Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7202
Authors: García Alcalde, Mauricio Andrés
Advisor: Langguth, Peter
Title: Biopharmaceutic Prediction of Oral Absorption from Immediate Release Dosage Forms
Online publication date: 6-Jul-2022
Year of first publication: 2022
Language: english
Abstract: Characterization of the efficacy and safety of pharmaceuticals is typically carried out by the pharmaceutical industry through assessment of pharmacokinetics in clinical trials performed in humans. However, outcomes of those studies do not depend only on the active pharmaceutical ingredient (API) but also on the whole pharmaceutical product. Therefore, even though two different products contain the same API at the same dose in the same dosage form, they may still showcase different efficacy/safety profiles. This situation can even occur after post-approval changes in the manufacturing/formulation of the same product. Considering the infeasibility of performing clinical trials every time a new formulation needs to be tested, the development of surrogate in vitro and in silico biopredictive methods becomes increasingly relevant. The aim of this dissertation is to discuss the development and implementation of biopharmaceutic methods to predict oral drug absorption from immediate release (IR) dosage forms. Carbamazepine (neutral) and ibuprofen (weak acid) were used as model drugs of the biopharmaceutic classification system (BCS) class II (highly permeable and poorly soluble), while acyclovir served as an example of the BCS class III (poorly permeable and highly soluble). Regarding carbamazepine, a high level of agreement between in vivo observations and the dissolution of tablets under compendial dissolution conditions (900 ml, 1% sodium lauryl sulfate media, apparatus II, 50 rpm) was found, as shown in Publication 1. For the second case, a biopredictive in vitro dissolution methodology for two ibuprofen suspensions was developed using bicarbonate buffer at physiological concentrations and compared to their in vivo equivalent dissolution. Moreover, the concept of surface pH and mechanistic mass transfer analysis were employed to successfully develop a surrogate media utilizing phosphate buffer (Publication 2). Conversely, for a BCS class III drug, as acyclovir, the pharmacokinetic profiles in subjects are determined by the permeability rather than the solubility in gastrointestinal fluids. The effect of the excipient chitosan on acyclovir permeability was better predicted by mucus-secreting ex-vivo models, such as rat jejunum mounted on an Ussing-chamber set-up (Publication 3). Furthermore, the variability in acyclovir oral pharmacokinetics seems to rely on physiological variables rather than formulation aspects related to tablet dissolution. In fact, the input of the in vitro dissolution of acyclovir tablets into a physiologically-based pharmacokinetic (PBPK) model resulted in the correct prediction of their bioequivalence, in spite of their different dissolution rates (Publication 4). In conclusion, biopharmaceutic prediction of oral absorption is possible for IR dosage forms, provided the surrogate methodology is rationally selected. The consideration of both the drug's physical-chemical parameters and the interaction between the pharmaceuticals and gastrointestinal contents are critical. The implementation of predictive surrogate methods in the pharmaceutical industry, as well as their acceptance from regulatory agencies, may result in the acceleration of drug development, while also reducing the number of clinical trials.
DDC: 540 Chemie
540 Chemistry and allied sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 09 Chemie, Pharmazie u. Geowissensch.
Place: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-7202
URN: urn:nbn:de:hebis:77-openscience-3fbfa46c-eb05-4fe3-bc4a-69a7d03a4c742
Version: Original work
Publication type: Dissertation
License: In Copyright
Information on rights of use: http://rightsstatements.org/vocab/InC/1.0/
Extent: Getrennte Zählungen
Appears in collections:JGU-Publikationen

Files in This Item:
  File Description SizeFormat
Thumbnail
biopharmaceutic_prediction_of-20220623075919234.pdf6.29 MBAdobe PDFView/Open