is something that came relatively more recently, past 15 or 20 years, whereas 20 to 30 years ago, the client-server architecture was being developed to serve the information management side of things and being able to register molecules and reactions. The one company that I worked with starting in 1995, MDL Information Systems, way back in 1978, had pioneered the workstation reaction management system. They actually had a reaction access system before they had a molecule access system. They were pioneering, "How do we represent a chemical structure, both graphically on a screen and at the same time, have it as a set of information that we can understand computationally and informationally so that when scientists need to find out about the molecules they're working on and the relationships to molecules they can buy or compare to what's known across the industry, or later on, across the internet, they have the ability to search and find any bit of information that's available about molecules of interest to them, reactions that can make those molecules, biological properties, chemical properties, and the like?"

As I'm walking through this, I realize that yes, there's been an evolution of technology that's been part of my career arc, going from that standalone workstation model, which evolved to client-server, and now you've got cloud-based, where the servers are no longer inside your institution, whether it's a university or a pharmaceutical company. That cloud-based architecture makes it so, "Hey, I've got a browser. I can do the same types of knowledge-mining that I used to rely on whatever I had available inside my institution or here on my workstation." Now, it's a wide-open environment where the tools have matured or are still maturing to enable that basic question that the scientist has, "What's known about this therapeutic area? What's known about biologics that are targeting oncology? What's known about small-molecule drugs that are antiviral agents that can benefit a wide variety of patients.

Data Science Across Human Health

ZIERLER: You alluded to it, but is your area of expertise, then, relevant across the broad spectrum of drug discovery and delivery? You're not just focusing on oncology, neurology, or pulmonology, it's everything? If it's medicine, and it's human health, what you offer is relevant.

STAUFFER: Yeah, I would say so. It's more from an IT standpoint, where there are tools and systems that make it so that all of those niche therapeutic areas are readily supported, so that when scientists have questions they need to answer or information they need to capture to share with their colleagues or their companies, they have, readily at hand, the ability to do that.

ZIERLER: That means that from an IT perspective, it's all information, and it all is relevant to whatever drug you're talking about.

STAUFFER: In a broad sense, yes. You've used the term data science, and I see myself more of a data scientist than a business analyst, although that's not to disparage business analysts. My background as a scientist–I can speak the languages of chemistry, biochemistry, biology, molecular biology and the languages of information systems. That terminology I use as a translator is brought to bear. I'm not interacting with scientists and saying, "Have you ever considered trying to do this with your experiments?" Mine is more of understanding that these are scientists that want to be able to optimize the conditions for purifying the manufacturing process related to a key biologic for oncology.

ZIERLER: Because your clients are competitors, how do you deal with information that's proprietary? What firewalls do you have to make sure that your work with one company doesn't spill over in terms of what you know in working with another company?

STAUFFER: When I'm working with a client, while I'm not an employee of the client, I'm a consultant or a contractor, I am, in effect, embedded and treated as though I am an employee in terms of having access to the client's IT systems, I have a client laptop that I work with so that I can fully engage with the project teams and any of the other stakeholders that we come across, whether they're scientists or people in regulatory or clinical areas, besides manufacturing or discovery. In terms of firewalls, in effect, by using the client laptop, I'm behind their firewall. I'm using their virtual private network, I have access to their systems, like anyone else. At Caltech, you have a laptop, you have different kinds of training that you go through to make you eligible to get access to certain systems. With each of the clients that I work with, for a given project, I'll get kind of a similar baseline training with each client that does all of the human resources stuff and the onboarding needed to make me eligible to get to the scientific information systems and do the training there that makes me effective as a consultant.

ZIERLER: How much of your work is on-site, and what can you do remotely?

STAUFFER: That's evolved over time. Early on, you'd have to be on-site to do all of the work. Then, as remote work became more prominent through the 2000s, I've been able to work primarily remotely, up to the pandemic. Since the pandemic, it was exclusively remote. Now, I can go back to the client sites as needed. It depends on the nature of the project. I've been with a rolling set of projects that have involved a lot of the same team members. As a consultant, having the familiarity and the credibility with them, I can engage with and meet with them virtually, using the appropriate intranet tools for the client. In short, right now, I'm almost exclusively remote. I'm available to go to the client site as needed.

From State College to Pasadena

ZIERLER: Let's now take it back and establish some personal history. What where you doing before you got to Caltech? What was your area of focus, what opportunities presented themselves that got you to Caltech?

STAUFFER: Well, before Caltech, I was at Penn State. I got undergraduate degrees there. I did a bachelor's in pre-medicine, a bachelor's in chemistry. There was something they had called a simultaneous degree program that you do all the requirements for each degree, then you have to have a certain number of credits above and beyond. I was able to pad my credits by placement exams for Spanish. I had had Spanish middle school, high school, and I placed out of 12 credits' worth of Spanish. You think about how much credits cost today, and those placement exams were worthwhile investments for me. But I started doing undergraduate research as a sophomore with my organic chemistry professor at Penn State's York campus, a gentleman named Ernie Harrison. He got me started in the lab. He also got me aware of being able to take graduate-level courses as an undergrad. When I went up to the main campus, University Park, I was taking graduate courses, and I started working in the lab with Phil DeShong, who was an assistant professor there. I believe Phil is probably, by now, emeritus at the University of Maryland. But in any case, getting into the lab, synthesizing molecules, learning safety in the lab, all of that was great foundational stuff to be doing so that when I got to Caltech, it was like, "Okay, I have some idea of what I can be doing here."

