Tag: Emerging Biotechnology

Talkin’ About an Evolution (of research oversight, that is!)

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To many scientists, the name Asilomar is synonymous with an historic event in the regulation of biotechnology. In 1975, experts from around the globe convened at the Asilomar conference center in California to discuss the promise and potential perils of an exciting and emerging technique, recombinant DNA technology.  The discussion laid the foundation for the  NIH Guidelines for Research Involving Recombinant or Synthetic Nucleic Acid Molecules (NIH Guidelines) The NIH Guidelines, aimed at ensuring the safe conduct of this burgeoning area of research, also gave rise to the   Recombinant DNA Advisory Committee (known simply as “the RAC”), an expert group comprising scientists, ethicists, public health experts, biosafety officials, and more, charged with providing advice to the NIH on matters related to recombinant DNA technology. In the late 1980s, the RAC took on a new role: advising NIH on the promising but very new area of human gene transfer research.

Forty years after Asilomar, recombinant DNA technology is ubiquitous in both basic and clinical research settings. As scientific understanding of recombinant DNA technology has evolved, so have the requirements that govern its use.  With this in mind, NIH has been examining the current oversight system for human gene transfer experiments and whether the review processes can be streamlined. To help craft a policy that maximizes scientific advances while ensuring public safety and trust, NIH asked the Institute of Medicine (IOM) to assess the role of the RAC in the oversight of human gene transfer research.  The IOM noted in its report that the RAC has served a valuable role, but concluded that the current level of oversight over each individual human gene transfer protocol is no longer justifiable.  The NIH agreed with this assessment and began developing a proposal for revising the process.

I am delighted to announce that today the proposal to simplify the human gene transfer protocol review process has been published in the Federal Register for public comment.  In short, NIH is proposing that protocols should only be reviewed by the RAC if an institutional oversight body (such as an Institutional Review Board or an Institutional Biosafety Committee) requests review because the proposed research is sufficiently novel.

This change is in keeping with current practice, as these committees have played a large role in overseeing this research for decades and have the expertise needed to ensure research is conducted in accordance with the highest scientific, safety, and ethical standards.

I encourage research stakeholders to provide feedback on the proposal during the 45 day comment period. Once NIH has considered all input, a final notice outlining the changes will be posted. Until then, the current requirements are still applicable.  This represents an important science policy principle: As science evolves, so must the policies that govern it.

I look forward to hearing your comments.

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Genomic Data Sharing: Part II – Playing by the Rules

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The discussions surrounding the Precision Medicine Initiative (PMI) have highlighted some of the policy challenges inherent in balancing the sharing of valuable research data with the protection of participants whose data is being shared. How do you ensure that researchers, and even participants themselves, have appropriate access to data while making sure that the data is not inadvertently or deliberately released or misused in a way that might present a risk to participants?

As mentioned in the last blog post: Part I – Enhancing Consent through the NIH Genomic Data Sharing Policy, the NIH is not new to this, of course, and has had success in developing policies that support the sharing of data that also harbors information about the disease status of research participants.  The NIH Genomic Data Sharing (GDS) Policy, which became effective on January 25, 2015, and its predecessor, the Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies (GWAS) have enabled the sharing of potentially sensitive genomic and phenotypic data from NIH-funded studies.  The ethical principles and privacy safeguards incorporated in the GDS Policy enable secondary use of NIH genomic data while respecting participant autonomy and protecting privacy.

These protections have been built into both the submission and access stages of the genomic data sharing process.  When investigators submit data, their institution must assure, through submission of an Institutional Certification, the appropriateness of the data submission as well as the secondary use of the data, based on the consent of the participants.  When qualified investigators seek access to the  data, they must describe how they intend to use the data through a Data Access Request (DAR) in the database of Genotypes and Phenotypes (dbGaP) and promise, through a  Data Use Certification (DUC) Agreement, to adhere to the GDS Policy’s ethical principles, terms of data access, and privacy safeguards.  Before access is granted, each request is reviewed by an NIH Data Access Committee (DAC) for consistency with the appropriate data uses, as outlines by the data submitters, and Policy expectations.

Since 2007, and under the GWAS Policy, approximately 3,700 datasets have been submitted and made available in dbGaP for secondary research, and nearly 21,000 access requests from over 3,300 investigators from 46 countries, have been approved by NIH.  Of the large number of approved requests, we can say that approved users of the data have adhered to the terms of Policy most of the time, and that only 27 violations of the Policy (out of the 21,000 approved requests) have been reported.  The figure below provides a schematic of this, as well as the general categories that these violations fall under.  Policy compliance violations, also known as data management incidents, have occurred in both the submission and access processes as well as in data security.  For example, in one case, an investigator accidentally reversed the labels for two datasets in a data submission, such that a dataset meant only for disease-specific secondary research was made available for general secondary research use and vice versa.  Fortunately, the mistake was discovered before the data were improperly used.  The datasets were then reconfigured with the appropriate use categories and made available again to the research community.  NIH has also made a similar mistake in handling the data once it was received.

