TRENDING TECHNOLOGIES
59
Development of active ingredients in the digital era
Quoc-Tuan Do and Philippe Bernard - Greenpharma
Consumer demand for sustainable and safe cosmetic products are growing year after year while products have to comply with an often very restrictive list of raw materials (e.g. EICIC), natural, organic, active, safe and cost-effective. Active ingredient producers, formulators and brand owners have to cope with these within a cosmetic market where trends can change very quickly. Meanwhile, data, information and
knowledge about natural sources/substances and skin biology have grown exponentially along with technical platforms to handle them: big data, chemoinformatics, machine learning and AI. Taken together, the market needs and the
availability of the technology, digital platforms offer a lot of opportunities in accelerating the development of new active ingredients at different levels: by analyzing the trends from the customers’ behaviour with AI tools,1
the
molecular contents in extracts (phytochemical profiling2
applications of extracts or molecules (biological profiling3
) or by predicting/identifying the ) and potential safety issues.4
Hereafter, we will focus on two profiling
methods to support the development of new actives.
Classical approach In general, the molecular content of extracts is poorly known and generally consists in the composition of grand families of phytochemical e.g. flavonoids, carbohydrates, proteins etc. Only some major compounds will be characterized. In this context, the development of an active
ingredient consists in trials and errors guided by bibliographic information that can be from
traditional use of plants or existing biological data. Safety issues may also be established by prior research. In vitro assays used for screening are rather simple; for instance, to identify antioxidant, anti-ageing (collagen, elastin) effects, pigmentation modulators, slimming and so on. If an interesting effect is detected, then
other more sophisticated studies may be performed on ex-vivo models and ultimately on clinical trials. Safety issues can raise during the development due to the presence of toxic molecules, thus jeopardizing the project. It will be a tremendous effort to workaround the problem without knowing the molecular
content and to find an optimal extraction method to discard the toxic compounds but keeping the interesting biological activities.
In silico approach - phytochemical profiling With the availability of data on natural substances, it is possible to build phytochemical database to organize heterogeneous information such as molecule names, structures, plants or other organisms that produce them, traditional uses of the plants and biological activities, in a same interface to facilitate access and cross link information to get new knowledge. Data mining with such database can help to derive new applications for known natural substances.5 The molecule data from such database can also support the analysis of extracts by using mass data. Recently, we developed a prediction tool named GAINS to perform phytochemical profiling. The goal of GAINS is to offer a global insight on molecules that can be contained in an extract. It is based on experimental data
Figure 1: Example of chromatogram (green line) overlaid with MS data 0
5 10 Time (min) 15 20
www.personalcaremagazine.com 25
acquired by UHPLC (ultra-high performance liquid-chromatography) and LC/MS/ MS (liquid chromatography with tandem mass spectrometry), data mining and MS fragmentation prediction. UHPLC allows to separate molecules
June 2023 PERSONAL CARE
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