- Division of Bioinformatics and Biostatistics Newest Branch — R2R (review-to-research and return)
- NCTR’s Contribution to Maintaining American Leadership in Artificial Intelligence
- Androgen Receptor Structural Changes Due to Antagonist Binding
- Massive Analysis Quality Control Society
Bioinformatics Research at NCTR
Division of Bioinformatics and Biostatistics (DBB) Newest Branch — R2R (review-to-research and return) Branch
NCTR’s newest research branch in DBB is called R2R (review-to research and return). The R2R branch focuses on “knowledge uptake” of the division research products for regulatory application and “data liberation” of regulatory data from the FDA product centers to facilitate regulatory science research, and thus promotes NCTR's interactions with the product centers. The four branches of DBB are: 1) bioinformatics, 2) biostatistics, 3) scientific computing, and 4) R2R.
The division director, Weida Tong, Ph.D. stated, “with the R2R program, the division’s capabilities continue to evolve to be more diverse, robust, and capable of meeting future requirements of the FDA.” Find more information about the Division of Bioinformatics and Biostatistics.
NCTR’s Contribution to Maintaining American Leadership in Artificial Intelligence (AI)
AI is a broad concept of training machines to think and behave like humans, which encompasses many methodologies. For example, machine learning is one of the major statistical approaches to realize AI with which the Division of Bioinformatics and Biostatistics (DBB) has developed many applications. Deep learning is one of the machine- learning approach that drives a broad application of AI in biomedical science. DBB has several projects in collaboration with other centers to 1) apply deep learning and 2) address regulatory needs. For example, the division is developing an AI-based screening and prioritizing approach for FDA’s Office of Regulatory Affairs (ORA) to use on regulated products entering the US. Another ORA collaboration — with their Arkansas Lab — involves filth detection focused on imaging analysis with deep learning. Currently, DBB is developing deep-learning methodologies to handle the large amount of FDA text documents, such as FDA-approved drug labeling documents and data from the FDA Adverse Events Reporting System.
For more information, contact Weida Tong, Ph.D., Director, Division of Bioinformatics and Biostatistics, FDA/NCTR.
Androgen Receptor (AR) Structural Changes Due to Antagonist Binding
Androgen Receptor (AR) Structural Changes Due to Antagonist Binding
Scientists from NCTR and Immuneering Corporation have identified the structural changes of the androgen receptor (AR) caused by antiandrogens (chemicals that inhibit male hormones) using simulations. The identified structural changes could facilitate AR targeting-drug discovery. Scientists need a three-dimensional (3D) structure of the wild-type AR bound with an androgen antagonist to understand the mechanism of antiandrogenic activity. However, this type of 3D wild-type AR is not available in protein data banks. By combining molecular docking and molecular dynamics simulations, the 3D structure of wild-type AR bound with the antagonist bicalutamide was studied. This finding revealed that the activation function 2 (AF2) site is key to understanding the impact of antagonist binding on subsequent co-regulator binding. The results and more information can be found in Frontiers in Pharmacology
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.For more information, contact Huixiao Hong, Ph.D., Division of Bioinformatics and Biostatistics, FDA/NCTR.
Massive Analysis Quality Control Society
The inaugural meeting of the Little Rock Chapter of the Massive Analysis Quality Control Society — organized by NCTR — was held September 7-8, 2018, in Little Rock, Arkansas. The participants were from FDA, the National Institutes of Health, biotechnology companies, and academia, with roughly 40 participants onsite and 10 online. Participants examined the progress of the FDA-led Sequencing Quality Control Project/Phase 2 (SEQC-2) in comprehensively assessing next-generation sequencing oncology-panel technologies. The SEQC-2 project aims to develop a set of validated genomic reference materials. SEQC-2 participants are conducting a cross-lab evaluation for eight Pan-Cancer panels. The panels examine the similarities and differences among the genomic and cellular alterations found across diverse tumor types. They are also examining four liquid biopsy-focused panels that can detect rare mutations of circulating tumor DNA. NCTR’s Director, William Slikker, Jr., Ph.D., gave opening remarks followed by regulatory perspectives from Dr. Jai Pandey of FDA’s Center for Devices and Radiological Health. After discussing the significant progress made by the SEQC-2 project, the participants developed a plan to advance the project.
The inaugural meeting of the Little Rock Chapter of the Massive Analysis Quality Control Society — organized by NCTR — was held September 7-8, 2018, in Little Rock, Arkansas. The participants were from FDA, the National Institutes of Health, biotechnology companies, and academia, with roughly 40 participants onsite and 10 online. Participants examined the progress of the FDA-led Sequencing Quality Control Project/Phase 2 (SEQC-2) in comprehensively assessing next-generation sequencing oncology-panel technologies. The SEQC-2 project aims to develop a set of validated genomic reference materials. SEQC-2 participants are conducting a cross-lab evaluation for eight Pan-Cancer panels. The panels examine the similarities and differences among the genomic and cellular alterations found across diverse tumor types. They are also examining four liquid biopsy-focused panels that can detect rare mutations of circulating tumor DNA. NCTR’s Director, William Slikker, Jr., Ph.D., gave opening remarks followed by regulatory perspectives from Dr. Jai Pandey of FDA’s Center for Devices and Radiological Health. After discussing the significant progress made by the SEQC-2 project, the participants developed a plan to advance the project.
For more information, contact Joshua Xu, Ph.D., Division of Bioinformatics and Biostatistics, FDA/NCTR.
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