Reactive crystallization: From mixing to control of kinetics by additives

Review of machine learning for lipid nanoparticle formulation and process development

Lipid nanoparticles (LNPs) are a subset of pharmaceutical nanoparticulate formulations designed to encapsulate, stabilize, and deliver nucleic acid cargoes in vivo. Applications for LNPs include new interventions for genetic disorders, novel classes of vaccines, and alternate modes of intracellular delivery for therapeutic proteins. In the pharmaceutical industry, establishing a robust formulation and process to achieve target product performance is a critical component of drug development. Fundamental understanding of the processes for making LNPs and their interactions with biological systems have advanced considerably in the wake of the COVID-19 pandemic. Nevertheless, LNP formulation research remains largely empirical and resource intensive due to the multitude of input parameters and the complex physical phenomena that govern the processes of nanoparticle precipitation, self-assembly, structure evolution, and stability. Increasingly, artificial intelligence and machine learning (AI/ML) are being applied to improve the efficiency of research activities through in silico models and predictions, and to drive deeper fundamental understanding of experimental inputs to functional outputs. This review will identify current challenges and opportunities in the development of robust LNP formulations of nucleic acids, review studies that apply machine learning methods to experimental datasets, and provide discussion on associated data science challenges to facilitate collaboration between formulation and data scientists, aiming to accelerate the advancement of AI/ML applied to LNP formulation and process optimization.

Mapping the influence of impurity interaction energy on nucleation in a lattice-gas model of solute precipitation

We study nucleation in the two dimensional Ising lattice-gas model of solute precipitation in the presence of randomly placed static and dynamic impurities. Impurity-solute and impurity-solvent interaction energies are varied whilst keeping other interaction energies fixed. In the case of static impurities, we observe a monotonic decrease in the nucleation rate when the difference between impurity-solute and impurity-solvent interaction energies is increased. The nucleation rate saturates to a minimum value with increasing interaction energy difference when the impurity density is low. However the nucleation rate does not saturate for high impurity densities. Similar behaviour is observed with dynamic impurities both at low and high densities. We explore a broad range of both symmetric and anti-symmetric interactions with impurities and map the regime for which the impurities act as a surfactant, decreasing the surface energy of the nucleating phase. We also characterise different nucleation regimes observed at different values of interaction energy. These include additional regimes where impurities play the role of inert-spectators, bulk-stabilizers or cluster together to create heterogeneous nucleation sites for solute clusters to form.

Vortex-like vs. turbulent mixing of a Viscum album preparation affects crystalline structures formed in dried droplets

Various types of motion introduced into a solution can affect, among other factors, the alignment and positioning of molecules, the agglomeration of large molecules, oxidation processes, and the production of microparticles and microbubbles. We employed turbulent mixing vs. laminar flow induced by a vortex vs. diffusion-based mixing during the production of Viscum album Quercus L. 10-3 following the guidelines for manufacturing homeopathic preparations. The differently mixed preparation variants were analyzed using the droplet evaporation method. The crystalline structures formed in dried droplets were photographed and analyzed using computer-supported image analysis and deep learning. Computer-supported evaluation and deep learning revealed that the patterns of the variant succussed under turbulence are characterized by lower complexity, whereas those obtained from the vortex-mixed variant are characterized by greater complexity compared to the diffusion-based mixed control variant. The droplet evaporation method could provide a relatively inexpensive means of testing the effects of liquid flow and serve as an alternative to currently used methods.

Step-By-Step Standardization of the Bottom-Up Semi-Automated Nanocrystallization of Pharmaceuticals: A Quality By Design and Design of Experiments Joint Approach

Nanosized drug crystals have been reported with enhanced apparent solubility, bioavailability, and therapeutic efficacy compared to microcrystal materials, which are not suitable for parenteral administration. However, nanocrystal design and development by bottom-up approaches are challenging, especially considering the non-standardized process parameters in the injection step. This work aims to present a systematic step-by-step approach through Quality-by-Design (QbD) and Design of Experiments (DoE) for synthesizing drug nanocrystals by a semi-automated nanoprecipitation method. Curcumin is used as a drug model due to its well-known poor water solubility (0.6 µg mL-1, 25 °C). Formal and informal risk assessment tools allow identifying the critical factors. A fractional factorial 24-1 screening design evaluates their impact on the average size and polydispersity of nanocrystals. The optimization of significant factors is done by a Central Composite Design. This response surface methodology supports the rational design of the nanocrystals, identifying and exploring the design space. The proposed joint approach leads to a reproducible, robust, and stable nanocrystalline preparation of 316 nm with a PdI of 0.217 in compliance with the quality profile. An orthogonal approach for particle size and polydispersity characterization allows discarding the formation of aggregates. Overall, the synergy between advanced data analysis and semi-automated standardized nanocrystallization of drugs is highlighted.