ZIERLER: Being on the pre-med track, were you already thinking about the possible connections from chemistry to biology? Was that sort of already on your mind, even as an undergraduate?

STAUFFER: Yeah, perhaps not in those terms, but yeah. I was looking at having an impact in medicine. I got excited with organic chemistry and saw, "Here's a way you can make molecules." Of course, you understand that drug discovery involves making molecules. At least, that was the primary way back then. Whether it's making the next big molecule that's going to help a lot of people or being a practitioner of medicine in practice or at a hospital, there was no formation of those ideas back then. But I was looking at trying to make a difference through science, whether it's chemistry or biology. In addition to graduate-level chemistry courses, I took some graduate-level biochemistry courses. I think for the pre-med degree, I had to do embryology. That was the most challenging biology course I had at Penn State. In part because the wet labs that we had to do were–you get the idea that in the chemistry lab, there's a lot of clean, neat, organized stuff you have control over. When you are doing biology, your environment of study is moving toward living creatures.

ZIERLER: Life is messy!

STAUFFER: Yes, that's a very good reminder. Another thing that happened at Penn State that had me involved with computing–I took Comp Sci 101 and did punch cards, and that was good to have done, but I was fortunate to be involved with a group of other undergraduates who were in chemistry, biochemistry, bright, enthusiastic, and looking to do some interesting things. One of those was Steve Mayo. We're both Penn State alums. I was aware that Steve was doing some really cool things with computer graphics. And when he got to Caltech, he, and Bill Goddard, and Barry Olafson formed BioDesign. They needed somebody to put their modeling algorithms to the test for small molecules. By the time I was at Caltech and in Dennis's group, I knew some molecular mechanics, I was familiar with those tools, and had used them, so BioDesign asked me if I could do some consulting for them. I would spend a few hours a week helping them to characterize how their molecular modeling package did with small molecules. They were focused on proteins and larger molecules.

Shift from Medicine to Fundamental Chemistry

ZIERLER: How did Caltech get on your radar? Did you know about Dennis Dougherty even from Penn State?

STAUFFER: I did not know about Dennis Dougherty from Penn State. Caltech got on my radar as one of the top chemistry graduate schools in the country. And they also have a strong biology department. You had asked me about the pre-med, and I did apply to MD/PhD programs. I got accepted to none of them. I applied to seven graduate schools for chemistry, and I got into all of them.

ZIERLER: What is the takeaway there?

STAUFFER: The takeaway, I think, was that my undergraduate arc shifted from biology and medicine to chemistry, organic chemistry, and perhaps bio-organic chemistry. And in terms of how I appeared as a PhD candidate, they probably saw, "Strong PhD. MD, we don't know if that's where he belongs." You decide where to go to graduate school, and I had envisioned I was going to do synthetic organic chemistry. And as you're deciding where to go to graduate school, you make a visit to the campus. I remember visiting Harvard and MIT, and it was in the middle of winter, and there was snow up there. And when I visited the West Coast, I visited Berkeley and Caltech on the same trip. I think I also combined that with a trip to UC San Diego. In any case, you get out to Caltech, and it's late January or February, and it's beautiful, so that gets your attention. But more importantly, when I was interviewing and meeting professors in chemistry, biochemistry, and biology, I got introduced to Dennis. He was put on my schedule, even though I didn't know anything about him at the time.

I was aware of Dave Evans and Bob Ireland, who did synthetic organic chemistry. I had heard of Peter Dervan, and I had heard of some of the folks on the inorganic chemistry side. I can recall there were seven of us from Penn State who had applied to all these schools, and seven got accepted to Caltech. I know six of us went there. Another one went to Berkeley. But I remember Harry Gray from the inorganic side of things came to Penn State and gave a talk, and after his talk, we got to go out and meet him. He wanted to meet all of these students that were looking to go to Caltech or another school for their graduate studies. Harry makes an impression on everyone. He certainly made an impression on us. But he helped us start to see that the Caltech environment, you don't get pinned down to any one thing. It's wide open. And that was exciting for me to know that I was going to have an opportunity to do graduate studies with some really top-notch people. When I interviewed, I met Dennis Dougherty, and he told me a little bit about what he was doing.

I was like, "Oh, that sounds neat. I never knew he was doing that." He was relatively new at the time compared to his more established senior colleagues. I believe he was an assistant professor and was about to graduate his first PhD student, Lisa McElwee-White. But what I remembered about Dennis was, "Oh, he's originally from Harrisburg, Pennsylvania. I'm originally from York, Pennsylvania. That's, like, 20 minutes away." He had gone to Bucknell, I went to Penn State. I got to know a bit of his biography. But in terms of deciding to come to Caltech, even though the synthetic organic chemists, I believe, Dave Evans moved on to Harvard before I even arrived at Caltech, and within a couple years, Bob Ireland would go to pursue another opportunity, it was like, "Gee, I guess I'm not going to be doing synthetic organic chemistry at Caltech. Should I consider going to another school?"

And it was like, "No, there's enough stuff wide open there that's going to challenge me and feed me." So I stuck with the decision to go to Caltech. I think what seemed strange to me was everybody else was getting into graduate school Labor Day or a few days after, and it was, like, the third week of September before we came out for the start of the fall term in 1983. But by then, I was thinking, "Peter Dervan or Dennis Dougherty?" Because Peter was doing some really cool stuff, too. When you get to Caltech, you have to do some coursework, and you've got other graduate students now. We're all jockeying for position of, "Who's lab here, who's lab there?" This and that. And I think there ended up being three from our class who joined Dennis's group. There were probably four or five who went to Peter Dervan's group.

