How To "Think Bigger" About Biosimilars

By Anna Rose Welch, Editorial & Community Director, Advancing RNA

A question we’ve heard time and time again is how similar must a biosimilar be to its reference product. Given the rising number of biosimilar approvals, it’s apparent regulators and manufacturers are successfully answering this question. But, as biosimilars enter the market, questions shift away from analytical and molecular similarity. Stakeholders are now posing questions about immunogenicity, the demographics and treatment histories of biosimilar patients, and physicians’ prescribing habits.

We’re at an interesting stage in this market, as real-world evidence (RWE) is being accrued every day in the form of new biosimilar patients, switching studies, and payer formulary changes. RWE, or data from real-world practice and use outside of clinical trials during drug development, is steadily becoming a key complement to randomized clinical trials. Epidemiologists’ work studying RWE can provide the answers that can’t be gleaned from analytical or clinical studies. (In fact, I’d argue epidemiologists, along with lawyers, should expect many years of gainful employment thanks to the biosimilar industry.)

As Nancy Dreyer, SVP and global chief of scientific affairs, real-world, and late-phase research for Quintiles, described in a panel about RWE at the DIA Biosimilars 2016 conference, “So far, we’ve been concentrating on how biosimilars are made and how they will affect patients. But we need to be thinking bigger.”

What Questions Need To Be Answered?

The patient population and prescriber practices at-large are incredibly complex. As such, many of the bigger biosimilar questions cannot be answered by a clinical study during biosimilar development.

For instance, prescribing practices have been the subject of numerous surveys and conference panels. There are a number of questions to ask: Why did the doctor choose to give a specific treatment to a specific person? Was a biosimilar given because of the patient’s financial status, or was it determined by the hospital formulary or a rebate?

“There are a lot of reasons that drive prescribing practices in situations where it’s not clear that one drug has a particular advantage over another,” Dreyer said. “Prescribing practices are not always evidence-driven. There are many other factors that drive those choices.”

Those in the audience outside of epidemiology, including myself, became privy to a new term: “channeling bias.” In medicine, patients are often “channeled” into specific categories. The channel in which they are placed ultimately determines which course of treatment they receive. For instance, physicians may choose to treat only newly diagnosed, treatment-naïve patients with the biosimilar, while keeping existing patients on the biologic. (In fact, we’re already seeing this in the biosimilar space today.) In some therapeutic areas, new drugs are often given to the sickest patients because existing treatments haven’t been beneficial.

“There are often systematic reasons as to why patients get certain treatments, and these systems can influence the final outcome for the patient,” Dreyer argued. “We need to understand who gets which drugs, and why. We need to be able to distinguish the effects of the biosimilars and the originator products in addition to the other treatments people are taking.”

How To Approach Real-World Evidence

The health system is only going to become more complicated. As the global market sees larger numbers of biosimilar competitors in each treatment class, there will be patients switching from one biosimilar to another biosimilar. There will be stops and starts in treatments. Tender changes or payer formulary changes may warrant switching back-and-forth between biosimilars and originators.

There are a growing number of ways to track RWE. Dreyer highlighted some of these existing sources of RWE, emphasizing big payer databases in particular. Payers catalog many different aspects of a patient’s treatment, including the reasons for each visit to the doctor, each hospitalization, diagnosis, and discharge.

But when reviewing this RWE, it’s important to keep in mind certain factors about the treatment in order to get an accurate picture of its performance.

For one, observable benefits or risks could be tied back to whether the biosimilar was given out as a monotherapy or part of a polytherapy regimen. In addition, Dreyer stressed familiarizing yourself with the reimbursement system, especially as we enter into a period of more frequent switching. Should there be a situation where a treatment is not covered by someone’s health insurance policy and the patient doesn’t switch, there likely won’t be a record of that particular treatment.

The way a drug is administered and distributed — by retail pharmacy or in the hospital or outpatient center — is also necessary to note. Retail pharmacies have more established methods of managing and reporting what is distributed compared to hospital or outpatient settings. The current complexity of the medical benefit could pose some challenges for accurate tracking of treatments.

The success of the biosimilar industry will depend on the industry’s ability to manage post-marketing data and adverse events and to widely circulate global scientific information. Thanks to Big Data, the industry has the opportunity to link disparate data sources, for instance clinical, socioeconomic, and genomic data. By looking into RWE, manufacturers can get a better sense of how biosimilars are being used and reimbursed.

Dreyer is often asked about the long-term use of biosimilars. While it can be possible to determine immediately (or at least within a period of days or weeks) how a patient responds to a new treatment, there is always the chance of future risks or benefits to taking that treatment. These effects may not show up until several years down the road. As Dreyer stated, the ultimate challenge for the industry (and for epidemiologists) is to establish a method of tracking all switches and stops in treatment to get a clear picture of biosimilar performance long-term.