The complexity of multiple requirements often leads researchers to provide two different consent forms—one for the overall
research project and the other specifically focused on issues relating to genetics (see "Biology of an Informed Consent Form,"
page 84). For example, in the general consent form, patients would agree to provide a sample of blood. However, the genomics
consent form must identify the specific types of genetic testing to be performed, what happens to the samples should a subject
withdraw from the study, and whether or not patients will be notified of results.
There's also a host of ethical issues that come along with any research related to patients and their genetic information.
Pharma companies must figure out how they will handle the issues associated with screening for "high-penetrance genes"—highly
predictive mutations that signal a major risk of disease development—which can cause psychological harm to individuals that
discover they carry a substantial risk of developing a serious or fatal disease. Consider, for example, age-related macular
degeneration (AMD), a leading cause of vision loss and blindness with no known cure. Researchers recently identified the presence
of two important genes as culprits in AMD development. Researchers found that 74 percent of study subjects with AMD had either
one or both of these genes, but no protective variants of either gene. How should sponsors handle telling patients they have
both of these traits?
Little safety information Personalized medicines should be safer for patients. Just look at the anti-HIV drug Ziagen (abacavir). About five percent of patients taking the drug experience
a serious adverse hypersensitivity reaction. But by testing patients, researchers can determine which ones are more likely
to have this reaction, and reduce the risk of that side effect to less than one percent.
In practice, however, personalized medicines come to market without much information about delayed side effects and long-term
safety and effectiveness. After all, small patient populations mean smaller trials and less data. Genzyme, for example, received
approval for Cerezyme to treat Gaucher disease from a pivotal trial based on data from only 30 patients.
Many personalized therapies are fast-tracked from Phase II to market. They receive accelerated approval because they treat
life-threatening or serious debilitating conditions for which there is no satisfactory alternative therapy. That means the
total experience with many of these drugs can be based on fewer than 100 subjects. Having so little information about patients'
experience means that researchers are less likely to be able to detect safety signals, should any exist.
The cost and complexity of clinical trials are not well suited to understanding how personalized therapies work in the real
world, or for providing the value claims payers need to put these drugs on formulary. Observational studies, however, can
be an attractive option for companies seeking that information—and a source of continuing connection with a disease community—if
designed and executed appropriately.
But small patient populations mean companies must make the most of their interactions with patients and healthcare professionals.
Here's some ways companies can make their research proposition attractive, and build lasting relationships with their physicians
Don't engage in unnecessary experimentation Companies' best chance of attracting participants is to make their research relevant to the marketplace, and attractive to
patients and medical professionals. This is particularly important in order to obtain buy-in from sites for post-approval
studies. The Office of the Inspector General guidance highlights the possibility that payments and other arrangements for
physicians conducting post-approval research might influence their clinician decision-making and cause overuse or inappropriate
prescribing. Therefore, in observational research, site reimbursements are generally minimal, at best.
Keep the protocol in line with physicians' offices When companies are bringing a drug to the market, they typically want to define the study population as narrowly as possible
to maximize their chance of showing efficacy: otherwise healthy individuals, who are nonsmokers, and aren't taking any other
drugs. But in observational studies, the population will vary—patients are going to have co-morbidities, use herbal remedies,
live in polluted areas, and may even be taking the drug for an off-label condition. Ensuring that the protocol has broad inclusion
criteria and limited exclusion criteria allows companies to capture how the drug works across a broad population, in ways
that doctors and patients are actually using the drug.