Kim Gilliam, ASA Marketing Project Manager

Chris Barker

Longtime statistical consultant Chris Barker had his sights set on retirement a year before the pandemic. He reflects, “While there is nothing good to be said about the pandemic, my retirement was interrupted by clients who asked me to return to work on drug development projects for the treatment of COVID-19. I recognized an essential role for statisticians during the pandemic to address—when and where possible—disinformation about the vaccine development efforts and a variety of other matters related to the COVID-19 virus, such as virus aerosol transmission. This was exciting.” So, Barker tracked the clinical trial and related COVID-19 research and often posted summaries in the ASA COVID-19 community.

Academic Background

Looking back, Barker admits his academic background was “not linear.” He originally went to graduate school to study economics but later decided to pursue a degree in biostatistics. After many years of working on pharmaceutical clinical trials, he came ‘full circle’ and started work as the sole statistician for the newly created Roche Global Health Economics Group and continued a health economics statistics role later at Johnson & Johnson. His responsibilities included preparing statistical analyses of the phase III trials to use in the economist models of cost-effectiveness, cost-utility, or cost consequences.

“In hindsight, my nonlinear path was exactly the training I needed,” said Barker. “My main academic transition was from economics to statistics, then effectively returning to economics. I was an undergraduate economics major with a side interest in molecular and cellular developmental biology at the University of Colorado, Boulder.”

In the current era of mRNA COVID vaccines, Barker said he first learned about mRNA in an undergraduate molecular biology course in 1974 from the developer of the first electron microscope photography scientific processes, procedures, and original photography—Keith Porter—and his collaborator Mary Bonneville at UC Boulder.

Barker pursued an economics degree at Northwestern University and, on the suggestion of a fellow student, entered a biostatistics program at the University of Pittsburgh, ultimately graduating from the University of Illinois Chicago School of Public Health. “That experience was perhaps sheer luck,” said Barker.

“It enabled me to take graduate statistics classes at UICSPH, Northwestern, and The University of Chicago, where I met Paul Meier,” Barker said. “He later hired me to work as a member of the small biostatistics group in the department of medicine. … In collaboration with Paul’s daughters, we published a newspaper article in STAT News recalling Paul’s work on ‘The Cutter Incident,’ in which Paul was part of the team that discovered failures in production practices at Cutter that led to vaccines that caused polio in young children.”

Pathway to Industry

Barker landed in the pharmaceutical industry at Lorex, a joint venture of Searle and Synthelabo, working on phase III clinical trials conducted in the United States of the now widely used sleep hypnotic drug Ambien. After moving to California in 1989, he worked at Syntex on an immunologic drug, which was eventually approved with the name CellCept and based on a molecule called mycophenolate mofetil.

His manager at the time, Mike Crager, assigned him to a project for which they only conducted studies on mice. He continued to work on the molecule until there was worldwide approval of CellCept for humans. According to Barker, these were the largest multicenter international clinical trials in transplant drugs ever conducted for people who receive a kidney, heart, or liver ‘solid’ organ transplant.

“Particularly gratifying, to this day, was that the endpoints of the clinical trial were acceptable to the FDA,” said Barker. “My medical colleagues and I defined for that first-ever clinical trial CellCept approval, which appears largely unchanged and in routine use today for every subsequent transplant drug approved by FDA.”

Shortly after the phase III clinical trials were analyzed and reported as positive—surpassing Barker’s wildest expectations—Roche acquired Syntex and he continued working at Roche.

During the 1990s, pharmaceutical health economics—pharmacoeconomics—was becoming an essential activity for every pharmaceutical company, often using the phase III trial results, said Barker. “Because of my initial education in economics and then biostatistics, both the vice president and director of the first Roche Global Health Economics and Strategic Pricing Group invited me to be the statistician for the economists located in Roche offices around the world. The pharmaceutical industry has since recognized that drug/medical device/diagnostic/vaccine developers must consider whether a new drug, etc., is likely to be reimbursed by Medicare in the United States and comparable health authorities in every other country. This provided me an opportunity to collaborate with nearly every clinical trial statistician worldwide at Roche.”

