Multiscale Simulations and Pharmacokinetic Modeling of Long-Acting Injectable Delivery Systems

Long-acting injectables (LAI) offer many practical benefits for patients in improving drug adherence to therapies for chronic diseases. LAI, administered either subcutaneously (SC) or intramuscularly (IM), can improve drug bioavailability, and reduce frequency of administration as well as regimen complexity. SC also has additional benefits over IM injections as being safer, less painful, and able to be administered at home. However, development and translation of these products into the clinic is often limited because of physiological complexity at injection site, such that absorption rate mechanisms are not well understood. Common predictive and correlative methods used in oral formulations, such as in vitro-in vivo correlations, are not well suited for SC physiology and are only capable of measuring a few parameters at a time, meaning relationships between parameters cannot be discriminately measured.

This project seeks to address this gap in knowledge by using computation to bridge the gap between suboptimal preclinical testing methods and human pharmacokinetic data. A Multiscale framework was developed by integrating a first-principles Multiphysics model of the SC space to experimental plasma concentration profiles using simulated absorption rates. First, our lab’s previous framework for lymphatic absorption of monoclonal antibodies (mAbs) was converted into small molecule absorption into the capillaries. Drug and formulation critical quality attributes (CQA) were determined for a solution injection of methotrexate, and a nanocrystal formulation of medroxyprogesterone acetate (MPA, Depo-SubQ Provera). Two dissolution models were incorporated to compare the difference between using average particle size (Noyes-Whitney) and particle size distributions (Population Balance Model, PBM) as CQA for nanocrystal LAI specifically. Absorption rates were validated using compartmental pharmacokinetic models, and sensitivity analyses were conducted to determine model parametric sensitivity. Overall, the modeling framework was able to determine the importance of and discriminate the effect of parameters on SC absorption rates.