And the thing that was appealing to me about Dennis was, he had some, to me, remarkably innovative ideas. He'd done some theoretical calculations, computational stuff. His approach was more mechanistic organic chemistry, and it aligned well with what I had in terms of experiences as an undergraduate, having taken graduate-level courses. It seemed like a good fit with the dynamic of the group. There were a few guys in the area above me. The year before, Tim Shepodd and Mike Petti had started, and they were doing the synthetic host-guest chemistry. They were kind of working on the first prototype. I was coming along, and it looked like I'd be doing the second one, a different class of structures to try and characterize synthetic host-guest models. The simple naive question was, "How do you bind grease in water?"

You needed to have a greasy inside and a water-soluble outside. Probably a week or two before, I had put this together (holding a plastic model of Dougherty synthetic host molecule). The models that we used in the lab at Caltech, the CPK models are much better in terms of giving you an idea of what you're building. This is a molecular model kit that I've had around for 30-plus years, and I thought, "Do I have enough pieces to be able to build what we had?" Not exactly, but it's close. This is the first prototype, the Petti-Shepodd prototype, if you will. The one that I did, I don't have that model yet. What we ended up finding, of course, is that you can bind a greasy thing inside the host, kind of a donut shape, and characterize a lot of things about them.

The Origins of Chemical Biology

ZIERLER: In considering Caltech, or once you got your bearings at Caltech, had you come across the term chemical biology? I know in the mid-1980s, this is really the revolution that Peter Dervan and others are leading. But was the term already being used, or is this a term that's sort of applied retroactively in recognition of what the new changes were at this point?

STAUFFER: I guess for me, it might be the latter. I don't know that we used the term chemical biology when I was at Caltech. There were those of us in the Division of Chemistry and Chemical Engineering, there were those of us in the Division of Biology. When I was meeting people to decide on which graduate school and which lab, you talk to people in different divisions, even though I'm in the Division of Chemistry and Chemical Engineering. But the term chemical biology came later. We had new labs that were built within the first year or two I was there. The Arnold and Mabel Beckman Laboratory of Chemical Synthesis. I'm pretty sure that was built to support the professors who were doing chemical synthesis, who perhaps had moved on to different locales. Not that we weren't doing chemical synthesis, but that wasn't our main initiative. Peter Dervan, Dennis Dougherty, their approach is to try and understand nature through chemistry tools. And chemical biology as a term, if they were using it then, I missed it.

ZIERLER: What would've been the term then? Would it have been inorganic biochemistry?

STAUFFER: I guess we called it bio-organic chemistry.

ZIERLER: Even though the ideas and the methodology were really different than traditionally what bio-organic chemistry would've conveyed? This is the newness of chemical biology, even if the term was not already in play?

STAUFFER: Yeah. Just jumping back a little bit, Leroy Hood was at Caltech I believe when I started, and he was in the Division of Biology, but he was already taking some of the inventions, the protein synthesizer, the DNA sequencing and synthesis equipment they were building there, and commercializing it. I believe Applied Biosystems was started maybe even a year or two before I got to Caltech by former Hood graduate students and post-docs. Those became the kinds of tools that bio-organic chemists might use. Peter Dervan was doing the sequence recognition molecules and doing a lot of bio-mimetic – bio-mimetic was another term we used for mimicking biology through chemistry, bio-mimetic chemistry, whether it's synthetic host-guest chemistry or the things that Peter Dervan was doing with his group, to great success. In terms of the terminology, I suppose we tried to stay buzzword-compliant and consistent within our field. I think as a naive graduate student, you don't know that, "Oh, yeah, you get to do this cool research because somebody's funding it." People like Dennis and Peter were getting grants approved that fund the graduate students and post-docs. If you want to be like those people, you have to be writing for grants as well. How you characterize your field, and your role in your field, and what you're doing, there's an art to that level of communication I think that now chemical biology is an effective term.

The Neurobiology Connection

ZIERLER: This will invite obviously an imprecise answer, but as a graduate student, as you're emphasizing breaking down these departmental and laboratory boundaries, did you feel in your group that you were all chemists who were now doing biology? Did you feel like it was a new science altogether? Did you feel like you were doing biology from a chemistry perspective?

STAUFFER: Not at that time. In terms of breaking boundaries, as a fourth- or fifth-year graduate student, I sat in on a neurobiology course. One of the instructors was David Anderson. There was another instructor whose name I don't recall. And this will help connect how I got from Caltech to Columbia for a post-doc. I'm sitting in this neurobiology course and learning about acetylcholine receptor. There were three to five lectures that were around membrane-bound neurotransmitter proteins. And the prototype there is the acetylcholine receptor. Acetylcholine is a quaternary ammonium compound. This is not it (holding plastic model), but this is a quaternary ammonium compound that we studied at great length in Dennis Dougherty's group. We were learning that if you want to bind a quaternary ammonium compound, you might use aromatic structures. Benzene, naphthalene, anthracene-type structures, which is what we had in our synthetic host. In nature, that means aromatic residues such as phenylalanine, tyrosine, tryptophan. With the neurobiology course, I started to dig into what's known about the binding site for acetylcholine in the nicotinic receptor and found that, "Well, there appear to be some aromatic residues. What characterizes that?" This got me thinking, "If the principles we're learning in Dennis's group in the synthetic host-guest realm are mimicked in nature, we should be able to find ways to demonstrate that."

