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Regulatory Science at the US Food and Drug Administration: Enhancing SCIENCE-based regulation of medical products Carolyn A. Wilson, Ph.D. Associate Director for Research Center for Biologics Evaluation and Research

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Page 1: Regulatory Science at the US Food and Drug …...Regulatory Science at the US Food and Drug Administration: Enhancing SCIENCE-based regulation of medical products Carolyn A. Wilson,

Regulatory Science at the US Food and Drug Administration: Enhancing SCIENCE-based

regulation of medical products

Carolyn A. Wilson, Ph.D. Associate Director for Research

Center for Biologics Evaluation and Research

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My comments are an informal

communication and represent my own best judgment.

These comments do not bind or

obligate FDA.

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FDA’s Regulatory Scope: 25 cents of every GDP dollar

Oplægsholder
Præsentationsnoter
Tobacco Control Act, passed in 2009, gave FDA the broad authority to regulate manufacturing, distribution, and marketing of tobacco products. FDA has the authority to adopt science-based product standards which could require reduction or elimination of a component to protect the public health. Overall goals of CTP are to prevent people from starting to use tobacco products, encourage tobacco users to quit and to reduce harm caused by tombacco use.
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Using Science and Regulation to Advance Medical Product Development

www.fda.gov

Regulatory Challenge Public Health

Novel Product

Regulatory Science Discovery

New Tools Regulatory Policy/Decision

Licensed Product

Improved Data – Benefit/Risk

Post-market Surveillance

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FDA’s Regulatory Science • Product Centers oversee and conduct

intramural laboratory and non-lab (i.e., epidemiology and biostatistics) research

• Office of the Commissioner and Office of the Chief Scientist: – Coordination/communication via working

groups – Intramural funding programs – Extramural funding programs

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FDA Regulatory Science: Regulatory Product Center Programs

Commissioner

Office of Foods and Veterinary

Medicine

ORA

CFSAN

CVM

Office of Medical

Products and Tobacco

CBER

CDER

CDRH

CTP

Oplægsholder
Præsentationsnoter
The Office comprises the Office of Counterterrorism and Emerging Threats (OCET), the Office of Health Informatics (OHI), Office of Regulatory Science and Innovation (ORSI), the Office of Scientific Integrity (OSI), the Office of Scientific Professional Development (OSPD), the Office of Minority Health (OMH), the Office of Women's Health (OWH), and FDA's National Center for Toxicological Research (NCTR).
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2016 CBER Goals Regulatory Science and Research

Goal 1. Advance the scientific basis for regulation of biologics, human tissues and blood to enhance safety, effectiveness, quality and consistency through development and evaluation of new concepts, methods, models, and reagents.

Goal 2. Develop and assess nonclinical models and methods with improved predictive value, and, as feasible, reduce, refine, or replace the use of animals, for evaluation of safety and effectiveness of CBER-regulated products.

Goal 3. Improve clinical evaluation related to CBER-regulated products through the use of new biomarkers, large scientific and healthcare datasets, and innovative design and analysis of clinical studies by applying new statistical, epidemiological, and mathematical modeling approaches, and considering patient input to inform benefit-risk assessment of general and special populations.

Goal 4. Prepare for future regulatory and public health challenges through investments in emerging science and technology, and develop and sustain varied scientific expertise.

www.fda.gov

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What about Zika Virus?

Initial focus: protect the blood supply:

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Zika and Protecting the Blood Supply….

Oplægsholder
Præsentationsnoter
Collaborative studies including 5 additional independent laboratories were carried out to define/confirm the viral loads by limiting dilution
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CBER: Mesenchymal Stem Cells Consortium

Sponsors have used some of CBER’s published methods to characterize their products; data provided in INDs

• Objective: Develop ways to identify quality attributes that predict safety and effectiveness.

