FDA: Advancing Dermal PBPK Models for Bioequivalence Assessment of Dermatological Drug Products Across Skin Disease States (U01)

Utilizing PBPK modeling for complex drug products that are applied on the skin to treat a disease condition locally, and/or after reaching the systemic circulation, is an approach that has gained attention in the recent years. Leveraging information on skin physiology and incorporating compound- and formulation-specific characteristics could lead to the development of dermal PBPK models intended to predict drug amounts in different skin layers. Importantly, the mechanistic nature of dermal PBPK models enable clinical pharmacologists to identify model parameters related to skin physiology, drug substance properties and formulation critical quality attributes that may impact the local or systemic bioavailability of the drug and assess their clinical relevance. This is critical for generic drug development since generic drugs have the same indication as the innovator drug products, but differ in their formulation. Ideally, a well-qualified dermal PBPK model may be leveraged to simulate virtual bioequivalence trials to assess bioequivalence between the generic drug product and its innovator (reference) drug product.

Topical dermatological products act locally, and local tissue concentrations at the site of action is a critical component in determine bioequivalence for such products. However, such data is not readily available or even measured for most products. Additionally, topical administration typically does not lead to quantifiable drug concentrations in the systemic circulation, rendering bioequivalence evaluation a challenging process for these complex dosage forms. Transdermal delivery systems also face challenges in their development process since their absorption into the systemic circulation is mediated via a complex organ, the skin. Drug exposure in the systemic circulation as well as any other tissue included in the model structure can be predicted and studied further using dermal PBPK modeling, thereby providing an innovative approach in evaluating bioequivalence and in addressing related issues for these complex dermatological and transdermal drug products.

Additionally, PBPK modeling allows the integration of in vitro data into the model to generate in vitro-in vivo correlations (IVIVCs) for drug products for which in vitro permeation data and pharmacokinetic data are available. There correlations can be leveraged to predict in vivo performance of formulations with similar drug delivery technology for which only in vitro data is available. For these reasons, dermal PBPK modeling is an extremely useful tool in the drug development process, in the interaction with regulatory agencies, and in decision making in the clinical setting.

Finally, dermal PBPK modeling can be utilized to extrapolate the predicted pharmacokinetic profile of a drug product dosed on healthy skin to a desired subpopulation whose skin may be diseased or otherwise different. To be able to do that, the developed dermal PBPK model will need to describe experimental observations in healthy skin reasonably well. Also, it is essential that the diseased skin physiology and healthy skin physiology at different body locations is well captured in the model. Under certain scenarios, knowledge on skin physiology parameters in special subpopulations such as pediatrics, elderly, and individuals of different race and gender can improve model predictability as well.

Objectives:

The main objective of the current funding opportunity is to identify skin physiology characteristics that differ between healthy and skin diseased subjects and incorporate them into dermal PBPK models to improve model predictability. Ultimately, the developed dermal PBPK models can be applied to conduct virtual bioequivalence assessments between brand name and generic dermatological drug products in patients and other special populations where in vivo bioequivalence studies with pharmacokinetic endpoints are not feasible.

Detailed description:

A proposed approach aiming at meeting the objectives outlined above is detailed below.

1. Identify key skin physiology characteristics that appear to be different between healthy and skin disease populations. Disease states that might be of consideration are: psoriasis, acne, athlete’s foot, ringworm, and “jock itch”, atopic dermatitis/eczema, rosacea, actinic keratosis, leprosy, dandruff, dermatitis herpetiformi, tinea pedis, tinea cruris, and tinea corporis.

Additional skin disease states might be identified in collaboration with the FDA research team to address regulatory needs.

Additionally, information on skin thickness, microstructure, hydration level, temperature, pH, presence of glands and hair follicles at different body locations for disease skin is considered valuable in model building for dermal PBPK models.

2. Retrieve information on skin physiology characteristics from several independent and accredited literature sources (e.g., peer review articles textbooks), utilize in house data if available or design and conduct studies that would allow the generation of the necessary experimental data in special populations of interest. Organize the retrieved information in an easily accessible database.

3. Develop dermal PBPK models for topical dermatological dosage forms and transdermal delivery systems that incorporate the previously collected skin physiology information.

The dermatological drug products that will be selected for dermal PBPK model development could cover a wide variety of active pharmaceutical ingredients (APIs) in terms of its physicochemical properties and permeability. Physicochemical properties of an API impact formulation stability, API release from the formulation when applied on the skin and partitioning through the different skin layers while being absorbed. Therefore, this research project could benefit from modeling APIs of distinctly different solubility, pKa and permeability (logP) profiles. Although not a requirement for the selection process of API to be studied, a Biopharmaceutics Drug Classification-like approach (Pharm. Res. 1995 Mar;12(3):413-20) in selecting API candidates for dermal PBPK model development will be welcomed. The Office of Generic Drugs recognizes the critical role of the formulation on the in vivo performance of a drug product; it is expected that information on the dosage form and formulation characteristics (drug product critical quality attributes) is a major component of the model structure. Therefore, dermatological dosage forms that are of interest in the model development process include, but are not limited to: creams, ointments, gels, emulsions, suspensions, lotions, solutions, films and patches.

Additional dosage forms and drug products (formulations) may be identified in collaboration with the FDA research team to address regulatory needs.

Although diseased skin physiology is the focus of the present research proposal, well characterized skin physiology across males and females, across different ages (e.g., pediatrics, elderly), across different races (e.g., white, Asian) is expected to already be a component of the developed dermal PBPK models. Finally, skin thickness, microstructure, hydration level, temperature, pH, presence of glands and hair follicles at different body locations for healthy skin might require further consideration during the model development process.

An important aspect of the skin physiology system-dependent parameters is quantifying the inter- and intra-subject variability associated with them. Including this type of variability into PBPK models results in more reliable predictions that can capture real-life scenarios of clinical relevance. An approach which prioritizes incorporation of variability around skin physiology parameters across different and within the same individual during model building is viewed positively.

4. Validate/qualify the previously developed dermal PBPK models by utilizing appropriate datasets retrieved from independent and accredited literature sources, utilizing in house data if available or designing and conducting studies that would allow the generation of the necessary experimental datasets.

Appropriate datasets that capture the subpopulation, study design and dosage form characteristics that were incorporated in the model are expected to be utilized for model validation/qualification.

5. Utilize the developed, qualified, models to evaluate bioequivalence for generic drug formulations. Virtual bioequivalence studies can be simulated to determine whether generic drug products that have been shown to not be bioequivalent to their innovators (positive control) or whether generic drug products that have been shown not to be bioequivalent to their innovators (negative control) are deemed not bioequivalent or bioequivalent, respectively, based on model output. Multiple scenarios should be simulated to demonstrate model flexibility, sensitivity and overall predictability.