基于质量源于设计的siRNA纳米吸入固体制剂

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Abstract 摘要

Therapy based on RNA interference (RNAi), which can be mediated by exogenous small interfering RNA (siRNA), has potential for the management of diseases at the genetic level by silencing gene function(s). In all eukaryotic cells, RNAi is an endogenous regulatory mechanism, where messenger RNA (mRNA) is degraded, preventing its translation into protein. A significant advantage of RNAi therapy is that siRNA is very potent and gene silencing is highly specific, ensuring few off-target effects. However, the delivery of exogenous siRNA to the RNAi pathway in the cytosol is a challenge, and there is a need for development of advanced delivery systems to ensure safe and effective delivery of siRNA to the intracellular target site. Recently, we demonstrated the ability of lipid-polymer hybrid nanoparticles (LPNs) composed of cationic lipidoid 5 (L5) and the biodegradable polymer poly(dl-lactic-co-glycolic acid) to effectively deliver siRNA directed against tumor necrosis factor alpha (TNF-α) intracellularly to macrophages. L5 is a novel lipid-like material consisting of a tetraamine backbone linked to five C12 alkyl chains. Here, we describe a systematic quality-by-design (QbD) approach including risk assessment and design of experiments to investigate the influence of critical formulation parameters (i.e., L5 content and L5:TNF-α siRNA ratio (w/w)) on the physicochemical properties and the TNF-α gene silencing ability of TNF-α siRNA-loaded LPNs, prepared by using a double emulsion solvent evaporation method. We then detail protocols for the manufacturing of more stable solid dosage forms of LPNs using freeze drying and spray drying processes, respectively. We also provide protocols for characterization of the physicochemical properties of the nanocomposite dry powders, including (1) process yield, (2) aerodynamic particle size, (3) surface morphology, (4) moisture content, and (5) solid state properties. General considerations are provided that emphasize the advantages and disadvantages of applying QbD approaches for optimizing nanoparticulate formulations.

RNA 干扰（RNAi）疗法通过外源性小干扰 RNA（siRNA）进行基因功能的沉默，展示了在基因层面治疗疾病的潜力。在真核细胞中，RNAi 是一种内源性机制，能降解信使 RNA（mRNA），阻止其转化为蛋白质。RNAi 疗法的主要优势在于 siRNA 的高效能和高度的特异性，使得脱靶效应较少。然而，将外源 siRNA 递送到细胞质中的 RNAi 通路是一个难点，因此，需要开发更先进的递送系统，确保 siRNA 能安全有效地到达细胞内靶点。我们最近的研究表明，采用由阳离子脂类物质 L5 和可降解聚合物聚（乳酸-乙醇酸）组成的脂质-聚合物混合纳米颗粒（LPNs）可以有效地将针对肿瘤坏死因子α（TNF-α）的 siRNA 递送到巨噬细胞中。L5 是一种新型的类脂材料，由一个四胺结构和五个 C12 烷基链构成。本文中，我们详细介绍了一种系统的质量源于设计（QbD）方法，包括风险评估和实验设计，用以研究关键配方参数（如 L5 含量和 L5 与 TNF-α siRNA 的质量比）对 LPNs 物理化学性质及其 TNF-α基因沉默能力的影响。这些 LPNs 通过双乳液溶剂蒸发法制备。同时，我们还介绍了通过冷冻干燥和喷雾干燥工艺制备更稳定的固体剂型 LPNs 的生产方法，并提供了其物理化学性质的表征方法，包括（1）生产产率，（2）空气动力学粒径，（3）表面形态，（4）水分含量，以及（5）固态性质。我们也讨论了应用 QbD 方法优化纳米颗粒配方的优势和局限。👀

1 Introduction 引言

Development of new therapeutics to treat diseases remains a constant challenge. RNA interference (RNAi)-based therapeutics represent promising alternative treatment options when traditional small-molecule drugs or/and peptide/protein-based therapy fail. Moreover, the use of RNAi-based strategies may overcome issues of drug resistance prevalent with traditional therapeutics. RNAi is an endogenous defense and regulatory mechanism based on posttranscriptional gene regulation that is mediated by small RNA duplexes, including microRNA (miRNA), short interfering RNAs (siRNAs), and short hairpin RNAs (shRNAs). By exploiting this pathway, exogenous siRNAs can be applied to silence the expression of virtually any gene, including targets which have traditionally been considered as undruggable. However, one of the key challenges associated with the successful realization of siRNA-based therapeutics is the requirement for safe and effective delivery approaches. To enter the RNAi pathway, siRNA has to be delivered into the cytosol of target cells, where it is incorporated into the RNAi machinery. However, unmodified siRNA is chemically unstable under physiological conditions, can be immunogenic, and does not readily cross cell membranes. Therefore, siRNA duplexes are usually chemically modified to increase the half-life and reduce undesired immunogenicity. Chemical conjugation of siRNA to biomolecules, e.g., cell-penetrating peptides, antibodies, lipids, or N-acetyl galactosamine, may (1) enable target-specific delivery, (2) improve serum stability, and (3) increase transfection efficiency. Alternatively, delivery systems may also be used to facilitate permeation of the large and hydrophilic siRNA molecules across the cell membrane into the cytosol. An example is the recently approved siRNA-based therapeutic ONPATTRO™ (Patisiran), which is an siRNA formulation based on lipid nanoparticles (LNPs) used for the treatment of hereditary transthyretin-mediated amyloidosis. In addition, a plethora of delivery systems are under exploration for ensuring safe in vivo delivery of siRNA, including lipid-based delivery systems, polymer-based delivery systems, and lipid-polymer hybrid systems. We have designed a novel delivery system based on lipid-polymer hybrid nanoparticles (LPNs) for efficient and safe delivery of siRNA into the cytosol, and we recently demonstrated the in vivo therapeutic efficacy of LPNs loaded with tumor necrosis factor alpha (TNF-α) siRNA for the treatment of experimental inflammation. These LPNs consist of two main components: lipidoid and poly(d,l-lactic-co-glycolic acid) (PLGA). Lipidoids belong to a novel class of cationic lipid-like materials that efficiently interact with polyanionic nucleic acids including siRNA via attractive electrostatic interactions and mediate cellular uptake, endosomal escape, and cytosolic delivery. PLGA forms the polymeric core of the LPNs allowing sustained release of siRNA and thus constitutes an inherent part of the LPN architecture. The lipidoid component interacts with the PLGA core and may form a membrane shell structure around the core. The cationic lipidoid headgroup neutralizes the anionic charge of the nucleic acid cargo, e.g., siRNA, while the hydrophobic alkyl chains play a role in cell membrane fusion. These LPNs can be prepared by using a multi-step double emulsion solvent evaporation method that enables efficient encapsulation of water-soluble and polyanionic compounds, e.g., siRNA. We have previously reported a detailed protocol for this method and identified critical formulation parameters (CFPs) and critical process parameters (CPPs). In this chapter, we detail methods for (1) quality-by-design (QbD)-based optimization of TNF-α siRNA-loaded LPNs using risk assessment and design of experiments (DoE), (2) manufacturing of solid dosage forms of LPNs applying freeze drying and spray drying processes, respectively, and (3) physicochemical characterization of the spray-dried nanocomposite LPN microparticles.

