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Home » Three Questions: Nicholas Schork, J. Craig Venter Institute, University of California, Translational Genomics Research Institute

Three Questions: Nicholas Schork, J. Craig Venter Institute, University of California, Translational Genomics Research Institute

July 20, 2015
CenterWatch Staff

CWWeekly’s semi-monthly company profile feature, Insider Insights, interviews executives of companies and organizations in the clinical trials space. Staff Writer Ronald Rosenberg sat down with Nicholas Schork, director of human biology at the J. Craig Venter Institute and a Professor at the University of California, San Diego and the Translational Genom­ics Research Institute in Phoenix.

Q: In your recent Nature essay, you wrote that precision medicine warrants switching everyday clinical trial care into solid N-of-1 trials (studies focused on a single person). To make these trials viable, what are some of the major data concerns as well as the practical problems that need to be solved?

A: I think it is safe to say that each patient is likely to have a unique genetic, behavioral and exposure profile that may influence their response to certain inter­ventions. Most physicians will have to take stock of this fact. If a drug or intervention works well on everyone—despite individual differences—then it should be used.

However, the sad fact is that’s not the case. More nuanced and personalized approaches to patient care are needed. Each patient is in essence presenting a research question that the physician will need to think through to determine the best approach. This does not necessarily mean that the physician will have to conduct an IRB-approved, sophisticated and costly study to figure out what to do. However, it might require considerations about the patient’s genomic profile or current microbiome profile that, in the past, often have not been examined.

Patients who fail to respond to available treat­ments or who have a condition in which there is equipoise surrounding the different interven­tions require more sophisticated approaches to figure out the best treatment option. That’s when a number of obvious issues come to light. The technologies for making measurements about the patient’s response to interventions must be reliable and specific to the disease and symptoms of relevance.

The costs associated with this effort also must be addressed. As a result, the whole payor/ payee self-pay/reimbursement ecology has to change. There also needs to be patient buy-in and a more symbiotic, mutually-beneficial relation­ship between the patient, physicians, the groups providing appropriate technologies and any in­vestigators involved. I believe this can be achieved and have seen it happen in many contexts.

Q: N-of-1 trials may be best for rare diseases, oncology and other indications where there is a combination of genetic and environ­mental factors that shape a person’s response to a specific treatment. However, these trials also could be designed to detect disease onset. Please explain.

A: If the community has bought in to personal­ized approaches to treating disease because each patient has a unique genetic, biochemical, behavioral and exposure profile, then it is a simple jump to buy into personalized disease monitor­ing. Essentially, many markers or indicators of a change of health status—such as blood proteins, the microbiome, heart rate variability, etc. —are quantitative as opposed to simply present/absent indicators, and as such take on values that can be very patient-specific.

By establishing the baseline or typical values and their errors for an individual over time, then one can determine if significant changes to those indicators have occurred, which might warrant further scrutiny. This concept of personal thresholds for biomarkers has been described and implemented. Individuals that are highly susceptible to a disease (e.g., germline TP53 mutation carriers and cancer) could benefit from personalized screening strategies. Their study could expose issues in personalized screening that are applicable to the general population. In addition, similar principles could be exploited in monitoring individuals for signs of relapse of a disease.

Q: Given that regulatory agen­cies, researchers and clini­cians are rightfully wary of moving away from classical clinical trials, why do you think the time is right to seriously consider implement­ing N-of-1 clinical trials?

A: There is full recognition that personalized medicine is rooted in biological realities about the way people respond to treatments or express certain phenotypes. The concept of the aggregated N-of- 1 trial is crucial. Studies focusing on individual patient profiles are aggregated to determine if a drug or intervention strategy has merit and likely to have utility for a larger number of individuals. This type of analysis would be crucial for drug approvals in the population at large.

Essentially, if one could show that there are unequivocal responders to an intervention, or individuals who certainly benefit from a disease monitoring strategy—from multiple appropri­ately motivated and powered N-of-1 studies— then one could look for patterns among those who responded/benefited versus those that did not. This could provide clues as to who might benefit from the intervention. Emerging methods for adaptive clinical trial designs and studies that assess algorithms for matching patients to drugs, not necessarily the individual drugs themselves, can facilitate this.

 

Email comments to Ronald at ronald.rosenberg@centerwatch.com. Follow @RonRCW

This article was reprinted from Volume 19, Issue 28, of CWWeekly, a leading clinical research industry newsletter providing expanded analysis on breaking news, study leads, trial results and more. Subscribe »

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