Consumer health products are developed or formulated based on marketing trends, trending “hero” ingredients, supplier stock formulations, and/or formulation expert subjectivity, and sometimes research. While these ways have historically made some market viable products which we all use and like, there isn’t a methodology or framework that can be used every time to make formulation decisions, that yield utmost effectiveness in terms of functionality, keeping in mind safety and delivery format constraints for the intended population.
In this blog, I introduce Evidence-First Functional Formulation Design, a decision science framework that can be followed to produce topical and ingestible consumer health product formulations in skincare, personal care, supplements, and nutritional food & beverage categories. This framework is repeatable, scalable, and traceable, which helps with its applicability in a real-world setting and can be facilitated using AI tools. The idea behind the framework is derived from how decision systems are designed, or data science solutions are built in the tech world, starting with a problem statement, objectives, constraints, and following up with scalability.
The following are the various steps involved in the framework, with an illustrative example to better understand how to apply the framework.
Step 1: Problem and Intended Population Definition
A clear problem statement and the population to which the problem is applicable are identified in this step. The clearer and the narrower the problem definition is, the more focused the final formulation is going to be. The problem definition can be derived from one’s own skin, personal care, or health-related issues, or generally observed health and wellness-related problems.
Illustrative Example: Postpartum mothers experiencing persistent low milk supply. The intended population here becomes Lactating women.
Step 2: Hypothesis Level Cause Identification
The problem now is tied to various reasons that can be contributing factors to the cause. Such factors can be identified through published research, clinical studies, and discussions on medical forums and websites. AI tools can be used here to consolidate the list of causes. It’s important to note that here, we are not indicating that the exact causes for the problem have been identified, but we’re merely stating all the factors that could be contributing to the problem that was defined.
Illustrative Example: Persistent low milk supply in lactating women is linked to the following through AI-assisted research.
- Low circulating prolactin
- Dehydration
Step 3: Functional Requirements
Each hypothesized cause is turned into relevant functional requirements for the formulation. This is done by identifying the biological and physiological processes that are commonly associated with the cause in scientific literature. Human judgment in terms of the relevance of the identified processes shouldn’t be skipped in this step. Supporting the identified processes would give us the functional requirements needed in this step. At the end of this step, we have identified processes associated with each plausible cause and functional requirements for the same.
Illustrative Example:
Hypothesized Cause 1: Low circulating prolactin
Associated Processes:
- Stress-mediated suppression of prolactin release
- Limited functional mammary tissue capacity
Functional Requirements:
1. Reduce physiological stress that interferes with prolactin signaling 2. Support mammary tissue development and function
Hypothesized Cause 2: Dehydration
Associated Processes:
- Inadequate fluid intake relative to milk production demand
- Loss of electrolytes affecting fluid absorption and retention
Functional Requirements:
- Replenish fluids through increased water intake
- Support hydration efficiency through electrolyte balance
Step 4: Evidence Discovery and Component Identification
For each functional requirement, components or ingredients are identified based on evidence found in clinical studies and scientific literature. Sometimes ingredient classes are identified instead of broken-down individual ingredients, in which case, ingredient classes can be further investigated to get individual ingredients.
Illustrative Example:
- Identified ingredients to reduce physiological stress that interferes with prolactin signaling: Ashwagandha, L-theanine, Magnesium, Yohimbe, Licorice root 2. Identified ingredients to support mammary tissue development and function: Goat’s rue, Moringa, Shatavari
- Identified ingredients to replenish fluids through increased water intake: Water 4. Identified ingredients to support hydration efficiency through electrolyte balance: Sodium, Potassium, Magnesium, Licorice root
Step 5: Ingredient filtering based on interaction, feasibility, and redundancy
If two ingredients interact negatively with each other or counteract each other, the ingredient with less strength in evidence can be eliminated. If two ingredients have the exact same functionality, which is unlikely, then one of them with less strength in evidence can be filtered out. If any of the ingredients are only studied at infeasible dosages that cannot be physically incorporated into a health product, then the ingredient can be filtered out. At the end of this step, a short list of ingredients to support all the functional requirements is obtained.
Illustrative Example:
Licorice root can promote potassium loss, undermining electrolyte balance, which is why it is removed from the list of ingredients in the formulation.
Step 6: Ingredient Dosage Determination:
Dosage for each requirement is assigned based on the dosage at which associated clinical studies show support for relevant functional requirements. If multiple dosage ranges are identified, the highest dosage is picked for maximum functional efficiency at this step and may be adjusted at later steps.
Illustrative Example:
Formulation after dosage determination
| Ingredient | Daily Dosage (example value) |
| Ashwagandha (root extract) | 300 mg |
| L-theanine | 200 mg |
| Magnesium (elemental) | 150 mg |
| Yohimbe (yohimbine-containing bark extract) | 10 mg |
| Licorice root (standardized extract) | 150 mg |
| Goat’s rue | 500 mg |
| Moringa (leaf) | 750 mg |
| Shatavari (root extract) | 500 mg |
| Sodium | 300 mg |
| Potassium | 200 mg |
Step 7 Safety Constraints Application:
Each ingredient at its identified dosage is analyzed for its safety for the intended population. If an ingredient is marked unsafe entirely or unsafe at a concentration, it is either eliminated out of the formulation, or its dosage is reduced to a level where it’s safe to be included.
Illustrative Example:
Although Yohimbe is identified as one of the ingredients to satisfy a functional requirement, it is unsafe to be used by postpartum women, which is why it is filtered out of the formulation list of ingredients.
Step 8: Delivery Format Constraints Application:
New ingredients are introduced to accommodate the necessary delivery format, such as powdered forms, tablets, capsules, and topicals. These ingredients are often introduced to balance pH, to stabilize the formulation, to act as binding agents etc., If a delivery format needs minor adjustments in the dosages of the ingredients, they can be made at this step. Again, AI tools can help with assisting the changes needed at this step.
Illustrative Example:
Formulation after delivery format ingredients addition
| Ingredient | Daily Dosage (example value) |
| Ashwagandha (root extract) | 300 mg |
| L-theanine | 200 mg |
| Magnesium (elemental) | 150 mg |
| Goat’s rue | 500 mg |
| Moringa (leaf) | 750 mg |
| Shatavari (root extract) | 500 mg |
| Sodium | 300 mg |
| Potassium | 200 mg |
| Dextrose (glucose) | 2,000 mg |
| Citric acid | 500 mg |
| Natural flavor (e.g., lemon) | 200 mg |
Step 9 Expert Review, Iteration, and Testing:
Once the final formulation is developed through various steps in the framework, it can be reviewed by an expert like a formulation specialist or a chemist, to make sure the formulation works exactly as is, in practice. Small pilot batches can be developed to test the stability, texture, and usability of the formulation. In some cases, mild adjustments to the dosages will have to be made to enhance the formulation.
Illustrative Example: Through pilot testing, the pH of the formulation slightly drifts over time, which needs to be adjusted with the addition of citric acid into the formulation. This doesn’t affect the functionality of the safety limits of the intended formulation.
PRACTICAL LIMITATIONS AND CONCLUSION:
In areas where the evidence, data, and scientific literature is sparse, some steps may not yield definitive results, which may need additional ways to gather components, plausible causes, and dosages for the formulation. The goal of the framework is not to replace expert judgement, but to greatly reduce the reliance on experts to come up with feasible functional formulations in consumer health formulation-based products.
This framework can be used by product teams, operational teams, founders, and executives to make product decisions without having expertise or deep domain knowledge. Formulations that are highly functional (backed by evidence), and safe can be rapidly developed using the mentioned methodology, enabling trust in the products.
Author: Apoorva Modali