Michael Christel is Group Managing Editor of Applied Clinical Trials, Pharmaceutical Executive, and Pharmaceutical Commerce. He can be reached at mchristel@mjhlifesciences.com.

Michael Christel

sat down recently with Jennifer Buell, PhD, chief operating officer at Agenus, a biotech focused on immuno-oncology, with a pipeline of checkpoint-modulating antibodies, cancer vaccines, adjuvants, and allogeneic adoptive cell therapies. Buell, who helped transform Agenus from a single-product, vaccine company to a platform organization with capabilities from target discovery to GMP manufacturing, discussed the unmet need for additional immunotherapies and combination strategies in cancer. Critical to this effort, Buell stressed the importance of building on learnings from the first wave of approved immune checkpoint inhibitors that target protein receptors PD-1, PD-L1, and CTLA-4 (e.g., Keytruda, Opdivo, Libtayo, Yervoy).

	Agenus is headquartered in Lexington, Mass., where its vaccine manufacturing is also housed; the company’s discovery function is based in Cambridge, UK, and GMP manufacturing for its antibody candidates is conducted in Berkeley, Calif.

	Q: What’s your view on the direction of the immunotherapy field at the moment?

One of the big questions in this area is how to bring real benefit to patients in a more effective way. How we’re looking at this-a 300-person company-is to build on the learnings from these huge trials that Merck and others do, and we’ll say, this subset of patients, they’re being cured, right? Why is that? And how do we increase the benefit or increase the number of patients that fall into that category?

	One example that we came under great scrutiny for was CTLA-4. In 2014, it was widely thought that anti-CTLA-4 was going to go away. The field concluded that it was too toxic, and would be replaced by anti-PD-1 [instead], for example. But we knew that CTLA-4 and PD-1 are very different mechanistically. They play different roles in the immune interaction with cancer. We have seen that with PD-1, patients will see some incremental benefits, but they are not seeing curative responses-and you don’t have the tail of the curve phenomenon with PD-1 that you have with CTLA-4.

	So, we not only pursued a first-generation CTLA-4, but in studying that tail of the curve, we identified cases where patients-the non-responders-have a genetic polymorphism. This population represents about 40% of patients; that’s a big population with a very precise reason for not benefitting. So we went after engineering our CTLA-4 antibody and designed it to amplify the beneficial features of the first generation and add features to expand the benefit to those patients who are not responding to the first-generation CTLA-4s.

 Our next-generation CTLA-4 is advancing in the clinic. We will start combinations with our PD-1 imminently. We believe this could be transformative for the field. Our first-generation CTLA-4 and PD-1 are in the clinic in trials designed to support our BLA [biologics license application] filing. When you take a PD-1 and you know that it works for lung cancer or melanoma, you add CTLA-4 and you increase the response rates and the durability. The most recent case was in renal cell carcinoma.

	Right now, we have two approaches to get to a BLA. One is a PD-1 monotherapy for patients with second-line cervical cancer. And then we have a combination, where we believe adding CTLA-4 on to that PD-1 will provide real benefit for patients.

	Q: Harnessing these combination immunotherapies, which can be more potent and less toxic than single agents-is essentially the key mission today, correct?

 What we know right now is that monotherapy has brought some good benefit to some patients; when you add the combination, you see these remarkable responses and you see durability-and they’re mechanistically-driven. The shortsightedness that the field had when it thought PD-1 was going to be the answer, was addressing only a single component of a complicated system. In cancer, putting all of your eggs in a basket, focusing on just one target location-the tumor, isn’t going to work. Think about systems biology, CTLA-4 is operating in a very different place; regulating in areas of immune modulation. With PD-1, you’re regulating locally. If you put the two together, that’s when you start to see the real antitumor benefit.

