Automated and Continuous Production of Polymeric Nanoparticles

Is it advantageous to use quality by design (QbD) to develop nanoparticle-based dosage forms for parenteral drug administration?

Parenteral administration is one of the most commonly used drug delivery routes for nanoparticle-based dosage forms, such as lipid-based and polymeric nanoparticles. For the treatment of various diseases, parenteral administration include intravenous, subcutaneous, and intramuscular route. In drug development phase, multiparameter strategy with a focus on drug physicochemical properties and the specificity of the administration route is required. Nanoparticle properties in terms of size and targeted delivery, among others, are able to surpass many drawbacks of conventional dosage forms, but these unique properties can be a bottleneck for approval by regulatory authorities. Quality by Design (QbD) approach has been widely utilized in development of parenteral nanoparticle-based dosage forms. It fosters knowledge of product and process quality by involving sound scientific data and risk assessment strategies. A full and comprehensive investigation into the state of implementation and applications of the QbD approach in these complex drug products can highlight the gaps and challenges. In this review, the analysis of critical attributes and Design of Experiment (DoE) approach in different nanoparticulate systems, together with the proper utilization of Process Analytical Technology (PAT) applications are described. The essential of QbD approach for the design and development of nanoparticle-based dosage forms for delivery via parenteral routes is discussed thoroughly.

Inhalable Nanoparticle-based Dry Powder Formulations for Respiratory Diseases: Challenges and Strategies for Translational Research

The emergence of novel respiratory infections (e.g., COVID-19) and expeditious development of nanoparticle-based COVID-19 vaccines have recently reignited considerable interest in designing inhalable nanoparticle-based drug delivery systems as next-generation respiratory therapeutics. Among various available devices in aerosol delivery, dry powder inhalers (DPIs) are preferable for delivery of nanoparticles due to their simplicity of use, high portability, and superior long-term stability. Despite research efforts devoted to developing inhaled nanoparticle-based DPI formulations, no such formulations have been approved to date, implying a research gap between bench and bedside. This review aims to address this gap by highlighting important yet often overlooked issues during pre-clinical development. We start with an overview and update on formulation and particle engineering strategies for fabricating inhalable nanoparticle-based dry powder formulations. An important but neglected aspect in in vitro characterization methodologies for linking the powder performance with their bio-fate is then discussed. Finally, the major challenges and strategies in their clinical translation are highlighted. We anticipate that focused research onto the existing knowledge gaps presented in this review would accelerate clinical applications of inhalable nanoparticle-based dry powders from a far-fetched fantasy to a reality.

Re-envisioning the design of nanomedicines: harnessing automation and artificial intelligence

INTRODUCTION

Interest in nanomedicines has surged in recent years due to the critical role they have played in the COVID-19 pandemic. Nanoformulations can turn promising therapeutic cargo into viable products through improvements in drug safety and efficacy profiles. However, the developmental pathway for such formulations is non-trivial and largely reliant on trial-and-error. Beyond the costly demands on time and resources, this traditional approach may stunt innovation. The emergence of automation, artificial intelligence (AI) and machine learning (ML) tools, which are currently underutilized in pharmaceutical formulation development, offers a promising direction for an improved path in the design of nanomedicines.

AREAS COVERED

the potential of harnessing experimental automation and AI/ML to drive innovation in nanomedicine development. The discussion centers on the current challenges in drug formulation research and development, and the major advantages afforded through the application of data-driven methods.

EXPERT OPINION

The development of integrated workflows based on automated experimentation and AI/ML may accelerate nanomedicine development. A crucial step in achieving this is the generation of high-quality, accessible datasets. Future efforts to make full use of these tools can ultimately contribute to the development of more innovative nanomedicines and improved clinical translation of formulations that rely on advanced drug delivery systems.

Highly Emitting Perovskite Nanocrystals with 2-Year Stability in Water through an Automated Polymer Encapsulation for Bioimaging

Lead-based halide perovskite nanocrystals are highly luminescent materials, but their sensitivity to humid environments and their biotoxicity are still important challenges to solve. Here, we develop a stepwise approach to encapsulate representative CsPbBr₃ nanocrystals into water-soluble polymer capsules. We show that our protocol can be extended to nanocrystals coated with different ligands, enabling an outstanding high photoluminescence quantum yield of ∼60% that is preserved over two years in capsules dispersed in water. We demonstrate that this on-bench strategy can be implemented on an automated platform with slight modifications, granting access to a faster and more reproducible fabrication process. Also, we reveal that the capsules can be exploited as photoluminescent probes for cell imaging at a dose as low as 0.3 μg_Pb/mL that is well below the toxicity threshold for Pb and Cs ions. Our approach contributes to expanding significantly the fields of applications of these luminescent materials including biology and biomedicine.

