Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound

Ultrasound-Mediated Cancer Therapeutics Delivery using Micelles and Liposomes: A Review

BACKGROUND

Existing cancer treatment methods have many undesirable side effects that greatly reduce the quality of life of cancer patients.

OBJECTIVE

This review will focus on the use of ultrasound-responsive liposomes and polymeric micelles in cancer therapy.

METHODS

This review presents a survey of the literature regarding ultrasound-triggered micelles and liposomes using articles recently published in various journals, as well as some new patents in this field.

RESULTS

Nanoparticles have proven promising as cancer theranostic tools. Nanoparticles are selective in nature, have reduced toxicity, and controllable drug release patterns making them ideal carriers for anticancer drugs. Numerous nanocarriers have been designed to combat malignancies, including liposomes, micelles, dendrimers, solid nanoparticles, quantum dots, gold nanoparticles, and, more recently, metal-organic frameworks. The temporal and spatial release of therapeutic agents from these nanostructures can be controlled using internal and external triggers, including pH, enzymes, redox, temperature, magnetic and electromagnetic waves, and ultrasound. Ultrasound is an attractive modality because it is non-invasive, can be focused on the diseased site, and has a synergistic effect with anticancer drugs.

CONCLUSION

The functionalization of micellar and liposomal surfaces with targeting moieties and the use of ultrasound as a triggering mechanism can help improve the selectivity and enable the spatiotemporal control of drug release from nanocarriers.

Modeling of Anti-cancer Drug Release Kinetics from Liposomes and Micelles: A review

Nanocarriers, such as liposomes and micelles, were developed to enhance the delivery of therapeutic drugs to malignant tissues. Internal or external stimuli can be applied to achieve spatiotemporal controlled release from these carriers. This will result in enhancing their therapeutic efficacy while reducing toxicity. Mathematical modeling is used to simulate drug release from nanocarriers; this will facilitate and optimize the development and design of desirable nanocarriers in a systematic manner, rather than a trial-and-error approach. This review summarizes nine mathematical models often used to simulate drug release from nanocarriers and reviews studies which employed these models to simulate drug release from conventional as well as temperature-, pH-, and ultrasound-triggered micelles and liposomes.

Pulsatile Drug Delivery System Triggered by Acoustic Radiation Force

Since biological systems exhibit a circadian rhythm (24-hour cycle), they are susceptible to the timing of drug administration. Indeed, several disorders require a therapy that synchronizes with the onset of symptoms. A targeted therapy with spatially and temporally precise controlled drug release can guarantee a considerable gain in terms of efficacy and safety of the treatment compared to traditional pharmacological methods, especially for chronotherapeutic disorders. This paper presents a proof of concept of an innovative pulsatile drug delivery system remotely triggered by the acoustic radiation force of ultrasound. The device consists of a case, in which a drug-loaded gel can be embedded, and a sliding top that can be moved on demand by the application of an acoustic stimulus, thus enabling drug release. Results demonstrate for the first time that ultrasound acoustic radiation force (up to 0.1 N) can be used for an efficient pulsatile drug delivery (up to 20 μg of drug released for each shot).

Multi-Model Investigation and Adaptive Estimation of the Acoustic Release of a Model Drug From Liposomes

This paper researches a suitable mathematical model that can reliably predict the release of a model drug (namely calcein) from biologically targeted liposomal nanocarriers triggered by ultrasound. Using mathematical models, curve fitting is performed on a set of five experimental acoustic drug release runs from Albumin-, Estrone-, and RGD-based Drug Delivery Systems (DDS). The three moieties were chosen to target specific cancers using receptor-mediated endocytosis. The best-fitting mathematical model is then enhanced using a Kalman filtering (KF) algorithm to account for the statistics of the dynamic and measurements noise sequences in predicted drug release. Unbiased drug-release estimates are realized by implementing an online noise identification algorithm. The algorithm is first deployed in a simulated environment in which it was rigorously tested and compared with the correct solution. Then, the algorithm was used to process the five experimental datasets. The results suggest that the Adaptive Kalman Filter (AKF) is exceptionally good at handling drug release estimation problems with a priori unknown or with changing noise covariances. In comparison with the KF, the AKF approach exhibited as low as a 69% reduction in the level of error in estimating the drug release state. Finally, the proposed algorithm is not computationally demanding and is capable of online estimation tasks.

Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles

This paper estimates the acoustic drug release from micelles after accurately identifying the underlying statistical noise characteristics in experimental data. The drug release is measured as a change in fluorescence as ultrasound is applied. First, the noise structure affecting the process dynamics and the measurement process is identified in terms of statistical covariance of the aforementioned quantities. Then, the identified covariance magnitudes are utilized to estimate the dynamics of drug release. The performance of different filters is investigated. The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. Experiments span a number of ultrasonic power densities for both non-targeted and targeted polymeric micelles (the targeting being accomplished using the folate moiety). The results suggest that the proposed algorithm, the optimal Kalman filter, performs better than the other two in all tests performed.