	It’s the first time we’ve been able to put “cure” and “cancer” in the same sentence. A good proportion of patients [in clinical trials with these combinations] have not relapsed beyond five years. That’s the benchmark today. Sometimes there’s a combo that isn’t as commercially rewarding. This is an important consideration. These effective products need to be accessible to patients. But you can take a CTLA-4 and a PD-1, and Bristol has shown this [in prostate cancer]; and then Merck came out last year at AACR and demonstrated that Keytruda plus a chemotherapy can not only bring benefit, but it’s also feasible-it’s cheaper, chemotherapy is accessible, centers are comfortable using it. At Agenus, our approach is to have the most effective agents, like antibodies, allogeneic cell therapies, and neoantigen vaccines, in-house. And we do. We plan to deliver high impact results for patients that can be easy to deliver for providers.

	What’s the real bar, then, [to combined checkpoint inhibition]? it’s access, right? We want patients to have access.

	Q: So is access more so the issue than actual response?

 Both are imporant. Right now, with MSI-high (H) colorectal cancer, you put PD-1 and CTLA-4 together, you see the real change in huge response rates and durability. You see the same with renal cell carcinoma. You have a PD-1 approved, you add CTLA-4 on to it, and you see real durability. That was a subject of the most recent approval for Bristol, and that the FDA looked at the durability response. Comparable response rates and durability of response was much more dramatic with the combination with CTLA-4. That’s the holy grail-the durable responses.

	But market access is an important one, too. Merck has used a smart approach, in which they’ve taken their PD-1 and put it on top of standard-of-care approaches. We can do the same, Bristol can do the same. But our focus is on much more disruptive changes. We’re looking at those polymorphic patients that aren’t going to respond to [anti-]CTLA-4, creating a product that can address the problem, and giving them the combination.

	Given that we own all of the products and the efficient process to develop them, we are in a strong position to enable access.

	Q: What technologies is your company using to help advance discoveries in I-O?

 We’re leveraging computational approaches to I-O. We’ll be publishing very shortly on a big data platform, in which we interrogate a series of omics-genomics, transcriptomics, proteomics. We’ve fully characterized the life cycle of a T-cell-we know when it’s tumor-fighting, we can watch it, and then we know when it gets really tired. And we know what it’s showing or expressing when it’s fatigued. And we also know when you can start to intervene. With certain therapies, you can reinvigorate that T-cell.

We’ve fully cut through big data and adaptive learning approaches, and now we’re intervening with different therapies in our pipeline to see when you can actually make that T-cell start fighting again. What’s the best way to do it? Sometimes it might be a monotherapy approach, sometimes it’s a combination of two approaches, sometimes it’s a bispecific antibody approach. We have two molecules in the clinic that were born out of this concept. The design of the molecules came from findings in our platform. One of the molecules is partnered with Gilead-that was the largest preclinical I-O deal in 2018.

Articles

How one biotech is tackling the unmet need for additional immunotherapies and combination approaches in cancer.

Next-Generation Focus in Immuno-Oncology

With drug-development efforts in Alzheimer’s disease continuing to produce underwhelming results—as clinicians have long battled the inherent diagnosis and translational research challenges associated with the disorder—it’s no secret that there is increased clinical focus now on the prevention and early detection of Alzheimer’s. Those were two 

areas of emphasis at the recent Alzheimer’s Association International Conference (AAIC) in Denmark

 at the event that reported a decline in incidence of dementia in the U.S. and Europe seems to indicate that reducing and even prevention of Alzheimer’s may be possible.

Critical to those pursuits, however, will be future learnings generated from the growing recognition today that treatment approaches in Alzheimer’s should target multiple pathologies, says Joyce Suhy, PhD, VP of neuroscience at 

., a provider of medical imaging solutions for clinical trials. Suhy notes that people who get dementia usually have mixed pathologies, whether it’s Alzheimer’s, 

, for example, or other similar neurodegenerative conditions. As evidence that researchers are focusing more on multiple pathologies, Suhy cites the recent 

 struck between the Michael J. Fox Foundation for Parkinson's Research and the Alzheimer's Association and the W. Garfield Weston Foundation around studying the links between the Parkinson’s and Alzheimer’s patient populations, with the hopes of reshaping future treatment targets.  

For Alzheimer’s, specifically, Suhy and her team at BioClinica are focused on helping drugmakers determine whether patients in clinical trials targeting the build-up of amyloid plaque in the brain—considered a crucial factor in the onset of disease—actually have that pathological feature. Most of the notable 

 are testing drugs that target amyloid. In addition, 

Novartis recently partnered with Banner Alzheimer's Institute (BAI)

 on a clinical study that will determine whether two Novartis experimental anti-amyloid drugs can prevent or delay the emergence of Alzheimer’s symptoms. 

