Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation

Abstract

In the era of the booming cosmetics industry, safety and efficacy evaluation have become crucial aspects in ensuring product quality and meeting consumer demands. The Chinese cosmetics market has witnessed rapid development. With an increasing emphasis on the safety and efficacy of cosmetics, a relatively comprehensive evaluation system has been gradually established. As pioneers in the cosmetics industry, Europe and the United States also possess mature and advanced experience in this regard. Based on years of work experience in the fields related to cosmetics safety and efficacy evaluation, the author of this chapter has summarized the characteristics of China, Europe, and the United States in this area. For safety evaluation, the entry points include cosmetics raw materials, packaging materials, chemistry and microbiology, as well as human testing. For efficacy evaluation, it is classified into categories such as cosmetics for freckle—removing and whitening, anti-hair loss, sun protection, anti-aging, and acne—treatment, repair, soothing, and those suitable for sensitive skin. By integrating the application of new AI technologies, this chapter presents a relatively scientific evidence-based system for cosmetics safety and efficacy evaluation to boost the high-quality development of the cosmetics industry.

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
Chapter
Establishing an Evidence-Based
System for Cosmetic Safety and
Efficacy Evaluation
LiYe, JianhuaZhang, TianChen, DongcuiLi and PengShu
Abstract
In the era of the booming cosmetics industry, safety and efficacy evaluation have
become crucial aspects in ensuring product quality and meeting consumer demands.
The Chinese cosmetics market has witnessed rapid development. With an increasing
emphasis on the safety and efficacy of cosmetics, a relatively comprehensive evalu-
ation system has been gradually established. As pioneers in the cosmetics industry,
Europe and the United States also possess mature and advanced experience in this
regard. Based on years of work experience in the fields related to cosmetics safety
and efficacy evaluation, the author of this chapter has summarized the characteris-
tics of China, Europe, and the United States in this area. For safety evaluation, the
entry points include cosmetics raw materials, packaging materials, chemistry and
microbiology, as well as human testing. For efficacy evaluation, it is classified into
categories such as cosmetics for freckle—removing and whitening, anti-hair loss,
sun protection, anti-aging, and acne—treatment, repair, soothing, and those suitable
for sensitive skin. By integrating the application of new AI technologies, this chapter
presents a relatively scientific evidence-based system for cosmetics safety and efficacy
evaluation to boost the high-quality development of the cosmetics industry.
Keywords: cosmetics, evidence - based system, safety assessment,
efficacy evaluation, AI
. Introduction
The evidence-based system, in simple terms, is a comprehensive decision-making
framework that is founded on scientific research evidence, industry standards and
regulations, consumer feedback and market data, as well as expert opinions and
consensus. At its core, it involves systematically collecting, evaluating, and integrat-
ing information from multiple sources to provide reliable grounds for the safety and
efficacy of cosmetics. This ensures that every stage of cosmetics, from research and
development to production and sales, adheres to high-quality standards. There is a
multi-faceted necessity for establishing an evidence-based system for the safety and
efficacy of cosmetics. Firstly, for consumers, accurate information regarding the
safety and efficacy of cosmetics is crucial for making informed purchasing decisions.
The evidence-based system can offer objective and scientific evidence, assisting

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
consumers in selecting cosmetics that are truly suitable, safe, and effective for them
and preventing potential health risks associated with the use of inappropriate prod-
ucts. Secondly, from the perspective of industry development, the evidence-based
system contributes to regulating the order of the cosmetics market. It encourages
enterprises to pay more attention to product quality; conduct product research, devel-
opment, and promotion based on scientific evidence; and reduce adverse phenomena
such as false efficacy claims. This, in turn, enhances the credibility and competitive-
ness of the entire industry. Thirdly, at the regulatory level, the evidence-based system
provides strong support for regulatory authorities in formulating policies and regula-
tions and conducting market supervision. It enables regulatory decisions to be more
scientific and rational, ensuring the healthy and stable operation of the cosmetics
market. With the continuous development of the cosmetics industry and the escalat-
ing demands of consumers, establishing a complete evidence-based system for safety
and efficacy has become an inevitable trend. It will lay a solid foundation for the
sustainable development of the industry.
. Construction of an evidence-based system for cosmetic safety
The cosmetics industry is continuously growing on a global scale, with new
products and technologies emerging constantly, offering consumers a wider range of
choices. However, the issue of cosmetic safety is increasingly drawing the attention of
the public and regulatory authorities. The chemical substances contained in cosmetics
may have an impact on human health. Therefore, ensuring the safety of cosmetics is
crucial for protecting consumer health and maintaining the industry’s credibility. The
cosmetic safety evaluation system is an essential safeguard for the safe market entry
of cosmetics, involving multiple aspects such as ingredient analysis, toxicological
testing, and clinical trials. This paper will provide a detailed discussion on the con-
struction principles, evaluation methods, and risk assessment of the cosmetic safety
evaluation system [, ].
. Principles of constructing the cosmetic safety evaluation system
.. Principle of scientificity
The construction of the cosmetic safety evaluation system must be based on sci-
entific principles and methods to ensure the accuracy and reliability of the evaluation
results. Generally speaking, cosmetic safety assessment should follow the principle of
weight of evidence, based on existing scientific data and relevant information, and
adhere to the principles of science, fairness, transparency, and case-by-case analysis.
During the implementation process, the independence of the safety assessment work
should be guaranteed [].
.. Principle of comprehensiveness
The evaluation system should cover all safety issues of cosmetics, including the
safety of raw materials, risk substances, formulations, production processes, and
packaging materials. This means that the evaluation system needs to take into account
all aspects of cosmetics to ensure a comprehensive assessment of their safety. Moreover,
cosmetic enterprises should have the concept of full life cycle safety assessment and risk

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management. That is to say, safety assessment should start before product development,
be implemented at the time of product registration and filing, accompany the product
after it goes to market, and run through the entire life cycle of the product [, ].
.. Principle of dynamism
With the development of science and technology and the changes in consumer
demand, the cosmetic safety evaluation system should be continuously updated and
improved. This requires the evaluation system to adapt to new scientific discoveries
and technological progress, as well as the new requirements of consumers for the
safety of cosmetics.
.. Principle of international coordination
Considering the global circulation of cosmetics, the evaluation system should
be consistent with international standards and regulations to promote international
trade. This requires the evaluation system to be coordinated with the international
cosmetic safety evaluation system, reducing trade barriers [, ].
. Framework of the cosmetic safety evaluation system
.. Safety evaluation of raw materials
The safety evaluation of raw materials is the foundation of cosmetic safety evalu-
ation, including the physicochemical properties and toxicological characteristics
of raw materials. The safety evaluation of raw materials requires a detailed safety
assessment of each raw material used in cosmetics and the risk substances that may be
brought in, to ensure that they are harmless to the human body [, , ].
.. Safety evaluation of formulations
The safety evaluation of formulations focuses on the overall safety of cosmetic
formulations, including the interactions and potential risks among the various
components in the formulation. Cosmetic products can generally be considered as
combinations of various raw materials and should be assessed based on all raw mate-
rials and risk substances. If it is confirmed that there are chemical and/or biological
interactions among certain raw materials, the risk substances produced and/or the
potential safety risks generated by these interactions should be assessed [].
.. Safety evaluation of production processes
The safety evaluation of production processes focuses on the safety issues that
may arise during the production process, such as cross-contamination and microbial
contamination. The safety evaluation of production processes needs to ensure that
the production of cosmetics complies with safety standards to prevent product
contamination.
.. Safety evaluation of products
The safety evaluation of products is the final stage of cosmetic safety evalua-
tion, including the physicochemical stability, microbiological safety, preservative