开发新的治疗方法以应对疾病依然是医学中的一大挑战。基于 RNA 干扰（RNAi）的疗法为传统小分子药物或肽/蛋白质疗法失效时提供了有力的替代选择。此外，RNAi 策略还能够克服传统疗法中常见的耐药性问题。RNAi 是一种内源性机制，通过转录后的基因调控来防御和调节，主要由小型 RNA 双链体（如微 RNA、短干扰 RNA 和短发夹 RNA）介导。通过利用这一机制，外源 siRNA 可以用来沉默几乎任何基因的表达，甚至包括那些传统上认为无法用药物靶向的基因。然而，成功实现 siRNA 疗法的一个主要难点是如何安全有效地递送 siRNA。要进入 RNAi 通路，siRNA 必须被递送到目标细胞的胞质中，并被整合进 RNAi 机制中。然而，未修饰的 siRNA 在生理环境下化学性质不稳定，容易引发免疫反应，并且难以通过细胞膜。因此，siRNA 双链体通常会进行化学修饰，以延长其半衰期并减少不必要的免疫反应。将 siRNA 与生物分子（如细胞穿透肽、抗体、脂质或N-乙酰半乳糖胺）结合，可能（1）实现靶向递送，（2）提高其在血清中的稳定性，和（3）提升转染效率。另一个选择是利用递送系统，帮助大分子和亲水性 siRNA 穿过细胞膜进入胞质。一个例子是最近获批的基于 siRNA 的药物 ONPATTRO™（Patisiran），它是一种基于脂质纳米颗粒的 siRNA 制剂，用于治疗遗传性转甲状腺素蛋白介导的淀粉样变性。此外，科学界还在探索多种递送系统，以确保 siRNA 在体内的安全递送，包括脂质、聚合物以及脂质-聚合物杂化系统。我们设计了一种新型的脂质-聚合物杂化纳米颗粒递送系统，能够高效且安全地将 siRNA 递送至胞质。我们近期展示了该系统负载肿瘤坏死因子α（TNF-α）siRNA 在体内实验性炎症治疗中的疗效。该系统由两部分组成：脂类物质和聚（乳酸-共-乙醇酸）（PLGA）。脂类物质是一类新型阳离子类脂材料，能通过静电作用与 siRNA 等多阴离子核酸高效结合，并促进细胞摄取、内体逃逸及胞质递送。PLGA 则构成纳米颗粒的聚合物核心，能够实现 siRNA 的持续释放。脂类物质与 PLGA 核心相互作用，可能形成包覆核心的膜状结构。脂类物质的阳离子头基中和了 siRNA 的阴性电荷，而疏水烷基链则在细胞膜融合过程中发挥作用。这些纳米颗粒可以通过多步骤双乳液溶剂蒸发法制备，从而实现水溶性和多阴离子化合物（如 siRNA）的高效包封。我们之前已经详细介绍了该制备方法，并识别了关键配方参数和工艺参数。在本章节中，我们将详细讨论（1）基于质量源于设计（QbD）的 TNF-α siRNA 负载纳米颗粒的优化策略，包括风险评估和实验设计，（2）利用冷冻干燥和喷雾干燥工艺制备固体剂型的方法，以及（3）喷雾干燥纳米复合颗粒的物理化学性质表征。

Applying QbD approaches in the design, development, and manufacturing of medicines ensures the quality of pharmaceuticals by employing statistical, analytical, and risk management methodologies. Such approaches help in identifying significant sources of variability that may affect formulations and processes and aid in meeting the desired characteristics. Thus, applying these principles in the design of an LPN formulation that displays optimal siRNA encapsulation efficiency and loading, balanced cytotoxic and gene silencing profiles, desired physicochemical properties, and stability ensures a robust formulation and a high-quality product. Hence, QbD is a logical and stepwise process (Fig. 1) involving the following principles: (1) risk assessment, (2) identification of the quality target product profile (QTPP), i.e., the product attributes that are critical to stability, safety, and efficacy, (3) identification of critical quality attributes (CQAs) based on the product, the process, and the QTPP, (4) screening of CFPs/CPPs to identify potential risk variables, (5) design of the process to deliver product and process attributes (CQAs and QTPP), (6) identification of a robust control strategy that ensures consistent formulation/process performance, and (7) validation of the formulation/process to demonstrate the effectiveness of the control strategy and to evaluate if the product formulated/processed within the identified optimal operating space (OOS) meets the QTPP.

