By Monica Heger
Pharmaceutical companies may be slow to adopt next-generation sequencing for drug development and clinical trials, but the technology's role is growing within that setting, according to discussions at the NGX: Applying Next-Generation Sequencing conference in Providence, RI, earlier this month.
At the conference, a number of experts weighed in on when in the drug development pipeline sequencing should be used; the hurdles that still remain in using the technology in both clinical trials and the drug development process; and why pharma is keeping an eye on the technology while at the same time remaining cautious in adopting it.
Data Interpretation
During a roundtable discussion on whole-genome and whole-exome sequencing in drug development, Jeremy Packer, a researcher in the bioinformatics division at Abbott Laboratories, said that data analysis continues to be a major hurdle for pharmaceutical companies.
Pharma is "concerned about the quantity of data and the interpretability of the data" from sequencing studies, he said. For instance, sequencing patients who have an adverse response to a drug and comparing that data to the genomes of patients without an adverse response is a "complex genetic problem," he said. There will be numerous variants, and picking out the relevant variants between the two groups and distinguishing between sequencing errors will be difficult.
There are variations in drug metabolism based on a person's ethnic background and gender that are much easier to measure and interpret than genome-wide data, he said. "Sequencing the exome or genome will have billions of confounding signals."
Richard Resnick, CEO of bioinformatics firm GenomeQuest, also said during a panel discussion that based on his interactions with pharma, the abundance of data and correlating variants to response remains a major concern in the industry.
Complicating the matter even more, said Packer, is that whether a person responds to a drug or has adverse side effects is not always related to genetic variations in the actual drug target.
"If response was related to the target, you could just sequence the target, but response is not always related to the target," he said.
Bradley Smith, vice president of translational medicine at contract research organization Quintiles, said that data interpretation is a major challenge. The data "needs to reach the standards of the clinician," he said. "If the technology doesn't reach those standards, it has little chance of being adopted."
In the clinical setting, "the requirements for technical and clinical validation are high," he added. Next-gen sequencing will have to demonstrate it can produce high-level, high-quality data, he said.
"Pharmaceutical companies have a lot to think about," he added. "So if you propose something that will be a cost, or may put their trial at risk, they're going to be very hesitant."
When to Sequence?
Deciding when in the drug development process to employ next-gen sequencing is another tricky question. Currently, those pharmaceutical companies that are using sequencing are primarily using it in very early, pre-clinical stages for discovery purposes (CSN 6/21/2011).
Attila Bérces, CEO of sequence data analysis company Omixon, said that while there is "lots of activity in the early stages" of drug development, ultimately, phase IV trials are where "there's the most money at stake."
Using sequencing to uncover biomarkers that are predictive of response has both the potential to "rescue a drug" as well as "reduce the market potential" of a drug, he said.
For instance, The US Food and Drug Administration may approve a drug based on its efficacy in a broad patient population, but it may actually be more effective in some patients and less effective in others. Similarly, a drug that fails to demonstrate sufficient efficacy in the broad population may have a much stronger effect on a subset of patients.
This is particularly true with cancer drugs, said Bérces, which are often only effective in a small proportion of patients who can be classified based on their mutational profiles. Sequencing could help determine the population for which a drug is most effective.
However, said Resnick, "if you incorporate sequencing after the trial has started, it's too late," because the results could delay the trial, causing the company to "lose patent life" for the drug.
Because pharmaceutical companies are so risk averse, they may be open to using genomic information to help ensure that clinical trials will succeed by enrolling the right patients into the right trials, but this approach has been slow to catch on.
In the meantime, there may be space for a new business model, said Quintiles' Smith, citing as an example Foundation Medicine's plan to develop a targeted sequencing panel of several hundred cancer genes that would help inform a patient's next line of therapy.
Additionally, he predicted that within the next five years, CROs like Quintiles could become more involved in the process, adding that he could see a situation where Quintiles would have a pool of patients that had already been sequenced, and could then be screened for drug response.
"We'll already have the patients for the trial," he said, and will be able to "find out fast whether those markers predict response or not."
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