Cosmetic Industry – Trends, Products and Quality Control

efficacy evaluation, toxicological safety, and compatibility of packaging materials
of the products.
. Methods of cosmetic safety evaluation
.. Laboratory testing
Laboratory testing is the main method of cosmetic safety evaluation, including
chemical analysis, microbiological testing, and toxicological testing. Laboratory test-
ing can provide direct evidence of the safety of cosmetics and is an important part of
the evaluation system. At present, with the implementation of bans on animal testing
for cosmetics in many countries or regions, the development and application of in
vitro alternative methods and computational toxicology methods are increasingly
drawing attention [, ].
.. Clinical trials
Clinical trials are an important means of assessing the safety of cosmetics, evalu-
ating the actual safety of products through human trials. Clinical trials can provide
safety data of cosmetics under actual usage conditions, which is crucial for assessing
the safety of cosmetics.
.. Risk assessment
Risk assessment is the core of cosmetic safety evaluation, providing a basis for
safety decision-making by assessing the exposure levels and health risks of potential
risk substances in cosmetics. The safety assessment of cosmetic products should be
exposure-oriented, combining the exposure levels such as the usage method, usage
site, usage amount, and residue of the products, to assess the safety of cosmetic
products and ensure their safety [, ].
. Steps of cosmetic safety risk assessment
.. Hazard identification
Hazard identification is the first step of risk assessment, that is, based on the
results of toxicological tests, clinical research, adverse reaction monitoring, and epi-
demiological studies of populations, to determine whether there is a potential hazard
to human health from the physical, chemical, and toxicological characteristics of raw
materials and/or risk substances.
.. Dose-response relationship assessment
Determine the relationship between the toxicological response of raw materials
and/or risk substances and the exposure dose. For threshold toxic effects, the No
Observed Adverse Effect Level (NOAEL) or Benchmark Dose (BMD) should be
obtained. For non-threshold carcinogenic effects, the dose that causes tumors in 
of experimental animals (T) or BMD is used to determine it. For raw materials and/
or risk substances with sensitization risks, the No Expected Sensitization Induction
Level (NESIL) should also be used to assess their sensitization [, , ].

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.. Exposure assessment
By assessing the site, concentration, frequency, transdermal absorption rate,
and duration of exposure of cosmetic raw materials and/or risk substances to the
human body and combining the particularity of the exposed subjects (such as adults,
children, infants, etc.), the exposure level is finally determined. When calculating
the exposure amount, the possibility of other exposure routes (such as inhalation,
ingestion, etc.) should also be considered; if necessary, the exposure situation from
other possible sources (such as food and environment, etc.) outside cosmetics should
be considered [].
.. Risk characterization
It refers to the description of the possibility and degree of damage to
human health caused by cosmetic raw materials and/or risk substances. The
Margin of Safety (MoS), lifetime cancer risk (LCR), and the comparison between
acceptable exposure levels and actual exposure amounts can be used to describe
the threshold toxic effects, non-threshold carcinogenic effects, and sensitiza-
tion effects of cosmetic raw materials and/or risk substances on the human body,
respectively [].
. Challenges and prospects of the cosmetic safety evaluation system
.. Challenges
The challenges faced by the cosmetic safety evaluation system include the safety
evaluation of new raw materials and plant extracts, the application of nanotechnol-
ogy, and the safety of personalized cosmetics. With the continuous development of
the cosmetics industry, new raw materials and technologies are emerging constantly,
posing new challenges to the cosmetic safety evaluation system. In addition, since
people in different countries or regions have different concepts and habits of cosmetic
consumption, there is a significant difference in their systemic exposure to various
products. Therefore, it is necessary to carry out real-world investigation and research
to supplement the data gap of exposure parameters.
.. Prospects
The cosmetic safety evaluation system is an important tool for safeguarding
consumer health and promoting the development of the cosmetics industry. Through
a scientific, comprehensive, dynamic, and internationally coordinated evaluation
system, the safety of cosmetics can be effectively assessed, and consumer rights
can be protected. In the future, with the progress of science and technology and the
changes in consumer demand, the cosmetic safety evaluation system will continue to
improve and develop.
.. Conclusion
Through a scientific, comprehensive, dynamic, and internationally coordinated
evaluation system, the safety of cosmetics can be effectively assessed, and consumer
rights can be protected. In the future, with the progress of science and technology and

Cosmetic Industry – Trends, Products and Quality Control

the changes in consumer demand, the cosmetic safety evaluation system will continue
to improve and develop.
. Construction of an evidence-based system for cosmetic efficacy
evaluation
The establishment of an evidence-based system for cosmetic efficacy evaluation is a
complex and systematic project that requires scientific and rigorous design from multiple
key dimensions. First and foremost, it is of utmost importance to deeply explore the
internal mechanisms by which different functions exert their effects. For instance, the
whitening effect may involve multiple mechanisms such as inhibiting the activity of
tyrosinase and hindering the production and transportation of melanin. On the other
hand, the anti-wrinkle effect may be closely related to promoting collagen synthesis and
enhancing the metabolism of skin cells. Only by accurately understanding these mecha-
nisms can a solid theoretical foundation be provided for subsequent efficacy evaluations.
Secondly, the rational selection of efficacy markers directly impacts the accuracy and
reliability of the evaluation results. Markers should be specific and capable of precisely
reflecting the claimed functions of cosmetics. For example, for the moisturizing effect,
the water content of the skin stratum corneum can be selected as a key marker. In the
case of the antioxidant effect, the level of intracellular reactive oxygen species (ROS)
may be a more appropriate marker. Furthermore, experimental design is the core part
of the entire evidence-based system. Basic principles such as randomization, control,
and replication should be adhered to ensure the scientific nature and reproducibility of
experimental results. When designing an experimental plan, numerous factors need to
be comprehensively considered, including sample size, grouping methods, interven-
tion measures, observation indicators, and time points. In addition, every detail in the
testing process cannot be overlooked. The screening of subjects should strictly follow
established standards to ensure their representativeness and to exclude interfering factors.
For example, for the evaluation of anti-aging effects, subjects whose age and skin type
meet specific conditions should be selected to avoid excessive individual differences from
affecting the experimental results. Testers need to receive professional and systematic
training, master various testing techniques and methods proficiently, and ensure the
accuracy and consistency of operations. At the same time, the correct operation of testing
equipment is also crucial for ensuring data quality. Equipment should be calibrated and
maintained regularly to ensure its stable performance. Moreover, external conditions such
as environmental temperature and humidity may also affect the testing results. Therefore,
the experimental environment needs to be strictly controlled and maintained within an
appropriate temperature and humidity range, and the interference of environmental
factors on the experiment should be minimized. Next, I will elaborate on some efficacy
categories about which consumers are more concerned.
. Construction of an evidence-based system for evaluating the efficacy of
cosmetics related to skin anti: Aging
.. Overview of skin aging
Aging is defined as a time-dependent, ongoing change in the functionality and
reproduction of higher organisms, associated with a greater likelihood of morbidity
and mortality []. Skin aging is a complex biological process marked by various