在药物的设计、开发和生产过程中，应用质量源于设计（QbD）方法能够通过采用统计分析和风险管理策略，确保药品的质量。该方法帮助识别那些可能导致配方和工艺变异的关键因素，并有助于实现预期的产品特性。因此，在设计 LPN 配方时，应用这些原则可以确保其在 siRNA 的封装效率、负载量、细胞毒性与基因沉默作用、理化性质及稳定性方面达到理想状态，从而确保配方稳健并生产出高质量的产品。QbD 是一种循序渐进的逻辑性过程（图 1），包括以下几个步骤：（1）风险评估，（2）确定质量目标产品特性（QTPP），即对产品稳定性、安全性及有效性至关重要的属性，（3）识别关键质量属性（CQAs），依据产品、工艺及 QTPP 确定，（4）筛选关键配方参数（CFPs）和关键工艺参数（CPPs），以找出潜在的风险因素，（5）设计生产工艺以满足产品和工艺特性（CQAs 和 QTPP），（6）建立稳健的控制策略，确保配方和工艺的稳定表现，以及（7）通过验证工艺和配方，确认控制策略的有效性，评估产品在最优操作范围（OOS）内是否符合 QTPP 要求。

Fig. 1 Scheme for implementing quality-by-design for a pharmaceutical product. QTPP quality target product profile, CQA critical quality attribute, CPP critical process parameter, CFP critical formulation parameter

Pulmonary administration is promising for the local delivery of target-specific siRNA in the treatment of lung diseases, e.g., chronic obstructive pulmonary disease (COPD), because systemic degradation and poor lung targeting associated with dosing via the oral and intravenous routes, respectively, are circumvented. Local delivery into the lungs may enable dose reduction, reduce systemic side effects, and avoid first past metabolism. However, several challenges are associated with pulmonary delivery, including the intrinsic barriers in the lungs, constraints related to dosage forms, e.g., the aerodynamic particle properties, and the complex immunopathogenesis of the disease, e.g., COPD. For pulmonary delivery, solid dosage forms are preferred for macromolecules and nanoparticles because they are cheaper, possess prolonged shelf-life, and do not require the so-called cold-chain, as compared to liquid dosage forms. Processes frequently used to manufacture solid dosage forms include freeze drying and spray drying. The siRNA-loaded nanoparticles are suspended in a solution containing a stabilizing excipient, e.g., mannitol or trehalose, and lyophilized, resulting in microparticles in which the nanoparticles are embedded. During spray drying, the liquid LPN dispersion containing stabilizing excipient(s) is aerosolized and dried, allowing for the engineering of microparticles with a specific mass median aerodynamic diameter (MMAD), which dictates lung deposition. We have identified a stabilizer and optimized spray drying parameters critical for the design of inhalable solid dosage forms of TNF-α siRNA-loaded LPNs. In addition to the MMAD, a number of other physicochemical properties of the dry powder determine the aerosol performance, lung deposition, and ultimately the therapeutic efficacy of the cargo, and they include particle shape, surface morphology, moisture content, and crystallinity. Here, we describe protocols for measuring these solid state properties using spray-dried, TNF-α siRNA-loaded LPNs.

肺部给药在靶向递送 siRNA 以治疗肺部疾病（如慢性阻塞性肺疾病（COPD））方面展现了良好的前景，因为它能够绕过通过口服和静脉给药所带来的全身降解和肺部靶向差的问题。局部递送可以减少药物剂量，降低全身副作用，并避免首过效应。然而，肺部给药存在一些挑战，包括肺部的天然屏障、与剂型相关的限制（如气动粒子性质）以及疾病的复杂免疫病理机制。相对于液体剂型，固体剂型对于大分子和纳米颗粒更为适用，因为固体剂型成本较低、保质期较长，并且不需要冷链。常用的固体剂型制造工艺包括冻干和喷雾干燥。siRNA 负载的纳米颗粒在含有稳定剂（如甘露醇或海藻糖）的溶液中悬浮后进行冻干，形成嵌入纳米颗粒的微粒。在喷雾干燥过程中，含稳定剂的液体 LPN 分散液被雾化并干燥，从而可以制备出具有特定质量中位气动直径（MMAD）的微粒，这决定了其在肺部的沉积情况。我们已经确定了一种稳定剂，并优化了喷雾干燥的关键参数，这对设计可吸入的 TNF-α siRNA 负载 LPN 固体剂型至关重要。除了 MMAD 外，干粉的其他一些物理化学性质也会影响气溶胶性能、肺部沉积和最终的治疗效果，包括粒子形状、表面形态、含水量和结晶度。本文中，我们描述了使用喷雾干燥的 TNF-α siRNA 负载 LPN 来测量这些固态性质的方法。👀

2 Materials 材料

1. Glassware and plasticware: All glassware and plasticware used for the preparation, storage, and processing of LPNs should be free from RNases. The glassware can be baked at 180 °C for at least 8 h, while RNase-free plasticware can be purchased commercially. For freeze drying, 6R glass vials (2827576, Buch and Holm A/S, Herlev, Denmark) are used. 玻璃和塑料器皿：所有用于制备、存储和处理 LPNs 的玻璃和塑料器皿必须不含 RNase。玻璃器皿可以在 180°C 下烘烤至少 8 小时，而无 RNase 的塑料器皿可以直接购买。冻干使用的玻璃瓶为 6R 型号（编号 2827576，来自丹麦赫勒夫的 Buch 和 Holm A/S）。

2. DEPC-treated water: 0.1% (v/v) diethylpyrocarbonate was mixed with Milli-Q® integral ultrapure water (Type 1) with vigorous shaking. Incubate the solution overnight, in the dark, at room temperature. Autoclave at 121° C for 30 min and allow to cool before use. DEPC 处理水：将 0.1%（体积比）的二乙基焦碳酸酯与 Milli-Q®超纯水（1 级）混合，充分摇匀。将该溶液在黑暗中室温放置过夜孵育。然后，在 121°C 下高压灭菌 30 分钟，冷却后方可使用。