I actually asked David Anderson, "Hey, who covers nicotinic acetylcholine receptor stuff?" and he named a few names, including Caltech's Henry Lester. But by this time, I was thinking, "What am I going to do for a post-doc?" I was looking outside of Caltech, and I ended up going to Columbia to work with Arthur Karlin, who had spent a significant part of his career investigating the acetylcholine receptor. I knew I was going to get to do more molecular biology, more biochemistry, broaden my set of lab tools. To come back to Caltech, auditing or sitting in on this neurobiology course gave me, I suppose, inspiration for some next steps in my career. Having the latitude to do that was great. And I know since then that Dennis and Henry Lester got together, and they've collaborated to do a lot more in-depth characterization of the nicotinic receptor for acetylcholine as well as other neurotransmitter membrane proteins. I suppose we ended up both being inspired and evolving in terms of, "What are we going to do that's going to be really cool and help us understand how nature works?"

ZIERLER: Because you were all over the place at Caltech in a good way, how did that affect your putting together the dissertation? How interdisciplinary was it as a result?

STAUFFER: The dissertation was fairly straightforward. It was for my work that I did in Dennis's lab. There are three proposals that one submits in conjunction with the dissertation. One of those was related to the implications of the work with Dennis for the nicotinic acetylcholine receptor, the stuff I was going to go off and explore. I don't recall the other two, quite frankly, but the dissertation itself was bringing together the work I did in his group. And we haven't talked in-depth about what that was. But part of what was important wasn't that second prototype that I was working on. Looking back at the first prototype, I described how the synthetic host in water could bind grease. The synthetic host in an organic solvent could also bind this (showing ATMA plastic model), which gave us some insight that the aromatic rings–and this predated the acetylcholine stuff in terms of thinking that this should work in nature–binding this quaternary ammonium compound in an organic solvent, that synthetic host has properties that don't require strictly what we would call hydrophobic binding.

"I fear the water. I hide from the water, and the safe place is inside this greasy donut." This quaternary ammonium compound is interesting. It's water-soluble, but it's very greasy. It's got one nitrogen and 10, 11, 12, 13 carbons. But adamantyl-trimethyl-ammonium, ATMA, the binding of it in an organic solvent told us the magnitude of binding that one could expect from a biological system for acetylcholine or for any other positively charged organic molecule. And that led to a lot of work down the road that reinforced that for not only acetylcholine receptor. There is a story to tell. There's an enzyme called acetylcholinesterase. It takes acetylcholine and splits it apart. In terms of acetylcholinesterase, where is that important? Your body has it. I'm thinking of bug spray. Bugs get sprayed with the toxin, and acetylcholinesterase gets all bound up, and it can't do its job. The bug dies. It can't process neural signals anymore. Paralysis, then in a few minutes, they're done.

When I was at Columbia University, I believe it was my second year there, Dennis and I had submitted a paper to Science describing the molecular recognition of acetylcholine by a synthetic receptor. Now, synthetic receptor becomes the term that replaces synthetic host. One of the data points that I collected in my graduate work was, "Can we bind acetylcholine with our synthetic receptor in water? Yes, we can. Ten micromolar." Not as strong as the sub-micromolar binding that we had for something like this (showing ATMA model), but nevertheless, what it showed, and what that paper helped others to recognize was that binding of organic molecules in an aromatic environment was possible, particularly positively charged small molecules. There was an investigator in Israel named Joel Sussman, an X-ray crystallographer, and one of his areas of study was acetylcholinesterase structure and function.

And apparently in his group, they had a crystal structure that they were trying to understand the implications for. One of the people in his group, I believe a post-doc, was a gentleman named Israel Silman. Israel Silman had been in Arthur Karlin's lab as, I believe, a graduate student. Dennis and I had our publication in December of 1990 in Science. In January of 1991, Israel Silman was visiting Arthur Karlin's lab, and he came to meet me because the paper that Dennis and I had published had given them insight that this cavity of aromatic residues at the bottom of which sits the active site for acetylcholinesterase, it made perfect sense that–I recall the paper they published said 14 highly conserved aromatic residues that line the cavity to the active site to the acetylcholinesterase. And he wanted to thank me for finding this out with a synthetic receptor because of its implications for their work. To them, all of this made sense. They were thinking, "This can't be right," until they understood from our paper that, in effect, the face of the aromatic residue is negatively charged, the edges are positively charged, partial charges, so that this diffuse negative charge, if you've got a whole cavity of them, you're going to be able to pass this type of structure (holding ATMA model) down through there.

ZIERLER: Why Columbia? What was so compelling about Columbia based on what you had accomplished at Caltech?

STAUFFER: I was going to have the opportunity to work with one of the key researchers for nicotinic acetylcholine receptor, Arthur Karlin. When I had interviewed with him to see if I would post-doc, he also had me meet not only others in biochemistry, but he had me meet people doing molecular biology. Basically, all of the people that I'd need to work with to carry forth this idea that I was bringing to his lab. That was exciting.

Columbia and Industry Pivot

ZIERLER: Now, to foreshadow a little bit here, did you already have interest in going into industry? Were you going to a post-doc because you were all in on faculty opportunities eventually? Or were you keeping both avenues open?

