PowerPoint Presentationeservices.personalcarecouncil.org/Meetings/2016Science... · 2016-10-26 ·...

10/26/2016

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Overview of Cosmetics Research at FDA

Nakissa Sadrieh, Ph.D.

Director, Cosmetics Division, OCAC/CFSAN/FDA

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Outline

• Objectives of cosmetics research in OCAC

• Examples of OCAC research

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What are Cosmetics • Defined in the Federal Food, Drug, and Cosmetic Act

(FD&C Act), Section 201 (i)

• Articles intended for: – Cleansing

– Beautifying

– Promoting attractiveness

– Altering the appearance

** Excludes “Soap” (alkali salt of fatty acid-CPSC)

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Cosmetics – FDA’s Authority

• Cosmetics must not be adulterated or misbranded

• The law does NOT provide for FDA pre-market approval

• FDA’s authority is post-market only

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Important Considerations • FDA regulates finished cosmetic products and ingredients formulated

therein • Manufacturers must ensure the safety of marketed cosmetic products

under intended conditions of use • FDA can take enforcement action on cosmetics products shown to be

misbranded and/or adulterated • FDA bears the burden of proof for establishing harm from individual

ingredients used in cosmetics • FDA may, through rule making, restrict or ban ingredients shown to be

unsafe • The only cosmetic ingredients that require premarket approval are

color additive (except for coal tar hair dyes) • Cosmetic products are formulated products that are comprised of

numerous cosmetic ingredients (there are over 23,000 ingredients monographed in ICICD-16, and additional ingredients from other sources, that could potentially be used in cosmetics)

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Importance of Research in OCAC

• Because cosmetics do not have premarket review, FDA takes into consideration, the following sources of information, in order to assess the safety of cosmetic products and ingredients, to support policy development, and to support necessary enforcement activities:

– Published research

– Published position papers from regulatory agencies

– Industry publications

– Adverse events reports

– Enforcement activities

– FDA research

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Mechanisms Used For OCAC Research

• Laboratory based work: – Methods development to identify and quantify ingredients

and other components in cosmetics – Establishment of screening tools for safety assessment of

selected ingredients

• Literature based work – Published papers – Databases

• Adverse events analysis • Market data analysis

• Computational/in silico model development for predictive toxicology

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Research Paradigm • Hypothesis generation from:

– Adverse events analysis

– In silico modeling

– Literature survey/ public inquiry

– FDA research and enforcement activities

• Testing via: – Use of contract mechanisms

– Use of available in-house screening tools for safety assessment of cosmetic ingredients

– Use of field laboratories

– Use of established collaborations/partnerships

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Examples of Current Areas of Research

• Adverse events analysis • Skin sensitization/allergen characterization and

identification • Dermal penetration • Inhalation toxicology • Ocular toxicology • Computational toxicology • Methods development:

– To analyze tattoo inks and pigments – To assist field offices with rapid screening methods

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Adverse Event Reporting

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Number of Adverse Events Per Year

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2014-2015 Report Source

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70%

19%

8%

2%

1%

0%

2014

Consumer

Industry

Friend/Relative

State/LocalGovernment

Health Professional

Attorney

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Types of Adverse Reactions Reported to FDA

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% of Non-Serious Vs. Serious Adverse Events (2013-2015)

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Cosmetic Adverse Events Categorized by Skin Care and Hair Care Products

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10

20

30

40

50

60

70

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2009 2010 2011 2012 2013 2014 2015

Percentage of Skin Care Products and Hair Care Products 2009-2015

Skin

Hair

Both

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Cosmetic Adverse Events Categorized by Leave On and Rinse Off Products

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2009 2010 2011 2012 2013 2014 2015

Percentage of Leave On Products and Rinse off Products 2009-2015

Leave On

Rinse Off

Both

Skin Sensitization/Allergen Characterization and Identification

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The Skin Immune System (Nestle et al. 2009. Nat.Rev.Immunol. 9:679)

• Distinct immune cells continually traffic between skin, circulation and draining lymph nodes

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The Impact of Chemicals on the Skin Immune System

(Kaplan et al. Nat.Rev.Immunol. 12:114)

• Chemicals that can penetrate through S. corneum , cells of S. granulosum and S. spinosum, can reach the first levels of the skin immune system

• Cosmetic ingredients may be “haptens”!