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Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation
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physiological changes that occur over time, in which human skin is continually sub-
jected to both intrinsic and extrinsic factors that affect its functionality as it ages [  ].
A comprehensive understanding of the hallmarks of skin aging is essential for the
formulation of effective skincare interventions. Rigorous evaluation of the efficacy
of skincare products is critical to ensure they effectively mitigate the signs of aging
and enhance skin health, ultimately supporting individuals in maintaining a youthful
appearance and improving their self-esteem.
Recently, study has outlined seven hallmarks related to skin aging: () genomic
instability (DNA damage) and telomere attrition; () epigenetic alterations and loss
of proteostasis; () deregulated skin nutrient-sensing; () mitochondrial dysfunc-
tion; () cellular senescence in skin; () stem cell exhaustion and dysregulation; and
() altered intracellular communication ( Figure  ) [  ]. The first two hallmarks are
recognized as primary hallmarks in that they attribute to the skin damage that initi-
ates the aging process. The third to the fifth hallmarks are categorized as antagonistic
hallmarks in that they are the responses to damage that attempt to counteract the
effects of aging. The last two hallmarks are integrative hallmarks that are the factors
contributing to the observable characteristics and phenotypes of aging skin [  ]. Each
of these hallmarks can be interconnected with one another during the process of skin
aging, contributing to the aging phenotype.
Figure 1.
Hallmarks of skin aging.

Cosmetic Industry – Trends, Products and Quality Control

.. Mechanisms of skin aging
Intrinsic skin aging refers to the natural aging process of the skin that occurs due
to time, genetic factors, and biological changes within the body, leading to a natural
decline in collagen and elastin production, reduced cell turnover, and decreased bar-
rier functions []. For example, there is a simultaneous decline in both the number
and functionality of fibroblasts, resulting in both the quantity and thickness of
collagen fibers to diminish and leading to a higher ratio of type III collagen compared
to type I collagen []. Aged skin also exhibits fragmentation of dermal collagen and
elastin, resulting in reduced skin elasticity and firmness []. Additionally, the prolif-
eration rate of the cell in basal layer declines, resulting in thinning in both epidermis
and epidermal–dermal junction [].
Extrinsic skin aging refers to the accelerated aging of the skin caused by envi-
ronmental factors such as air pollution, solar radiation, smoking, and nutrition
[]. Notably, photoaging due to ultraviolet (UV) radiation is the most significant
contributor to extrinsic skin aging. UVA (–nm) and UVB (–nm) rays
reach the earth in considerable amounts, posing risks to skin structures by directly
inducing DNA damage and indirectly causing genetic instability through the genera-
tion of reactive oxygen species (ROS). UVB radiation primarily induces cyclobutane
dimers (CPDs), while -hydroxy--deoxyguanine (-OHdG) is a common marker for
assessing DNA damage from UVA exposure []. Furthermore, ROS elicited by UV
rays activate nuclear factor kappa-B (NF-kB), leading to increased expression of pro-
inflammatory cytokines such as IL-α, IL-, and TNF-α [], contributing to inflam-
matory disorders. Additionally, exposure to infrared radiation (IR; nm–mm)
has harmful effects, including the induction of matrix metalloproteinase (MMP)
expression, collagen degradation, and an increase in skin mast cells [].
Indeed, both intrinsic and extrinsic factors can lead to irreversible senescence in
skin cells. This process is driven by telomere shortening, mitochondrial dysfunction,
and the activation of DNA damage response signaling, ultimately resulting in cell
cycle arrest []. The senescent skin cells demonstrate the elevation age-associated
biomarkers such as pINKa, pWaf-, HMGB, senescence-associated beta-galac-
tosidase (SA-β-gal), and downregulation in lamin B []. Meanwhile, senescent cells
also exhibit senescence-associated secretory phenotype (SASP), in which they induce
altered secretome including pro-inflammatory cytokines, chemokines, and growth
factors or proteases, providing influential consequences on the microenvironment
by modulating the immune system, remodeling ECM, and altering cellular func-
tions []. Altogether, the accumulation of senescent keratinocytes and fibroblasts is
attributed to the loss of integrity and function of the skin.
.. Visible signs of skin aging with underlying mechanisms
The intrinsic and extrinsic skin aging differ in terms of their clinical traits and
visible signs. The hallmarks of intrinsic skin aging are fine lines, laxity, and xerosis,
whereas extrinsic skin aging is characterized by coarse wrinkles, irregular pigmenta-
tion, and lentigines (age spots) [].
... Fine lines and laxity
Fine lines and skin laxity are both indicators of aging caused by intrinsic and
extrinsic factors impacting the skin. Fine lines are defined as small, shallow creases

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that develop primarily due to the thinning of the epidermis and a reduction in col-
lagen and elastin levels. In contrast, skin laxity refers to the skin’s diminished ability to
regain its original shape after being stretched, resulting in a loose and sagging appear-
ance due to a loss of firmness and elasticity.
The development of fine lines and laxity is primarily driven by age-related deg-
radation of collagen, elastin, chondroitin, and hyaluronic acid in fibroblasts. This
process is accompanied by an increased expression of matrix metalloproteinases
(MMPs), which are enzymes that break down components of the extracellular matrix
(ECM) []. Together, these changes contribute to the visible signs of aging in the
skin. Meanwhile, the intrinsic aging-related generation of ROS also contributes to
these processes []. Other age-related factors like hormonal change, weight loss, or
gravity also contribute to skin contour deformities []. Nevertheless, the induction
of these fine wrinkles can be different among diverse ethnical groups with varied
anatomical regions [].
... Xerosis (skin dryness)
Dry skin, or xerosis, is a common dermatological condition affected by various
factors, including hydration levels, sebum production, and environmental influences.
The condition is often linked to an age-associated alteration in skin barrier function,
particularly in the stratum corneum []. As skin ages, there is a notable reduction
in both the size and secretory activity of sebocytes, leading to a significant decline in
surface lipids and skin hydration []. Indeed, in menopausal women, research indi-
cates a marked increase in the pH of the hydro-lipid film and a reduction in sebum
production. Moreover, the expression of osmolyte transporters such as SMIT and
TAUT is also negatively correlated with age, which further affected water homeostasis
by decreasing the keratinocyte volume and leading to xerosis [].
... Coarse wrinkles
Coarse wrinkles are deep lines with a rough texture that appear on the skin.
Compared to intrinsic skin aging, the extrinsically induced tissue damage is more
pronounced in the epidermis and dermis. Chronic UV exposure over extended
periods significantly disrupts the normal skin architecture, with many histological
changes associated, with photoaging being the most evident in the ECM of the dermis
[]. Notably, the dermal elastic fibers are profoundly affected by UV radiation. In
response to photodamage and photoaging, ROS accumulation further induced the
damage of DNA, proteins, and lipids, which affects the skin-repair function [].
Moreover, upon UV exposure, elastic fibers initially undergo hyperplastic changes,
leading to an increase in the amount of elastic tissue produced [].
... Lentigines (age spots)
Age spots, or lentigines, are hyperpigmented macules resulting from increased
melanocyte proliferation that associate with age, chronic sun exposure, or other
exposome like air pollution []. Recent study also discovered that chronic
inflammation and the infiltration of pro-inflammatory M macrophages also
contributed to lentigines formation []. The occurrence of lentigines is marked
by changes throughout the entire skin structure, including the epidermis, the
dermal-epidermal junction, and the dermis []. The formation of lentigines is