3. Tris-EDTA (TE) buffer (100× concentrate): When diluted to 1×, it contains 10 mM Tris–HCl and 1 mM disodium EDTA (pH 8.0). Tris-EDTA（TE）缓冲液（100 倍浓缩）：稀释至 1 倍时，包含 10 mM Tris-HCl 和 1 mM 二钠 EDTA（pH 8.0）。

4. siRNA stock solution: 2′-O-methyl-modified Dicer substrate asymmetric siRNA duplex directed against TNF-α (TNF-α siRNA, 17,928.334 g/mol) was generously provided by GlaxoSmithKline (GSK, Stevenage, UK) as dried, purified, and desalted duplexes (Table 1 ( clbr://internal.invalid/OEBPS/html/485053_1_En_9_Chapter.xhtml#Tab1 )). Weigh an amount that will result in a final siRNA concentration of 1 mM in an RNase-free microcentrifuge tube and dissolve it in TE buffer. Reanneal the strands by denaturing the solution at 94 °C for 2 min, followed by gradual cooling at room temperature for reannealing, and store the stock solution at −20 °C in RNase-free microcentrifuge tubes. siRNA 储备溶液：针对 TNF-α的 2'-O-甲基修饰的 Dicer 底物非对称 siRNA 双链（分子量 17928.334 g/mol）由葛兰素史克（GSK，英国斯蒂文尼奇）提供，经过干燥、纯化和脱盐处理。称取适量，使 RNase 无菌离心管中的终浓度为 1 mM，并溶解于 TE 缓冲液中。将溶液在 94°C 加热 2 分钟使其变性，然后在室温下慢慢冷却退火。储备溶液保存在-20°C 的无菌微量离心管中。

5. LPNs loaded with an siRNA prepared as described previously. 已按照前述方法制备的 siRNA 负载 LPNs。

6. A solution of 2% (w/v) polyvinyl alcohol (PVA) in DEPC-treated water. 在 DEPC 处理水中制备 2%（重量/体积比）聚乙烯醇（PVA）溶液。

7. A solution of 5% (w/v) trehalose dihydrate in DEPC-treated water. 在 DEPC 处理水中制备 5%（重量/体积比）海藻糖二水合物溶液。

8. A solution of 5% (w/v) mannitol in DEPC-treated water. 在 DEPC 处理水中制备 5%（重量/体积比）甘露醇溶液。

9. Design Expert Software (Stat Ease Inc., Minneapolis, MN, USA). Design Expert 软件（来自美国明尼阿波利斯的 Stat Ease Inc.）。

10. Epsilon 1-4 LSCplus freeze dryer (Martin Christ, Osterode am Harz, Germany).Epsilon 1-4 LSCplus 冻干机（来自德国的 Martin Christ 公司）。

11. Mini Spray Dryer B-290 equipped with a high performance cyclone separator for small particles (BÜCHI Labortechnik, Flawil, Switzerland). Mini Spray Dryer B-290 喷雾干燥机，配备高性能小颗粒旋风分离器（瑞士 Flawil 的 BÜCHI Labortechnik 公司）。

12. Thermogravimetric analyzer Discovery TGA 550 with TRIOS software (TA Instruments, New Castle, DE, USA). Reusable platinum pans (TA Instruments, Taastrup, Denmark) with a capacity of 100 μL are utilized for loading the powders. Discovery TGA 550 热重分析仪，配有 TRIOS 软件（来自美国特拉华州的 TA Instruments 公司）。使用 100 μL 容量的可重复使用铂盘（TA Instruments，丹麦 Taastrup）来装载粉末。

13. Aerodynamic Particle Sizer Spectrometer 3321 equipped with a small scale powder disperser and Aerosol Instrument Manager software (TSI Instruments, Shoreview, MN, USA). 气动粒子粒径分析仪 3321，配备小型粉末分散器和气溶胶仪器管理软件（来自美国明尼苏达州的 TSI Instruments 公司）。

14. Cressington Sputter Coater 108 (Cressington Scientific Instruments, Watford, UK). Cressington Sputter Coater 108 镀膜机（来自英国沃特福德的 Cressington Scientific Instruments 公司）。

15. Hitachi TM3030 Scanning Electron Microscope (Hitachi High-Technologies, Solna, Sweden). Hitachi TM3030 扫描电子显微镜（来自瑞典 Solna 的 Hitachi High-Technologies 公司）。

16. XPERT PRO X-Ray diffractometer with a PW3050/60 generator and PIXcel Detector and X’Pert Data Collector software for data analysis (PANalytical, Almelo, Netherlands). XPERT PRO X 射线衍射仪，配有 PW3050/60 发电机和 PIXcel 检测器，并配备用于数据分析的 X'Pert Data Collector 软件（荷兰阿尔梅洛的 PANalytical 公司）。

Table 1 TNF-α siRNA sequences and modification patterns. Upper case letters represent ribonucleotides, lower case letters represent deoxyribonucleotides, underlined capital letters represent 2′-O-methylribonucleotides, and p is a phosphate residue

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3 Methods 方法

3.1 Design of Experiment (DoE) 实验设计

To design and set up the experiment, the Design Expert® program is used. An Ishikawa or fishbone diagram is utilized for risk assessment (Fig. 1A) . To design a TNF-α siRNA-loaded LPN formulation with the desired physicochemical properties and in vitro performance, the QTPP is defined (Fig. 1B) based on the CQAs (Fig. 1C, Table 2). The process parameters (Fig.1D) are kept constant because the processes related to LPN preparation have been optimized previously. Based on previous data, the L5 content is varied at three levels (15–25%, w/w), while the L5:TNF-α siRNA weight ratio is varied at four levels from 15:1 to 5:1 (Table 3, Fig. 1E, see Note 1). The response surface DoE used in the experiments represents a randomized, I-optimal (see Note 2), custom design (Fig. 2) to accommodate two continuous numeric factors [the L5 content (%, w/w) and the L5:TNF-α siRNA weight ratio] where no categorical factors are varied (Table 3) for a total of 12 design points. These points are replicated with one additional design point so that the total number of runs is 25. A total of seven responses to the CFPs are measured. It is recommended to use the highest order models, which are not aliased to fit the data, and in this case, it is quadratic (see Note 3).