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Replacing Animal Testing with in Chemico/In Vitro Testing

(Martin et al. 2010. Cell.Mol.Life Sci. 67:4171)

• Designed to test Key Events of Adverse Outcome Pathway

• Limitation: Proposed to test hapten/carrier mechanism only

• No single assay is going to be sufficient to evaluate the sensitization potential of any chemical

• Weight of evidence (WoE) approach, where the results of two concordant out of three performed tests are taken into account

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Adverse Outcome Pathway

ADME

Penetration of test chemical

Key Event 4 Key Event 2 Key Event 3 Key Event 1

MIE Cellular response

Organ response

Adverse outcome

Lipophilicity

Transformation of test chemical

Pre-hapten

Pro-hapten

Hapten binding

Stress response

Activation of DC

T-cell activation

Skin sensitization

DPRA HTS-DCYA

NMR-DCYA

KeratinoSens LuSens

h-CLAT U-SENS

LLNA

GPMT

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Human Cell Line Activation Test (h-CLAT)

Flow cytometry detection of two induced surface protein

markers in human monocytic leukemia cell line

Current Status: A number of cosmetic ingredients are

under investigation

H-CLAT

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The Human Cell Line Activation Test (h-CLAT) • The h-CLAT measures the upregulation of markers of dendritic cell activation in THP-1

cells. Cell surface increases of > 2-fold CD54 and > 1.5-fold CD86 indicate dermal sensitizers.

We are now preparing to test a panel of potential dermal sensitizers and non-sensitizers

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KeratinoSens™

A reporter gene assay measuring activation of the

Keap1-Nrf2-ARE signaling pathway. Measures

luciferase activity via luminescence

Status: Once the assay has been established in our

labs, we will begin testing of cosmetic ingredients.

KERATINOSENS™

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Direct Peptide Reactivity Assay (DPRA)

Uses HPLC to monitor chemical depletion of

nucleophile-containing synthetic peptides

Status: we are using this assay to test cosmetic

ingredients.

DPRA

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Goals of sensitization/allergen research • Compile published scientific evidence for the

characterization of sensitizers/allergens • Identify criteria and basis for characterizing sensitizers/

allergens • Identify potential sensitizers/allergens in cosmetic

product • Provide outreach to educate the public on the safe use of

cosmetics • Work collaboratively internationally through

International Cooperation on Cosmetics Regulation (ICCR)

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Ocular Toxicology

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Ocular Irritation (establishing models)

Current Plans

• ATCC CRL-11135 (human corneal epithelial cells)

– Monolayer culture

• Short time exposure (STE) Assay

– Cells are exposed to test chemical for 5 minutes

– Exposure is followed by a cytotoxicity/cell viability test

• Neutral Red Assay

– Cytotoxicity test

– Healthy cells absorb the red dye

– The dye is extracted with ethanol followed by colorimetric analysis in a plate reader

Future Plans

• EpiOcularTM (3D ocular epithelial model)

• Bioplex (expression of cytokines and inflammatory mediators)

• Focus on mild to moderate irritants for cosmetics

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Taken from IIVS website

Inhalation Toxicology

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Assessment of Cosmetic Ingredient Inhalation Toxicity-Using a 3D Human Airway Epithelium Model

• Conduct cell viability test to assess toxicity of selected cosmetic ingredients in 3D normal human-derived tracheal/bronchial epithelial (NHBE) in the EpiAirway® model.

