October 1, 2007 (Vol. 27, No. 17)

Reeducating Medical Professionals and Public Is Mandatory to Overcome Substantial Obstacles

Harvard Medical School is hosting “Personalized Medicine: A Call to Action” at the end of November. Participants will discuss obstacles to the adoption of personalized medicine and showcase evidence that will stimulate stakeholders to act and overcome these barriers. All this could change the practice of medicine by incorporating genetics and genomics into the clinic to achieve better outcomes for patients in a cost-effective manner.

The meeting will explore multiple perspectives on how the personalized medicine revolution has been put into practice and what is required on the part of physicians, patients, payors, provider organizations, pharmaceutical innovators, and the business community to ensure its future success.

Personalized Medicine Defined

This of course begs the question of how personalized medicine is defined. “One of the things we have been doing is trying to project where the field of personalized medicine is going, because from a population-segmentation perspective, we are already in a personalized medicine world,” says Brent Vose, vp and head of oncology at AstraZeneca (www.astrazeneca.com).

For example, there are ways to segment how a population will react to treatment for HIV and also certain types of cancers, although Vose is quick to point out that these are still in the relatively early stages of development. “The responsibility is to see if we can predict toxicity or those most likely to benefit,” adds Vose. “This reflects quite a change in how we do drug discovery and patient identification, and the tools we need to ask these questions.”

Gary Neil, M.D., group president, CNS/IM franchise at Johnson & Johnson (www.jnj.com), says that in defining personalized medicine, most people focus immediately on genotype and gene expression as a specific way to identify a potential therapeutic for a patient. “It’s more than gene expression and phenotyping if you want to talk about the best treatment option for a diagnosis,” he explains. “We need to also be asking the patient ‘what do you prefer?’ In personalized medicine, there has to be an understanding of personal, patient-centric choices.”

Diagnosis has also become much more complex, adds Tom White, Ph.D., CSO and vp of R&D at Celera (www.celera.com). “It’s no longer a question of do you have the disease. Now it’s ‘are you at risk for the disease and has there been disease onset?’ Also disease classification ties into prognostics: Is the prognosis good or bad? Are there multiple treatment options? How do you choose the most effective with the least risk? What is the risk for adverse events? Is there a way to modify the course of therapy? Celera approaches these problems from a diagnostics, monitoring, and therapeutic perspective,” Dr. White notes.

Issues and Obstacles

Therein lies one of the biggest challenges. “Physicians are taught to learn a catalog of diseases and a repertoire of treatment for those diseases, but what we’re finding now is that when you ascribe a diagnosis, you’re moving away from that repertoire and trying to individualize therapy from a pharmaceutical perspective. It’s believed that we have benefited from this model,” explains Dr. Neil.

Klaus Lindpaintner, M.D., Ph.D., Roche distinguished scientist and vp, research head, Roche Genetics and Roche Center for Medical Genomics, F. Hoffmann-La Roche (www.roche.com), says that the main problem is naïveté about the likelihood of finding sufficiently informative markers that can ethically and cost-effectively be deployed in medical practice and that are based on properly conducted prospective clinical trial results.

“So far only HER2 seems to fulfill these criteria,” says Dr. Lindpaintner. “A typical example for how not to do it is a test for DPYD and TYMS to allegedly curb Fluorouracil (5-FU) toxicity where, despite some plausible arguments being put forward, there is no supporting data.

“In fact, we have unpublished data to the contrary. Using this test may well end up in unwarranted denial of a life-saving medicine to cancer patients. The issues hardest to reconcile are doing the appropriate prospective, controlled, replicate trials to define the actual product profile of a test and examine whether it lives up to the desired target product profile.”

Dr. White agrees. “We need more telling examples in addition to HER2. Right now there are molecular diagnoses that can be made for leukemia, but the classification is used as a clinical treatment. This isn’t very effective because often more information is needed before you can properly prescribe a treatment.”

“What we’ve learned is that the marketplace needs more evidence to establish value for personalized medicine. At the same time, this is a field that is still in the very early stages and it needs more time to establish itself,” adds Peer Schatz, CEO of Qiagen (www.quiagen.com).

One of the biggest issues that Vose sees is the ability to identify patient populations. “You need to see linkage between molecular targets and the disease; there are healthcare demands that require an instantaneous response, and these are the things we agonize about.”

“If you’re talking about monoclonal antibodies, or some small molecules, that’s the driver to a lot of drug discovery right now,” notes Vose, “but the uncertainty involved in the hypothesis of prediction may mean that it’s not possible to develop the therapeutic and diagnostic in the same timeframe.” The biomarker remains a question. One example Vose mentions is that EGF kinase-receptor expression was once incorrectly labeled as the predictor of response.

Tom Miller, managing board member of Siemens Medical Solutions (www.siemens.com), says that an absolute convergence of diagnostic testing, devices, drugs, and information will be required to bring new medicines to market. “In fact, the entire cycle of medical discovery and care standards definition, from bench to bedside, will have to change with diagnostic tests to identify relevant patient sub-populations being developed in lock-step with new pharmaceuticals becoming the norm,” he reports.

“Pharma will have to radically change its development paradigm as it cannot afford to spend as much to develop new drugs that will only drive a much smaller future revenue.”

Perceptions of pharma, Dr. Neil thinks, are also problematic. “It’s expensive to develop drugs, and it isn’t easy recouping that investment,” says Dr. Neil.

“It’s easy to say that pharma is reluctant to go the personalized medicine route because it will threaten the pharma blockbuster model, but the reality is that our knowledge and the technology of personalized medicine is still in its infancy. We see great opportunity for more efficient drug development and new paradigms of funding related to outcomes rather than just selling pills. We don’t want to create a medicine that is effective only 40 percent of the time. We want every patient who can benefit to get the appropriate therapy and none who will not benefit.”