Advanced molecular imaging techniques can aid in these efforts by ensuring a patient’s pathology is matched appropriately. Further, they provide clinical investigators with sophisticated tools to monitor Alzheimer’s in their studies.
  
  Suhy chaired a 

 on neuroimaging at AAIC, where BioClinica team members presented recent clinical trial progress using amyloid PET screening for enrichment of patient recruitment for early-stage Alzheimer’s.

She notes that advances over the past decade in amyloid phenotyping, whether through PET scans or imaging of cerebrospinal fluid (CSF) flow, have helped to better target enrollment in Alzheimer’s trials, particularly as researchers are increasingly studying subjects with more prodromal and milder cognitive impairment. In its presentation, BioClinica reported higher amyloid-negative rates due to the inclusion of earlier-stage patients, when compared to historical trials, which focused more predominately on the mild-to-moderate Alzheimer’s population.

“As we’re moving towards earlier screening for enrolling patients into Alzheimer's disease trials, we find an increasing rate of patients that are amyloid-negative,” says Suhy. “Many of these patients may never advance to mild-to-moderate Alzheimer's.” 

Uncovering these earlier clues can be valuable for drug developers when recruiting patients for Alzheimer’s treatment trials targeting amyloid. In past studies, otherwise qualified individuals—who turns out didn’t have amyloid clusters in their brains—were often enrolled, adding significant noise to those trials. The challenge, Suhy says, is that these subjects typically meet the various clinical criteria for the study protocol, such as memory or cognitive decline, and, therefore, are considered good candidates for enrollment. They often progress smoothly through the screening process, and only when getting a PET scan at the end is it discovered they are amyloid-negative.
   
  "If a patient doesn’t present with amyloid in the brain, then a drug targeting amyloid will not be effective,” says Suhy. “In other words, the drug target must be present in order for a drug to work. Hence, the current and important initiatives for screening clinical trial patients using molecular imaging like PET or CSF analysis to verify the presence of pathology and enroll appropriate patients for a trial.” 

Suhy points out that there are several ways to enrich Alzheimer’s patient populations to increase the chances of a successful trial. Besides PET or CSF imaging, some studies are looking at genotype ApoE 2, for example. 

“By identifying patients earlier in the course of disease, clinicians can maximize their ability to treat and ultimately help patients,” she says. “A key aspect to this is the identification and selection of the right patients.”  

AAIC, held in Copenhagen, Denmark’s capital city, featured more than 150 data unveilings in Alzheimer’s R&D. One particular notable development, according to Suhy, is the continued promise of tau PET tracers. Tau neurofibrillary tangles, like amyloid, represent one of the hallmark pathologic signs of Alzheimer’s. Though still early in testing, it is thought that tau is more closely linked to memory decline than amyloid, and, therefore, tau imaging—and the development of ligands for early detection of Alzheimer’s risk—may eventually be a better tool for determining cognitive impairment than amyloid imaging. 

Another takeaway for Suhy was the release of 

Phase II results for Genentech drug crenezumab

, a monoclonal antibody that target all forms of amyloid beta. Though crenezumab did not meet its primary endpoints for cognition and function, a secondary analysis showed promising cognition effects in the milder Alzheimer’s patient cohort when taken at a higher dose. Suhy believes this data further reinforces the importance of early screening of disease risk.
       

It's no secret that there is increased clinical focus now on the prevention and early detection of Alzheimer's.