According to Barker, one of many fascinating discoveries and a seemingly not well-known aspect of pharmaceutical drug (or device, diagnostic of vaccine) pricing is called “discrete choice” modeling, or more formally, “conjoint analysis”—a method originally developed by John Tukey. Barker was impressed by the rapid adoption of Bayesian biostatistical methods by the pharmaceutical industry and regulatory agencies worldwide. He encourages graduate students to learn computer programming and stresses the importance of learning to develop, estimate, and interpret Bayesian statistical models, clinical trials, and other experiments using Bayesian methods.

Statistics and the Pharmaceutical Industry

During the 1990s, Barker was particularly fond of working with health economics data (e.g., hospitalizations, medication usage, doctor visits), which he says was long recognized as “some of, if not the messiest” data collected in the pharmaceutical industry. Barker said, “By messy, I do not imply it was collected poorly, but that substantial resources—mainly investigators and trained industry people—are required to guarantee the accuracy of the data and the data are inherently complex.”

Furthermore, at Roche, there was a corporate-wide policy that health economics outcomes were not to be used as a basis, for example, the primary trial endpoint used for drug approval by regulatory agencies. Barker said, “Fortunately, I was able to publish two sole-author publications about some interesting technical and data-related issues. I discovered one when estimating the Kaplan Meier Mean using commercial software.”

“I believe it to be a completely innovative and novel way of summarizing and graphically displaying so-called concomitant medication data,” said Barker. “I adapted the existing methodology from Bill Nelson for the ‘mean cumulative function’ … By my good fortune, one of Paul Meier’s daughters forwarded a copy of my KM [Kaplan Meier] paper to Paul and reported back to me that his comment was, ‘Reads well.’ Having worked for Paul and attended his classes, I considered that high professional praise and as close to the Nobel as I’ll ever get.”

Barker describes his role in health economics as a type of “liaisonship” with the clinical trial statisticians and project economist. He kept the clinical trial statistician apprised of how clinical trial results and those analyses might be used in the economics models. “I was sensitive to avoiding situations where the clinical trial statisticians prepared an analysis one way, while a different analysis and possibly a different interpretation was prepared in health economics,” said Barker. “This was never a serious problem. I recall, however, that I had little success trying to explain ‘noninferiority’ analyses to the economists and I was unsuccessful in having the noninferiority results explicitly included in the economic models. My concerns and approach appear to be consistent with the recommendations of the FDA about economic and similar models of the trial results.”

In hindsight, there are a few things Barker wished he’d known back then. “I don’t think that the high probability many pharmaceutical companies will acquire or be acquired by another—or substantially restructure their company—regardless of the size of the company, is unusual in the pharmaceutical industry,” Barker said. “This does not reflect on one’s talents. It is enormously disruptive to the individual statistician and their family and their career path. My experience so far is that, and my personal assessment is that, long-term employment opportunities and career growth for statisticians are abundant in the pharmaceutical industry.”

Importance of ASA Membership

As a member of the ASA, Barker says the benefits he’s received in his career are quantifiable. He has volunteered in a variety of roles, ranging from his service as president of both the Sacramento and San Francisco Bay Area chapters to his service on the Dixon Committee and with Statistics Without Borders to his current service as chair of the ASA Statistical Consulting Section. “One fond memory of my San Francisco Chapter work is developing the annual program for Bay Area statisticians to give a lecture about careers in statistics to students in AP Statistics classes in area high schools,” said Barker.

Currently, Barker is working to expand the visibility of the Sacramento Chapter to local graduate and undergraduate statistics departments.

Gratitude

Over the years, many mentors and individuals have inspired Barker, providing him with guidance and playing pivotal roles in his education and career. He was inspired by his thesis adviser, Paul Levy, chair of the biostatistics department at the University of Illinois Chicago School of Public Health, whom he refers to as an “expert” in sample surgery methodology.

Barker credits his early career choices to Carol Redmond, emeritus professor of biostatistics at the University of Pittsburgh, who offered him his first job working on oncology clinical trials during graduate school. She also taught him principles for communication and interpretation of clinical trials he still uses today.

And there is Meier, who Barker met as a student in his biostatistics seminars at The University of Chicago. “All of these people and more helped pave the path of this statistician’s life,” said Barker.