• Outcomes – Demonstrated that Consensus MSC Markers do not

Correlate with Functional Heterogeneity • Donor or Tissue Culture Age Differences

– Developed assays to identify and qualify predictive product characteristics for cell therapy products – Published findings

PCBM1632

1108

77

1676

96

PCBM1641

PCBM1662

8F35

60

1277

56

PCBM1655

0

2

4

6

8

10

12

14

16

Passage 3Passage 5Passage 7

% Ni

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Lo Surdo JL et al., Cytotherapy, 2013.

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MSC Consortium Publications

11

• Differentiation – Quantitative Approaches to Detect Donor and Passage Differences in Adipogenic Potential and

Clonogenicity in Human Bone Marrow-Derived Mesenchymal Stem Cells. 2012. Lo Surdo, JL, and Bauer, SR. Tissue Engineering: Part C 18: 877-889.

– Automated Microscopy as a Quantitative Method to Measure Differences in Adipogenic Differentiation in Preparations of Human Mesenchymal Stem Cells. 2013. Lo Surdo, JL, Millis, B. and Bauer, SR: Cytotherapy. 2013 15: 1527-40

• Proteomics – Improved proteomic profiling of the cell surface of culture-expanded human bone marrow

multipotent stromal cells. 2013. Samuel T. Mindaye, Moonjin Ra, Jessica Lo Surdo, Steven R. Bauer, Michail A. Alterman. J Proteomics 78: 1-14.

– Global proteomic signature of undifferentiated human bone marrow stromal cells: Evidence for donor-to-donor proteome heterogeneity. Mindaye, ST, Ra, M, . Lo Surdo, JL, Bauer, SR, and Alterman, MA. 2013.. Stem Cell Research 11: 793-805

– System-wide survey of proteomic responses of human bone marrow stromal cells (hBMSCs) to in vitro cultivation. Mindaye, ST, Lo Surdo, JL, Bauer, SR, and Alterman, MA. 2015. Stem Cell Research in press

• Immunomodulation – Assessment of immunosuppressive activity of human mesenchymal stem cells using murine antigen

specific CD4 and CD8 T cells in vitro. 2013. Nazarov, C., Lo Surdo, J.L., Bauer, S.R., Wei, C-H. Stem Cell Research & Therapy 4:128.

• Genomics – Gene markers of cellular aging in human multipotent stromal cells in culture. 2014. Ian H Bellayr,

Jennifer G Catalano, Samir Lababidi, Amy X Yang, Jessica L Lo Surdo, Steven R Bauer and Raj K Puri. Stem Cell Research & Therapy, 5:59

• Epigenetics – Chromatin Changes at the PPAR-g2 Promoter During Bone Marrow-Derived Multipotent Stromal Cell

Culture Correlate With Loss of Gene Activation Potential. Lynch, PJ, Thompson, EE, McGinnis, K, Rovira-Gonzalez, YI, Lo Surdo, JL, Bauer, SR, Hursh, DA. Stem Cells 33: 2169-2181.

• Sector Overview – MSC-based product characterization for clinical trials: An FDA Perspective. 2014. Mendicino, M,

Bailey, AM, Wonnacott, K, Puri, RK., and Bauer, S.R. Cell Stem Cell 14:141-145

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12 www.fda.gov 12

Improve Access to Post-market Data Sources and Explore Feasibility of Their Use in Different Types of Analyses

Improve Risk Assessment and Management Strategies to Reinforce the Safe Use of Drugs

Evaluate the Effectiveness and Impact of Different Types of Regulatory Communications to the Public and other Stakeholders

Evaluate the Links among Product Quality Attributes, Manufacturing processes, and Product Performance

Develop and Improve Predictive Models of Safety and Efficacy in Humans

Improve Clinical Trial Design, Analysis, and Conduct

Enhance Individualization of Patient Treatment

I

II

III

IV

V

VI

VII

http://www.fda.gov/Drugs/ScienceResearch/ucm264327.htm

CDER: 7 Regulatory Science Topics

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Supporting evaluation of biosimilars: Analytical technologies to evaluate recombinant proteins 2D-NMR analysis of the higher-order structure of filgrastim (G-CSF, biosimilar for Neupogen): approval of this first biosimilar in 2015 • Originator product, Neupogen, and three unapproved drug

products evaluated at four labs on 6 instruments • Same analytical software applied to all data • Sufficient resolution to obtain high degree of similarity with

quantitative analysis revealing shifts tracking to variations in temperature, pH/ionic strength of solvent, or change in higher order structure.