Alzheimer's Focus Increases on Earlier Screening for Pathological Triggers

Since the release of the Final Rule by the Department of Health and Human Services (HHS) in February 2013,

 the Physicians Payment Sunshine Act, more formally referred to as Open Payments, has been in place for almost 18 months. However, it will likely be over the course of the next few months where the implications of the law and its contentious requirements will start to be fully realized. On Sept. 30, records of payments or transfers of value (TOV) issued by pharmaceutical, biologic, and medical device manufacturers to physicians or teaching hospitals are set to be made available by the Centers for Medicare & Medicaid Services (CMS) on a public searchable website. All manufacturers of products covered by Medicare, Medicaid, or the Children’s Health Insurance Program (CHIP) will be required to report such information annually, including tracking all payments of more than $10 made to investigators and clinical trial research sites. The Sunshine Act, passed as part of the Affordable Care Act in 2010, was instituted to prevent inappropriate influence on research, education, and clinical decision-making and to avoid conflicts of interest that can compromise clinical integrity and patient care. 

Affected parties have spent the last year trying to interpret the law’s complex reporting requirements, while meeting a March 31 deadline for reporting aggregate 2013 payment data to CMS (collected from Aug. 1–Dec. 31, 2013). By last month, companies were required to submit detailed 2013 payment/transfer of value data. And although there is still skepticism that the information will actually go public by Sept. 30, a panel of experts at DIA’s 50th Annual Meeting in San Diego agreed that for any entity involved in the transfer of information that ultimately helps patients—whether it’s medical affairs, medical communications, medical science liaisons, medical writing, industry-sponsored publications, etc.—they must be ready to adapt to the new changes and expect more, not less transparency globally, as other regions are expected to follow the US lead. To that end, it is crucial, the speakers said, for life sciences companies and other stakeholders to understand the implementation of the new law, and communicate that with their investigators and clinicians. Guidance on transfer of value is country-specific and appears to be evolving quickly, one expert noted. However, transfer of value as it relates to scientific publications in the Sunshine Act remains unclear, she said, with interpretation generally company-specific. The speakers stressed the importance of educating authors about a company or customer’s specific policy on transfer of value.

The panel discussed the impact of the Sunshine Act on medical and scientific communications, particularly in relation to journal reprints and publications support; the role of the medical science liaison; and the potential consequences of the new law on actually hindering the interchange of valuable research. Overall, the discussion has seemingly moved well beyond issues involved in defining expenses for meals and travel, for example, to attempts to more firmly understand the reporting requirements in areas such as research payments. The scope of research covered under the Sunshine Act includes preclinical research and FDA-sanctioned Phase I to Phase IV clinical trials. The law applies to investigator-initiated studies and product development that are subject to a written agreement/contract or a research protocol, including those trials conducted through a CRO or other intermediary. The entire research payment must be reported, including the entity paid and the study principle investigators. Speakers pointed out that it is optional to report the context of the clinical trial.

The discussion also noted the importance of medical science liaisons in addressing payments disputes that arise directly with the clinicians. According to the Federal Register, there will be a 45-day review period of reported payment information prior to public disclosure. The review will be done via a secure website, which covered recipients will be able to access. Following the review, there is a 15-day period for dispute resolution. Recognizing the expanse of data involved, CMS published a notice in May encouraging additional feedback on dispute resolution and the corrections process. The agency was accepting comments until early June. 

DIA panel experts noted that there is concern around the ability of clinicians who are busy running their practices and dealing with other responsibilities to appropriately review the payment data in the 45-day window, and then, once a dispute is initiated and submitted, to resolve those quickly; manufacturers will be similarly challenged to resolve payment disputes within the 15-day period. Speakers acknowledged the potential of dealing with disgruntled clinicians as the payment disclosure system takes effect. For medical science liaisons, who may be confronted about research-related payments, the need to stay informed on their company’s public policies as well as evolving research and dispute resolution processes is crucial, experts said. Medical science liaisons may also be called upon to triage reported payment disputes.   

Challenges in reporting research and other forms of payment under the Sunshine Act may be highlighting a broader concern in the world of drug development and clinical trials. One speaker on the DIA panel raised the possibility of potential unintended consequences stemming from the law. Among those may be the reaction of key opinion leaders in the medical community who may be hesitant to contribute to a research paper, fearing their names will appear on a pharma payments list. A related consequence may be the impact on the quality of publications, if clinicians are less likely, as authors, to translate valuable data and put it in a clinical context. Reverting primarily to authors from inside the industry is a possible option, but many journals only accept papers authored by practitioners and investigators. The sentiment is if clinicians share less research, due to the Sunshine Act, it may ultimately hurt patients. The law, however, provides limited information, speakers said, with respect to the role of non-industry authorship of papers that communicate medical research results. CMS has indicated, according to one speaker, that payments for medical research writing and/or publication should be included in the research payment. 

