Tommy Lasorda, the revered Major League Baseball manager, once said: "No matter how good you are, you're going to lose one-third of your games. No matter how bad you are, you're going to win one-third of your games. It's the other third that makes the difference." Members of the Biomarkers of Anti-TNF-α Therapy Efficacy in Rheumatoid Arthritis to define Unresponsive Patients Consortium — or BATTER-UP — can relate. Though they say that TNF-α inhibitors have improved the lives of many rheumatoid arthritis patients, BATTER-UP's members also note that these biologics are not effective treatments for every patient. To that end, they seek to validate biomarkers that predict patient response to anti-TNF therapy in an effort to advance personalized medicine for the disease.
"The numbers in the literature vary," says John Carulli, director of genetics and genomics at Biogen Idec. "But broadly speaking, about one-third of the patients [on anti-TNF therapies] have no appreciable clinical response. Another third have a very good clinical response — they're actually great drugs for those people. And the other third is somewhere in between."
Michael Weinblatt, co-director of clinical rheumatology at Brigham and Women's Hospital, says he and other clinicians "believe that there ought to be predictors of patient response." Since oncologists can, in many cases, determine the best therapies for their patients based on molecular markers, why couldn't rheumatologists do the same?
"As a science, we have seen brilliant breakthroughs in personalized medicine already — mostly in the oncology arena," says Mark Curran, senior director of immunology biomarkers for Centocor Research and Development. "I anticipate that the same concepts are applicable to auto-immune disease, and consortia like BATTER-UP will play an important role in facilitating the … move from aspiration to discovery to clinical practice."
An unprecedented team
The story of BATTER-UP begins in Peter Gregersen's lab at the Feinstein Institute for Medical Research in Manhasset, NY. In 2004, Gregersen and his colleagues in the Auto-immune Biomarkers Collaborative Network — or ABCoN — profiled gene expression in a prospective trial of 116 rheumatoid arthritis patients who were beginning anti-TNF therapies. The ABCoN team presented its data at the American College of Rheumatology's 2007 annual scientific meeting. In its ACR abstract, the team noted that while "no single good predictor emerged from an analysis of biomarkers at baseline ... combinations of biomarkers may be useful in prediction of clinical response to anti-TNF therapy."
At the time, Biogen Idec had several anti-TNF therapeutics in its development pipeline. Carulli, aware that ABCoN "had done a really fantastic job of creating a rich data set on a relatively small cohort" of rheumatoid arthritis patients, approached Gregersen in 2006 to propose a pharmacogenomics collaboration to address questions about differential anti-TNF therapy response. For Biogen Idec — which markets the anti-TNF drug Rituxan that it developed in collaboration with Genentech and Roche — "the goal was really to rationalize the treatment," he says.
In a 2008 Molecular Medicine paper, Carulli and Gregersen — along with their collaborators at Boston University, the Broad Institute, Radboud University Nijmegen Medical Centre in the Netherlands, and Genentech — report candidate polymorphisms associated with differential anti-TNF treatment response, which they identified in a genome-wide association study on an initial set of 89 ABCoN cohort patients. Then, in 2009, Carulli, Gregersen, and their colleagues at Biogen and Feinstein streamlined these candidates to an eight-gene panel. In a Genomics paper, the team shows that the panel is 89 percent accurate in predicting anti-TNF response. Aware that validating the predictive power of these transcripts would require a large, prospective clinical trial, Carulli, Gregersen, and the others began recruiting collaborators from across academia and industry, and BATTER-UP was born.
The eight transcripts from the Genomics study will serve as the consortium's reference set in its forthcoming trial, for which it aims to enroll 1,000 patients. "That eight-gene data set is … accurate to the limits of that patient cohort," Carulli says. "While we're aiming to validate that test — and that would be fantastic — we also recognize that maybe we'll do better [with] something different."
BATTER-UP has begun to enroll patients across 26 US states. Rheumatoid arthritis patients who have not taken anti-TNF drugs — or those being prescribed a different TNF-α inhibitor — who meet the diagnostic eligibility criteria and elect to participate in this study will be evaluated for clinical characteristics and provide blood samples during their initial visit as well as three months later. Patient samples will be shipped to Gregersen's lab, where his team will perform genotyping and gene expression analyses. Study participants who do not achieve a "good response" after 14 weeks of treatment will be considered TNF-α inhibitor unresponsive.
Beyond genotype and gene expression data, the BATTER-UP team also aims to interrogate protein and RNA expression in order to uncover novel predictors that may add to — or supersede — those in the initial test set.
A level playing field
BATTER-UP's rheumatoid arthritis research efforts illustrate industry's shift toward collaborative efforts for personalized medicine. The consortium's existence is "pretty exciting. ... We've never, ever been able to do this in rheumatology — to get multiple companies with competing interests to work together in this protocol," Weinblatt says.
Centocor's Curran says that public-private consortia "serve not only to resource important experiments, but provide opportunity for organizations to share methods and thinking. As the pharmaceutical industry is forced to embrace external innovation principles, efforts like BATTER-UP serve as incubators for learning how to perform large and complex experiments."
For these collaborations to succeed in a pre-competitive environment, Curran says it is critical that participants agree unanimously on an answerable research question. "There must be shared objectives such that multiple partners are willing to contribute resources, including staff," he says. "The questions we want to answer are difficult, complex, and, in many cases, costly. Where it was once possible to go it alone, we now face the realities of needing to combine resources. ... Especially when considering the heterogeneity of a crippling inflammatory disease like RA."
Should the BATTER-UP team validate biomarkers for anti-TNF response, the patient care payoff will be significant, Weinblatt says. Equipped with molecular data, physicians would "be able to be smarter about initiating treatments in patients," he adds. While anti-TNFs will likely remain the go-to biologics for rheumatoid arthritis treatment, a simple blood test paired to a biomarker--based companion diagnostic could "rationalize and streamline the decision-making process," Biogen Idec's Carulli says. And because TNF- α inhibitor therapies are costly — on the order of $20,000 or more per year — both patients and health care payors will see the benefits of clinicians' administration of the "right treatment for the right patient," Weinblatt adds.
Looking into the future, Carulli is hopeful that the data generated by this study may also be useful in developing novel rheumatoid arthritis drug targets for TNF-α inhibitor unresponsive patients.
"It took effort, but in retrospect, [it] was a terrific collaborative effort in forming BATTER-UP and initiating the consortium," Carulli says. "Now we are focused on successfully enrolling the trial and executing on protocol objectives and, to date, we are off to a really great start." Bases loaded, batter up.
Members: Feinstein Institute for Medical Research, Harvard Medical School, Biogen Idec, Bristol Myers-Squibb, Centocor Research and Development, Crescendo Bioscience, Genentech, Regeneron Pharmaceuticals, Sanofi-Aventis, and Medco Health Solutions
Funding: Equal contributions from all industry participants (except Medco, which serves as the consortium's contract research organization)
Timeframe: Actively enrolling patients. Study start date: June 2010. Estimated study completion date: July 2012