Analysis of Chemical Structures and Therapeutic Activity of Agents for HIV and Tuberculosis

Analysis of Chemical Structures and Therapeutic Activity of Agents for HIV and Tuberculosis

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.

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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.

Publication Highlight: Gryphon publishes review using NIAID’s ChemDB to explore trends in funding and HIV drug development 

Figure 4. Accumulation of target-specific compounds tested and hiv drug approvals over 35 years (1984-2018). Source: Jackson et al, J AIDS Clin Res 11 (2020)

Gryphon Scientific performed a retrospective analysis of trends in HIV small molecule drug development over the last 35 years using data from the ChemDB database, published in the December 2020 issue of the Journal of AIDS & Clinical Research. The paper analyzes these data alongside data on NIH funding, U.S. Food and Drug Administration drug approvals, and new target identifications to explore the influences of these factors on anti-HIV drug discovery research. This analysis demonstrated that levels of research activities follow funding trends and that interest in HIV therapeutic research activities remains strong despite the increasingly wide suite of therapeutic options that have accumulated over the past few decades. The paper further evaluates the nuances in these trends and discuss implications for future research on HIV therapeutics and development of new therapeutics. The full publication can be read here.

Resources

Development of Innovative Training Materials on Research Translation to Strengthen Zoonotic Disease Prevention, Detection, and Response Capabilities

Development of Innovative Training Materials on Research Translation to Strengthen Zoonotic Disease Prevention, Detection, and Response Capabilities

Overview

Gryphon Scientific developed and delivered innovative training workshops on applying research to policies and programs in human and animal health, fusing concepts–research translation and One Health–that are rarely addressed together. By engaging a multi-sectoral group of in-country stakeholders from the research, public health, and veterinary sectors, the workshops helped build workforce capabilities in research translation and supported the strengthening of multi-sectoral networks to promote national preparedness for zoonotic disease threats.

Motivation

Research translation plays a critical role in the development of evidence-based policies and programs for preventing, detecting, and responding to infectious diseases. Many infectious disease threats are zoonotic – affecting both humans and animals – so that outbreaks in or interventions targeting one sector have spillover effects on the other sector. A “One Health” approach to combating zoonotic diseases can strengthen prevention of and enable more rapid detection of and response to zoonotic disease threats. One Health is a multi-sectoral, interdisciplinary approach that involves the collaborative effects of multiple sectors and disciplines to achieve the best health for people, animals, and the environment. However, training and other resources addressing the complexity of research translation to health challenges affecting multiple sectors are limited.

Methods

To strengthen zoonotic disease prevention and control capabilities in Egypt and Indonesia, Gryphon Scientific collaborated with in-country partners to develop and deliver innovative training workshops on applying research to policies and programs in human and animal health. We developed a novel framework for research translation in a One Health context to provide a conceptual basis for the training activities, representing the first of its kind to fuse the concepts of research translation and One Health. Using best practices in adult learning methodology and active learning, the project team developed a suite of training materials including case studies based on local research and a systems mapping activity to identify communication pathways supporting research translation. The training materials were piloted in two workshops in Cairo, Egypt and Surabaya, Indonesia with multi-sectoral groups of in-country stakeholders from the research, public health, and veterinary sectors.

Results

The workshops helped build workforce capabilities in research translation and supported the strengthening of multi-sectoral networks in Egypt and Indonesia, thereby promoting national preparedness for zoonotic disease threats. These experiences validated the relevance and utility of the One Health Research Translation Framework in guiding the design of research applications that are locally relevant, beneficial, and effective. Additionally, the workshops demonstrated the value of our training concepts and approach in fostering multi-sectoral collaborations that support effective translation of research to zoonotic disease challenges.

Resources

The training materials and One Health Research Translation Framework are licensed under a Creative Commons license, allowing for free and unlimited distribution for non-commercial use. The materials developed for the Egypt workshop are available in English and Arabic, and the materials developed for the Indonesia workshop are available in Bahasa Indonesia. These materials can be adapted to local disease concerns for other training events or used to develop research translation strategies for specific zoonotic disease issues.

Assessing the Risks and Benefits of Conducting Research on Pathogens of Pandemic Potential

Assessing the Risks and Benefits of Conducting Research on Pathogens of Pandemic Potential

Overview

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.

Resources

Identifying Biomarkers to Predict Radiation Exposure

Identifying Biomarkers to Predict Radiation Exposure

Overview

Following a mass casualty nuclear event, the ability to precisely determine an individual’s radiation exposure (biodose) is critical for the accurate identification of critically exposed individuals for treatment. To support the development of an accurate biodose tool, Gryphon Scientific developed a supervised machine learning pipeline to identify the most important biomarkers (miRNA and mRNA signals) for predicting radiation exposure. This work was performed in collaboration with the Experimental Therapeutics Section at the National institutes of Health (NIH) National Cancer Institute (NCI).

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.