In all Policy compliance violation cases, NIH has worked cooperatively with the violator to remedy the situation.  Most importantly, however, and to the best of our knowledge, none of the 27 Policy compliance violations have resulted in harm to the research participants from which the data were generated.  Additional information on Policy compliance violations and specific cases, as well as other statistics on data submission, access, and use, are available on the Facts & Figures section of the GDS Policy website.

In order to advance our understanding of how the myriad of genetic, environmental, and behavioral factors interact to play a role in human health and disease, we must continue to enable the responsible sharing of genomic and associated data broadly within biomedical research community, while at the same time respecting the wishes of study participants.    NIH’s policies for sharing of genomic data have led the way and set a precedent for culture changes in sharing all types of data, including sharing of data though groundbreaking initiatives such as PMI.

For more information on the GDS Policy please visit the GDS website.

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Burden of Disease and NIH Funding Priorities

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Co-Authored by Carrie Wolinetz and Sally Rockey

Recently, many voices have asked how NIH considers public health needs when setting funding priorities. The quick answer is that public health needs are a critical factor in our decision making-in addition to scientific merit, portfolio balance, and budgetary considerations. But the question of how one measures public health need, as it turns out, isn’t as simple as you might think.

Public health needs are not only reflected by how many people have a particular disease, but also by the burden of disease – the impact of a health condition as measured by mortality, morbidity, financial cost, and other indicators. Different diseases can impose vastly different kinds of burdens. Some diseases may cause premature death, while other chronic conditions may cause long-term disability and impose a great emotional and monetary toll for patients, family members, and society. Many diseases vary widely in the severity of symptoms, the acute vs. chronic nature of the disorder, treatment strategies, and health outcomes. A thousand people with influenza, for example, is not equivalent to a thousand people with headaches. To further complicate matters, identifying affected individuals can be challenging; diagnosing certain psychiatric disorders is far different than diagnosing diabetes. Current disease burden may not necessarily predict future disease burden. Consider the potential burden that the recent Ebola epidemic may have created had it not been contained. And finally, NIH will invest in research on certain diseases that are close to a cure, to propel us towards the ultimate goal of eradication.

Clearly, there can be no “one size fits all” approach to measuring and comparing the burden across different diseases. Nevertheless, we wanted to look at a few possibilities for depicting the relationship between disease burden and NIH funding. Thus, NIH’s Office of Extramural Research and Office of Science Policy collaborated on an exploratory analysis, which you can see on our new burden of disease page on RePORT. This page illustrates how NIH funding levels relate to U.S. and global deaths and disability-adjusted life years (DALYs)—a measure that quantifies the number of healthy years of life lost due to morbidity or premature mortality caused by disease. This analysis comes with several caveats, however, and more information can be found via the methodology link on the disease burden page.

We think you’ll find these data and we hope this analysis contributes to the conversation of advancing public health through scientific research. That being said, disease burden can’t be the only factor in setting funding priorities. NIH is also committed to funding research into rare diseases, which affect a smaller component of the population, thus skewing burden measures. Much of the NIH portfolio involves basic research, which seeks to understand the basic biological processes involved in both health and disease. Basic research doesn’t neatly map onto the burden of a single disease or condition, especially for areas such as genetics or pediatrics. Many of the projects from NIH’s basic research portfolio produce findings that can have implications for the cause and treatment of a variety of diseases, and can be applied across several fields.

As NIH sets its priorities, it’s important that we monitor the public health landscape for unmet needs and emerging challenges, so that the research we support translates into meaningful health benefits. Scientific disciplines mature at different rates, and not all areas are equally ripe for major scientific progress. For example, advances in imaging technologies and tools for mapping connections between neurons now allow us to study the brain and the diseases that affect it in a way that would not have been possible a decade ago. Investing the same amount of money into two different areas can generate very different returns for increasing scientific knowledge and advancing human health. Getting the most out of NIH’s research investment means making smart investments, which come from a deep understanding of the scientific landscape. So while we’re looking forward to using these analyses as a jumping off point for a larger conversation about priority setting, NIH believes that a process that includes multiple measurements of public health needs, but is also informed by scientific opportunity, allows us to fund the best science.

Dr. Sally Rockey is the NIH Deputy Director for Extramural Research and blogs about NIH research funding policies and data at her blog, Rock Talk.

Sally Rockey
NIH Deputy Director for Extramural Research
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