When you think of epidemiology, you may picture a team of health professionals working to track an outbreak of infection. But an entirely different kind of scientific sleuthing is done within pharma and biotech companies.
Amgen Scholar alumnus Anne Beaubrun, an epidemiologist within Amgen’s Center for Observational Research in Thousand Oaks, California, analyzes reams of data to track the safety and effectiveness of the company’s drugs before or after they are brought to market. The latter responsibility comprises ‘post-market surveillance’ and is particularly exciting because it covers millions of data points as one tracks real-world use of a therapeutic.
According to Anne, one of the key goals of epidemiology, within the pharma and biotech industry, is to critically assess the benefits and risks of medicines over time and provide that information to regulatory agencies and patient and health care providers. The analyses completed by epidemiologists also inform policy-making and commercial decision-making.
Despite the importance of epidemiologists to the pharmaceutical industry, many have never heard of these roles, Beaubrun says. And only a handful of graduate programs scattered throughout the US offer training in pharmaceutical outcomes and policy. Beaubrun graduated from one of them, at the University of North Carolina at Chapel Hill, with a PhD in 2013.
Immediately after graduating, Beaubrun landed her current role at Amgen as an epidemiology research manager. With the support of her dissertation advisor, she had the opportunity to work on an Amgen study and complete a publication with Amgen scientists during her last year as a graduate student.
We talked to Beaubrun, who participated in the Amgen Scholars Program in 2007, about what she does, and about general career advice for Amgen Scholars.
Can you tell me a little more about what you do, and why you do it?
Regulatory agencies and policy-making organizations require robust, scientifically valid studies that inform the risks and benefits of our products.
Increasingly, reimbursement authorities like government and private insurers want evidence to demonstrate the value of our drugs. So a big part of the work we do on a daily basis is to provide that evidence using real-world data. Specifically, we conduct studies to inform the following questions when our drugs are out on the market: 1) How are doctors and patients using it?; 2) What kind of patients are receiving the drug?; 3) What are the short- and long-term effects of using our drug?
Our research benefits a range of stakeholders. The regulators want to know about the safety of our drugs. We also inform the marketing and the commercial side by forecasting how many people we expect to use our drug. Finally, we educate patient communities and health care providers about the benefits and risks of a drug.
How did you get interested in pharmacoepidemiology?
Like many [students studying STEM], at first I was interested in medicine. After a while, I was drawn to health care research. My PhD program at UNC-Chapel Hill was in the department of pharmaceutical outcomes and policy. I was interested in learning the population-level effects of medication use. In the controlled environment of clinical trials, you’ll have information on the efficacy of a drug, probably among a few hundred individuals. With population-level research, I study the real-world effectiveness of our drugs once thousands or even millions of people are now taking them. That’s what makes it really cool. I love what I do.
Where do you get your data?
A big part of the data that I use is administrative claims and electronic health record data. For instance, Medicare data describes health care treatment patterns for the elderly population. Whenever the patient goes to the doctor, a claim is submitted. Claims contain information describing whether the patient is deceased; their diagnosis; procedures the doctor performed during the visit; and the medication they are taking. In keeping with HIPAA [Health Insurance Portability and Accountability Act] requirements, any identifying information about the patient is removed from the data.
What are any intellectual challenges of your work?
When performing secondary research, there are a lot of things that you don’t know. There are patient-level variables in claims data that you may not be able to obtain such as whether or how much an individual smokes when conducting a study of heart disease patients. A big part of what we try to do, and what epidemiology does in general, is try to control for bias.
What general career advice would you give to Amgen Scholars?
Keep your mind open to new potential career paths. You can use your skill set to help patients and it doesn’t have to be in the traditional way.
Also, learn how to communicate well. A lot of people undervalue how critical it is, especially in my role, to be able to communicate effectively. A lot of these soft skills are not usually taught within scientific programs. But I can’t emphasize how much they matter. A big part of what I do is to communicate scientific information to a variety of audiences. I do so through oral presentations, technical reports, and peer reviewed publications.
How can you refine your skills? Do you learn on the job?
On-the-job training is a large part of it. When you’re not in school anymore and you don’t have a large number of classes to choose from, you have to seek it out on your own. What I do is attend local conferences on leadership, negotiation and public speaking. You may need to pay registration fees for these opportunities, but you should consider it an investment.
It sounds like what you do, publishing and attending meetings, is actually somewhat similar what an academic scientist does?
Yes, we have internal research projects, but if you’re trying to inform clinical practices, you’ve got to get [such projects] out in the peer-reviewed literature and present at scientific meetings. So I’m writing papers and submitting them for publication. I’m attending conferences. It’s the best way to get our research out there, to the right audiences.