Dr. White sees peer-reviewed publications, and the resulting FDA applications for diagnostic kits that can reference these publications, as a strong aid to test registration. “You can’t underestimate the role of peer-reviewed publications and the clinical utility they associate with testing,” notes Dr. White. “The agency is open to approving, fairly rapidly, tests whose clinical utility is already accepted. Peer-reviewed papers were critical in gaining clearance for two deep vein thrombosis tests and one for irinotecan toxicity, and also helped ease the clinical trial requirements.”

Dr. White says that the ability for companies to do retrospective analysis of biomarkers in consented samples from previous prospective trials cuts out time that would otherwise be spent performing a new prospective study and waiting for clinical outcomes. “Access to the Framingham Heart Study and other big government studies such as the Women’s Health Initiative study on hormone replacement could be very useful for smaller companies to demonstrate the clinical utility of new diagnostic markers for heart disease.”

Obstacles Beyond Science

There’s good reason for pharma to want to shoot for higher effectiveness. “There is an understandable reluctance on the part of payors to reimburse for medicines that don’t work,” says Dr. Neil. The zeitgeist is moving us toward outcome-driven reimbursement.

Interestingly enough, screening for diseases is not currently covered by many insurance companies, although diagnostics for treatment selection are reimbursed by Medicare. “Reimbursement is going to be a big consideration,” adds Dr. White. “There needs to be a lot of education, both with physicians and the public.”

Dr. White posits that the FDA will take on this role on the diagnostics side. “The FDA intends to regulate multivariate testing by focusing on algorithms, and the regulatory oversight will affect CLIA labs,” he adds. “Prognostic tests will be easier and apparently take less time to gain clearance. Predictive tests will have a longer approval process and need to be extremely accurate.”

Schatz notes that because this field is so new, “holistic thinking, with regard to how to develop and commercialize the concept of personalized medicine, is not broadly established. Results are needed to validate the investments. The values of monitoring, profiling, and stratifying need to be made clear, and once these are made clear, educating efforts for prescribers, payors, providers, and purchasers of tests will be the next step.”

Regulatory issues will be a force to reckon with in the near future and on many fronts including privacy and ethics, which have been debated at length. “But this debate must occur as real-time analysis of actual patient outcomes will be required as the numbers will be too small to wait for retrospective epidemiology.”

Schatz adds that current regulatory policies, including FDA guidelines, simply do not exist. For example, how do we govern clinical trials from a personalized, genomic/proteomic standpoint? By definition, each will be on a smaller scale, drawing from a smaller set of potential patients with outcomes that benefit a distinct disease sub-population.

“Probably one of our biggest challenges is that our knowledge base is so fragmentary,” says Dr. Neil. “Our biggest barrier is our lack of knowledge to make rational decisions. The FDA is still figuring out how to regulate this new science, and then as we develop diagnostic tools based on genetics, we run into privacy issues and possible discrimination. Other questions remain such as whether insurance will pay for what is considered then a preexisting condition, so there are a lot of things that we need to figure out and educate the public and the medical community about.”

Converging technologies will also play a role, says Dr. White. “Consider how IT can and will integrate a patient’s records. Patient privacy is going to be a big consideration.”

Absolutely critical, says Schatz, is the dialogue between pharma and academia. “From the perspective of creating better and more effective and efficient diagnostic tools, the continuum between the research done in academia, the development in pharma, and diagnostics is crucial. Access to this continuum is an important value consideration for pharma companies considering partnering in personalized medicine.”

Identifying Patients

There have been successes. Identifying patients for whom treatment might not work is no small consideration. There is indeed cost benefit to expenditure on targeting those patients most likely to benefit, Vose says. “In cases where there is a predictor, you can achieve better outcomes. If the response to your drug is seven percent but you can select populations for which you think it might work, that number goes up to 40 percent, that’s a real advance,” explains Vose.

“So if you take a broader definition of the term personalized medicine, that’s where we are now, with glucose testing for diabetes and cholesterol testing for heart disease. As for gene therapy, 10 years ago I would have said it would be here in 10 years. Now I’d have to give it another 10 years,” concludes Vose.

“We’re working on it, we embrace it, and when you look at the Velcade story, we’re willing to put our money where our mouth is,” adds Dr. Neil. “We’re willing to help work on laws to protect patients, give them privacy, and allow them to make informed, educated decisions about their treatment. By 2020, we’ll probably have the policy worked out as well as reimbursement and privacy issues, and there will be more predictive diagnostic kits out there. We’re at the threshold of personalized medicine, but its development is not going to be fast.”

Dr. Lindpaintner cautions that the challenges ahead are great. “Primary healthcare (PHC) is as old as medicine, nothing conceptually new at all. PHC equals differentiated medicine equals differential diagnosis is the only way forward for patient-oriented medicine, which is very different from public health,” says Dr. Lindpaintner.

“New technologies ring in exciting new possibilities in this age-old game but only if we are realistic, prudent, and modest in our expectations in the short and mid-term. Unless we start looking at this in a much more scientifically rigorous fashion and cut out all the hype, this will be a huge disaster in terms of unmet expectations and wasted resources.”

Miller adds that the healthcare industry must provide evidence that individualized care not only improves outcomes but also reduces costs by eliminating testing and treatment that is ineffective.

“Acceptance of personalized care as the norm is still on a distant horizon, one that will not be reached until the supporting body of evidence reaches a critical mass large enough to convince regulators, policy makers, and private industry to make the changes discussed previously,” says Miller. “I think that, with sustained effort, this will be achieved within the next 10 years. I emphasize the word sustained because without a long-term collaboration among all constituents on all fronts, personalized medicine will remain a lofty vision.”

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