Effective Communication for Pharmacometricians with Joga Gobburu

Joga Gobburu
Dr. Joga Gobburu

The modeling and simulation revolution is transforming our approach to drug development. Quantitative pharmacology models can yield valuable insights that help sponsors make better decisions regarding their drug programs. For pharmacometricians to influence decision making, they must be able to effectively communicate.

Dr. Joga Gobburu is a Professor at the University of Maryland Schools of Pharmacy and Medicine and is Executive Director of the Center for Translational Medicine at the School of Pharmacy. He joined me to discuss his strategies for effective communication, his work to improve pharmacometrics tools, and his fearless approach to training the next generation of modelers.

Suzanne Minton: I always like to learn about peoples’ outlook on life. Ernest Hemingway has been credited with the idea of the “six word novel.” He once bet a group of friends that he could craft an entire story in six words. He came up with “For sale: Baby shoes, never worn” and won the bet. If your life was a six-word novel, what would it be?

Joga Gobburu: My “novel” is six words in Hindi: Jo dar gaya samjho mar gaya. The translation is “One who is afraid is as good as dead. “

SM: I love that saying as your motto! Does that mean that you’re fearless in life and in your approach to pharmacometrics?

JG: [Laughter.] I don’t know about that, but that’s my aspiration.

SM: I recently read and enjoyed your tutorial in CPT Pharmacometrics and Systems PharmacologyCommunicating to Influence Drug Development and Regulatory Decisions.” What inspired you to write that article?

JG: Over the 20 years I have been in this field, I have noticed that we train our students in pharmacometric methodologies but not so much in its applications. As a result, they often have difficulty converting their technical work into an impactful contribution. We say that our job is done when the model is successful. But the real test of the value of our work is informing key drug development decisions. We don’t seem to be as equipped to do that.

Lately, few modelers have come forward with some recommendations on how to communicate models. And I just had a fundamental disagreement with that because we never communicate models; we communicate decisions or recommendations.

So I thought, maybe I should express my opinion on this topic. To me, communication to influence decision making is critical. Especially in our field, because pharmacometrics is a relatively young discipline. Most other drug development disciplines—medicine, statistics, chemistry—have been around for a long time. Thus, their value is easily understood and accepted.

Pharmacometricians must be able to communicate what we’re offering, what we bring to the table, and the value of pharmacometrics for this approach to grow. As long as we operate solely as modelers― technical experts― the field cannot expand its influence.

SM: What would be your biggest piece of advice for someone who came to you and said that they wanted to be a better communicator?

JG: Better communication comes from three things. One is understanding the environment in which an organization operates. It doesn’t matter which organization per se. You need to understand how decisions are made and the fundamental traits of that organization. That has nothing to do with modeling.

Second, we need to frame key questions accurately and precisely. That skill comes only with practice.

Third, we spend a lot of time planning our analysis. I think that we should spend double that amount of time planning the communications strategy. After all, every pharmaceutical company creates a marketing strategy to support the commercial success of approved drugs. The same concept is true for pharmacometric models: you need to craft a “marketing strategy.”

SM: That’s good advice. Prior to coming to the University of Maryland, you served as the Director of the Division of Pharmacometrics at the Office of Clinical Pharmacology at the U.S. FDA. Your educational background includes both a Doctorate in Pharmaceutical Sciences and a Master’s of Business Administration (MBA). How have these diverse aspects of your career and training influenced your view of the importance of scientific communication?

JG: What I’ve learned from interacting with business leaders as well as going through MBA training is an appreciation for how we manage the field. How do we create new opportunities for younger scientists? How do we create positions in pharmacometrics to make this field sustainable? Those business world lessons can be applied to the scientific world, where I spend most of my time.

SM: You lead the pharmacometrics training program at the University of Maryland. How are you incorporating teaching communications skills into the curriculum of this program?

JG: At the University of Maryland, we believe in the importance of scientific communication. Our pharmacometrics students are required to take a course called “Strategic Communications and Negotiation.” This course is taught by a faculty member from the School of Business at the University of Maryland and a faculty member who is a communications consultant, who actually taught me while I was an MBA student at Johns Hopkins University.