为了设计和设置实验，使用了 Design Expert®程序。风险评估通过 Ishikawa 或鱼骨图进行（图 1A）。为了设计具有理想理化性质和in vitro性能的 TNF-α siRNA 负载 LPN 配方，首先定义了 QTPP（图 1B），基于 CQAs（图 1C，表 2）。过程参数（图 1D）保持不变，因为与 LPN 制备相关的工艺已经经过优化。根据先前的数据，L5 含量在三个水平上变化（15–25%，w/w），而 L5:TNF-α siRNA 的重量比在四个水平上变化，从 15:1 到 5:1（表 3，图 1E，见注 1）。实验中使用的响应面 DoE 为随机化的 I-optimal（见注 2）定制设计（图 2），以适应两个连续的数值因素 [L5 含量（%，w/w）和 L5:TNF-α siRNA 的重量比]，且没有分类因素的变化（表 3），设计点总数为 12 个。为了获得总共 25 次实验运行，这些点经过一次额外的设计点复制。总共测量了七个响应变量。建议使用不具别名的最高阶模型来拟合数据，在本例中为二次模型（见注 3）。

Table 2 Quality target product profile and critical quality attributes

^aEC₅₀ = Effective concentration for 50% effect

^bIC₅₀ = Inhibitory concentration for 50% effect

Table 3 Critical formulation parameters investigated for the design of experiment

Fig. 2 Workflow for using Design-Expert® in response surface methodology for optimizing the loading of siRNA into LPNs

3.1.1 Statistical Model Optimization 统计模型优化

1. The model is evaluated using prediction-based metrics via Fraction of Design Space (FDS) statistics because the goal for optimization is to maximize the predictability of the responses rather than screening (Table 4). The standard error of mean (SEM) should be as low as possible in a maximal FDS (Fig. 3a). In this case, the SEM is 0.479 in 95% of the design space (Fig. 3b), which is in agreement with the guidelines recommended by Stat-Ease Inc. 通过设计空间分数（FDS）统计数据进行预测基础的指标评估模型，因为优化的目标是最大化响应的可预测性，而非筛选（表 4）。最大 FDS 中的标准误差（SEM）应尽可能低（图 3a）。在本案例中，设计空间 95%的范围内的 SEM 为 0.479（图 3b），这与 Stat-Ease Inc.推荐的指导原则一致。

2. The next step is to analyze the responses to the CFPs using analysis of variance (ANOVA), which can be found on the left panel of Design-Expert® under the title “Analysis” and then responses. For the sake of simplicity, only one response (the zeta potential) is described in this protocol (Fig. 4a). A detailed explanation of these values can be found in the program under the ANOVA section. 下一步是使用方差分析（ANOVA）来分析 CFPs 的响应，相关内容可在 Design-Expert®左侧面板中“Analysis”标题下找到，然后选择响应。为了简化起见，本方案中只描述了一个响应（zeta 电位）（图 4a）。这些数值的详细解释可以在程序的 ANOVA 部分找到。

3. The predicted R2 value of 0.962 is in reasonable agreement with the adjusted R2 of 0.979, i.e., the difference is less than 0.2 (Fig. 4b, Table 5). The adequate precision is a measure for the signal-to-noise ratio. A ratio larger than four is desirable. A ratio of 42.93 indicates an adequate signal-to-noise ratio. Hence, this model can be used to navigate through the design space. 预测的R²值为 0.962，与调整后的R²值 0.979 基本一致，即差异小于 0.2（图 4b，表 5）。适当的精度是信噪比的衡量标准，所需比率应大于 4。42.93 的比率表明具有足够的信噪比。因此，该模型可以用于设计空间的导航。

4. From the above results, it is evident that the zeta potential is significantly affected by the CFPs and that the model is valid for navigation throughout the design space (see Note 4). 从上述结果可以明显看出，zeta 电位显著受到 CFPs 的影响，且该模型对于设计空间内的导航是有效的（见注 4）。

Table 4 Statistical analysis of the I-optimal, custom, quadratic model based on 25 experimental design points

^adf: Degree of freedom

Fig. 3 Fraction of the design space plot displaying the numerical cover of the design space with mean standard error (a) and a three-dimensional plot of critical formulation parameters displaying the design space with the standard error of design (b). Red circles represent experimental data points in duplicates

Fig. 4 Scatter plot showing the agreement between predicted and measured values of the zeta potential (a) and a three-dimensional plot showing the effect of critical formulation parameters on the zeta potential (b). Red circles represent experimental data points in duplicates

Table 5 Statistical parameters depicting the zeta potential in relation to the design

3.1.2 Determining the Optimal Operating Space 确定最佳操作空间

The optimal operating space (OOS) represents the part of the experimental design space where the criteria defined by the QTPP are met (Fig. 5a). The OOS is identified by separately modeling all the responses, as explained above, and then utilizing a numerical and graphical optimization tool, which can be found in the Design-Expert® program under the heading “Optimization” under Analysis. The criteria can be modified according to the desired responses and characteristics of the LPNs (Fig. 1F). As examples, the zeta potential and polydispersity index (PDI) are modeled. Modeling of the former results in numerous solutions based on the input and the desired range, followed by assigning a desirability score (0 to 1) to the combination of CFPs (Fig. 5b). The desirability score should not necessarily be high because it depends on how well the agreement is between the input and the desired numbers, rather than the absolute value. A graphical optimization plot (Fig. 5a) is a semiquantitative overlay plot of the OOS superimposed on the original design space, providing a visual representation that can be adjusted graphically by changing contour lines (see Note 5).

