Insights into accelerated liposomal release of topotecan in plasma monitored by a non-invasive fluorescence spectroscopic method

Biopredictive tools for the development of injectable drug products

INTRODUCTION

Biopredictive release tests are commonly used in the evaluation of oral medicines. They support decision-making in formulation development and allow predictions of the expected in-vivo performances. So far, there is limited experience in the application of these methodologies to injectable drug products.

AREAS COVERED

Parenteral drug products cover a variety of dosage forms and administration sites including subcutaneous, intramuscular, and intravenous injections. In this area, developing biopredictive and biorelevant methodologies often confronts us with unique challenges and knowledge gaps. Here, we provide a formulation-centric approach and explain the key considerations and workflow when designing biopredictive assays. Also, we outline the key role of computational methods in achieving clinical relevance and put all considerations into context using liposomal nanomedicines as an example.

EXPERT OPINION

Biopredictive tools are the need of the hour to exploit the tremendous opportunities of injectable drug products. A growing number of biopharmaceuticals such as peptides, proteins, and nucleic acids require different strategies and a better understanding of the influences on drug absorption. Here, our design strategy must maintain the balance of robustness and complexity required for effective formulation development.

Nanomedicine at the crossroads - A quick guide for IVIVC

For many years, nanomedicine is pushing the boundaries of drug delivery. When applying these novel therapeutics, safety considerations are not only a key concern when entering clinical trials but also an important decision point in product development. Standing at the crossroads, nanomedicine may be able to escape the niche markets and achieve wider acceptance by the pharmaceutical industry. While there is a new generation of drug delivery systems, the extracellular vesicles, standing on the starting line, unresolved issues and new challenges emerge from their translation from bench to bedside. Some key features of injectable nanomedicines contribute to the predictability of the pharmacological and toxicological effects. So far, only a few of the physicochemical attributes of nanomedicines can be justified by a direct mathematical relationship between the in vitro and the in vivo responses. To further develop extracellular vesicles as drug carriers, we have to learn from more than 40 years of clinical experience in liposomal delivery and pass on this knowledge to the next generation. Our quick guide discusses relationships between physicochemical characteristics and the in vivo response, commonly referred to as in vitro-in vivo correlation. Further, we highlight the key role of computational methods, lay open current knowledge gaps, and question the established design strategies. Has the recent progress improved the predictability of targeted delivery or do we need another change in perspective?

Tridimensional Retinoblastoma Cultures as Vitreous Seeds Models for Live-Cell Imaging of Chemotherapy Penetration

A preclinical model could aid in understanding retinoblastoma vitreous seeds behavior, drug penetration, and response to chemotherapy to optimize patient treatment. Our aim was to develop a tridimensional in vitro model of retinoblastoma vitreous seeds to assess chemotherapy penetration by means of live-cell imaging. Cell cultures from patients with retinoblastoma who underwent upfront enucleation were established and thoroughly characterized for authentication of human tumor origin. The correlation of the in vitro tridimensional structures resembling human spheres and dusts vitreous seeds was established. Confocal microscopy was used to quantify real-time fluorescence of topotecan as a measure of its penetration into different sizes of spheres. Cell viability was determined after chemotherapy penetration. The in vitro spheres and dusts models were able to recapitulate the morphology, phenotype, and genotype of patient vitreous seeds. The larger the size of the spheres, the longer the time required for the drug to fully penetrate into the core (p < 0.05). Importantly, topotecan penetration correlated with its cytotoxic activity. Therefore, the studied tridimensional cell model recapitulated several characteristics of vitreous seeds observed in patients with retinoblastoma and were successfully used to assess live-cell imaging of chemotherapy penetration for drug distribution studies.

Simulation of Stimuli-Responsive and Stoichiometrically Controlled Release Rate of Doxorubicin from Liposomes in Tumor Interstitial Fluid

PURPOSE

To simulate the stimuli-responsive and stoichiometrically controlled doxorubicin (DOX) release from liposomes in in vivo tumor interstitial fluid (TIF), the effect of ammonia concentration and pH on the DOX release from liposomes in human plasma at 37°C was quantitatively evaluated in vitro and the release rate was calculated as a function of ammonia concentration and pH.

METHODS

Human plasma samples spiked with DOX-loaded PEGylated liposomes (PLD) or Doxil^®, containing ammonia (0.3-50 mM) at different pH values, were incubated at 37°C for 24 h. After incubation, the concentration of encapsulated DOX in the samples was determined by validated solid-phase extraction (SPE)-SPE-high performance liquid chromatography.