STAUFFER: I went there with the idea of going into academia. That was my objective. I knew I might spend three or four years doing a post-doc. I was anticipating I would be getting a lot of experience with protein biochemistry and molecular biology, adding to my knowledge base toolset with the idea that I could attract chemists who were interested in solving biological problems, biochemists, biologists who weren't afraid to think about things from a chemistry standpoint. I thought there would be a lot to attract them. I had interviewed for faculty positions. I would say, in hindsight, what I didn't appreciate, trying to be a chemist doing biology or a biologist doing chemistry, is that your first faculty position, at least when they were looking at me, they're looking for someone who they can put a clear label on. "Are you an organic chemist? What are you?" I wasn't enough of a chemist for the chemistry departments or biochemist for the biochemistry departments. In effect, I failed to market myself at it properly to recognize, "What is it that my customer wants?"

ZIERLER: This is a strategic problem for Caltech alumni because they're so far ahead of the field in the way that they define themselves. You need 5 or 10 years for the rest of the field to catch up. This is not the first time I've heard something like this.

STAUFFER: Yeah. I can't lay the blame on the world for not catching up, but I think I'll admit to being naive. I've learned a few things since then, as we all do.

ZIERLER: Leaving Columbia, thinking about the job market, how had that shifted your perspective on what was happening at Caltech? Not from the inside looking around you, but from the outside looking back, in terms of particularly what Peter Dervan was doing to the field.

STAUFFER: I thought what Peter Dervan was doing to the field was validating something that I said naively while I was visiting Caltech as an undergraduate. What I said to one of the biology professors I interviewed with was, "I don't think biologists are doing their research with enough of an understanding or taking into account enough of the chemistry that's involved." The professor was very charitable in his response to at least allow me the arrogant naivete to elaborate in terms of Peter Dervan and those coming from his group were teaching the field, that you can do a whole lot of exploring nature using chemistry. And if we call that chemical biology, sounds like a good fit to me.

But looking back at Caltech from when I was at Columbia, that was still kind of the phase of, "I don't have what academia's looking for, and that kind of stings." Circumstances had me looking at industry because it wasn't like I was saying no to academia, but I needed to find something that was coming next, and that turned out to be working with a software company doing computational chemistry, CAChe Scientific. Then, about a year and a half later, getting into managing information, chemistry and biology data, and being the translator. But in terms of what was going on at Caltech, I hadn't been following the field as carefully as when I was a graduate student and a post-doc, so my intellectual investment there had diminished.

ZIERLER: Anecdotally among your peers, both at Caltech and Columbia, was industry an increasingly viable pathway for careers at this point with all of the advances, with the emergence of biotechnology? Was this something that was an easy pivot to you that might not have been, had this been your experience 10 or 15 years earlier?

STAUFFER: I would certainly say so. Thinking back, I would say the area that became chemical biology, for those of us in the Dougherty and Dervan labs, and similar labs, part of what was happening was that biotech was starting to blossom. And they needed smart, creative people who knew how to solve problems and use these very innovative tools, molecular biology, protein biochemistry, and the like. Ten years before, the maturity wasn't there. But I hadn't really thought of it as turning to industry as a more viable option. I know thinking back to the folks I'm aware of from Caltech and Columbia that those who are in academia have, in effect, figured out how to kind of grab onto their ideas, and not let go, and pursue them through funding agencies. And at least for myself, going into industry has given me the latitude to solve different kinds of problems in creative ways where the funding comes from the company. I don't know how it feels to be a principal investigator at a university who's renewing grants every few years, applying for new grants to support students. I didn't get to have the experience of that model. It's foreign for me.

Translating Science in Business

ZIERLER: Obviously, it worked out in industry. It was not the same experience you had in the job market for academia. What aspects of your experience, both in graduate school and as a post-doc, particularly in IT and data management, computation, where was there that obvious connecting point as you pursued industry opportunities?

STAUFFER: The connecting points were something I alluded to earlier as a translator, being fluent in science, and to that end, compared to others who would come into the industry, for someone who spoke science well, I was pretty conversant in IT. And so, going into industry, then it becomes, "How do I speak IT better and better without losing the science?" Being in pharma IT helps that a lot. I would say I don't follow the cutting edge of synthetic host-guest chemistry. I occasionally will peek back at Dennis's list of publications and see what's come since. I know there was a crystal structure that was published of just the extra membrane portion of the acetylcholine receptor, which included the binding site, which helped to confirm all of the notions that we had going in. I know Dennis and Henry Lester wrote a Nature note that came along with the Nature paper that gave that structure from another lab somewhere around 2000.

ZIERLER: In your first experiences out in the so-called real world, how much were you bringing where there was a demand because they didn't have it, industry was new to this, and what aspects were you joining something that was already in building mode? Were you attractive in industry because there was this new combined expertise that you had and they didn't have, or was that infrastructure already in progress, and you were joining that?