Cosmetic Industry – Trends, Products and Quality Control

attributed to the accumulation of photoaged cells, which are characterized by
the presence of lipofuscin bodies and changed keratinocyte proliferation [].
Furthermore, the formation of rete ridges in the affected epidermis impedes the
upward migration of melanin in the basal layer []. Concurrently, a deficiency in
SDF serves as a significant stimulus for melanogenic processes, exacerbating the
mottled pigmentation characteristic of age spots [].
.. Evaluation methods for skin aging
... Cell-based in vitro method
In vitro methods for evaluating skin aging use cell models that simulate the human
physiological environment. Advances in cell culture technology are shifting from D
to co-cultures and D skin models, enabling better assessments of raw materials and
cosmetics.
D monolayer cell cultures involve the application of human keratinocytes and
fibroblasts. Commonly used human skin fibroblasts include HFF- (Human Foreskin
Fibroblasts), BJ (Bjerknes Fibroblasts), and HDF (Human Dermal Fibroblasts),
whereas epidermal keratinocyte cell lines frequently used in research are HaCaT and
NHEK (Normal Human Epidermal Keratinocytes). Researchers often use hydrogen
peroxide (HO) or UV stress to model extrinsic skin aging, while intrinsic aging
models are less common []. Since UVB affects the epidermis and UVA penetrates
the dermis, models expose HDF/HFF- cells to UVB and NHEK/HaCaT cells to UVA.
In addition to fibroblasts and keratinocytes, melanocytes are also used in studies of
skin aging. For example, NHEM (Normal Human Epidermal Melanocytes) is utilized
to understand the processes associated with skin aging [].
In terms of D culture models, these are advanced in vitro constructs that replicate
the structure and function of human skin. Commercially available reconstructed
skin models include EpiDerm™, SkinEthic™, and Episkin™ currently widely used
in studying skin aging []. Moreover, bio-printed models incorporate skin cells such
as keratinocytes, fibroblasts, and melanocytes, which are also able to create human
skin equivalents []. Other than these, skin organoid cultures and “skin-on-chip”
technologies also provide detailed representation of skin in vivo, allowing the study of
intricate tissue interactions during aging [].
The most common experiments for assessing anti-aging activities focus on various
effects. Cell proliferation and viability tests typically employ CCK (Cell Counting
Kit-) or MTT (-(,-Dimethylthiazol--yl)-,-Diphenyltetrazolium Bromide)
assays. Antioxidation experiments assess oxidative stress-related factors such as
superoxide dismutase (SOD), malondialdehyde (MDA), reduced glutathione (GSH),
catalase (CAT), and reactive oxygen species (ROS) []. Additionally, collagen
production and matrix metalloproteinase (MMP) assays are widely used in cellular
skin aging studies []. The expression levels of hyaluronan synthases (HAS, HAS,
and HAS), which are involved in hyaluronic acid synthesis, are commonly used as
age-related markers for skin moisture []. Other senescence-related biomarkers
found in skin tissues, directly linked to senescence hallmarks, are listed in the table
below (Table ) []. Each of these assays has unique features, and typical techniques
such as immunoassay (ELISA), RT-qPCR, flow cytometry, immunofluorescence, and
Western blotting can be employed for identification.

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DOI:http://dx.doi.org/10.5772/intechopen.1009010
Marker Gene name Related skin aging
hallmark
Identification methods
CDKNA
(p INKA)
Cyclin-dependent
kinase inhibitor A
cellular senescence immunoblot, RT–qPCR,
WB, IHC, IF,
FISH, immunostaining
CDKNA
(pCIP)
Cyclin-dependent
kinase inhibitor A
cellular senescence immunoblot, RT–qPCR,
WB, IHC, IF
IL- Interleukin- SASP Immunoblot, RT–qPCR,
WB, microarray,
immunoassay (ELISA), IF,
IHC
TNF Tumor necrosis
factor
SASP Immunoblot, RT–qPCR,
WB, microarray,
immunoassay (ELISA), IF,
IHC
HAX HA.X variant
histone
genomic instability IF, IHC, WB, RT–qPCR
IL-αInterleukin-αSASP RT–qPCR,
immunoassay (ELISA), flow cytometry
IL-βInterleukin-βSASP RT–qPCR, microarray, WB,
cytokine array, immunoassay
(ELISA), IHC, IF
SA-β-gal Senescence-
associated
β-galactosidase
cellular senescence Colorimetric and fluorescent staining and
microscopy, IHC, IF, X-Gal crystal detection
via electron microscopy, flow cytometry,
SA-β-gal staining, X-gal precipitation
CXCL C–X–C motif
chemokine
ligand 
SASP Immunoassay (ELISA), RT–qPCR
HMGB High-mobility
group
box 
genomic instability RT–qPCR, IHC, IF,
WB, ELISA
MMP Matrix
metallopeptidase 
SASP WB, immunoassay (ELISA),
RT–qPCR, IHC
CXCL HGNC: SASP immunoassay (ELISA),
RT–qPCR, flow cytometry
MMP Matrix
metallopeptidase 
SASP RT–qPCR, immunoassay, microarray,
ELISA, IHC
MMP Matrix
metallopeptidase 
SASP RT–qPCR, immunoassay (ELISA)
LMNB Lamin B cellular senescence IF, RT–qPCR, WB
MMP Matrix
metallopeptidase 
SASP immunoassay (ELISA), RT–qPCR
Telomere
length
Telomere length telomere attrition FISH, TRAP assay, RT–qPCR
Lipofuscin Lipofuscin cellular senescence Sudan Black B staining
MKI Marker of
proliferation Ki-
cellular senescence IF