• Establish toxic and non-toxic doses to determine most suitable cytotoxicity assays to use. – Trans-Epithelial Electrical Resistance (TEER) Measurement Method – MTT Cell Viability Assay – LDH (lactate dehydrogenase) Cytotoxicity Detection Assay

• Perform Elisa-based assay using the Bio-Plex instrument to assess for induction/suppression of pro-inflammatory cytokines-biomarkers for inhalation toxicity

– IL-1 alpha – IL-1 beta – IL-6

• Conduct microarray gene expression analysis to determine which genes are up-regulated and down-regulate

• Determine cellular bioenergetics, including mitochondrial respiration and glycolysis to assess effect of cosmetic ingredients on cellular metabolism

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Dermal Penetration

Report on Research Progress for Detecting Dermal Toxins Reconstructed human epidermis (RhE) is comprised of primary human keratinocytes that have been induced to form a multi-layered, 3D tissue that can be grown in culture dishes. Relative to 2D cell cultures, the benefit of the RhE model is that compounds can be applied directly to the stratum corneum layer to more directly simulate dermal exposure.

Skin Irritation Test (SIT) The SIT uses RhE to assess dermal irritants. Viability < 50% indicates an irritant.

Using the OECD test guideline for the SIT, we found < 50% viability for 6 of 6 known irritants, and > 50% viability for 6 of 6 known non-irritants. Our data closely matched data published by the developer of the SIT.

FDA will use the SIT to evaluate compounds of unknown toxicity for dermal irritation using the SIT.

Reconstructed human epidermis (RhE)

• In previous studies, positively charged (bPEI-coated) and neutral (PEG-coated) 20nm AgNPs penetrated into human skin more than negatively charged (citrate-coated) AgNPs.

• A 24h mass-balance in vitro dermal penetration study was conducted with neutral (PEG-coated) and positively-charged (bPEI-coated) 20nm AgNPs in aqueous solution to determine the extent of silver penetration throughout the layers of human skin.

• Cotton swabs (washes), tape strips (surface bound particles and stratum corneum), epidermis, dermis, receptor fluid, and parafilm were all analyzed by ICP-MS to determine % applied dose of silver recovered in analytes.

In Vitro Penetration of Branched Polyethyleneimine (bPEI) and Polyethylene Glycol (PEG) Coated Silver Nanoparticles (AgNPs) into Human Skin: a Mass Balance Study

Results from this study suggest there is minimal in vitro dermal penetration of AgNPs in human skin.

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Computational Toxicology

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Development of Skin Sensitization Models

• Objectives:

Compile and curate a large and diverse dataset of chemicals with known human skin sensitization potentials

Develop multiple validated QSAR models (with additional external validation) using this dataset and three different software programs

Development a WoE approach to predict accurately the human skin sensitization potential of ingredients and contaminants in cosmetic products and subsequently to provide scientific information to fill the critical data gaps for the safety assessment.

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Composition of Dataset Used to Build Models

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Development of QSAR Models

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• Five validated QSAR models have been

developed using three different software

programs:

– ADMET Predictor

– Case Ultra

– Leadscope Enterprise

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Prediction of Training Set (n = 463) from the QSARs

and the WoE Approach

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Prediction of External Validation Set (n = 51) from the

QSARs and the WoE Approach

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QSAR Models for Skin Permeation

Using SciMatics Program The dependent variable used in the QSAR analysis is the logarithm of the in vitro penetration coefficient through human skin, log Kp Partial Least Square (PLS) Regression log Kp = 0.3007*tp1 + 0.2283*tp2 + 0.337*tp3 + 0.625*tp4 + 0.2576*tp5 + 0.2244*tp6 + 0.3469*tp7 + 0.3416*tp8 + 0.1635*tp9 + 0.1177*tp10 + 0.07483*tp11 + 0.2524*tp12 + 0.2308*tp13

Number of chemicals = 201 R-Squared = 0.857 Q-Squared = 0.817 Skewness = 0.414

-14

-12

-10

-8

-6

-4

-2

0

-14 -12 -10 -8 -6 -4 -2 0

log

Kp

(O

bse

rve

d)

log Kp (Predicted)

Observed Vs Predicted log Kp

Conclusion: The training set is very well described by PLS model with 13 components. Cross-validation shows that the constructed model can be used to predict the Kp value of untested chemicals

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R-Squared = Pearson correlation coefficient squared Q-Squared = Q-squared statistic over a data set SRCC = Spearman's Rank Correlation Coefficient RMSE = Root mean square error

Using ADMET Predictor (Simulation Plus)

Multiple Linear Regression (MLR) Number of chemicals = 201 Number of descriptors used = 45

