Scenario Modeling for Personal Care Products

Many personal care products aspire to deliver both immediate results as well as prolonged effects over time.  Yet, when addressing conditions like body odor, greasy hair, or oily skin, the nature of human biology brings unique challenges to the product development process.  While modeling tools are commonly used to help develop a wide range of products, these tools can be viewed as too complicated or impractical to apply to the dynamic physiological processes and variability that are central to personal care products.  In the absence of models, comparing the merits of new ideas can be difficult, a complexity that leads to time consuming and costly physical tests as the default method for validating new technologies.

But simplified models can be practical and useful for personal care product development.  Leveraging existing scientific knowledge, along with a disciplined focus on the parameters that drive consumer value are central to a pragmatic approach to modeling.  In the context of dynamic physiological processes, three imperatives are vital to effective modeling:

Isolate Parameters of Valuedo not try to model everything; stay focused on the parameters that are most important to consumer satisfaction and product purchase.  To ensure that models are informative and practical to use, it is essential to focus on main parameters of value (MPVs).  MPV’s can then be translated to the underlying physical phenomena that drive performance and factored into predictive models.  The concept is straightforward: only model what is most important.

Simulate the Biological Systembuild algorithms that simulate how physiological processes evolve in time while accounting for inherent product characteristics.  By characterizing the behavior of the underlying process (typically as a function of time), models can establish a baseline for measuring performance under different scenarios.  Then, as new technologies or compounds are introduced to the model, it is possible to anticipate the impact at the time of application, as well as measure the duration and profile of impact over time.

Run Relevant Scenariosuse the model to run simulations against different delivery systems, formulations, methods of use, and target area conditions.  With a baseline algorithm in place (Imperative #2), the model must also account for the variety of factors external to the target substance that impact product performance.  These factors typically can include the delivery system, consumer use practices, elements of the surrounding environment (the supersystem), and the variability of important target system parameters (e.g., hair density, hair follicle thickness).

After constructing and pressure testing the model, any number of scenarios – combinations of formulations and delivery systems under varying conditions – can be assessed.  The model can be used as a preliminary screen to test concepts and combinations of ideas quickly.  Ruling out ideas that may have minimal or adverse impact on product performance will reduce the time and cost of proof of principle testing.

With a simplified model, innovation teams can:

  • Screen different compounds to anticipate product performance under varying conditions
  • Measure the relative impact of different types of solutions prior to physical testing
  • Isolate variables that will require physical test validation
  • Set priorities for product development roadmaps.

Even though personal care products often target complex and dynamic biological systems, models do not have to be overly complex to yield powerful insights and time saving results.  Effective modeling can yield insights into product performance potential at the point of action and over time.  Running candidate solutions under different model scenarios can bring greater focus to proof-of-concept testing and reduce product development cycle times.

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