NIH Announces Genetic Testing Registry

On March 18, the National Institutes of Health (NIH) announced the development of a Genetic Testing Registry (GTR).   NIH established the GTR to serve as the single public resource to provide detailed information about the 1600+ genetic tests for patients and consumers.  The database, which will be populated voluntarily by genetic test providers, is expected to be available in 2011.
 
This is good news in that the database reflects impressive advances in the field of personalized medicine and an increased number personalized medicine products.

In announcing the GTR at the PhRMA annual meeting, NIH Director Dr. Francis Collins called for broad public and industry input on registry design.  The Personalized Medicine Coalition is encouraging its members and others interested in personalized medicine to share insights and ideas about the registry.  The database design can be reviewed and comments can be provided through the National Center for Biotechnology Information (NCBI) website at  http://www.ncbi.nlm.nih.gov/gtr/.

Opportunities to participate will be announced through the Federal Register soon.  Comments and questions can also be submitted anytime by emailing GTR@od.nih.gov.

A Victory for Patients and Personalized Medicine

President Obama signed landmark health care reform legislation into law today which represents a major victory for personalized medicine.  This legislation is the first time that the principles of personalized medicine were formally voted on and passed by both houses of Congress and signed into law by a president.  This bill not only recognizes the emerging science of personalized medicine, but ensures it is aligned with the conduct and use of comparative effectiveness research (CER).

Good news aside, there is a lot of confusion about what was actually signed into law and I’d like to help clarify.

On Sunday, the House passed the same bill that the Senate passed on Christmas Eve, H.R. 3590, that incorporated personalized medicine throughout the structure of its CER provisions.  Therefore, health care reform will:

• Expand the research agenda to include primary research on molecularly-informed trials;
• Ensure research recognizes  potential differences including genetic and molecular sub-typing;
• Improve the quality of the science generated from CER by incorporating new information and technological innovations into its studies, reviewing and updating evidence as necessary, and outlining what future research will be necessary to address perceived gaps;
• Incorporate research on patient preferences in the scope of work, including patient quality of life and physician choice; and
• Create an independent research methods committee that includes experts in molecular diagnostics;

After it passed H.R. 3590, the House then passed a reconciliation package (H.R. 4872).  Note that the version of H.R. 4872 approved by the Rules Committee is not the same as the version of H.R. 4872 that was approved earlier by the Budget Committee.  This earlier version contained placeholder language that was replaced with the reconciliation package.  The reconciliation package included a smaller set of changes (e.g., changing the excise tax on high-cost health plans) that does NOT mention CER.  Therefore, it is likely that the Senate version of CER signed into law today—which recognizes personalized medicine throughout its provisions—will not be changed by the Senate in reconciliation.  The Senate is scheduled to consider that package this week.

As of the President’s signing earlier today, the United States has a health care reform bill that recognizes personalized medicine as the law of the land.  Implementation will require a lot of work to ensure that CER is personalized—work to which the Personalized Medicine Coalition is committed.

Can we continue making progress in the fight against cancer, while at the same time meeting the challenge of demonstrating value for innovative therapies?

I think we can.

A paper released today by Boston Healthcare Associates describes some of the important considerations in meeting these goals. The paper, Recognizing Value in Oncology Innovation, highlights the growing role of personalized medicine in cancer care. This trend towards focusing on cancer treatments that are targeted to patients with particular genetic variations or other biomarkers illustrates how innovation can drive better patient care and improved health care value.

The paper also describes the broader dynamics of progress in cancer care, in which new drugs and biologics receive approval from the FDA based on initial clinical trial results, and then accrue additional evidence on their role and value over a considerable period of time (in some cases decades).  Boston Healthcare identified five mechanisms through which this occurs:

• development of evidence of improved outcomes in the initial FDA-approved indication;
• use earlier in treatment line and in earlier disease stage;
• use in different disease indications;
• use in combination with other agents; and
• use in combination with specific biomarkers.