SM: In your CPT tutorial, you performed a strengths, weaknesses, opportunities and threats (SWOT) analysis. You cited “conventional thinking” as a threat to a pharmacometrician’s ability to influence key drug development decisions. What do you mean by this and how can pharmacometricians overcome this threat?

JG: Pharmaceutical companies are ultra-conservative in their approach to drug development. In fact, they are more conservative than the regulatory agencies. I don’t think most people understand that, but it is true. This conventional thinking invokes prescriptive behavior. When a person gets conventional, what do we do? We embrace approaches that have been in use for a long time. Because maybe our grandfather used the same thing, or our fathers used the same thing. It doesn’t mean the conventional approaches are necessarily the best. Conventional thinking, in terms of drug development, means using the same approaches that have been used for decades.

Pharmacometrics introduces innovation. It challenges the conventional thinking on how to develop drugs. Thus, there can be a clash between conventional and innovative approaches.

SM: That would suggest that the ability to communicate your work becomes even more important because you’ve got to overcome that conventional thinking.

JG: That’s correct. Drug developers often use conventional thinking because of their comfort level. They are used to looking at things in a certain way. And it doesn’t mean it’s the right way or the best way for a given problem. People are comfortable with the approaches that they’ve used in the past. When you come up with a different approach, a different way to analyze data, or a different type of solution, then you’re displacing these drug teams from their comfort zone into a “discomfort zone.” Pharmacometricians must acknowledge that discomfort to be influential.

SM: That makes sense. You can’t get people to be on the same page unless you get them comfortable first. In your paper, you discuss different ways of communicating: a deductive versus an inductive approach. When a pharmacometrician senses that the sponsor is unfamiliar with pharmacometrics and isn’t comfortable with it, what sort of approach should he use and why?

JG: There are two types of clients that pharmacometricians generally work with. The first is the interdisciplinary drug team. This group is comprised of chemists, statisticians, clinicians, microbiologists, and so on. When your target audience is interdisciplinary, we use an inductive approach. We share our conclusions up front and then explain how we arrived at these recommendations. With this type of audience, we shouldn’t be overly technical.

The second type of client involves working within clinical pharmacology. In this situation, we can use a deductive approach because the primary purpose is to achieve consensus. In this setting, it’s appropriate to take a deeper dive into the technical nuances of the particular model being used.

SM: The University of Maryland Center for Translational Medicine Program and Certara have had a productive relationship for years. Can you elaborate on this ongoing collaboration?

JG: Sure. The University of Maryland and Certara have had strong relationships since I joined the university. The collaboration has several components. First, the university receives access to Phoenix software that we use to train the students in our pharmacometrics program. The program is 100 percent online, and our students are often concurrently employed full time at various companies in the pharmaceutical industry. Having access to software that makes learning pharmacometrics easier and more efficient was a desirable feature. That’s something unique with the Phoenix software; it’s easier to teach pharmacometrics using that software.

The next part of the collaboration is software-related research. We help “pressure test” Certara’s population PK/PD modeling software, Phoenix NLME, by using it for almost all of our research projects and for projects that we do with pharmaceutical companies. We provide feedback to the software developers at Certara on how to improve the software.

Lastly, we collaborate with Certara to develop applications that can add value to the Phoenix NLME module. Some of the recent applications have related to support for making plots and running Phoenix in a batch mode.

Chatting with a pharmacometrics thought leader

I’d like to thank Dr. Gobburu for pulling up a seat at the Roundtable and sharing his insights with us. Learn more about his work at the University of Maryland’s Center for Translational Medicine.

For another perspective on scientific communication, please check out this review by Certara’s Ellen Leinfuss of Peter Bonate’s book “Be a Model Communicator and Sell Your Models to Anyone.” What are the biggest challenges you face in communicating the value of modeling and simulation approaches to a non-modeler audience? Let me know in the comments!