Applications of mechanistic modeling and simulations in compound and dosage forms selections / by Eric Akwasi Mintah
Physiologically based pharmacokinetic (PBPK) modeling and simulation techniques have been adopted in the pharmaceutical industry to aid in compound selection and dosage form development in recent years. This is a result of easier access to computers and advanced knowledge of species physiology. The mechanistic modeling approach utilizes the compound’s physiochemical properties, formulation related factors, route of administration and species physiology in order to predict the concentration-time profile in plasma and tissues. In this dissertation, different predictive and mechanistic models (ADMET®, ACAT®, OCCAT® and metabolite tracking approaches in Gastroplus®) were applied to simulate the concentration time profiles of various compounds. We applied mechanistic modeling techniques to predict the concentration-time profiles of curcumin and its analogs in order to identify potential drug candidates for future preclinical and clinical studies. An in silico based absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction tool in Gastroplus® (version 8.5, Simulations Plus, Inc., Lancaster, CA, USA) was utilized. For this purpose, we performed model qualifications by comparing the simulated pharmacokinetics data of pure curcumin and compared to the observed data from literature. Curcumin analogues and other compounds that showed higher potential for oral absorption were selected for further study. In our second project, we evaluated the predictability of the new oral cavity compartmental absorption and transit (OCCAT®) model by utilizing commercial buccal and sublingual (fentanyl, buprenorphine, nicotine, miconazole, rizaptriptan and testosterone) formulations. The new OCCATTM model was able to simulate the PK parameters/profiles of published multiple doses of buccal and sublingual drugs administered to healthy and patient population. Varying degrees of bias was observed for all the simulated PK parameter values as compared to the published parameter values for the compounds tested based on the computed % predictability error. Although, the new OCCAT model can be used to support the formulation development and regulatory decisions, its applicability and the predictability for specific drug needs to be adequately qualified. In another project, we conducted mechanistic analysis to track the metabolites of tenofovir disoproxil fumarate (TDF) using PBPK modeling. The main goal of the project was to track the pharmacokinetics of a prodrug, tenofovir disoproxil fumarate (TDF) and its parent drug, tenofovir. Finally, the mechanistic modeling approach was utilized to simulate the disposition, including potential metabolic pathways of 4-benzylpiperidine based on its predicted physiochemical properties.
Mintah, Eric Akwasi