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Summary of Computational Model Development

An in silico method for skin sensitization in humans was developed at FDA/CFSAN that utilizes five different QSAR models in a WoE approach

Two in silico skin permeation models have been developed to

date, and additional models will be developed, in order to establish an adequate in silico method for predicting dermal penetration

Performance of the in silico methods may further be improved

by incorporating MOA models into a WoE prediction In silico methods will be very useful in helping to identify

cosmetic ingredients that may require further toxicological evaluation

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Methods Development Examples: 1. Tattoos inks and pigments

2. Screening methods for field laboratories

1. Tattoo Ink and Pigment Analysis

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What is Tattooing?

• Tattooing is the practice of injecting tattoo ink between the epidermis and dermis of the skin

– Traditional tattoos are applied anywhere on the body

– Permanent makeup tattoos are applied to the face, intended to look like makeup

– Medical uses include breast reconstruction and surgical markings

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Challenges of Developing Methods for Tattoo Pigment and Ink Characterization

• Identification of pigments in tattoo inks is difficult because of factors such as:

– Low solubility of the pigments

– Interferences from additional tattoo ink components (e.g., witch hazel, resins)

– Low amounts of pigments in some tattoo inks

– Limited access to pigment standards

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• Tattoo pigments must be insoluble in tattoo inks to prevent migration from the skin

• Organic pigments: – High tinting strength (intense colors)

– Wide range of shades/colors

– May contain potentially harmful compounds (e.g., amines)

• Inorganic pigments: – Natural sources may also contain clay, silica, etc.

– Synthetic sources are more pure

– Shade/color may fade over time

– May contain heavy metals

Tattoo Pigments


Chemistry of Tattoo Pigments

Pigment categories

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Organic and Organometallic Pigments

Pigment Red 170

Pigment Brown 25

Pigment Orange 16

Pigment Violet 23 Pigment Red 122

Pigment Blue 15


• Iron oxides

– Magnetite • Fe3O4; iron(II,III) oxide

– Hematite • Fe2O3; iron(III) oxide

– Goethite • -FeO(OH)

– Lepidocrocite • -FeO(OH)

– Limonite • Mixture of goethite,

lepidocrocite, clay, silica

• Carbon black

– C

• Titanium dioxide

– TiO2; rutile, anatase

• Barium sulfate,

– BaSO4; barite

• Kaolinite clay

– Al2Si2O5(OH)4

• Calcium carbonate

– CaCO3; calcite

Inorganic Pigments


Methods for Identification of Pigments in Tattoo Inks

Liquid chromatography – UV-visible spectrophotometry

X-ray powder diffraction

Raman spectroscopy

XRD method Raman method

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Test solubility of available organic pigments in polar solvents and develop LC method for their identification.

Develop XRD method for the identification of inorganic pigments and organic pigments not identifiable by LC.

One method may be confirmatory for another method, especially for difficult to analyze pigments and pigments present in low amounts.

Develop Raman method for the identification of carbon black and pigments not identifiable by LC.

This strategy considers the chemistry of individual pigments for use in rapid screening of tattoo inks

Overall Strategy


Tatt

oo

pig

men

ts

LC method monoazo pigments, PO13, PO16, PY14, PR122

XRD method

iron oxides

titanium dioxide

PY83, PV23, PG7, PB15

monoazo pigments, PO13, PO16, PY14, PR122

Raman method

carbon black

titanium dioxide

PY83, PV23, PG7, PB15

Summary of Methods for Pigment Identification

Incr

easi

ng

anal

ysis

tim

e


Summary

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Approaches for Assessing Contaminants in Tattoo Inks

• Heavy metal contaminant screening study: – Analyze samples by x-ray fluorescence to obtain elemental profile

– Evaluate various means of sample preparation. Tattoo inks may contain compounds incompatible with current acid digestion procedures

– Complete single lab validation on an ICP-MS method for the detection of 9 elements (As, Cd, Pb, Hg, Sb, Cr, Co, Cu, Ni)

– Analyze tattoo inks using the optimized preparation technique and ICP-MS

• Tattoo ink contaminant screening study: • Develop an extraction method to remove color components and allow for focus on

contaminants

• Optimization of LC-HRMS method to obtain representative chemical profiles of the compounds within the inks