最佳操作空间（OOS）是实验设计空间中满足 QTPP 定义标准的部分（图 5a）。OOS 通过分别建模所有响应来确定，如上所述，然后使用 Design-Expert®程序中“Optimization”工具进行数值和图形优化，路径为“Analysis”下的“Optimization”。可以根据 LPN 的期望响应和特性修改标准（图 1F）。以 zeta 电位和多分散指数（PDI）的建模为例。对前者进行建模后，会根据输入值和期望范围产生多个解决方案，并为 CFP 组合分配可取性评分（0 到 1）（图 5b）。可取性评分不必过高，因为它取决于输入与期望数值之间的一致性，而非绝对值。图形优化图（图 5a）是将 OOS 叠加在原始设计空间上的半定量叠加图，提供了可以通过改变等高线图进行调整的视觉表示（见注 5）。

Fig. 5 Overlay plot of the original design space (gray) and the optimal operating space (yellow) (a). Desirability plot displaying the optimal L5 content and L5:TNF-α siRNA weight ratios at which both the responses (zeta potential and PDI) fulfill the criteria (all colors except dark blue, for which one additional criterion is not met) (b). Red circles represent experimental data points in duplicates

3.1.3 Constructing the Plots 绘制图表

1. For all responses, analyze the data by ANOVA using the highest order model that is not aliased. 对所有响应使用最高阶非混淆模型，通过 ANOVA 进行数据分析。

2. Set the desired lower and upper values for the responses found under the criteria tab. In this case, the target is a zeta potential in the range of 15–30 mV, while for the PDI, the lower value is set to 0.0 with an upper limit of 0.15 (see Note 6). 在“Criteria”选项卡下设置响应的期望下限值和上限值。在本例中，zeta 电位的目标范围设定为 15–30 mV，而 PDI 的下限值设定为 0.0，上限值设定为 0.15（见注 6）。

3. Combine all responses by clicking on solutions, which provide a numerical point value of the CFPs where all the responses meet the pre-set criteria. 通过点击“Solutions”按钮，结合所有响应，提供一个数值点，即在此 CFP 组合下所有响应均满足预设标准。

4. Under the “Graphs” tab, select the response as desirability and change the graph type to contour plots. 在“Graphs”选项卡中，选择“Desirability”作为响应，并将图表类型更改为等高线图。

5. The region shaded toward the red (Fig. 5b) represents the optimal L5 content and L5:TNF-α siRNA weight ratio where both responses (zeta potential and PDI) display the desired values (see Note 7). The edge of failure is the boundary between the blue region and the other colored regions, where either one or more responses do not fulfill the set criteria (Fig. 1G). 图中向红色区域（图 5b）阴影部分代表最佳的 L5 含量和 L5:TNF-α siRNA 重量比，在该区域 zeta 电位和 PDI 均显示期望值（见注 7）。边界失效点是蓝色区域和其他彩色区域之间的分界线，在该分界线处一个或多个响应未能满足设定标准（图 1G）。

6. The overlay plot can be constructed by selecting Graphical Optimization and entering the desired values. The black contour lines on the graph can be adjusted to visualize how the responses affect the operating space. 可通过选择图形优化（Graphical Optimization）构建叠加图，并输入期望值。可以调整图表上的黑色等高线，以可视化响应如何影响操作空间。

3.2 Freeze Drying 冻干

The liquid TNF-α siRNA-loaded LPN dispersions are freeze-dried using trehalose as the stabilizing excipient.

TNF-α siRNA 负载的 LPN 液体分散体使用海藻糖作为稳定剂进行冻干。

1. For each 2 mL LPN batch, place a total of three glass vials in a laminar flow cabinet. 在层流柜中为每个 2 mL 的 LPN 批次准备共三个玻璃瓶。

2. Add 1.67 mL 10% (w/v) trehalose solution and 1.67 mL LPN dispersion to each glass vial and mix several times by pipetting. The total volume is 3.34 mL (see Note 8). 向每个玻璃瓶中加入 1.67 mL 10% (w/v)的海藻糖溶液和 1.67 mL 的 LPN 分散液，并通过移液器多次混合。总容量为 3.34 mL（见注 8）。

3. Carefully transfer 1.1 mL of the mixture to the bottom of the remaining three vials (see Note 9). 小心将 1.1 mL 混合物转移到剩余三个玻璃瓶的底部（见注 9）。

4. Insert RNase-free butyl rubber caps partially onto the necks of the vials to allow the water to evaporate during the freeze-drying cycle. 将 RNase-free 丁基橡胶帽部分插入瓶颈，以便在冻干过程中让水分蒸发。

5. Carefully place the filled glass vials on a pre-cooled shelf (+5 °C) of the freeze dryer. 将装满的玻璃瓶小心地放置在冻干机的预冷货架上（+5 °C）。

6. Close the door and the aeration valve of the freeze dryer and run the program (Table 6). 关闭冻干机的门和通风阀，并运行程序（表 6）。

7. After completion of the program, close the vials entirely by turning the vial stoppering device. 程序完成后，通过转动瓶塞装置完全密封瓶子。

8. Repressurize the freeze dryer slowly with atmospheric air by partially opening the aeration valve. 通过部分打开通风阀，慢慢将冻干机重新加压至大气压。

9. After complete repressurization, remove the freeze-dried LPNs and store them at 4 °C. 完全加压后，取出冻干的 LPN 并将其存放在 4 °C。

Table 6 Freeze-drying parameters

^aMn = Main drying

^bFn = Final drying

^cdT = Time increment

3.3 Spray Drying 喷雾干燥

The liquid dispersions of TNF-α siRNA-loaded LPNs are spray dried using mannitol as stabilizing excipient. The dry powder LPN microparticles are separated from the airstream by centrifugal forces using a high-performance cyclone. The spray drying settings used are as follows: a feed flow rate 0.3 mL/min, an outlet temperature of 50 °C, an aspirator capacity of 90%, and an atomizing airflow of 742 L/h.

