The U.S. policy landscape for countering biological threats is split into two main groups: 1) biosecurity, which specifically focuses on preventing theft, diversion, or deliberate malicious use of biological sciences knowledge, skills, materials, and technologies to cause harm; and 2) biodefense, which involves the development of capabilities and knowledge to assess, detect, monitor, respond to, and attribute biological threats. This project involved the first ever systems-based analysis of the entire U.S. biosecurity and biodefense policy landscape, which enabled greater understanding of the functional relationships between policies as of 2017. These analyses, along with reviews of methodologies for measuring policy implementation and historical case studies to better understand factors that lead to opportunity costs, informed the development of a roadmap for implementing biosecurity and biodefense policies that leverages science and technology advances and minimizes security risks. In addition to the roadmap, this study presents two analytic frameworks for evaluating policy implementation and analyzing opportunity costs.

Figure 1. This figure shows a relational map of U.S. biosecurity and biodefense policy by policy subject. Each white circle is a unique U.S. Code, international agreement or partnership, Executive or agency-level policy, program activity (if not already associated with a U.S. Code, international partnership, or agency-level policy), guidance, or guidelines. The colored circles signify subject area. The size of the nodes reflects the number of policies associated with each subject area and the distance between nodes reflects the degree to which policies are linked based on the underlying relational database. The lines reflect direct relationships between policies and subject areas based only on existing policies before 2018. This map does not reflect associations of subject area based on conceptual similarities, but rather associations by direct links between existing policies.

Figure 2. These objectives were derived from combining the core components of Homeland Security Presidential Directive 10/Biodefense for the 21st Century, Presidential Policy Directive 2/National Strategy for Countering Biological Threats, and other relevant policies. The science and technology categories (blue text) were derived from policy documents and funding announcements for research and development for biodefense. Similarly, the policy scope was derived from policy documents and discourse over the past 18 years.

Figure 3. This figure shows the potential indirect effects of U.S. biosecurity and biodefense policies on U.S. biodefense objectives. Each circle is a unique U.S. Code, international agreement or partnership, Executive or agency-level policy, program activity (if not already associated with a U.S. Code, international partnership, or agency-level policy), guidance, or guidelines. The white circles represent the direct biodefense objectives (columns) that policies in each of the subject area categories (rows) addresses. The colored circles indicate possible indirect effects of the policies in the subject area categories to biodefense objectives. The green circles indicate capability-building activities. The pink circles indicate requirements, the red circles indicate regulations, and the burgundy circles indicate restrictions, all of which seek to promote biosecurity and biosafety activities. The blue circles are policies that criminalize development and/or use of biological weapons or their delivery systems. Horizontal comparisons between the purpose of a policy (i.e., direct biodefense objective) and the potential indirect effects of a policy should be made.

Background

While some experts felt that industry posed a great biosecurity risk and therefore regulation was necessary, other experts held that the risk of misuse was low and that the potential harms of regulation, such as lost innovation or stunted economic growth, would outweigh the benefits. Among those calling for regulation, a range of oversight and governance mechanisms were proposed, including licensing customers, screening DNA sequences, or simply increased record-keeping. Gryphon conducted a three-month study to investigate the trade-offs associated with options for reducing the biosecurity risks associated with the CSNA industry. We developed recommendations  on how the federal government could best help secure the industry.

Methods

Gryphon’s recommendations were based on data gathered from a thorough review of the scientific literature as well as interviews with scientists who use CSNAs in their research and companies who produce CSNAs. Scientific literature was reviewed to understand how CSNAs could be misused, as well as the prevailing thoughts on biosecurity and the CSNA industry. Additionally, regulations, laws, and guidelines relevant to the oversight of the CSNA industry were reviewed. Interviews were conducted with users of synthetic DNA to understand how delays in ordering CSNA, and any financial costs associated with regulation, would affect their work. Interviews were also conducted with companies producing synthetic DNA—including interviews with all of the largest suppliers representing 85% of the total industry value. Following data collection, a variety of regulatory options were evaluated ranging from customer licensing to sequence screening.

 Results

Based on the data we collected, Gryphon developed several oversight options, highlighting the costs and benefits of each option, to inform policymakers on how to proceed. Each option was given ratings in a variety of categories such as burden to market, cost, and effectiveness for biosecurity, to allow our client to understand the trade-offs associated with each option. The Department of Health and Human Services (HHS) later developed our recommendations into official guidance to providers of synthetic DNA. The industry later formed a voluntary industry group, the International Gene Synthesis Consortium, who used the HHS guidelines as a starting point and developed further guidance with which all member companies must comply as a condition of joining the group.

 Resources

The Custom Synthetic Nucleic Acid Industry and Biosecurity: A Systems Analysis report was released in December 2007 for The Department of Homeland Security: Science and Technology Directorate .