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Marker Gene name Related skin aging
hallmark
Identification methods
TAF Telomere-associated
foci
telomere attrition ImmunoFISH
TPBP Tumor protein p
binding protein 
genomic instability IF, IHC, IF foci
Table 1.
Senescence-related markers in skin.
... Human efficacy evaluation
.... Methods for testing skin firmness and hydration
As skin ages, its hydration, elasticity, and overall biomechanical properties change
significantly. Several advanced techniques are employed to assess these factors,
providing insights into skin condition.
Corneometry with suction method is a technique that uses negative pressure to
draw skin into a test probe equipped with optical systems for measuring skin displace-
ment over time. Common corneometer, like the MPA-Cutometer, evaluates the
hydration of the outer layer of the stratum corneum []. The water content in the
stratum corneum affects the capacitor’s behavior, resulting in changes in its capacity
that correspond to the skin’s hydration levels []. Another instrument includes the
Frictiometer ® FR, which measures skin friction. It operates by rotating a Teflon
cylindrical probe; a smoother skin results in lower torque and friction values, while
dry, wrinkled skin exhibits higher friction.
Pressure method is based on Young’s modulus, which describes the material’s resis-
tance to deformation under stress. The Skin Elastimeter is a compact, portable instru-
ment used to assess skin elasticity through indentometry. It features a central tip on
a reference plate, and when applied to the skin, it causes a temporary indentation of
up to .mm. A built-in sensor measures the force needed to create this indentation,
allowing for the calculation of the skin’s immediate elasticity []. Instruments like
the Delfin ElastiMeter utilize this principle to assess skin elasticity. Another method
includes the torsion method, in which a central disk is adhered to the skin, with a ring
attached to it. By applying torque, the angle of rotation is measured to evaluate skin
elasticity []. The Dia-stron Dermal Torque Meter DTM is a representative device for
this method.
Transepidermal water loss (TEWL) is a crucial indicator of skin barrier function
and hydration levels. The Tewameter® TM  is a non-invasive device specifi-
cally designed to measure TEWL. It features a probe with a sensitive sensor that is
applied to the skin’s surface to assess water evaporation over time. By detecting the
rate of water vapor loss, it provides valuable insights into the integrity of the skin’s
barrier.
Shear Wave Propagation assesses skin viscoelasticity by analyzing the acoustic
waves in the frequency of .-kHz []. Other devices, such as the BCT
for measuring biomechanical properties, the Venustron for soft tissue testing, the
Extensometer for stretch testing, and the BLS Ballistometer for impact testing,
also provide scientific evidence for claims of skin firmness.

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.... Methods for testing skin roughness and anti-wrinkle efficacy
Dry, rough skin with wrinkles is a characteristic of aging. Key parameters for assess-
ing skin roughness include friction, roughness, and smoothness. Anti-wrinkle efficacy
refers to the ability to reduce the appearance of wrinkles or make them less noticeable.
Changes in various physical and chemical indicators, such as the number, length,
volume, area, and depth of wrinkles, are important metrics for assessing skin aging.
Common methods include D imaging analysis, D image analysis, and profilometry.
The use of D skin imaging systems combined with computer image processing is
a standard method for evaluating wrinkle parameters due to its speed, accuracy, and
high resolution. Instruments like the Primos® system and the EvaSKIN and EvaFACE
systems (which focus on localized and full-face assessments, respectively) examine
alterations in skin structure by evaluating isotropy parameters [].
Portable D imaging systems like the C-Cube from Pixience and Antera D from
MIRAVEX enable rapid and precise assessment of skin texture and wrinkles. These
devices utilize computer-assisted surface reconstruction and multidirectional lighting
to enhance user engagement and provide clear image analysis [].
Devices like the VISIA or VISIA-CR facial analysis systems capture images under
standard, UV, or polarized light []. Specialized software like Mirror Photo Tools
and Image-Pro Plus can analyze these images for relevant wrinkle parameters.
Profilometry methods, including laser, optical, and mechanical skin profiling, also
enable quantitative wrinkle analysis. Instruments like the Visioline® VL utilize
these techniques, often requiring silicone replicas of the skin surface for accurate
assessments to assess skin macro-relief parameters [].
The VisioScan ® VC plus system uses a uniform UV light source and a high-resolu-
tion CCD camera to capture images of the skin’s surface. The SELS software analyzes the
grayscale distribution, providing clinically relevant parameters: skin smoothness (SEsm),
roughness (SEr), desquamation level (SEsc), and wrinkle status (SEw). This high-
resolution UV imaging method offers a simple, cost-effective, and accurate approach for
evaluating cosmetic efficacy by directly assessing skin surface morphology and dryness.
.... Methods for testing skin structure
Aging affects the physiological structure of the skin. Device like the Ultrascan
UC utilizes a MHz ultrasound frequency to produce high-resolution images of
skin at depths of –mm, allowing analysis of skin thickness, cross-sectional area,
and aging severity. Similarly, the high-frequency ultrasound probes from DermaLab
Combo® by Cortex and DermaScan C can conduct related tests. Other devices
like the Two-Photon Excitation Microscopy (TPEM) and MPT flex (Multiphoton
Tomography) employ near-infrared femtosecond laser technology for sub-micron
spatial resolution in skin optical biopsy, allowing visualization of dermal collagen and
elastin fibers in vivo and making them suitable for studying skin aging [].
Line-field confocal optical coherence tomography (LC-OCT) is another type
of non-invasive imaging technique that merges the principles of optical coherence
tomography and reflectance confocal microscopy with line-field illumination []. It
produces cell-resolved images of the skin in various orientations, including vertical,
horizontal, and three-dimensional views. Since LC-OCT generates substantial data,
automated deep learning algorithms are highly relevant for aiding image analysis.

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
TheLC-OCT also covers algorithms designed for skin layer segmentation and kerati-
nocyte nuclei segmentation.
. Evaluation of cosmetics products for sensitive skin: Methods and approaches
Sensitive skin has become a significant concern in both dermatology and the
cosmetic industry, with more consumers seeking products that are gentle yet effec-
tive. However, the evaluation of cosmetic products for sensitive skin is a complex
task, as sensitive skin reacts differently to various stimuli compared to normal skin
types. Determining whether a cosmetic product is suitable for sensitive skin requires a
combination of subjective assessments, objective measurements, and clinical testing.
This essay will explore the methods used to evaluate the suitability of cosmetics for
sensitive skin, focusing on product safety, effectiveness, and consumer experience.
.. Overview of sensitive skin
Sensitive skin refers to a skin type that exhibits heightened reactions to environ-
mental factors, skincare products, or internal triggers, such as stress or hormonal
changes. People with sensitive skin often experience symptoms such as redness,
irritation, itching, or burning sensations when exposed to stimuli that do not affect
individuals with normal skin. These reactions are often linked to a compromised skin
barrier, which makes the skin more prone to irritation and allergic reactions.
The evaluation of cosmetic products suitable for sensitive skin is essential for
ensuring both the safety and efficacy of products designed to soothe or avoid trig-
gering sensitive skin reactions. Cosmetic products, including moisturizers, cleansers,
sunscreens, and makeup, need to be evaluated to ensure that they do not exacerbate
skin issues like irritation, dryness, or redness.
... Purpose of evaluation methods
The primary objectives of evaluating cosmetic products for sensitive skin are:
• To ensure product safety: This includes determining that a product does not cause
irritation, allergic reactions, or any other adverse effects on sensitive skin.
• To assess product effectiveness: Evaluating how well the product can soothe or
enhance the condition of sensitive skin, such as improving hydration, reducing
irritation, and strengthening the skin barrier.
Cosmetic products are typically evaluated using both subjective methods (such
as consumer surveys and expert assessments) and objective measurements (such as
skin hydration and barrier function tests). Combining these methods ensures that the
products meet both safety and performance standards.
.. Challenges in evaluating cosmetics for sensitive skin
... Variability in individual skin sensitivity
One of the major challenges in evaluating cosmetics for sensitive skin is the vari-
ability of individual skin responses. Sensitive skin is not a uniform condition, and

