“Perhaps some day the precision of the data will be brought so far that the mathematician will be able to calculate at his desk the outcome of any chemical combination, in the same way as he calculates the motions of celestial bodies.” —Antoine-Laurent Lavoisier
A successful product involves many factors, but none is more important than the formulation itself. However well a product may be marketed, it is the stuff in the bottle that earns consumer loyalty, and the chemical toolbox has a constantly expanding range of new raw materials. A formula has numerous ingredients and can be varied in thousands of ways—how can the best one be found? An even greater challenge arises when ingredients interact or change with circumstances.
The old way to formulate involved a chemist at a bench making multiple trials. Large companies have an army of R&D staff generating new products. Ideally, there are some general guidelines of how much of each material to use or the ratios of some materials—say the ratio of the anionics to the alkanolamide in a shampoo—but, still, a lot of trial and error is involved in getting just the right properties.
Experiments create data, and fortunately when data is graphed, patterns can emerge. In a shampoo formulation, the salt curve is an obvious example. In many systems, adding salt first makes the viscosity go up, but too much causes a precipitous decline. Aiming a bit to the left of the peak point gives maximum viscosity, with a little wiggle room if too much salt is added. A simple correlation of viscosity to salt content is a powerful formulation tool.
The situation gets more challenging when new materials are involved or the ingredients can interact. If order of addition is critical, suddenly the number of possibilities jumps exponentially. The poor chemist might wish for a robot to generate every possibility and present the optimum blend. That robot has arrived.
“Combinatorial chemistry” is the fancy term for flinging multiple experiments against a wall and seeing what sticks. The history of combinatorial chemistry goes back to the work of Bruce Merrifield of Rockefeller University in the 1960s, which led to his Nobel Prize in Chemistry in 1984. Early work centered on peptide synthesis. By the 1990s, it became a primary method for drug discovery. The principles are now being applied to the complex interactions of some types of personal care formulations.
The perfume industry has used robots for years, both on a lab scale and in production. The nature of fragrances involves mixing hundreds of chemicals for each formula, and using a different formula for every customer and application, so a lot of repetitive work is involved. However, the robotics never became central to the fragrance creation process, just an extra pair of hands.
Major fragrance houses do use combinatorial chemistry to create new aroma molecules, making thousands of experiments to locate a handful of useful products. This is similar to the use of combinatorial chemistry in drug discovery. Lack of a precise structure-odor relationship limits the possibilities for the rational design of fragrance molecules, so trial and error can be the only feasible approach.
Applying the Tools
With robots making samples and the concepts of combinatorial chemistry and high-throughput screening, all that remains to be done is to apply the tools to complex cosmetic formulation issues. The Institute for Formulation Science is at the heart of just such an activity.
Robots exist that can make 2,000 formulas a day—a Beckman-Coulter Liquid Handler, for example, is capable of 350 an hour. They aren’t soup to nuts finished formulas but simple mixes that show critical interactions. The robot can make thousands of iterations, but surely a human must evaluate them. Not so—many observations, too, can be automated. A spectrophotometer can measure concentrations, and a crossed polarizer reveals liquid crystal structures. Adhesion (tackiness) can be measured with a flexible lens test.
Robert Lochhead1, 2, 3 is a pioneer in applying combinatorial chemistry to personal care applications. He has used the interaction of a cationic polymer with an anionic surfactant as an example in his publications. And this combination is critical for the modern conditioning shampoo.
The basic science was unraveled by E. Desmond Goddard4 in seminal papers published in the early 1990s. It is complicated unless one is a polymer chemist, but the basic idea is that the interaction of a polymer with a surfactant changes with conditions, such as the amount of solvent present. It is possible for the polymer and surfactant to live happily together for a while but separate upon dilution.
The separation of phases allows the polymer to deposit on the hair, rather than wash off with the surfactant. Since the interactions are complex, a robot generating hundreds of experiments, tools to analyze the results and a computer to turn it into a pretty picture showing the results is a formulator’s dream.
The triangular phase diagram shows regions where coacervates are absent and others with a maximum concentration of phase-separated coacervate. The diagrams are different for every polymer. Surfactant composition and electrolyte concentration are some other key variables.
It is formidable technology, yet it is, in essence, but an extension of a salt curve. Data is gathered, plotted and informed decisions made. It takes the rather haphazard way much cosmetic formulation is done and places it in a formal platform, allowing vastly increased data entry and information processing.
At the beginning of a study, informed humans are required to establish the test criteria. When the robots, analyzing devices and computers are done, there is still room for human intervention. The results must be confirmed in a lab under the usual formulation conditions. The data usually involves specific components of the formulation, not the complete product, so conventional methods are employed to achieve the final formulation. So at the end, people are still needed, but they have wonderful new tools that allow the creation of technically advanced products.
- RY Lochhead, LR Huisinga, T Waller, A Brief Review of Polymer/Surfactant Interaction, Cosm & Toil, Feb (2004)
- RY Lochhead, LR Huisinga, T Waller, Deposition from Conditioning Shampoo: Optimizing Coacervate Formulation, Cosm & Toil, March (2006)
- RY Lochhead, LR Huisinga, Revolutionary Trends in the Advancement and Integration of Cosmetic Science: Combinatorial Formulation,” IFSCC Magazine, 10 3 July/Sept (2007)
- ED Goddard, KP Ananthapadmanaban, Interactions of Surfactants with Polymer and Proteins, CRC Press, 1993
Steve Herman is president of Diffusion LLC, a consulting company specializing in regulatory issues, intellectual property, and technology development and transfer. He is a principal in PJS Partners, offering formulation, marketing and technology solutions for the personal care and fragrance industry. He is an adjunct professor in the Fairleigh Dickinson University Masters in Cosmetic Science program and is a Fellow in the Society of Cosmetic Chemists.