Another topic of emphasis surrounding the Sunshine Act is the issue of journal reprints and the classification placed on articles from scientific journals that are disseminated to physicians as transfers of value, and, therefore, reportable to CMS. A panelist presented a survey of how pharma and biotech medical information departments are addressing the reporting of reprints and other educational materials as a transfer of value. In a question about unsolicited requests from physicians, 78% of departments surveyed said they report reprints as transfers of value when they send them as part of their response. Thirteen-percent indicated they no longer send reprints, due to the Sunshine Act. Such actions haven’t necessarily translated to a considerable drop in volume of unsolicited requests for medical information. The survey found that following the implementation of the Sunshine Act reporting requirements, 57% of respondents report no change in their inquiry volume, while 14% say the volume of inquiries has decreased.   

1. Department of Health and Human Services, “Medicare, Medicaid, Children’s Health Insurance Programs; Transparency Reports and Reporting of Physician Ownership or Investment Interests; Final Rule,” 2013. 

http://www.cms.gov/Regulations-and-Guidance/Legislation/National-Physician-Payment-Transparency-Program/Downloads/Final-Rule.pdf

With the public release of physician payment data slated for September, the implications for medical and scientific communications are many.

New Dawn for Transparency

The practice of comparative effectiveness research (CER), its promise spotlighted in recent years amid the legislative push to measure the value of medicines in the real world, has had little impact on actual healthcare decision-making to date. That was the consensus from experts speaking on the subject at the DIA 50th Annual Meeting in San Diego, though the slow go to real practice change is not due to a lack of interest or attention in CER. Today, there is more education and guidance available on the conduct of non-interventional approaches, and groups such as the Agency for Healthcare Research and Quality (AHRQ), the Patient-Centered Outcomes Research Institute (PCORI), and NIH are moving closer to an agreement on uniform research standards governing this area. 

In addition, opportunities exist to use real-world evidence more widely. The European Medicines Agency (EMA) issued guidance last year on post-authorization safety studies, now requiring the collection of risk-benefit data as well. No longer is it enough to simply identify side effects in the observational setting; pharmaceutical companies must now take a more granular approach, examining different subpopulations to determine their respective risk-benefit balance.

 There is also increasing demand from FDA that drug manufacturers conduct observational studies on a new product’s effectiveness, and healthcare payers and clinicians are eager as well to view more detailed health outcomes data to inform prescribing and reimbursement decisions. 

It is believed that 15% of current postmarketing commitments have non-interventional study designs, and the number of patient registry studies listed on ClinicalTrials.gov reportedly jumped from the hundreds to the thousands from 2013-2014. 

“CER is going to be a fundamental game-changer in how we practice medicine, and will help us get access to the right medicines at the right time for the right patient,” Nancy Dreyer, chief of scientific affairs and senior VP at Quintiles Outcome, the CRO’s real-world and late-phase research division, told 

, leading up to a DIA session she participated in on CER and healthcare decision-making.

Dreyer noted, however, that at the moment, learning healthcare systems still lack the tools and training necessary to best interpret real-world data and help implement it into healthcare delivery. Kimberly Westrich, director of health services research at the National Pharmaceutical Council (NPC), a policy and research organization, also pointed to a lack of good studies and not enough dissemination of quality studies as factors contributing to the current gap between promise and reality for CER. Such factors are likely influencing stakeholder perceptions of CER’s role in the healthcare landscape. According to findings from a NPC survey presented by Westrich, only 6% of respondents feel there will be substantial improvement in CER’s impact on healthcare decision-making in the next year. That figure does increase to 21% when applied to the next three years and 42% to the next five years.    