• Complimentary analysis by NMR for the detection of ink solvents and unknown compounds

• Chemometric methods, such as PCA, for statistical classifications and clustering. Data base building using clustering results

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2. Rapid Screening Method Development for Detecting Active Pharmaceutical Ingredients in

Cosmetic Products • Cosmetic products, may contain ingredients that also happen to be

Pharmacologically Active Ingredients (APIs)

• Because the levels of individual cosmetic ingredients in formulated products is not reported on the label, the FDA needs rapid screening methods to identify ingredients that may be of potential concern.

• An LC-HRMS method using Q-Orbitrap mass spectrometry to analyze

multiple classes of APIs in cosmetics is being developed for: – Use in subsequent market survey(s) to determine the identify and

quantify APIs in cosmetic products – Sharing with field offices, for rapid identification of products that may

require further enforcement activities

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Approach

• Compile a list of potential APIs in cosmetics • Select some representative stable isotopically

labeled analogs as internal standards for these APIs, to compensate for matrix effect and for loss of recovery

• Develop an LC-HRMS method and evaluate method performance (accuracy, precision, and limits of quantitation)

• Create an HRMS library for the APIs • Develop sample prep procedures and evaluate

matrix effects and recoveries • Analyze approximately 30 commercial products

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Ketoconazole 65277-42-1

Spironolactone 52-01-7

Minoxidil CAS #: 38304-91-5

Finasteride 98319-26-7

Flutamide 13311-84-7

Dutasteride 164656-23-9

Structures of APIs that we investigated


RT: 3.00 - 10.00

3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0

Time (min)

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1004.31

4.32

4.384.27 4.48 4.88 8.127.29 8.377.58 7.86 9.559.048.857.11 9.30 9.693.32 5.16 5.92 6.875.453.80 6.575.80 6.053.57

6.17

6.20

6.22

6.25

6.61

6.446.43

6.65

6.40 7.73 7.787.717.304.96 7.09 8.23 8.49 8.83 9.579.25 9.944.55 5.14 5.50 5.84

6.69

6.74

6.776.64 6.91 7.90 8.16 8.33 8.86 9.629.317.313.32

7.25

7.28 9.67

5.67

NL: 2.15E8

m/z= 210.13284-210.13704 MS 20151221_Pos_APIs_With_ISs_Standard_08

NL: 1.51E7


NL: 4.50E7


NL: 5.47E7


NL: 1.59E5


Representative Chromatograms of APIs Standards without Smoothing


Results for the cosmetic products (n=3)

http://www.sigmaaldrich.com/catalog/product/sigma/s3378?lang=en&region=US

http://www.sigmaaldrich.com/catalog/product/sigma/f9397?lang=en&region=US

http://www.abblis.com/Product/getProductInfo.do?pid=9276

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A rapid UHPLC-HRMS method to detect selected APIs in cosmetics has been

developed and validated. This is the first UHPLC-HRMS method to detect these

analytes. The method was successfully applied to cosmetics products

The linear range was 1.00 to 1,000 ng/mL for most of the analytes with r2 > 0.992

Matrix effects were evaluated by using isotopically labeled analogues (also used

as internal standards). The matrix effects were effectively compensated using the

labeled internal standards. The matrix effects were also minimized by diluting the

extracted sample solutions prior to injection

Recoveries at four spiking levels ranged from 90.0 to 110% with RSDs less than

10% for most of the analytes

More cosmetic products will be evaluated

Summary of Rapid Screening Method Development Project

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Final Conclusion • FDA does cosmetics research to support policy

development and to carry out it regulatory mandate: – Guidances

– Regulations

– Enforcement actions

• The goal of OCAC research is to promote public health and support public confidence in cosmetic product quality AND safety

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Contact Information

Office of Cosmetics and Colors

5001 Campus Drive

College Park, MD 20740

Phone: 1-240-402-1130

Nakissa Sadrieh, Ph.D., Director, Cosmetics Division

[email protected]

GSRS 2016 67

mailto:[email protected]

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