Ghasriani, Houman, et al. "Precision and robustness of 2D-NMR for structure assessment of filgrastim biosimilars." Nature Biotechnology 2016 http://www.fda.gov/newsevents/newsroom/pressannouncements/ucm436648.htm

www.fda.gov

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FDA Regulatory Science: OC Programs

OC

Office of the Chief Scientist

Office of Counter-Terrorism and

Emerging Threats

National Center for Toxicological

Research

Office of Regulatory Science

and Innovation Office of Women’s

Health

Office of Minority Health

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15 www.fda.gov

National Center for Toxicological Research:

Supporting Multi-Agency Tox21 FDA’s Modernizing Toxicology

• Develop better models of human adverse response • Identify and evaluate biomarkers and endpoints that can be

used in non-clinical and clinical evaluations • Use and develop computational methods and in silico

modeling

Oplægsholder
Præsentationsnoter
Hi Carolyn note the addition to your slide….“Refine:Reduce:Replace” We hear this refrain associated with use of animal models, but it serves equally as a simplified mission expression for “Modernizing (Regulatory) Toxicology.” In particular most all of our current research objectives are to improve accuracy for evaluation and prediction of safety and efficacy of products. Thusly I categorize each of our effort examples for what they really are intended to be. “Personalized Medicine” as a label too may be much more descriptive of our goals, and may not raise the issues that the “Modernize Toxicology” moniker has raised since it was first iintroduced in the OCS research document of 2010. With that consideration the research objective could be stated as “1. Personalized Toxicology to Enhance Product Safety.”
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Predictive Pharmacology in silico* QSAR (Quantitative Structure Activity Relationship)

• 50 years - Traditional drug discovery tool

• Based on classical (large body) mechanics

• Regression/classification outcomes based on measurement of 2D and 3D structural/reactive chemical descriptors.

• E.g. EDKB

QSDAR (Quantitative Spectral Activity Relationship)

• QSDAR patent 2004 3D QSDAR* patent 2011

• Based on quantum (very small body) mechanics; e.g. NMR chemical shift data

• Partial least squares and discriminant analysis of experimental or in silico generated NMR data

• E.g. PLD and hERG binding *incorporates inter-atomic distance

www.fda.gov

Bioimaging: Replace?

* "All models are wrong but some are useful“ George Box 1978

Oplægsholder
Præsentationsnoter
Although none of us believe that our biological/physiological and computational knowledge has advanced to the pt where we just do a Star Trek recorder reading to get results, We do invest in steps towards toxicology in silico as an aid to mark chemicals for further scrutiny for in vitro and in vivo testing. Note the footnote on this first slide: * "All models are wrong but some are useful“ George Box 1978 These types of techniques also can be specially useful when unanticipated events occur during post market surveillance. In this and the next slide we illustrate “true” predictive in silico modelling can be done for unanticipated idiosyncratic events occur (PLD = phospholipidosis; and hERG binding…literally the human Ether-à-go-go-Related Gene, (initially labelled in fruit flies), or more sensibly blocking this receptor resulting in QT-elongation. Left Table is QSAR. The current std to predict activity of a chemical, either efficacy or toxicity, is the QSAR (with several variations). It is based on any one of a number of laboratory measured parameters and depending on the situation is moderate to 50/50% in success. (Large body mechanics was developed, and is very accurate in predicting planetary movements.) Right Table is QSDAR: NCTR scientists have developed a patented process based on quauntum mechnics, the study of matter and energies on the scale of atoms and subatomic molecules. The theory and practice is based upon on a quantum mechanics experiment, the NMR spectra. Knowledge of the NMR phenonemon has advanced to the stage that the spectra of any molecule in solution can be predicted by computer programs: thusly, “true in silico.”
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020406080100120140160PPM

13C-NMR

122.