TNF-α siRNA 负载的 LPN 液体分散体采用甘露醇作为稳定剂进行喷雾干燥。通过使用高性能旋风分离器，利用离心力将干粉 LPN 微粒与气流分离。喷雾干燥的设置如下：进料流速为 0.3 mL/min，出口温度为 50 °C，吸气器容量为 90%，雾化气流量为 742 L/h。

3.3.1 Preparation of the Feedstock Dispersion for Spray Drying 喷雾干燥的进料分散液制备

1. The total volume of the feedstock dispersion should be 10 mL. In the 10 mL volume, the total solid content, i.e., the LPNs and mannitol, should be 250 mg out of which the LPNs constitutes 5% (w/w). This corresponds to 12.5 mg LPNs and 237.5 mg mannitol. 进料分散液的总体积应为 10 mL。在这 10 mL 的体积中，总固体含量（即 LPN 和甘露醇）应为 250 mg，其中 LPN 占 5% (w/w)。这对应于 12.5 mg LPN 和 237.5 mg 甘露醇。

2. In a glass container, pipette 4.75 mL mannitol solution (5% w/v), 1.67 mL LPN dispersion, and 3.58 mL DEPC-treated water. Pipette up and down to mix. 在一个玻璃容器中，移液加入 4.75 mL 甘露醇溶液(5% w/v)，1.67 mL LPN 分散液，和 3.58 mL DEPC 处理水。上下移液混合。

3.3.2 The Spray Drying Process 喷雾干燥过程

1. Assemble the spray drying chamber, the two-fluid nozzle, the feed tube, the connectors, the cyclone separator, and the collection vial. 组装喷雾干燥室、双流体喷嘴、进料管、连接器、旋风分离器和收集瓶。

2. Connect the outlet of the spray dryer to the dehumidifier. 将喷雾干燥器的出口连接到除湿机。

3. Before turning on the spray dryer, ensure that the atomizing gas (nitrogen) inlet valve is open, the dehumidifier is turned on, and that proper ventilation systems are in place.在启动喷雾干燥器之前，确保雾化气体（氮气）入口阀门打开，除湿机已开启，并且适当的通风系统已就位。

4. Switch on and configure the spray dryer: set the atomization airflow to 742 L/h (corresponds to 60 mm on the Q-flow indicator), the inlet temperature to 70 °C, and the aspirator capacity to 90%. The desired outlet temperature of 50 °C is achieved with the above configuration, when the peristaltic pump is set to 5%. 打开并配置喷雾干燥器：将雾化气流量设定为 742 L/h（相当于 Q-flow 指示器上的 60 mm），将入口温度设定为 70 °C，吸气器容量设定为 90%。当蠕动泵设定为 5%时，以上配置可实现所需的 50 °C 出口温度。

5. Turn on the inlet temperature, the aspirator, and the peristaltic pump. When the inlet temperature rises above 40 °C, start pumping in MilliQ water. 打开入口温度、吸气器和蠕动泵。当入口温度上升到 40 °C 以上时，开始泵入 MilliQ 水。

6. When the inlet and outlet temperatures are stabilized at the predefined values, remove the feed tube from the MilliQ water and put it in the glass vial containing the LPN dispersion. 当入口和出口温度稳定在预设值时，将进料管从 MilliQ 水中移出，放入装有 LPN 分散液的玻璃瓶中。

7. After the LPNs are spray-dried, place the feed tube in the MilliQ water to rinse the system for any remaining product. LPN 喷雾干燥完成后，将进料管放入 MilliQ 水中，以冲洗系统中的残余产品。

8. Turn off the aspirator, the pump, the air inlet valve, and the dehumidifier, followed by disassembly of the individual parts. All parts should be washed and dried with compressed air. 关闭吸气器、泵、空气入口阀和除湿机，随后拆卸各个部件。所有部件都应清洗并用压缩空气干燥。

9. The powder in the collection vial can be collected by scraping the walls with a soft spatula (see Note 10). 可以通过使用软铲刮取收集瓶壁上的粉末来收集粉末（见注释 10）。

3.3.3 Powder Yield 粉末收率

The powder yield is measured as the weight difference between the collected powder compared and the initial total solid content of the dispersions before spray drying. It is calculated as the weight difference of the collection vial before and after spray drying divided by the initial total solid content of the dispersions (Eq. 1).粉末收率通过比较喷雾干燥前分散液的初始总固体含量与收集的粉末重量差异来衡量。其计算方法为喷雾干燥前后收集瓶的重量差异除以分散液的初始总固体含量（公式 1）。

Powder Yield %=Wt.of collection vial after spray drying mg−Wt.of collection vial before drying mgInitial total solid content mg×100

3.4 Moisture Content 水分含量

The residual moisture content in the dry powders is determined by thermogravimetric analysis (TGA) after heating approximately 10 mg of the samples at a constant rate of 30 °C/min up to 300 °C The water loss caused by evaporation is calculated in percent and defined as the moisture content.