Continuous Nanoprecipitation of Polycaprolactone in Additively Manufactured Micromixers

The polymeric ouzo effect is an energy-efficient and robust method to create nanoparticles with biologically degradable polymers. Usually, a discontinuous or semi-continuous process is employed due to its low technical effort and the fact that the amount of dispersions needed in a laboratory is relatively small. However, the number of particles produced in this method is not enough to make this process economically feasible. Therefore, it is necessary to improve the productivity of the process and create a controllable and robust continuous process with the potential to control parameters, such as the particle size or surface properties. In this study, nanoparticles were formulated from polycaprolactone (PCL) in a continuous process using additively manufactured micromixers. The main goal was to be able to exert control on the particle parameters in terms of size and zeta potential. The results showed that particle size could be adjusted in the range of 130 to 465 nm by using different flow rates of the organic and aqueous phase and varying concentrations of PCL dissolved in the organic phase. Particle surface charge was successfully shifted from a slightly negative potential of −14.1 mV to a negative, positive, or neutral value applying the appropriate surfactant. In summary, a continuous process of nanoprecipitation not only improves the cost of the method, but furthermore increases the control over the particle’s parameters.

Supramolecular engineering of hydrogels for drug delivery

Supramolecular binding motifs are increasingly employed in the design of biomaterials. The ability to rationally engineer specific yet reversible associations into polymer networks with supramolecular chemistry enables injectable or sprayable hydrogels that can be applied via minimally invasive administration. In this review, we highlight two main areas where supramolecular binding motifs are being used in the design of drug delivery systems: engineering network mechanics and tailoring drug-material affinity. Throughout, we highlight many of the established and emerging chemistries or binding motifs that are useful for the design of supramolecular hydrogels for drug delivery applications.

Applications of Nanoparticle-Antibody Conjugates in Immunoassays and Tumor Imaging

Modern diagnostic technologies rely on both in vitro and in vivo modalities to provide a complete understanding of the clinical state of a patient. Nanoparticle-antibody conjugates have emerged as promising systems to confer increased sensitivity and accuracy for in vitro diagnostics (e.g., immunoassays). Meanwhile, in vivo applications have benefited from the targeting ability of nanoparticle-antibody conjugates, as well as payload flexibility and tailored biodistribution. This review provides an encompassing overview of nanoparticle-antibody conjugates, from chemistry to applications in medical immunoassays and tumor imaging, highlighting the underlying principles and unique features of relevant preclinical applications employing commonly used imaging modalities (e.g., optical/photoacoustics, positron-emission tomography, magnetic resonance imaging, X-ray computed tomography).

High Throughput Preparation of Poly(Lactic-Co-Glycolic Acid) Nanoparticles Using Fiber Fluidic Reactor

Polymeric nanoparticles (NPs) have a variety of biomedical, biotechnology, agricultural and environmental applications. As such, a great need has risen for the fabrication of these NPs in large scales. In this study, we used a high throughput fiber reactor for the preparation of poly(lactic-co-glycolic acid) (PLGA) NPs via nanoprecipitation. The fiber reactor provided a high surface area for the controlled interaction of an organic phase containing the PLGA solution with an aqueous phase, containing poly(vinyl alcohol) (PVA) as a stabilizer. This interaction led to the self-assembly of the polymer into the form of NPs. We studied operational parameters to identify the factors that have the greatest influence on the properties of the resulting PLGA NPs. We found that the concentration of the PLGA solution is the factor that has the greatest effect on NP size, polydispersity index (PDI), and production rate. Increasing PLGA concentration increased NP sizes significantly, while at the same time decreasing the PDI value. The second factor that was found to affect NP properties was the concentration of PVA solution, which resulted in increased NP sizes and decreased production rates. Flowrates of the feed streams also affected NP size to a lesser extent, while changing the operational temperature did not change the product's features. In general, the results demonstrate that fiber reactors are a suitable method for the large-scale, continuous preparation of polymeric NPs suitable for biomedical applications.