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Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation
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different people may react to the same product in different ways. Factors such as age,
genetics, skin type, and lifestyle can all influence how an individual’s skin responds to
a particular cosmetic product. This variability makes it difficult to establish universal
standards for evaluating cosmetic products.
... Subjective nature of consumer experiences
While clinical testing can provide objective data, the subjective experiences of
consumers play a significant role in determining whether a product is truly suitable
for sensitive skin. Many people with sensitive skin rely on their own experiences, such
as sensations of stinging, burning, or itching, to gauge whether a product is suitable
for them. This makes it essential to include consumer feedback and self-reported
assessments in product evaluation.
... Environmental and lifestyle factors
Skin sensitivity can also be influenced by external factors such as temperature,
humidity, pollution, and the use of other skincare products. For instance, harsh
weather conditions or the use of certain makeup products can exacerbate skin sen-
sitivity. Thus, evaluating cosmetics for sensitive skin requires consideration of these
factors to assess how the product interacts with the skin in real-world conditions.
.. Evaluation methods for cosmetics products
... Subjective assessment methods
.... Self-reported questionnaires
Self-reported questionnaires are commonly used to gather insights from con-
sumers about their experiences with cosmetic products. These questionnaires ask
participants to assess the product’s effects on their skin, including any symptoms like
irritation, redness, or discomfort.
To evaluate cosmetics products for sensitive skin, self-reported questionnaires
could be collected pre- and post-cosmetics product usage.
• Examples of questionnaires:
⚬Sensitive Skin Questionnaire (SSQ) [, ]: This tool helps assess the degree of
skin sensitivity based on responses to environmental stimuli and product use.
⚬Dermatological Life Quality Index (DLQI) [, ]: This tool evaluates how skin
conditions (like sensitivity) impact a person’s daily life, focusing on physical
and emotional well-being.
• Benefits: Self-reported questionnaires provide valuable information about how
products perform in real-world conditions and offer insights into consumer
satisfaction.
• Limitations: The subjective nature of self-reporting means results can vary based
on individual perceptions, experiences, and expectations.

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
.... Interviews and consumer feedback
In-depth interviews or focus groups can provide a more detailed understanding
of how consumers perceive a product’s impact on their sensitive skin. These methods
can help identify specific irritants or beneficial effects that might not be captured in
standardized questionnaires.
• Importance: Detailed interviews allow for exploring how specific ingredients
or formulations interact with sensitive skin, providing insights that may not be
immediately apparent through clinical testing.
... Objective assessment methods
.... Patch testing
Patch testing is a well-established method used to determine if a cosmetic product
causes skin irritation or allergic reactions. In this test, small quantities of a product are
applied to patches of skin (usually on the back or inner arm) and left for a specified
time (typically –hours). The area is then observed for signs of redness, swelling,
or blistering [].
• Use in sensitive skin: Patch testing helps identify whether a product triggers irritation
or allergic responses in sensitive skin, such as rashes or eczema-like symptoms.
.... TEWL (transepidermal water loss) measurement
TEWL is a critical measure of skin barrier function and is especially useful in
assessing products designed for sensitive skin. Increased TEWL is indicative of a
compromised barrier, which is common in sensitive skin [, ].
• Procedure: A specialized device, such as a Tewameter®, measures the amount of
water lost through the skin’s surface.
• Use in sensitive skin: Products that help restore barrier integrity and reduce TEWL
are considered beneficial for sensitive skin.
.... Clinical irritation testing
This test involves applying a product to a controlled area of the skin and monitor-
ing it for any signs of irritation, redness, or other adverse effects. Irritation testing
can be conducted in a clinical setting to assess how a product behaves under typical
conditions of sensitive skin [, ].
• Use in sensitive skin: Clinical irritation testing helps determine if a product is too harsh
for sensitive skin or if it provides a soothing effect without causing adverse reactions.
.... Skin hydration and barrier function assessments
In addition to TEWL, skin hydration levels are a key indicator of skin health.
Sensitive skin often exhibits reduced hydration due to a weakened barrier function [].

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Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation
DOI:http://dx.doi.org/10.5772/intechopen.1009010
• Method: Corneometry is often used to measure skin hydration levels. A well-hydrated
skin barrier is essential for reducing irritation and sensitivity. Cosmetics that
improve hydration and strengthen the skin’s barrier are highly beneficial [].
.... Facial stinging test
The facial stinging test [], particularly the lactic acid sting test (LAST), is a
widely used method to evaluate the reactivity of sensitive skin. It specifically mea-
sures subjective sensations of discomfort, such as stinging, burning, or tingling, after
applying a potential irritant to the face. Here’s a detailed look at this test.
..... Procedure
• Participant selection:
⚬Test subjects are typically chosen based on self-reported sensitivity or derma-
tologist assessment.
⚬Subjects often have a history of sensitive skin but no active dermatological
conditions (e.g., eczema, rosacea) during testing.
• Test substance:
⚬Commonly used substances include lactic acid (–), a known irritant for
sensitive skin.
⚬The cosmetic product being tested can also be directly applied.
• Application:
⚬Commonly used substances include lactic acid (–), a known irritant for
sensitive skin.
⚬The cosmetic product being tested can also be directly applied.
• Observation period:
⚬The subject is asked to report any sensations of stinging, burning, or discom-
fort over a set time, typically –minutes.
• Scoring:
⚬Reactions are rated on a subjective scale (e.g., =no stinging, =mild,
=moderate, =severe).
⚬Some protocols also record visible signs of irritation, though the test primarily
focuses on subjective sensations.
.... Forearm tape stripping and capsaicin application test
Forearm Tape Stripping and Capsaicin Application Test (FA-TS-CAT) was developed
as an alternative to traditional facial stinging tests for sensitive skin evaluation [].

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
Itcombines tape stripping (to mimic facial skin sensitivity) and capsaicin application
(to induce irritation), which accurately simulates the natural recovery trend observed
in sensitive skin following product application. This model not only enhances assess-
ment efficiency but also ensures higher safety and adherence of subjects, providing a
practical tool for the development and validation of sensitive skincare products and
treatments.
..... Procedure
. Preparation
• Participant selection :
⚬ Participants with varying degrees of skin sensitivity are chosen, often includ-
ing both sensitive and normal skin types for comparison.
• Site selection :
⚬ The volar forearm is typically used due to its accessibility and relatively
uniform skin properties.
. Tape Stripping (TS)
• Purpose : To partially disrupt the skin barrier by removing layers of the stratum
corneum.
• Process :
⚬ Adhesive tape is repeatedly applied and removed from a specific area of the
forearm.
⚬ The number of strips (usually –) is standardized to achieve controlled
disruption.
⚬ The degree of disruption can be measured using transepidermal water loss
(TEWL).