Sub-millisecond microfluidic mixers coupled to time-resolved in situ photonics to study ultra-fast reaction kinetics: the case of ultra-small gold nanoparticle synthesis

We report a continuous microreactor platform achieving sub-millisecond homogeneous reagent mixing (∼300 μs) for a time-resolved study on the synthesis of ultra-small gold nanoparticles (NPs). The microreactor (coupled with small angle X-ray scattering, UV-vis, and X-ray absorption spectroscopy for in situ and in operando characterizations), operates within mixing time frames below system characteristic times, providing a unique opportunity to deepen the comprehension of reaction and phase transition pathways with unprecedented details. The microreactor channel length can be approximated to a given reaction time when operated in continuous mode and steady state. As a result, the system can be statically investigated, eliminating technique-dependent probing time constraints and local inhomogeneities caused by mixing issues. We have studied Au(0) NP formation kinetics from Au(III) precursors complexed with oleylamine in organic media, using triisopropylsilane as a reducing agent. The existence of Au(III)/Au(I) prenucleation clusters and the formation of a transient Au(I) lamellar phase under certain conditions, before the onset of Au(0) formation, have been observed. Taking advantage of the high frequency time-resolved information, we propose and model two different reaction pathways associated with the presence or absence of the Au(I) lamellar phase. In both cases, non-classical pathways leading to the formation of NPs are discussed.

Recent Advances in Enabling Green Manufacture of Functional Nanomaterials: A Case Study of Bioinspired Silica

Global specialty silica production is over 3 million tonnes per annum with diverse applications across sectors and an increasing demand for more complex material structures and surface chemistries. Commercial manufacturing of high-value silica nanomaterials is energy and resource intensive. In order to meet market needs and mitigate environmental impacts, new synthesis methods for these porous materials are required. The development of the bioinspired silica (BIS) product system, which is the focus of this review, provides a potential solution to this challenge. BIS is a versatile and greener route with the prospect of good scalability, attractive process economics and well controlled product materials. The potential of the system lies not only in its provision of specific lead materials but also, as itself, a rich design-space for the flexible and potentially predictive design of diverse sustainable silica nanomaterials. Realizing the potential of this design space, requires an integrative mind-set, which enables parallel and responsive progression of multiple and dependent research strands, according to need, opportunities, and emergent knowledge. Specifically, this requires development of detailed understanding of (i) the pathways and extent of material diversity and control, (ii) the influences and mechanisms of scale-up, and (iii) performance, economic and environmental characteristics and sensitivities. Crucially, these need to be developed for the system overall, which sits in contrast to a more traditional research approach, which focuses initially on the discovery of specific material leads at the laboratory scale, leaving scale-up, commercialization, and, potentially, pathway understanding to be considered as distinctly separate concerns. The intention of this review is to present important recent advances made in the field of BIS. Specifically, advances made along three research themes will be discussed: (a) particle formation pathways, (b) product design, and (c) scale-up and manufacture. These advances include first quantitative investigation of synthesis-product relationships, first structured investigation of mixing effects, preparation of a broad range of functionalized and encapsulated silica materials and continued industrial engagement and market research. We identify future challenges and provide an important foundation for the development of new research avenues. These include the need to develop comprehensive and predictive product design models, to understand markets in terms of product cost, performance and environmental considerations, and to develop capabilities enabling rapid prototyping and scale-up of desired nanomaterials.

Controlling nanoparticle formation from the onset of nucleation through a multi-step continuous flow approach

HYPOTHESIS

Metallic nanoparticles of various shapes and sizes can be synthesised through a diversity of bottom-up pathways, such as precipitation induced by chemical reduction. Varying composition, by adjusting concentrations or adding/replacing species, is the predominant strategy to tune nanoparticles structures. However, controlling time down to the onset of precipitation, nucleation, should also provide a powerful means to control nanostructuration.

EXPERIMENTS

We perform sequential reagent additions with a time resolution down to the millisecond. We use a millifluidic continuous flow setup consisting of tangential mixers in series, which allows flow rates up to dozens of litres per hour. We systematically vary both addition order and delay for each reagent involved in the synthesis of silver nanoplates. The resulting dispersions are compared using UV-visible spectroscopy, transmission electron microscopy and small-angle X-ray scattering.

FINDINGS

We show that synthesis pathways differing only in the order of sub-second additions lead to drastically different synthetic outcomes. Silver nanoparticles of different shapes and sizes, displaying an array of plasmonic colours, are synthesised at the same final composition by tuning the composition pathways along time. Our results unlock a previously inaccessible portion of the space of parameters, which will lead to an enhanced structural diversity, control and understanding of nanoparticles syntheses.

A temperature-reduced method for the rapid growth of hybrid perovskite single crystals with primary alcohols

In this work, we present the simple and temperature-reduced reactive inverse temperature crystallisation (RITC) method to rapidly grow high-quality organic lead trihalide perovskite single crystals.

Reactive crystallization: a review

Reactive crystallization is not new, but there has been recent growth in its use as a means of improving performance and sustainability of industrial processes.

Memristive TiO2: Synthesis, Technologies, and Applications

Titanium dioxide (TiO2) is one of the most widely used materials in resistive switching applications, including random-access memory, neuromorphic computing, biohybrid interfaces, and sensors. Most of these applications are still at an early stage of development and have technological challenges and a lack of fundamental comprehension. Furthermore, the functional memristive properties of TiO2 thin films are heavily dependent on their processing methods, including the synthesis, fabrication, and post-fabrication treatment. Here, we outline and summarize the key milestone achievements, recent advances, and challenges related to the synthesis, technology, and applications of memristive TiO2. Following a brief introduction, we provide an overview of the major areas of application of TiO2-based memristive devices and discuss their synthesis, fabrication, and post-fabrication processing, as well as their functional properties.

Continuous reactive crystallization of an API in PFR-CSTR cascade with in-line PATs

The influence of PFR on crystal size distribution, reaction and crystallization yields, and supersaturation level was investigated.