Overview

For over 10 years, Gryphon Scientific has managed NIAID’s ChemDB Database, a publicly available database with a diverse set of data describing the biological activity and chemical properties of small molecules with potential therapeutic applications for human immunodeficiency virus (HIV) and Mycobacterium tuberculosis. Gryphon leads a team in a variety of tasks to maintain the database and facilitate use of the data, including literature surveillance, data abstraction, and advanced scientific analysis of drug development data. The database has been used by researchers at NIAID, across the U.S., and internationally for structure-activity relationship studies, virtual drug discovery, and other research to further discovery of therapeutics for HIV/AIDS and tuberculosis.

Methods and Results

In support of the public portion of ChemDB, the Gryphon team monitors public sources to identify literature describing small molecules with potential therapeutic applications for HIV and M. tuberculosis in the pre-clinical development stage, then abstracts complex chemical and biological data in a standardized fashion for addition to the database. In support of the proprietary portion of the database that includes confidential experimental data from NIAID partner laboratories, the Gryphon team performs literature reviews, advanced analysis of drug development data, and other support. ChemDB now contains more than 408,000 compounds from more than 32,000 references. Approximately 292,000 of these compounds are in the public dataset, and 115,000 compounds are in the proprietary dataset. Approximately 150,000 public compounds have associated anti-HIV data, 47,000 public compounds have associated anti-Mycobacterium tuberculosis data, and 111,000 public compounds have data on other pathogens. The database has been used by researchers at NIAID, across the U.S., and internationally to further drug discovery.

In October 2014, the White House Office of Science and Technology Policy (OSTP) announced a funding pause on selected “Gain of Function” (GoF) research involving influenza viruses, SARS coronavirus, and MERS coronavirus, namely experiments that are “reasonably anticipated to confer attributes to influenza, MERS, or SARS viruses such that the virus would have enhanced pathogenicity and/or transmissibility in mammals via the respiratory route” (White House OSTP Moratorium Memo). OSTP called for a deliberative process to evaluate the risks and potential benefits of this research, which would culminate in the development and adoption of a new US Government (USG) policy governing the funding and conduct of GoF research and the cessation of the funding pause.

Approach

The National Science Advisory Board for Biosecurity (NSABB) served as the official federal advisory body on GoF research issues and was responsible for developing recommendations for the appropriate level of Federal oversight of GoF research. To inform the NSABB’s deliberations on this issue, Gryphon Scientific was contracted by the NIH Office of Science Policy to conduct risk and benefit assessments (RBA) of GoF research involving the pathogens subject to the funding pause. Our assessment was divided into four components:

1. Biosafety risk assessment
2. Assessment of biosecurity risks due to intentional acts against the laboratory
3. Assessment of biosecurity risks due to misuse of information
4. Benefit assessment

Contained on this page are Gryphon’s final and draft reports to NIH OSP and NSABB, Gryphon’s presentations on the RBA, as well as Supplemental Information supporting the conclusions and findings in the report.

Methods

Gryphon analyzed data from a set of experiments in mice measuring changes in mRNA and miRNA expression following different levels of radiation exposure using microarrays. The experimental design included multiple radiation doses and timepoints post-exposure, yielding microarray data featuring 3,000 mRNA and 24,000 miRNA probe values. The microarray datasets included a high number of features (miRNA/mRNA signals) but a low number of observations per radiation exposure category (mice in each experimental group), presenting analytic challenges. We implemented an ensemble of state-of-the-art feature selection algorithms to identify the miRNA and mRNA signals that change the most (increase or decrease) with different levels of radiation exposure, representing the first time some of these algorithms had been applied to microarray data. We selected the top 20-30 signals that were able to differentiate between different levels of radiation exposure with the highest level of predictive accuracy in a predictive classification model. Models were developed with and without time point data (knowing how long post-exposure the blood samples were taken) to better understand the signal change over time following radiation exposure. With these signals, Gryphon developed and validated a predictive classifier of radiation exposure using support vector machine and random decision forest algorithms.

 Results

The results were analyzed for their biological relevance to radiation injury and were used to advance the NCI’s goal towards understanding biological pathways that are most affected by radiation exposure. This work will inform the design of future animal radiation exposure response experiments and is an important step in the development of a biodosimeter following a mass casualty radiation event. Feature selection algorithms were used to identify the 23 miRNAs and 22 mRNAs with the greatest expression changes in response to radiation exposure in a time and/or dose dependent manner. Classification models based on the miRNA or mRNA signatures were developed and validated using a test dataset; accuracy in the predictive models was estimated at 56% and 93%, respectively.

 Resources

The paper, “Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model” was published in the Biomarkers Journal in May, 2018.