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Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation
DOI:http://dx.doi.org/10.5772/intechopen.1009010
. Capsaicin Application (CAT)
• Purpose: To test the sensory response of the skin. Capsaicin, the active compo-
nent in chili peppers, stimulates nociceptors (pain-sensitive nerve endings).
• Process:
⚬A small amount of capsaicin solution (e.g., .–.) is applied to the
stripped area.
⚬Capsaicin is left on the skin for a fixed duration, typically a few minutes.
. Observation and scoring
• Sensory response: Participants report sensations such as burning, stinging, or
tingling using a standardized scale (e.g., =no sensation, =unbearable).
• Visual assessment: Redness, swelling, or other visible signs of irritation are
recorded.
. Post-test evaluation
• Recovery monitoring: TEWL or other skin recovery parameters may be measured
over time to assess how quickly the barrier function is restored.
.. Clinical trials and controlled studies with sensitive skin subjects
Clinical trials play a central role in evaluating the safety and effectiveness of cos-
metic products for sensitive skin. These trials typically involve randomized controlled
studies (RCTs) where participants are either given the product or a placebo, and their
skin’s response is carefully monitored over time. The demand for products formulated
specifically for sensitive skin increases, and there is a growing emphasis on scientifi-
cally sound evaluation methods. These methods aim to ensure that cosmetics are not
only effective but also safe for individuals with sensitive skin, who are more prone
to reactions such as irritation, itching, and redness. Evaluating the suitability of
cosmetic products for sensitive skin involves both subjective and objective testing
techniques to assess the product’s safety, performance, and long-term benefits.
.. Technological advances in cosmetics evaluation
With the rapid development of technology, new tools and techniques have
emerged to enhance the evaluation process. These advances enable more accurate and
comprehensive assessments of how cosmetic products interact with sensitive skin,
providing both consumers and manufacturers with valuable insights.
... Role of artificial intelligence (AI) in skin evaluation
Artificial intelligence (AI) has been increasingly integrated into dermatologi-
cal and cosmetic research, offering new ways to analyze skin data and predict how
products will perform on sensitive skin. AI can be applied to various aspects of skin
evaluation:

Cosmetic Industry – Trends, Products and Quality Control

.. Discussion
The evaluation of cosmetics for sensitive skin is a multifaceted process that
requires both subjective and objective testing methods to ensure that products are
safe, effective, and beneficial for individuals with skin sensitivity. With advancements
in technology and clinical testing, the industry is continually improving its ability to
cater to sensitive skin concerns.
As the demand for sensitive skin solutions grows, future developments will
likely include even more personalized skincare options, aided by AI and wearable
technology, to offer real-time assessments of how products interact with individual
skin types. Ensuring safety and efficacy will remain paramount, and as consumer
awareness increases, more sophisticated testing and reporting methods will drive the
development of better products tailored to the needs of sensitive skin.
. Leveraging artificial intelligence for evidence-based cosmetic evaluation:
Safety, efficacy, and mildness
Artificial intelligence (AI) is revolutionizing multiple industries, and the cosmetic
sector is no exception [–]. In the context of evaluating the safety, efficacy, and
mildness of cosmetic products, AI presents an opportunity to enhance and accelerate
traditional evaluation methods. By utilizing AI-driven tools, the cosmetic industry
can better predict risks, analyze large datasets, optimize formulations, and ultimately
deliver products that meet consumer demands for safety, efficacy, and mildness with
greater precision []. In this section, we explore how AI technologies can be inte-
grated into evidence-based cosmetic evaluation systems, providing more accurate and
timely results, reducing reliance on animal testing, and improving overall product
development.
.. AI in safety evaluation: Predicting toxicity and irritation risks
Traditionally, the safety of cosmetic products has been evaluated through in vivo
(animal) and in vitro (cell culture) testing, which can be time-consuming, expensive,
and ethically challenging. AI, particularly machine learning (ML) algorithms, has
the potential to dramatically enhance safety evaluations by predicting toxicity and
irritation risks based on chemical structures, ingredient interactions, and biological
response models [].
... Predictive toxicology
Molecular Modeling and Virtual Screening: One of the primary ways AI contrib-
utes to safety evaluation is through predictive toxicology. Machine learning models
can analyze chemical structures and predict their potential toxicity [, ]. Trained
on extensive datasets such as the Toxicology Data Network (TOXNET) and EPA data-
bases, these AI systems can identify patterns between molecular features and toxico-
logical outcomes. This enables the prediction of how new cosmetic ingredients might
behave in human systems, reducing the need for animal testing. Recent advances in
deep learning (DL) allow for more accurate predictions, even with complex molecular
interactions [, ]. These models can also help identify previously overlooked
toxicological concerns, ensuring products meet safety standards without unnecessary
experimentation.

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In Silico Models for Dermal Absorption: Another promising application is
the prediction of dermal absorption and skin irritation. AI models simulate how
cosmetic ingredients penetrate the skin barrier and predict potential irritation or
allergic reactions. This process, enhanced by datasets from in vitro tests and clinical
studies, could significantly reduce human and animal testing. AI-powered simula-
tions help create more realistic models of skin responses, leading to more accurate
safety evaluations [].
... Risk assessment models
Quantitative Structure-Activity Relationship (QSAR) Models: AI-powered QSAR
models evaluate ingredient toxicity by correlating chemical structure with biological
activity. These models use databases of known substances to predict hazards for novel
ingredients by comparing their chemical structures with those of known toxic or non-
toxic compounds. The growing use of AI in QSAR models helps cosmetic companies
avoid harmful substances and enhance the safety of new formulations [, , ].
Adverse Outcome Pathways (AOP): AI can also be employed to map adverse
outcome pathways (AOPs), which describe the sequence of biological events from
chemical exposure to adverse health effects []. AI tools aggregate data from various
sources to build comprehensive AOP networks, improving understanding of how
specific ingredients might cause skin damage, allergic reactions, or systemic toxicity.
This approach is increasingly important for refining ingredient safety assessments,
ensuring that cosmetic formulations are both effective and safe.
.. AI in efficacy evaluation: Enhancing clinical trials and consumer insights
While safety is a critical concern, the efficacy of cosmetic products is equally
important. AI can streamline and enhance efficacy evaluation by improving clinical
trial design, analyzing consumer feedback, and simulating real-world usage scenarios
to predict product performance [, –].
... Optimizing clinical trials and operations
Predicting Efficacy in Different Skin Types: AI can help predict how individuals
with varying skin types or conditions (e.g., dry skin, acne-prone skin) will respond to
cosmetic products []. By analyzing data from previous clinical trials, dermatologi-
cal studies, and skin physiology databases, AI can segment consumers into more accu-
rate subgroups. This targeted approach ensures that clinical trials are more reflective
of real-world usage, improving the relevance and efficiency of product evaluations
[, ].
Simulating Long-Term Efficacy: Long-term efficacy testing, particularly for
products targeting aging, skin elasticity, or hydration, often requires extensive trials.
AI models can simulate the long-term effects of cosmetic products, predicting their
impact over months or years without the need for prolonged human trials. This
significantly reduces the cost and time associated with clinical testing, accelerating
product development while ensuring reliability in efficacy predictions [, ].
Minimal Clinical Trials and Precise Operation: Over the past decade, esthetic
dermatology has seen major innovations to treat various skin issues, such as acne
scars, pigmentation, skin aging, and blood vessel problems. However, many esthetic
treatments still carry risks, especially for patients with different skin types or complex

