(180d) An Integrated Methodology for Chemical Product Design: Application to Hair-and Skin-Care Emulsions

Authors: 
Orjuela, A., Universidad Nacional de Colombia
Arrieta-Escobar, J., University of Lorraine
Bernardo, F. P., University of Coimbra
Camargo, M., University of Lorraine
Morel, L., University of Lorraine
Due to the large number of ingredients commercially available for the formulation of consumer products, and because their multi-functionality, emulsified cosmetic product design is a challenging task. The traditional design approach often relies on costly and time consuming trial-and-error experimental procedures. In recent years, systematic approaches to reduce time and resources using computer-aided mixture/blend design (CAMbD) have been proposed [1-2]. Based on predictive models for product properties and mixed-integer optimization, these design methodologies are able to explore a large domain of possibilities. They are however of limited applicability to few formulated products due to the lack of reliable models for properties prediction or for synergic effects.

In particular industrial sectors such as the cosmetics one, there is a considerable amount of heuristic knowledge, namely regarding qualitative function of ingredients, their incompatibilities and positive synergies, as well as their impact on sensorial attributes, which is a critical aspect for product acceptance [3]. This heuristic knowledge has been recently incorporated into a systematic CAMbD methodology [4] using mixed-integer optimization with logical constraints [5] and in this work is further developed for cosmetic emulsions. The method considers a list of available ingredients classified according to their main function (e.g., emollients, emulsifiers, rheology modifiers). Then, heuristics regarding ingredients’ selection, their concentrations in final product, and the manufacturing procedures are formulated as logical conditions, and further translated into algebraic constraints. These constraints, together with other known restrictions (technical, toxicological and/or legal, etc.), define a reduced design space. The search in this space is guided by property models relating product composition to key physicochemical properties or sensorial attributes. The multi-objective function is composed of a weighted sum of Taguchi functions with a target value for each cost/performance requirement (e.g. softness, greasiness and thickness of the product, etc.), which could be adapted by the designer. Through integer cuts, the entire set of feasible solutions within the reduced design space or a subset of interest may be generated.

To illustrate the proposed methodology, two case studies of a rinse-off conditioner and a body lotion are presented. From an initial list of 24 emollients, 4 rheology modifiers and 8 emulsifiers, a set of alternative formulations and respective manufacturing procedures is listed. The first 5% of these resu-lting alternative formulations were produced and then analyzed using instrumental and sensorial methods. The predicted values of the performance were similar for most of the formulations, confirming the potential of this methodology to model emulsified products.

REFERENCES

[1] L. E. K. Achenie, R. Gani, V. Venkatasubramanian, Eds., Computer Aided Molecular Design: Theory and Practice. Amsterdam: Elsevier, 2002.

[2] M. Mattei, G. M. Kontogeorgis, R. Gani, «A Systematic Methodology for Design of Emulsion Based Chemical Products», In: Karimi IA, Srinivasan R, eds., Computer-Aided Chemical Engineering, vol 31. Amsterdam: Elsevier, 2012, pp. 220-224.

[3] A. M. Pensé-Lhéritier, «Recent developments in the sensorial assessment of cosmetic products: A review», Int. J. Cosmet. Sci., 2015, vol. 37, pp. 465-473.

[4] J. Arrieta-Escobar, F. Bernardo, A. Orjuela, M. Camargo, L. Morel, « An Integrated Methodology for Emulsified Cosmetic Product Formulation Using Integer Programming with Logical Constraints», (Provisionally accepted paper for ESCAPE 27)

[5] H. P. Williams, Model building in mathematical programming, 5th ed. John Wiley & Sons, 2013.