RESULTS

Accelerated DOX release (%) from liposomes was observed as the increase of ammonia concentration and pH of the matrix, and the decrease of encapsulated DOX concentration. The release rate was expressed as a function of the ammonia concentration and pH by using Henderson-Hasselbalch equation.

CONCLUSIONS

The DOX release from PLD in TIF was expressed as a function ammonia concentration and pH at various DOX concentrations. Further, it was found that the DOX release from liposomes in a simulated TIF was more than 15 times higher than in normal plasma.

Ion-Pairing Contribution to the Liposomal Transport of Topotecan as Revealed by Mechanistic Modeling

Actively loaded liposomal formulations of anticancer agents have been widely explored due to their high drug encapsulation efficiencies and prolonged drug retention. Mathematical models to predict and optimize drug loading and release kinetics from these nanoparticle formulations would be useful in their development and may allow researchers to tune release profiles. Such models must account for the driving forces as influenced by the physicochemical properties of the drug and the microenvironment, and the liposomal barrier properties. This study employed mechanistic modeling to describe the active liposomal loading and release kinetics of the anticancer agent topotecan (TPT). The model incorporates ammonia transport resulting in generation of a pH gradient, TPT dimerization, TPT lactone ring-opening and -closing interconversion kinetics, chloride transport, and transport of TPT-chloride ion-pairs to describe the active loading and release kinetics of TPT in the presence of varying chloride concentrations. Model-based predictions of the kinetics of active loading at varying loading concentrations of TPT and release under dynamic dialysis conditions were in reasonable agreement with experiments. These findings identify key attributes to consider in optimizing and predicting loading and release of liposomal TPT that may also be applicable to liposomal formulations of other weakly basic pharmaceuticals.

An in vitro assessment of liposomal topotecan simulating metronomic chemotherapy in combination with radiation in tumor-endothelial spheroids

Low dose metronomic chemotherapy (LDMC) refers to prolonged administration of low dose chemotherapy designed to minimize toxicity and target the tumor endothelium, causing tumor growth inhibition. Topotecan (TPT) when administered at its maximum tolerated dose (MTD) is often associated with systemic hematological toxicities. Liposomal encapsulation of TPT enhances efficacy by shielding it from systemic clearance, allowing greater uptake and extended tissue exposure in tumors. Extended release of TPT from liposomal formulations also has the potential to mimic metronomic therapies with fewer treatments. Here we investigate potential toxicities of equivalent doses of free and actively loaded liposomal TPT (LTPT) and compare them to a fractionated low dose regimen of free TPT in tumor-endothelial spheroids (TES) with/without radiation exposure for a prolonged period of 10 days. Using confocal microscopy, TPT fluorescence was monitored to determine the accumulation of drug within TES. These studies showed TES, being more reflective of the in vivo tumor microenvironment, were more sensitive to LTPT in comparison to free TPT with radiation. More importantly, the response of TES to low-dose metronomic TPT with radiation was comparable to similar treatment with LTPT. This TES study suggests nanoparticle formulations designed for extended release of drug can simulate LDMC in vivo.

Mechanistic model and analysis of doxorubicin release from liposomal formulations

Reliable and predictive models of drug release kinetics in vitro and in vivo are still lacking for liposomal formulations. Developing robust, predictive release models requires systematic, quantitative characterization of these complex drug delivery systems with respect to the physicochemical properties governing the driving force for release. These models must also incorporate changes in release due to the dissolution media and methods employed to monitor release. This paper demonstrates the successful development and application of a mathematical mechanistic model capable of predicting doxorubicin (DXR) release kinetics from liposomal formulations resembling the FDA-approved nanoformulation DOXIL® using dynamic dialysis. The model accounts for DXR equilibria (e.g. self-association, precipitation, ionization), the change in intravesicular pH due to ammonia release, and dialysis membrane transport of DXR. The model was tested using a Box-Behnken experimental design in which release conditions including extravesicular pH, ammonia concentration in the release medium, and the dilution of the formulation (i.e. suspension concentration) were varied. Mechanistic model predictions agreed with observed DXR release up to 19h. The predictions were similar to a computer fit of the release data using an empirical model often employed for analyzing data generated from this type of experimental design. Unlike the empirical model, the mechanistic model was also able to provide reasonable predictions of release outside the tested design space. These results illustrate the usefulness of mechanistic modeling to predict drug release from liposomal formulations in vitro and its potential for future development of in vitro - in vivo correlations for complex nanoformulations.