Another roadblock in CER adoption, according to Brian Mittman, a senior scientist with Kaiser Permanente Dept. of Research & Evaluation, Care Improvement Research Team, speaking during the session, is the physician community’s general conservative response to evidence—that while often an appropriate response to single efficacy-related studies, is not appropriate, Mittman believes, in the face of better forms of evidence such as those captured by systematic reviews and CER studies that are well-designed. Another factor influencing the implementation of CER, Mittman says, is the uneven level of support and investment site-by-site. There are cases where research teams are on-site promoting CER and evidence-based adoption, while also measuring findings and providing feedback; but such efforts are not scalable enough across a study program to achieve practice change on a large scale, Mittman notes.    
   
  To help improve the translation and dissemination of CER, researchers, through an initiative funded by the NPC, have developed the Good ReseArch for Comparative Effectiveness (GRACE) checklist, a screening tool that helps identify and validate the observational research that is sufficient enough for decision support.

 The 11-item checklist, led by Dreyer’s group at Quintiles in collaboration with NPC, has been applied to hundreds of literature reviews, Dreyer says, conducted by GRACE volunteers representing academic, government, and private sectors, with the backdrop question being, “Is this adequate for the study purpose?” Another useful tool in assessing good practice for observational studies is the federal handbook, “Registries for Evaluating Patient Outcomes: A User's Guide,” commissioned by the AHRQ.

 The guide, now in its third edition, has helped inform pharmacovigilance legislation in the European Union.

There are emerging tools in the medical data space that are attracting notice from healthcare stakeholders interested in CER. For example, with the growing availability of electronic medical record (EMR) data, there are now opportunities to collect clinical detail on health outcomes, along with the traditional data mined from insurance claims (e.g., prescription use, physician/hospital visits).
   
  For healthcare payers, specifically, there is great interest in using CER data to aid in formulary and reimbursement decisions. Agencies such as the National Institute for Health and Care Excellence in the UK have made payer determinations based on patient registries. Health plans and pharmacy benefit managers, however, are still limited in their understanding of CER and, thus, any resulting evidence has had little impact on the way payers reimburse for different therapy options, the speakers said.
    
  “Payers thrive on CER, they just won’t tell you how to do it,” Dreyer told us. “It’s not as simple as, ‘This drug costs more.’ Payers have a surprisingly long view. They want to know over the long-term is this benefit really going to make a difference. They need a lot of very detailed information, and they want to know about their patients. [Centers for Medicare & Medicaid Services] will say, ‘I want [the data] in the elderly; don’t bring me a clinical trial in younger people.’ People out in the Southwest will say, ‘I have a Spanish population.’ There’s all kinds of specialty issues.”

The challenge, therefore, is providing payers the right evidence and the right comparators. Sponsors have attempted to placate insurers in the past through head-to-head trials, which have garnered significant notice, but have often left payers unconvinced of a drug’s ultimate effectiveness in the specific therapeutic market. That’s largely because the comparators chosen are often older drugs not covered on formularies, or a company’s new product has not been used enough in the real-world environment. Hence, any comparative data is of less importance to payers.      

“If nobody is using your product, they’re very hard to study in non-interventional studies,” says Dreyer. “There’s some wonderful new drugs that looked good in the clinical setting and physicians won’t touch them. The real-life experience is very different from the clinical trial experience. So several new products never made it. They were good but you needed the real-world setting to understand the value.”
  
  To better deliver the quality evidence sought, pharmaceutical companies need to identify which consumers are the new adopters of drugs in their target markets and find patient populations with similar characteristics to conduct CER, Dreyer said. Understanding the context of real-world studies has become increasingly important. For example, patients in a crowded treatment market are less likely to switch to a new product. With evidence demands increasing from regulators and payers alike, sponsors are realizing the necessity to conduct smaller trials in more sensitive populations. 

“You have to start somewhere,” Dreyer told us. “It comes down to having a good enough product that people are willing to give it a try, and then watching who uses it and how they use it, and finding similar people…  It’s the concept of treatment heterogeneity. [Trials typically target] the average patient, the average treatment, the average treatment effect. But no one is average. No one gets an average treatment effect.”


