Novel convolution-based In vitro-In vivo correlation (IVIVC) model with time scaling and bioavailability sub-models for, JORNAY PM®, a methylphenidate hydrochloride delayed-release and extended-release capsule
Pawan Kumar Gupta, Bev Incledon, Jogarao V. S. Gobburu, Roberto Gomeni
University of Maryland Baltimore
Objectives:
Methylphenidate hydrochloride (MPH) is a central nervous system stimulant and is used as a first line of treatment for attention deficit hyperactivity disorder [1, 2, 3]. Delayed-release and extended-release (DR/ER) MPH (JORNAY PM®) with MPH as the active moiety is the first drug utilizing Ironshore Pharmaceuticals & Development, Inc.’s novel and proprietary drug delivery technology that contains two functional film coatings that act synergistically to achieve a unique pharmacokinetic (PK) profile.
The objective of this work is to develop Level A In vitro-in vivo correlation (IVIVC) model to support DR/ER-MPH post-approval manufacturing changes in accordance with FDA guidance [4].
Methods:
The time course of the MPH drug concentration resulting from an arbitrary dose was considered as a function of the in vivo drug absorption and the disposition and elimination processes defined by the unit impulse response function using the convolution integral [5].
Dissolution data from three different in vitro and in vivo studies were used for the entire convolution-based IVIVC modeling and its validation. The entire analysis comprised the following steps:
- A dissolution model is first developed to estimate the fraction dissolved in vitro, of the three different release formulations: fast, medium, and slow using dissolution data from an in vitro study.
- The individual PK data from an in vivo study were utilized to characterize the disposition and elimination of the Immediate Release (IR) formulation of MPH.
- The individual PK data for all three formulations from another in vivo study were used to develop the PK model to estimate the fraction absorbed in vivo fabs(t), similar to that reported by Gomeni et al [6]. The mean volume (V) and the mean elimination rate constant (Kel) in this analysis were fixed to the corresponding V and Kel estimates respectively obtained from the IR MPH PK analysis and the bioavailability between the formulations was fixed as zero.
- The scatterplots of fdiss(t) versus fabs(t) and Levy were used to assess potential temporal differences in the in vitro and the in vivo processes and a time scaling function was included in the model to establish IVIVC. The mean PK data of the three extended-release formulations were used to develop the basic IVIVC model. The mean and BSV of V and Kel were fixed to the estimates from IR PK and fraction absorbed analysis respectively. In addition to the parameters, the relative bioavailability fractions for medium and slow formulations compared to fast formulation were also estimated to account for differences in bioavailability among the formulations. The basic IVIVC model was refined by including a sub-model describing the relationship between time to 50% drug dissolution in vitro and the relative bioavailability of the formulations using a quadratic polynomial to make it suitable for external validation.
The model was finally validated internally and externally per the US FDA recommendations [4].
All data wrangling, modeling, simulations, and plotting were performed using Pumas V2.3.1 (Baltimore, MD) [7].
Results:
The Sigmoid-Emax type model was found to adequately describe the final in vitro dissolution model. The IR MPH PK was best described by a 1-compartment model with a first-order absorption process, with a lag-time, and linear elimination. The temporal difference in the scatterplot of fdiss(t) versus fabs(t) and Levy plots suggested a potential need for a nonlinear component describing the time-shifting, time-scaling, and time-shaping factors which were incorporated in the model to establish IVIVC12. The IVIVC model was then refined by including a sub-model to make it suitable for external validation.
The % Prediction error calculated for peak plasma concentration Cmax and area under the curve to infinity AUC0-∞ met the FDA expectation for internal as well as external validation. The entire analysis was done in NONMEM also and the results are identical to Pumas [8].
Conclusions:
Level A IVIVC model is developed to support JORNAY PM® post-approval manufacturing changes by evaluating a point-to-point correlation between the fraction of drug absorbed in vivo and the fraction of drug dissolved in vitro. The final (refined) IVIVC model can now be used to predict in vivo profiles for different in vitro profiles of JORNAY PM®.
.
References:
[1] CADDRA. The Canadian ADHD Practice Guidelines for the diagnosis and treatment of ADHD. Available at: https://adhd-institute.com/disease-management/guidelines/caddra-guidelines/. Accessed 25 January 2023.
[2] AAP. Clinical practice guideline that provides recommendations for the diagnosis and treatment of children with attention-deficit/hyperactivity disorder (ADHD). Available at: https://www.cdc.gov/ncbddd/adhd/guidelines.html. Accessed 25 January 2023.
[3] Dulcan M, Benson R. Summary of the Practice Parameters for the Assessment and Treatment of Children, Adolescents, and Adults with ADHD. Journal of AACAP. 1997;Vol 36, Issue 9:1311-1317.
[4] FDA. Guidance for industry. Extended release oral dosage forms: development, evaluation, and application of in vitro/ in vivo correlations. https://www.fda.gov/media/70939/download. Accessed 25 January 2023.
[5] Gomeni R, Fang L, Bressolle-Gomeni F, Spencer T, Faraone S, Babiskin A. A general framework for assessing in vitro/in vivo correlation as a tool for maximizing the benefit-risk ratio of a treatment using a convolution-based modeling approach. CPT Pharmacometrics Syst Pharm. 2019;8: 97-106.
[6] Gomeni R, Bressolle-Gomeni F. Comparison of alternative population modeling approaches for implementing a level A IVIVC and for assessing the time-scaling factor using deconvolution and convolution-based methods. AAPS J. 2020;22(3):67.
[7] Rackauckas C, Ma Y, Noack A, et al. Accelerated predictive healthcare analytics with Pumas, a high performance pharmaceutical modeling and simulation platform. bioRxiv. 2020.
[8] Mould D, Upton R. Basic concepts in population modeling, simulation, and model-based drug development- part 2. CPT Pharmacometrics Syst Pharmacol. 2013;2:e38.