23

157.

1215

9.15

15N-NMR

-85.

90

NN

• 15N- and 13C NMR 3D-QSDAR

• NCATS experimental PLD testing (n=1070; acc=83%), used a HepG2 cell line while the hERG assay (n=1385; acc=86%) used U-2 OS viral transduced cells

• Tendency 3D-QSDAR to predict false positives/ No tendency to predict false negatives

PLD n=1070 hERG n=1385

Experimental Validation Of the hERG and PLD 3D-QSDAR in silico Model

Oplægsholder
Præsentationsnoter
This slide has three types of data. The upper left cartoon shows and example of the data for Nitrogen-15 and Carbon-15 NMR and the right portion demonstrates the graphing of atoms in space from NMR data with the calculated distance for the 3rd-dimension (3D-QSDAR). The lower left column of bullets depict the performance of the 3D-QSDAR structural-characteristics calculations against the in vitro test results obtained from the National Center for Advancing Translational Sciences (NCATS) robot being used in the robot used in Tox21 effort. In these comparisons the experimental accuracy (aka. “acc”) of 3DSDAR calculation to match the in vitro testing results using those compound showing positive results is expressed as 83% accuracy for the phospholipidosis (PLD) and 86% accuracy for comparison for the hERG assay data. This is the performance accuracy characteristic is the figure of interest using the 3D-QSDAR to screen chemicals with positive indications for further toxicology evaluation. National Center for Advancing Translational Sciences (NCATS). In further evaluation it can be shown that the 3D-QSDAR has a tendency to slightly over predict the positive compounds (false positives), and a tendency to predict very few false negative compound results. (If NCATS results could not determine positive or negative, they were not used in this comparison. Nevertheless, 3D-QSDAR tests showed some NCATS equivocal results as positive for the tests; the 3D-SDAR result is backed by published clinical literature.) In the graph on the right is the same comparison data expressed in terms of the more typical clinical expression of biomarker performance. The AUC performance evaluation figure using the 3D-QSDAR is 0.90 for PLD and 0.88 for hERG testing and is expressed as results are “true positive” and “false positive”. This data expression also includes the negative findings of the robot tests as well. Assuming that the robot results are correct, a perfect correlation of the 3D-QSDAR to the robot would be 1.0 (aka if a perfect 45o were shown there would be zero correlation of results between methods) This slight increase in performance is attributed to the fact that the data sets in both toxicities are 1/3 positive compounds and 2/3 negative compounds.
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Office of Regulatory Science and Innovation

• Oversees two major extramural programs in regulatory science: – Broad Agency Announcement http://www.fda.gov/ScienceResearch/SpecialTopics/RegulatoryScience/ucm301667.htm – Centers of Excellence in Regulatory Science (CERSI) http://www.fda.gov/ScienceResearch/SpecialTopics/RegulatoryScience/ucm301667.htm

• University of Maryland • Georgetown University • Johns Hopkins University • UCSF/Stanford • Yale/Mayo

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Objective: Develop an anatomical and functional population model of the musculoskeletal system to facilitate virtual clinical trials

Collaboration with Dr. Thor Besier, Auckland Bioengineering Institute and CDRH

Overview and Outcomes: • Open source software enables users to visualize the

musculoskeletal system; create computational models of anatomical structures based on patient data.

• Database enables access to raw medical image data, motion capture and muscle performance data gathered in the international Physiome Project. Includes pelvis, femur, tibia, fibula and patella.

• Users query database for similarities and differences in range of anatomical data.

BAA example: The Musculoskeletal Atlas Project (MAP)

https://simtk.org/home/map

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CERSI Program Joint efforts between FDA and academic institutions to collaborate on projects that promote regulatory science, including innovative research, education, and scientific exchange under a cooperative agreement grant (U01).

Address scientific challenges arising from new medical product development and regulatory activities

Collaboration with academic partners on research that supports FDA’s regulatory mission & improves public health.