STAUFFER: I think it is more the former. When I joined MDL Information Systems after CAChe Scientific, I was identified as someone to–"Hey, are you looking for a job?" I had a job. Somebody said, "Hey, we think you'd fit in well here because of the ability to speak science and speak IT." At least in my younger years, I was still getting comfortable speaking in front of audiences about both of those together. There was opportunity to grow with the job as far as–the position on my résumé says field application scientist. That's basically, "I'm going along with the sales person as the subject-matter expert on how the software works and serves the science that these folks are trying to do." But they recognized that I would be a good fit for their sales team, introducing what was at the time cutting-edge client-server chemical information management systems to pharma. For the next three to five years, we were hitting our revenue targets and exceeding them tremendously. What that means is, you make your target, and you get a bonus, and everybody's happy. The salespeople are making big piles of money. Those of us in field applications were doing all right, too. It felt like, "This industry thing isn't so bad."

ZIERLER: What were the satisfactions in comparing a life of basic research, whether or not it connects to applications, to really doing something where there's an obvious end goal in mind, both as it applies to human health impacts and profit margins?

STAUFFER: I would argue it's not so black and white, even in academia. There is a target. The basic research is framed with a target in mind. And those of us with targets, to achieve them, there's basic investigation and creativity activities that are involved that–our pharmaceutical clients have markets that they're trying to serve. Ten to 15 years ago, every pharma company wanted the billion-dollar molecule. Now, it's the $20-billion molecule. I believe with COVID, that was the $90-billion molecule, as it were, for the Pfizer vaccine. But in any case, that thing that's going to pay the bills so that we can do the basic research in pharma that's going to find us the next big molecule or successful revenue generator so that we can continue to thrive as an organization and help our patients do the same.

To come back to your question, I think finding the creativity, the basic research free-wheeling aspects, there are aspects of what I do as a consultant that are probably more innovative in terms of starting with, "Here's a problem to solve. What's the best way to solve it? I probably don't have the best way to solve it. I have "a way" to solve it. It might be a quicker way than the best way." A lot of the consulting I do is project-based. There's a temporary-ness to what needs to be done. This is a roundabout way of saying what I do for a lot of my consulting work is, I live and breathe in Microsoft Excel.

And this grows out of having worked with an information systems company that had databases for chemists and biologists, databases that run on platforms like Oracle. I'm familiar with working with Oracle databases. I'm familiar with scientists preferring to work with Excel spreadsheets, so providing them tools that can either allow them to work directly in Excel or in an Excel-like environment is often very appealing. The learning curve is shallower than if you have a new application that's nothing like they've ever seen before. But helping to solve problems with managing information that people can communicate with using Microsoft Excel is a lot of what I do the past 5 to 10 years.

Corporate Response to Economic Change

ZIERLER: I'll ask a macroeconomics question. Between, for example, the dot-com boom and bust at the turn of the century, the financial crisis in 2008, 2009, how does that affect your day-to-day in terms of stability, the science, the computation you're able to do?

STAUFFER: Big changes in the economy mean big changes in what clients are focused on. Mergers and acquisitions happen. As a consultant, any kind of change is good because it means that people that weren't working together before now have to learn to work together. And that also means that their data has to work together. You're bringing together a mergers and acquisitions model of big pharma. Company A works with this kind of data management system, company B works with this kind of system. We're either merging or acquiring. We need to have new systems. Even the systems that we had before are–I don't know when it started becoming planned obsolescence, but it's well-understood that IT systems don't last forever. Newer ones come along that are better, cheaper, faster.

We talked about going from workstations, to client-server, to the cloud. Somebody wants to go to the cloud. Well, what does that mean? What do they do with the information they have already in these databases that they spent time, effort, and money on? As a consultant, from a strategic standpoint, I'm advising on what the options and recommendations are for getting from where you are to where you want to go. "And here are the things you need to keep in mind because it's going to take you two, three, four, five years to do that." When companies do due diligence on a pharma merger, part of what they're doing is identifying what IT systems are impacted so that their CIO of the new company can make decisions about, "What are we going to keep? What are we going to make legacy and let sit? And what are the new things we're going to do?"

ZIERLER: You've lived through so many mergers. What does that mean in terms of appetite for risk-taking? Where is a merger good for pushing the science and data in new directions, and where does it mandate a more conservative approach? And what's better?

STAUFFER: This is a difficult question for me because I would say as a consultant, I see IT departments that are generally more risk averse. They don't want to be the reason that a pharmaceutical company doesn't make its target. If you think about the COVID vaccine, there was a lot invested in making that all happen with the idea that the return would be there. And I believe that was very wise to do that. Mergers and acquisitions tend to make companies less tolerant of risk.

ZIERLER: Is that generally not welcome by you? Is that antithetical to pushing the science, pushing data initiatives in new directions?

STAUFFER: With a merger, you've got staff from both companies that realize that change is coming. Company A people know what company A systems are like. Company B people know what company B systems are like. Now, they have to figure out together how they're going to play nice. You're going to have some people at company A that go, "I'm going to go do something else," whether it's with another company or what have you, take the golden parachute, depending on where they are in their careers. Same for company B. When you're trying to get the new systems to work together, there's generally a lot of aversion to risk because it's like, "I'm familiar with what I'm doing. I don't want to have to take on what somebody else is doing." The people that are, shall we say, left on the island that haven't left or been voted off eventually recognize they have an opportunity to do the next new thing.

And so, they go from more risk-averse to being ready to take risk again because once they accept that change is coming, if they can be in charge of that, then it's like, "Okay, I'm ready to take that risk." As a consultant watching this and making recommendations, recommendations are typically based upon what we've seen in other circumstances. No two things are exactly the same. We're sharing perspectives more in the abstract than the concrete, but because we as consultants get hired to help with the process, we're keeping an eye on not only what the new set of tools is going to be and what the new IT systems are going to do. We're involved with the change management, helping the people who are still on the island to be able to adapt to the things that are new and the new things that are coming.