We examined numerous existing therapies to characterize and illustrate these different mechanisms.  In the report, we highlight four specific therapies that illustrate these points.  For example, imatinib (Gleevec®) was first approved in 2001 for treatment of advanced stages of chronic myeloid leukemia and second-line treatment for the earlier, chronic phase of the disease.  Approval was based on surrogate endpoints showing patient response to treatment at the cellular level.  By 2007, the clinical benefit was dramatically demonstrated through research showing an 88% survival rate for patients after six years of treatment, compared to an average five year survival of 48% prior to imatinib. Similarly, the evaluation of docetaxel (Taxotere®) based on early results would have substantially underestimated the drug’s impact on survival for patients with squamous cell carcinoma of the head and neck by more than 4.5 years.

In the paper, we also examine cancer therapies for which the optimal use is guided by genetic markers [trastuzumab (Herceptin®) and cetuximab (Erbitux®)]. With cetuximab, for example, subsequent studies identified a subgroup of patients with a genetic mutation who were less likely to respond to the drug. Patients without the mutation showed an overall survival of 15.6 months, compared to 5.6 months for patients with the mutation.

The Personalized Medicine Coalition addresses this important issue in its payer principles, noting that evidence on the full value of new personalized medicine technologies emerges over time after initial introduction. “As with most new technologies, the evidence available early in their life cycle might not be of the highest level or as conclusive as that available for other diagnostics and therapeutics,” PMC says.

If therapies such as those described in the Boston Healthcare paper had been subject to strict coverage policies that imposed rigid, up-front assessment of value, they might never have reached many patients. Indeed, in countries that make use of these types of assessments, cancer patients have faced potential barriers to treatments like imatinib and trastuzumab. As we seek policies to support continued progress against cancer and addressing rising health care costs, it is important for policy-makers to understand this aspect of medical progress, and ensure that emerging personalized medicine technologies continue to be developed and made available to patients.

Harnessing the Power of Health IT in a New Era of Translational Research

In the final years of the 20^th century and the first decade of the 21^st century, tremendous progress has been made toward bridging a recognized chasm between science and the real world, and specifically in medicine, between biomedical research and its application in healthcare.  Three identified “blocks” to translation have impeded the use of research findings to better the lot of our patients: T1, the translation of laboratory findings to clinical care, T2, the application of best evidence identified during T2 to everyday clinical care; and T3, wider generalization of research findings to improve the health of the community and, more broadly, the public.  The recent deluge of funding for comparative effectiveness research (CER) represents, in large part, an attempt to conquer T2 and T3.  T1, however, persists and presents a fundamental impediment to personalized medicine.

To overcome T1, and transfer T1 knowledge to T2, will require true integration of the clinical and research spheres – an integration that necessitates bidirectional information flow from the patient and physician in the clinic to the research scientist and back again, in an iterative cycle of hypothesis, question, answer, and testing of that answer in the real world setting.  To support this sort of information exchange, we will need: new coordinated health information technology (HIT) systems that span former “silos” in the biomedical community, and that can collect and manage large volumes of disparate and heterogeneous data; culture change that engages clinicians and researchers in a common mission of inquiry to improve care; communication channels that fuel hypothesis generation, and that support the translation of research findings into change in clinical practice, and; decision support mechanisms that help clinicians leverage the power of large-scale aggregated data to improve care for the individual patient.  In short, we need a new model of care, one that harnesses the potential of HIT and integrated clinical/research data to dismantle the T1 block. The purpose, fundamentally, of such a model will be to enable personalized medicine.

In advancing “rapid learning healthcare,” the Institute of Medicine has spearheaded the development of a new healthcare paradigm in which personalized medicine could become a reality.  Efforts are underway to develop this paradigm and its prerequisites.  As one such example, the Cancer Biomedical Informatics Grid (caBIG®) championed by the National Cancer Institute has tackled the development of an infrastructure promoting large-scale data interoperability spanning the data type boundaries from the basic sciences to clinical care and the patient report.  As we seek to match novel therapeutics and trials to patients, and to personalize care using individually relevant information, critical steps will be: (1) providing access to data, (2) generating data, and (3) making sense of the data.  Making sense of data needs to be facilitated at the levels of basic science (to guide translation of in silico research results into clinical practice change and further discovery), the population (to allow CER to guide health services decisions and policy), and the individual patient (to enable personalized medicine).  New data generated in any of these steps should be reinvested in the system to iteratively update the knowledge base.