Support training needs for FDA, new scientists, & scientific community.

Enhance extramural partnerships and expand scientific exchanges.

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CERSI Example: Eliciting Patient Preferences to Enhance

Regulatory Science Research Project

Objective • Advance and apply stated preferences among people with

type 2 diabetes Overview & Outcomes • National survey assessed priorities for diabetes self

management and treatment preferences • Collaborated with patient organizations to create patient-

centered studies for lung cancer, acute myeloid leukemia and Duchenne muscular dystrophy

• Direct impacts of patient organizations – pilot results from collaboration with Leukemia and Lymphoma Society to be presented at FDA patient preference meeting

www.fda.gov

Johns Hopkins University

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FDA Regulatory Science: OC Programs

OC

Office of the Chief Scientist

Office of Counter-Terrorism and

Emerging Threats

National Center for Toxicological

Research

Office of Regulatory Science

and Innovation Office of Women’s

Health

Office of Minority Health

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Medical Countermeasures Initiative Regulatory Science Program • Established in 2010 under the Medical Countermeasure

Initiative (MCMi) to support intramural and extramural research

• Priority research areas – Identifying, developing, and qualifying drug development

tools (e.g., animal models, biomarkers) – Developing methods to assess product quality and related

product release assays – Validating next-generation in vitro diagnostics platforms – Assessing the performance of emergency medical equipment – Enhancing emergency preparedness and response

capabilities, including risk communication and tracking and evaluating the safety and clinical benefit of MCMs used during public health emergencies

www.fda.gov/medicalcountermeasures

Oplægsholder
Præsentationsnoter
Take home: goal is to create the tools that support regulatory decision making.
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MCMi extramural regulatory science example: Cross-Species Immune System Reference Garry Nolan, Stanford University

Objective: Conduct a comprehensive cross-species analysis of immune system function to inform the choice of appropriate models for MCM development Overview & Outcomes • Universal antibody panels for humans, macaques, African green

monkeys, and mice • Exposed blood from humans, three species of non-human primates, and

mice to cytokines, viral and bacterial antigens, or receptor ligands; analysis via CyTOF mass cytometry

• Species- and gender-specific differences in immune response, the effect of anesthesia on NHP immune function and blood chemistry, and macaque-specific sensitivity to bacterial threat agent

• Open access cross-species immune response database: http://immuneatlas.org

www.fda.gov/medicalcountermeasures

Oplægsholder
Præsentationsnoter
Take home: intramural (FDA scientists from the medical product centers) and extramural projects to address regulatory science gaps...
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361 Projects

17 Disease Areas

31% Sex Differences

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FDA Office of Women’s Health Established 1994

www.fda.gov/womenshealthresearch Obias-Manno et al. The Food and Drug Administration Office of Women’s Health: Impact of science on regulatory policy. J Women’s Health 2007;16(6):807-817. Elahi et al. The Food and Drug Administration Office of Women’s Health: Impact of Science on Regulatory Policy: An Update. J Women's Health 2016; 25(3):222-234.

Oplægsholder
Præsentationsnoter
The Office of Women’s Health provides research grants to FDA scientists to conduct studies to support FDA regulatory decision-making on the safety and efficacy of products used by women. OWH does not have a formal extramural program but they do have research collaborations with NIH. OWH has funded 361 projects since the research program was established in 1994. They have supported studies in 17 disease areas. The majority have focused on heart disease. You can learn more about the regulatory impact of OWH-funded research in two publications: Obias-Manno et al. The Food and Drug Administration Office of Women’s Health: Impact of science on regulatory policy. J Women’s Health 2007;16(6):807-817. Elahi et al. The Food and Drug Administration Office of Women’s Health: Impact of Science on Regulatory Policy: An Update. J Women's Health 2016; 25(3):222-234.
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OWH-funded research has contributed to FDA policy and advanced knowledge of SEX DIFFERENCES IN HEART DISEASE