Cosmetic Industry – Trends, Products and Quality Control

sensitive skin conditions. The advent of AI presents a promising solution, offering
greater precision, safety, and personalized care for these treatments [, ].
... Consumer data analysis
AI tools can analyze vast amounts of consumer feedback from social media,
product reviews, and forums. Natural language processing (NLP) algorithms can
mine text data to identify common sentiments, concerns, and benefits reported by
users []. For example, if a product claims to reduce wrinkles, AI can analyze cus-
tomer reviews to determine if users are noticing positive changes and assess product
performance across diverse consumer groups. This real-time feedback loop supple-
ments clinical trial data and provides manufacturers with insights into how products
perform in varied demographics [, ].
Predicting Product Effectiveness Based on Ingredient Interaction: Machine
learning can help identify which ingredient combinations are most likely to produce
effective results []. By training models on large datasets of active ingredients,
formulations, and clinical outcomes, AI can predict which combinations will deliver
the best anti-aging, moisturizing, or acne-fighting effects. This reduces the number of
formulations that need to be tested in clinical trials, speeding up the product develop-
ment process.
.. AI in mildness evaluation: Ensuring skin compatibility and sensitivity
Cosmetic mildness is crucial for ensuring consumer safety and satisfaction,
particularly for individuals with sensitive skin or conditions like eczema []. AI can
support mildness evaluation by predicting skin irritation, optimizing formulations
for sensitive skin, and developing non-irritating ingredients [, ].
... Skin irritation and sensitization prediction
Dermal Irritation Models: AI-driven models can predict whether a product will
cause skin irritation by analyzing chemical properties of ingredients such as pH,
molecular size, and polarity. These models use data from patch tests, human clinical
trials, and historical irritation data to forecast a product’s likelihood of causing irrita-
tion. By integrating these models into the product development process, AI can help
manufacturers design gentler products for sensitive skin [, , ].
Skin Sensitization Prediction: AI can predict whether a product will cause allergic
reactions or sensitization. Sensitization models trained on large datasets of chemical
exposure and allergic responses identify substances that may trigger allergic contact
dermatitis (ACD). By avoiding allergens and formulating with skin-sensitive ingredients,
AI helps manufacturers create safer products for individuals with delicate skin [].
... Personalized mildness assessments
Customized Skin Care Recommendations: AI-powered platforms can assist
consumers in identifying products that are best suited to their individual skin types
and sensitivities. By analyzing inputs such as skin type, existing conditions (e.g.,
acne, rosacea), and ingredient preferences, AI algorithms can recommend products
that align with individual needs. These personalized recommendations ensure that
consumers use products that are both effective and gentle [].


Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation
DOI:http://dx.doi.org/10.5772/intechopen.1009010
Real-Time Skin Sensitivity Monitoring: Emerging AI-driven wearable technolo-
gies can track changes in skin sensitivity in real-time. Wearable devices with sensors
monitor parameters like skin temperature, hydration levels, and pH. The data are
sent to AI-powered platforms that assess how well a product is performing, providing
real-time feedback on skin sensitivity and product effectiveness [].
.. Challenges and future directions in AI for cosmetic evaluation
While AI holds great promise for transforming cosmetic evaluation, several
challenges remain. Data quality and standardization are critical, as machine learn-
ing models are only as good as the data they are trained on. Additionally, ethical
concerns regarding data privacy, especially in consumer-driven applications, must
be addressed. Moreover, the regulatory landscape for AI in cosmetic evaluation is
still evolving, with guidelines for AI-driven tools in this industry under development
[, , , ]. Looking ahead, advances in deep learning, natural language process-
ing, and computer vision could revolutionize cosmetic evaluation even further. AI
technologies may one day enable fully autonomous testing, from formulation design
to real-time performance monitoring. This would drive innovation in the cosmetic
industry while enhancing consumer safety and satisfaction [].
... Summary
The integration of AI in cosmetic evaluation is transforming how products are
assessed for safety, efficacy, and mildness. By leveraging predictive models, enhanc-
ing clinical trial designs, and improving consumer insights, AI promises a more
efficient, effective, and consumer-centered approach to cosmetic development.
However, addressing challenges such as data quality and privacy, as well as navigating
the evolving regulatory framework, will be key to fully realizing AI’s potential in the
cosmetic industry. As AI technologies continue to evolve, they will not only enhance
product safety and effectiveness but also ensure that products are designed with
consumers’ individual needs and sensitivities in mind.
. Conclusion
In the current booming cosmetics industry, the establishment of an evidence-
based system for evaluating the safety and efficacy of cosmetics is of crucial impor-
tance. The cosmetic safety evaluation system constructed in the article encompasses
multiple aspects such as raw materials, formulations, production processes, and
products. Starting from the fundamentals like physical and chemical properties and
toxicological characteristics, it employs methods such as laboratory testing, clinical
trials, and risk assessment to ensure safety. Its risk assessment includes steps such as
hazard identification, dose-response relationship assessment, exposure assessment,
and risk characterization, ensuring accurate control of potential risks. The cosmetic
efficacy evaluation system is developed for different functions. In terms of skin
anti-aging, it deeply analyzes the internal and external mechanisms of skin aging and
various visible signs and uses methods such as in vitro cell experiments and human
efficacy evaluation to measure the anti-aging effects of products. For cosmetics for
sensitive skin, it fully considers the differences in individual skin sensitivity, consum-
ers’ subjective experiences, and the influences of environmental and lifestyle factors.

Cosmetic Industry – Trends, Products and Quality Control

Author details
LiYe,*, JianhuaZhang,, TianChen, DongcuiLi and PengShu
 Dermatology Hospital, Southern Medical University, Guangzhou,Guangdong,
China
 Southern Medical University (NMPA Key Laboratory for Safety Evaluation of
Cosmetics), Guangzhou,Guangdong, China
 N.O.D Topia (GuangZhou) Biotechnology Co., Ltd., Guangzhou,Guangdong, China
 Simpcare (GuangZhou) Biotechnology Co., Ltd., Guangzhou,Guangdong, China
 Department of Environmental Health, Shanghai Municipal Center for Disease
Control and Prevention, Shanghai, China
 Hua An Tang Biotech Group Co., Ltd., Guangzhou,Guangdong, China
 HBN Research Institute and Biological Laboratory, Shenzhen Hujia Technology Co.,
Ltd., Shenzhen, China
*Address all correspondence to: dlpfbyy@.com
It comprehensively conducts evaluations through subjective assessments (such as
questionnaires and interviews) and objective measurements (such as patch testing
and transepidermal water loss [TEWL] measurement) and ensures the safety and
effectiveness of products with the help of clinical trials. Looking ahead, with the
continuous innovation of technology, cutting-edge technologies such as organoids,
organ-on-a-chip, and artificial intelligence will be deeply integrated. These technolo-
gies are expected to further enhance the accuracy and scientific nature of the evalua-
tion; overcome challenges such as the safety of new raw materials, the application of
nanotechnology, and the safety of personalized cosmetics; and optimize the evalua-
tion process. It will meet consumers’ increasingly diverse and personalized needs and
vigorously promote the cosmetics industry to move toward a higher-quality, safer,
and more reliable development stage. While safeguarding consumers’ rights and
interests, it will also promote the prosperity and innovation of the industry.
©  The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of
the Creative Commons Attribution License (http://creativecommons.org/licenses/by/.),
which permits unrestricted use, distribution, and reproduction in any medium, provided
the original work is properly cited.

Establishing an Evidence-Based System for Cosmetic Safety and Efficacy Evaluation
DOI:http://dx.doi.org/10.5772/intechopen.1009010

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