The caBIG® experience has taught us that just having access to better HIT does not, in itself, advance personalized medicine.  Though a powerful tool, HIT alone is not enough to bulldoze the translation blocks.  Why?  Because healthcare is not a purely technical matter; rather, it is a human system, fundamentally dependent upon human understanding, acceptance, and behavior.  All of these must change in order to transform information flow through HIT, implement a new data-driven model of healthcare, and thus realize the vision of personalized medicine.  The individual stakeholders in medicine need to be aligned behind the new vision – through incentives to participation that speak to each one.  First, the new model needs to be structured, and to function, so that the HIT makes sense to real human beings using the system (clinicians, staff, patients, administrators, clinical researchers, basic scientists); HIT must represent “value added” to the existing system from the perspective of each stakeholder.  Second, interoperable data must be generated, so that the system has “grist for the mill” of inquiry; we have to start somewhere and someone needs to be encouraged to put their first big toe in the water — there is nothing like a “big story” to bring along the naysayers.  Third, to build confidence in the approach, we must make sure that privacy, confidentiality and the sanctity of personal health information are preserved. And fourth, novel ways to make sense of ever-growing databanks need to be developed; these methods may include new approaches for visualization, decision support systems, Bayesian and other branched analytic approaches, CER, and in silico research.  Current efforts focus on generating interoperable data (the middle step), but neglect to create systems that make sense of the data and promote its use, or that provide a structure and an engine to produce the data.

Finally, and, in my mind, most importantly, a critical next step is to define a reorganization of medicine at the point of care.  The new model must fully utilize available data and linked datasets, and must help clinicians understand the data and apply it in tailoring care to their individual patients.  If it makes sense to them, clinicians and patients will drive this.  In the background, interdigitated with the growing body of clinical experiences captured in linked clinical/research databases, will be the robust evidence base comprising published results of basic science, clinical research, and translational studies.  The resulting combination creates a system in which each patient’s care is guided by personal history and characteristics, the experiences of similar patients included in local and massive national longitudinal datasets, and the historical evidence base constituting an up-to-date state of the science.  Our challenge, today, is to develop this system beginning at the point of care, with the patient.

Hamburg Highlights FDA Commitment to Personalized Medicine at PMC Annual Luncheon

When Dr. Margaret (Peggy) Hamburg delivered the Sixth Annual State of Personalized Medicine Address at the National Press Club on February 25, she impressed and energized the audience by announcing the Agency’s intent to release draft guidance on companion diagnostic regulation by the end of 2010.

As the PMC contends and she noted to the audience, for innovations to occur in personalized medicine, FDA needs to outline clear expectations and standards for approval.

According to Hamburg, FDA intends “to clarify our expectations for the kinds of clinical trials and levels of confidence needed to satisfy us that a test is accurate and that it can be used to help shape clinical judgments.…We also are working internally to make sure we have a common understanding across all centers and throughout the agency about the kind of evidence needed when a test result is being used to shape a drug trial, or drug approval or relabeling.  We also intend to make sure the communication line between sponsors and CDER and CDRH is clear, and that sponsors get consistent advice about how to take the next step in development.

We expect to have this guidance finished by the end of the year.”

She also promised that FDA would be flexible, collaborative, open, and clear throughout this process.   Hamburg concluded her remarks by sharing her enthusiasm and commitment for reducing regulatory barriers at FDA for personalized medicine.

Dr. Hamburg has clearly outlined sound goals – to articulate clear procedures and requirements within and among FDA centers for the approval of personalized medicine products– and a sound way to achieve them –through an open and collaborative process.  PMC members are excited by this commitment and are equally committed to working with her to this end since achieving these goals represents a necessary step in assuring that our regulatory processes are appropriately designed for the science of personalized medicine.

The full text of Dr. Hamburg’s speech is available here: https://ageofpersonalizedmedicine.files.wordpress.com/2010/03/pmc-luncheon_hamburg-speech_02-25-10.pdf.