Oplægsholder
Præsentationsnoter
Because heart disease is the leading cause of death in women, the Office of Women’s Health has funded 63 projects since 1994 to help the Agency better understand sex differences in the sex differences in the diagnosis and treatment of cardiovascular disease. This research has examined issues such as QT interval prolongation, cardiotoxicity from breast cancer drugs, and sex differences in various cardiac interventional therapies. The research results have led to a better understanding of cardiovascular disease in women and contributed to the development of guidance documents for drug and device development for men and women. I will highlight two examples of OWH-funded projects in these areas: Sex differences in Drug-induced Cardiac Arrhythmias the QTc interval is a poor biomarker for predicting prolonging of the QT interval which can lead to an irregular or abnormal heart beat called Torsade de pointes (TdP), as a prolongation of the interval does not necessarily cause TdP. investigated the use of other biomarkers such as the QRS-T angle, T magnitude and ventricular gradient that may discriminate between drugs that cause a benign QT prolongation and drugs that cause malignant QT prolongation Assessed sex differences in drug-induced cardiac arrhythmias from 2 FDA (Critical Path) funded projects 2. Sex-Specific Outcomes for Heart Failure Devices – Cardiac Synchronization Therapy (CRT)
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OWH-FUNDED RESEARCH, Example Higher Risk for Drug-Induced Arrhythmias for Women Investigator: David Strauss – FDA CDER

• Between 1991 and 2003, 6 drugs were withdrawn from marketing in the US because of Torsade de Pointes (TdP) tachycardia

• Women are at higher risk

• Project assessed the ability of novel ECG biomarker strategies to differentiate benign from malignant drugs that prolong the QT and sex difference in QTc prolongation

• Regulatory Impact: Understanding the mechanisms of QTc prolongation and determining if drug-induced abnormal heart rhythms may be prevented by combining drugs will ensure safety of approved drugs for women and men.

Oplægsholder
Præsentationsnoter
OWH supported research as a part of two FDA Critical Path projects to assess sex differences in drug-induced cardiac arrhythmias. Several drugs have the potential to cause the prolonging of the QT interval which can lead to an irregular or abnormal heart beat called Torsade de pointes (TdP) that can ultimately lead to sudden death. Women are at higher risk for TdP due to: Longer QTc at baseline and Exposure to higher drug concentrations In 1994, OWH funded research to understand the mechanism of the sex differences in drug-induced QT prolongation. OWH also supported additional research on metabolic drug-drug interactions contributing to QT prolongation. OWH-funded research contributed to the development of the FDA guidance to industry on study requirements for the assessment of QT prolongation potential of drugs for men and women. 14 drugs have been removed from the market because they cause this arrhythmia and up to 70% of the cases occur in women. OWH continues to fund research in this area to help us better understand the reasons why women and men respond differently to drugs and why women are at higher risk for some types of drug-induced arrhythmias. A current OWH-funded project is addressing the second issue: Why might women be at higher risk for TdP? We know that women have: Increased baseline QTc Higher drug concentrations in women  However, a greater sensitivity to drug-induced QTc prolongation has not be shown in 2 FDA-sponsored clinical trials  Also, not sure if women have higher torsade de pointes risk at any given QTc value The QTc interval is a poor biomarker for predicting prolonging of the QT interval which can lead to an irregular or abnormal heart beat called Torsade de pointes (TdP), as a prolongation of the interval does not necessarily cause TdP. This current study is assessing the ability of novel ECG biomarker strategies to differentiate benign from malignant drugs that prolong the QT and sex difference in QTc prolongation. Investigated the use of other biomarkers such as the QRS-T angle, T magnitude and ventricular gradient that may discriminate between drugs that cause a benign QT prolongation and drugs that cause malignant QT prolongation Regulatory Impact: Helps to understand the reasons why women are at higher risk for some types of abnormal heart rhythms caused by drugs and to determine if drug-induced abnormal heart rhythms may be prevented by combining drugs. Together, this will ensure the safer use of drugs in women.
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Vision: A world where health equity is a reality for all Mission: The Office of Minority Health advances FDA’s regulatory mission in addressing the reduction of racial and ethnic health disparities and in achieving the highest standard of health for all.