  1. European Medicines Agency, “Guideline on Good Pharmacovigilance Practices,” 2013. 

  http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2012/06/WC500129137.pdf

2. “Grace Principles: A Validated Checklist for Evaluating the Quality of Observational Cohort Studies for Decision-Making Support,”


http://www.graceprinciples.org/doc/GRACE-Checklist-031114-v5.pdf

3. Agency for Healthcare Research and Quality, “Registries for Evaluating Patient Outcomes: A User's Guide: 3rd Edition,” 2014. 

http://effectivehealthcare.ahrq.gov/search-for-guides-reviews-and-reports/?pageaction=displayproduct&mp=1&productID=1897

The potential of comparative effective research in transforming healthcare remains untapped, but the opportunities are there.

"Evidence" Trail Elusive

While at DIA’s 50th Annual Meeting, we got the chance to speak with Nancy Dreyer, chief of scientific affairs and senior VP at Quintiles Outcome, the CRO’s real-world and late-phase research division, about the current tide for comparative effectiveness research (CER). Dreyer is the leader of the 

, which has developed good practice principles for observational studies of comparative effectiveness. She also is a contributor to the federal handbook “

Registries for Evaluating Patient Outcomes: A User's Guide

 What trends do you see emerging in CER at the moment?

 The uses of CER are growing dramatically. There have been some tremendous changes in the world. One of them is, we know how the FDA has risk-management programs—if a drug comes on the market and they’re concerned about the safety but they think it’s worth marketing, they require post-authorization safety commitments. In Europe, they’ve changed the dynamic. It’s not just safety, but they’ve taken into account effectiveness. It’s not enough to look and say somebody had a side effect. They’re looking in different subpopulations and saying for these people, the benefits are really strong or the risks are small for this population. Europe is ahead of the U.S. because they’re asking for [data] on benefits as well as risks. They have 

 so they can require benefit-risk data collection after launch.

 How have perceptions of CER evolved among healthcare payers?

 Payers thrive on CER, they just won’t tell you how to do it. Because every question they ask is, ‘Why should I pay for this?’ It’s not as simple as, ‘This drug costs more.’ Payers have a surprisingly long view. They want to know over the long-term is this benefit really going to make a difference. Then their decisions are yes/no; ‘I’ll cover it or not. I’ll cover it for this person because of their other comorbidities but not for this person.’ They need a lot of very detailed information.

 What about the sponsor’s responsibility in providing CER and real-world data to payers and regulators?

 They used to measure time to market approval, which is pretty important. Now they’re starting to look at time to reimbursement. Time to reimbursement means you had enough data to convince somebody [to cover your product]. There’s some great stories about drug companies that do these head-to-head trials because that’s what they think the payer will want. But then they come out with their study and the payer tells them it wasn’t the right comparison. So they spent how many tons of millions on the wrong evidence? Head-to-head trials aren’t very popular, because you’re not likely to have the comparator that will be important by the time it’s done. The real-life experience is very different from the clinical trial experience. Several new products never made it. They were good but you needed the real-world setting to understand the value.

 You have to build that evidence outside the clinic setting. It comes down to having a good enough product that people are willing to give it a try, and then watching who uses it and how they use it, and finding similar people. You have to find the right comparators. Companies have to start to understand who are the new [treatment] adopters and find people who are similar to them. We do lots of studies in people who are getting their first treatment, for example. It’s all about the context in those real-world studies. That’s where the value is.      

  What tools are supporting the advancement and implementation of CER?

 There’s an exponentially growing interest in this area, but we traditionally didn’t know what data to use. The only data that was readily available was insurance claims data. Now that there’s so much more electronic medical record data available, we’re starting to marry those and have the real clinical detail along with, ‘Did you actually fill the prescription?’ There are a lot more tools available to pharma companies and to payers and to regulators that they’re starting to pay attention to. Because you can’t do everything in a very expensive prospective study. Sometimes you need to have early indicators.

 Where do you see the future of CER in helping shape healthcare decisions? 

 CER has the ability to improve not only access to medicine but the practice of medicine. It’s at the heart of these learning healthcare systems that are talked about. They just don’t have all the tools yet. CER is going to be a fundamental game-changer in how we practice medicine and will help us get access to the right medicines at the right time for the right patient. The technology is enabling these changes, but it’s the training and the experience of the people that implement it and interpret it that’s going to be most important.  