ZIERLER: How does this inform your decision to change company? When do you stay put, when do you see the opportunity to move on?

STAUFFER: I'm not sure with where my career is now that that applies. My employer is CGI. I'm a contractor through CGI to different pharmaceutical companies. When I was with MDL Information Systems, I went through six mergers and acquisitions, and this is company sizes around plus or minus a few hundred people. It was the seventh one that I was part of a reduction in force. That was something that happened to me. It wasn't my choice. Through that, I positioned myself in the job market as a business analyst, and I've been working as a consultant, but through an employer company. I think about a move I made from Paragon to BT Global Services. The role of BT Global Services was positioned to something similar to what I'd done as a field application scientist with MDL Information Systems. I was going to be involved in teacher/translator of sciences for information systems related to discovery research. I was like, "Hey, I enjoyed doing that. I'd like to do it again." That position turned out not to be as valid as I had anticipated it should've been. Happily, I hadn't burned bridges at the company I had left seven months previous, and I came back to them and was able to land on my feet in a new project in a different area of the pharmaceutical industry.

ZIERLER: In embracing the business side of things and positioning yourself as a business analyst, obviously, you don't have an MBA or a business background. How much of it is common sense, how much of it is understanding the business side from all of this experience, and how much did you really need to read up on economics and corporate finance?

STAUFFER: There's a lot of common sense that comes with experience, I would say. I think part of what you get from Caltech, Columbia, the progression is that there are lots of opportunities to learn as you go. There's a certain attitude of, "I want to find out more about this and understand it better." In terms of understanding business, it's recognizing that, "When I was in graduate school, working in the lab, I was trying to solve this problem that was leading me to my dissertation, whereas the people that are using computational chemistry tools, or information systems in industry, they have a different set of problems they're trying to solve. Let me understand what those are so that the value proposition of our IT systems and tools is presented in a way that makes sense."

There's the business of, "What do I need to do for my job?" but also the recognition that this ecosystem that is pharma IT, the pharmaceutical industry, that there are different objectives that different levels have. As a field application scientist working with sales people, every few years, we'd get some refresher sales training, such as customer-centric selling, to establish effective communication models that are brought to bear: as part of a sales team, you need to be able to understand what your client's overall business is, and to start to see for the particular people you're interacting with, whether they're on the IT or science side, what their critical business issues are and how you can relate to them.

The Biotech Response to Covid

ZIERLER: Moving our conversation closer to the present, we already covered how COVID impacted you in terms of remote work. What about the on the science side, on the biotech side? Did you have a front-row seat to how some of these companies responded to the crisis, both in terms of just work culture and coming up with therapies?

STAUFFER: I would say work culture, yes. On the therapies side, no, not in terms of the science. The work culture, there's a general challenge of, "How do we keep the trains running? How do we keep manufacturing medicines when the people are not able to be on site?" This comes down to companies recognizing that the people involved in manufacturing are essential. They develop the safety protocols with–I don't know that they necessarily had full hazmat suits, but I remember seeing the movie The Andromeda Strain when I was much younger, and I've had that picture in mind when I hear hazmat suit and biological contamination. But to your question, the work culture became one of, at least in the projects that I've been involved with, "How am I going to work from home?"

It's not only, "How do I do the work that I'm responsible for at home?" If somebody needed to be in the lab to do something, they were now figuring out how to structure their workday to do that and to remain effective in the other aspects of their job. Not everybody went remote. My role is one that could be remote. There were others whose roles could be remote, but they hadn't been remote before. The work culture is one where you have some people who don't have a dedicated home office, and they have to try to create one. Maybe they have a spouse who's also in a similar boat. "Where am I going to be?" We had some cases where you've got two working spouses. The day care that their kids would go to was no longer available to them. They're scrambling and trying to figure out, "How am I going to get my work done? How am I going to manage all the family stuff that used to be managed in different ways?"

I would say the first three to six months were very chaotic for lots of people. My role was not only to recognize that they were struggling, but to remind them that, "Hey, we can do this. Our projects have goals that you're helping us meet. We'll get it done in the one or two hours that you have available to be meeting with us in a given day." The new meaning of work-life balance became, I would say, life-work balance. Because life suddenly became dominant during the work day.

Wrangling the Best from Computers and Instrumentation

ZIERLER: We'll move the conversation right up to the present. What are you working on right now? What's important to you?

STAUFFER: I work on making sure that the laboratory equipment and the computers that support that equipment are state of the art, that they are secure, and that the people that use them have all of the tools on those systems to do their work. That work is primarily manufacturing of biologics and vaccines. Mine is a support role. If any one of those systems goes down, there's a backup for it. I have experience with helping one of my clients to bring systems back online after a cybersecurity incident that wiped out half the systems in the company. I was part of a team, and we were able to do it in two months when they thought it would take a year. I was able to be helpful because of things that I had experience with going back to Caltech. It's like, "Hey, let's learn how to use this computer." Going back to Caltech, a Silicon Graphics workstation. Man, that was the greatest new toy. But even before that, there was the Macintosh IIci. There was the IBM AT, the bread box. Back then, there wasn't a whole lot of software for doing scientific work. Certainly, the Silicon Graphics workstation did. But how do you learn to use a computer? You probably started by playing some games. And then, "Okay, now we need to do some meaningful work." Games are fun, but you master them, and they become boring.