Goal 1- To improve and strengthen regulatory science informing the research and evaluation of sub-population data associations with race and ethnicity.

Goal 2- To strengthen FDA capacity to address minority health and health disparities across the Agency.

Goal 3- To promote effective communication and the dissemination of information to the public, particularly underserved, vulnerable populations.

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FDA Office of Minority Health March 2010 Affordable Care Act- Section 10334 mandated creation of OMH across all HHS divisions

Oplægsholder
Præsentationsnoter
Section 10334 of the ACA mandated the creation of Offices of Minority Health across HHS, including the FDA. The FDA OMH’s vision is to promote a world where health equity is a reality for all. In particular, OMH’s first two goals (read these goals out loud) as they relate to regulatory science are addressed by it’s Research and Collaboration Program (RCP).
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Research and Collaboration Strategies

• Intramural Challenge Grants • Intramural ORISE Fellows • Extramural ORISE Fellows

Support/Fund Research Projects

• FDA Centers for Excellence in Regulatory Science and Innovation Program

• 2015 Genomics and Health Disparities Lecture Series with the National Human Genome Research Institute (NHGRI)

Collaborations

• OMH Speaker Series • CDER Scientific Seminars • Pharmacy Intern Program • Institute of Medicine Roundtable on Promotion of Heath

Equity and the Elimination of Health Disparities • Part 15 Hearings/CERSI Workshop

Training/Workshops

FDA Office of Minority Health

Oplægsholder
Præsentationsnoter
Under the RCP, we lead the agency’s efforts to prepare guidance documents to inform industry practices. For example, we are in the process of updating the 2005 Guidance Document to Industry on Race and Ethnicity Data in Clinical Trials. We work with external academic partners and also fund projects under FDA’s Centers for Excellence in Regulatory Science and a limited number of health disparities research fellowships. We also support FDA intramural research for projects targeting issues that can inform the regulatory decision making process related to health disparities, such as the study of molecular differences in triple negative breast cancer and multiple myeloma. We participate the Office of Chief Scientist Intramural Research Program, now in its 3rd year of support for FDA scientists engaged in health disparities research. And, we support ORISE research fellows, pharmacy students Workshops: April 2014: Public Hearing on the Food and Drug Administration Safety and Innovation Act (FDASIA) Section 907 April 2015: Institute of Medicine, Roundtable on the Promotion of Health Equity and the Elimination of Health Disparities, “Strategies for Ensuring Diversity, Inclusion, and Meaningful Participation in Clinical Trials: A Workshop” December 2015: “Clinical Trials: Assessing Safety and Efficacy for a Diverse Population” co-sponsored with Johns Hopkins CERSI February 2016: FDASIA 907 Public Meeting: “Progress on Enhancing the Collection, Analysis and Availability of Demographic Subgroup Data”
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Project: Improving Health Literacy and Cultural Competency in Current FDA Risk Communication PI: Olivia Carter-Pokras, PhD Objective: Evaluate how health information is relayed by examining health literacy and cultural competency of Food and Drug Administration (FDA) consumer materials on HIV/AIDS and Hepatitis B/C Outcomes: • Majority of pages scored at the college or graduate reading level (>12). • Epidemiology of population health and health care disparities are key

components of cultural competency training for health professionals • Although many websites contain data and statistics, statistics presented

are not representative of the intended audience and material is not useful • Publication: Health Literacy and Cultural Competency of FDA Consumer

Materials

FDA Office of Minority Health, Example

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Summary Science-based regulation is improved when

FDA engages in research proactively and reactively to address critical knowledge

gaps that reduce uncertainty in regulatory decision-making.

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With Thanks

• Robert Fisher, OCET, OCS • York Tomita, Khaled Bouri, Shaila Shaheed, ORSI • Martin Mendoza, OMH • Emmanuel Fadiran, OWH • Steve Bauer, Maria Rios, CBER • Ruth Barratt, CDER • Tom Flammang, NCTR