ZIERLER: Harkening back to what you learned at Caltech is perfect segue to the last part of our talk. Now that we've worked right up to the present, let me ask first, how have you stayed close to the science? You said over the course of our discussion, you're fluent in science. Now that you're so involved in industry, and IT, and the data, is it just sort of the language that you've learned, and you just stay on it? Do you keep up with the literature? Do you go to conferences? How do you stay close to all the science?

STAUFFER: I would say it's more from having not lost it. How do I know I haven't lost it? I think I'm still an effective translator. When I am in the client laboratory space talking with the scientists, and they're talking about, "Hey, we need to take this cell culture and move it over here, we're doing this and that in these conditions," and I know what they're saying, and I'll ask them a question or two, they'll say, "You understand what we're saying? You know what we're talking about?" "Yeah. Yeah, I do." And part of it comes just from day-to-day. When anybody goes to the doctor or dentist, or some kind of medical stuff is going on in the family, I'm often invited along to make sure they don't lose anything in translation. I can ask questions and help family members make sure they're understood. I know from talking to members of my family that I unfortunately often talk over their heads. It's not intentional, but it happens. I go off on tangents, as I have in this conversation. I get excited about something, and it's like, "I don't think they understand what I'm talking about. How can I make this simpler?" It's a constant reminder to keep it simpler. My kids are great at reminding me of that.

ZIERLER: I'm on the elusive hunt for the history of the term chemical biology. The term itself was not front and center to you either in graduate school or your post-doc experience so much. What about over the course of your career? Where have you seen the term crop up? Where have you associated it with the advances that you were part of at Caltech?

STAUFFER: The term is not something I come across or have heard used in my roles, either with MDL Information Systems or in my career as a business analyst. But the concepts are, I think, pretty much and have been ingrained in the pharmaceutical industry for over a decade. Particularly in terms of pharmaceutical industry going from small-molecule drug discovery to expanding to include biologics. A lot of the medicines today are grown in cell culture rather than synthesized in a lab with small molecule reagents in solvents. The term "chemical biology" is not so familiar, but the concepts have been around for over a decade, easily.

ZIERLER: Have you kept up with Caltech over the years? Do you keep up with Dennis or your fellow students?

STAUFFER: Not as much as I would have liked. I'm aware of their different careers or roles through tools like LinkedIn. I mentioned earlier, I'll check out Dennis's Caltech page from time to time, see how far back I have to go until I recognize names. I think I was last at Caltech in 1999. I happened to swing back for a few days, and I got to meet some of the people in that group, then-current grad students and post-docs, and it was as bit disarming. They, I think, viewed me as something of a legend. When you're there, you're just a grad student trying to figure out a set of problems and make enough mistakes until you're successful.

ZIERLER: Of all the work you've been involved in over the course of your career, what's been most satisfying, both in terms of helping businesses achieve success, and then beyond that, what it is that the business is ultimately after, which is developing drugs that help people?

STAUFFER: When I was with MDL Information Systems, they were introducing a biological screening data management system, and it was kind of an empty canvas that companies could use. And what I saw that it lacked, and what it was understood by others to lack, was a set of examples that showed you what this could be. I created a set of examples that were rich enough and wide-ranging enough so that the system was given value in the eyes of people who couldn't see value before. That was rewarding to be able to create something like that using the tools that we were going to be turning over to companies, and the people within those companies would be able to take, shall we say, the paint-by-numbers and then go create their own works of art within the tool. Even though those works were keeping track of the different levels of screening and testing they were doing to determine which therapeutic candidates were going to advance. That's from the discovery side.

ZIERLER: Then the business side, where have been some major business successes that you've been a part of?

STAUFFER: There are the business successes where we made our revenue target. Those are satisfying in the moment. It's like, "We won the game." I mentioned earlier this company that had a cybersecurity incident that needed to keep its medicines in production. They were scrambling to make sure that their supplies remained intact. I had a small part in helping that manufacturing process continue. This was something that was before the pandemic. I wish I could say during the pandemic, something I did made a difference with one of the vaccines, but I was not involved in any of those.

ZIERLER: Finally, I want to ask a question that looks to the future. Because obviously, there are so many more advances that we can imagine, in data science, IT, and pharmaceuticals, what do you see as having built as an enabling technology for the future? If you've ever served in a mentorship capacity, ever worked with young people as they look to forge their careers. What have you built that might suggest where all of this is headed?

STAUFFER: I think for someone I would mentor, I'll give you an example. I've told you about my facility using Microsoft Excel. I can share what I do with someone, and they recognize that that's pretty cool. But until they have the curiosity to dig in and go find something else to do with it, it's not theirs, and they're not going to carry it forward. It's still mine. I would say to someone I would mentor, "Develop that curiosity to go figure out what needs to be figured out. Be relentless." I've had numerous times with problem solving where my attitude begins with, "This can be solved. It might be really hard. I might not be the one who gets to do it." I've seen throughout my career, other people have been able to do it. But the attitude is one that, "This can be solved. If I get to do it, great. If I don't, someone else does it, that's fine, too." But we all have our contribution to make.

ZIERLER: But believing, "This can be solved," is really the Caltech way, right?

STAUFFER: Absolutely.

ZIERLER: This has been a wonderful conversation. I want to thank you so much for spending the time.

STAUFFER: Thank you.

[END]