干粉中的残留水分含量通过热重分析 (TGA) 来确定，方法是以恒定速率 30 °C/min 加热约 10 mg 样品至 300 °C。蒸发引起的失水量以百分比计算，并定义为水分含量。

3.4.1 Sample Preparation and Loading 样品制备与加载

1. In case the pans are reusable, burn them for a few seconds with an oxidizing flame and remove the charred residue, if any, with a soft-bristled brush. 如果使用可重复使用的坩埚，用氧化火焰烧坩埚几秒钟，并用软毛刷清除任何残留的炭化物。

2. Handle the pans by the bow with a blunt tweezer. 使用钝镊子从弓部处理坩埚。

3. Place the cleaned pans in the autosampler and note the direction in which they are placed (see Note 11). 将清洁后的坩埚放入自动进样器中，并记录它们的放置方向（见注释 11）。

4. In the TRIOS program, calibrate the weight of the pans using the tare function. 在 TRIOS 软件中，使用去皮功能校准坩埚的重量。

5. Note down the pan numbers in the autosampler and select the pans that should be calibrated. 记录自动进样器中的坩埚编号，并选择需要校准的坩埚。

6. Carefully remove the pans from the autosampler and fill them with approximately 15 mg spray-dried LPN powder, which will cover the bottom of the pans (see Note 12). 小心地从自动进样器中取出坩埚，并加入约 15 mg 喷雾干燥的 LPN 粉末，使粉末均匀覆盖坩埚底部（见注释 12）。

7. Place the pans in the autosampler in the same position as they were tared. 将坩埚放回自动进样器中，保持与去皮时相同的位置。

8. Navigate to “Experiments” in the software and create a new experiment. 导航到软件中的“实验”选项，创建一个新实验。

9. Set up the experiment with a temperature range from 30 to 300 °C and a ramp of 30 °C/min and start the experiment. 设置实验温度范围为 30 至 300 °C，升温速率为 30 °C/min，并启动实验。

10. After the experiment, allow the instrument to cool down. 实验结束后，让仪器冷却。

11. Data can be analyzed by clicking on Results and opening the experiment file. 通过点击“结果”并打开实验文件，可以对数据进行分析。

12. Right-click on the curve where the weight is 100%, click on Analyze, and then Weight change. 右键点击重量为 100%的曲线，点击“分析”，然后选择“重量变化”。

13. Drag the black, cross-haired circle to a point just after the drop in weight at around 120 °C and accept the change. 将黑色的十字光标圆圈拖动至大约 120 °C 处的重量下降点，确认变化。

14. At this temperature, the weight change in the sample can be attributed to the loss of moisture (Fig. 6). 在此温度下，样品的重量变化可归因于水分的损失（图 6）。

Fig. 6 Representative thermogravimetric analysis plot of spray-dried siRNA-loaded lipidoid-polymer hybrid nanoparticles

3.5 Aerodynamic Particle Size 动力学粒径

The MMAD of the spray-dried powders is measured using an aerodynamic particle sizer.

喷雾干燥粉末的质量中位空气动力学直径（MMAD）通过空气动力学粒径分析仪测量。

1. Adjust the air capillary flow rate to 5 L/min. 将气流毛细管的流速调整至 5 L/min。

2. Place the spray-dried powders on the sample disc and gently spread the powders with the supplied soft-bristle brush at appropriately spaced positions. 将喷雾干燥的粉末放在样品盘上，并使用提供的软毛刷将粉末轻轻均匀地铺在适当的间隔位置。

3. Carefully dock the sample disc on the turntable, direct the tube on the sample path, set the rotation rate to 7, clockwise (CW) or counter-clockwise (CCW). 小心地将样品盘固定在旋转台上，将管子对准样品路径，将旋转速率设置为 7，顺时针 (CW) 或逆时针 (CCW) 旋转。

4. Create a new experiment, save the data file, and start data collection. 创建一个新实验，保存数据文件，并开始数据收集。

5. Note down the results from the statistics table and save the aerodynamic diameter graph. Figure 7 shows a population distribution of particles displaying an aerodynamic diameter 1–6 μm and an MMAD 3.3 μm. 从统计表中记录结果，并保存空气动力学直径图。图 7 显示了粒子的分布，空气动力学直径为 1–6 μm，MMAD 为 3.3 μm。

Fig. 7 Representative aerodynamic particle size distribution of spray-dried siRNA-loaded lipidoid-polymer hybrid nanoparticles measured by using an Aerodynamic Particle Sizer spectrometer equipped with a Small-Scale Powder Disperser. The mass median aerodynamic diameter (MMAD) was estimated to be approximately 3.3 μm

3.6 Surface Morphology 表面形态

The morphology of the spray-dried particles is examined by scanning electron microscopy (SEM) operated at an accelerating voltage of 15 kV, a working distance of 5.8 mm, and an emission current of 53,500 mA.

喷雾干燥颗粒的形态通过扫描电子显微镜（SEM）在加速电压为 15 kV，工作距离为 5.8 mm，和发射电流为 53,500 mA 的条件下进行检查。

3.6.1 Sample Preparation and Loading 样品制备与加载

1. Place a double-sided conductive carbon adhesive tape on the stub making sure to secure it firmly. 将双面导电碳胶带粘在样品台上，确保其牢固固定。

2. With the help of a metal spoon, sprinkle the powder on the carbon tape (see Note**13). 用金属勺将粉末撒在碳胶带上 (*参见注 *13)。

3. Gently tap the stub on a hard surface to remove excess powder. 轻轻敲击样品台表面，以去除多余的粉末。

4. Lift the lid of the surface coating chamber, remove the glass tube, transfer the stub, which has the sample on it to the plate inside the chamber, put the glass tube back to its position, and close the lid of the chamber. 打开表面涂层腔的盖子，取下玻璃管，将样品台转移到腔内的托盘上，放回玻璃管并关闭腔室盖子。

5. Switch on the sputter coater. In the “Auto” mode, press the “Cycle” button until the display shows “20,” and start the coater (see Note 14). 打开溅射镀膜机，在“自动”模式下，按“Cycle”按钮直到显示屏显示“20”，然后开始镀膜 (参见注 14)。

6. Switch off the coater and remove the stub when the chamber is repressurized (see Note 15). 镀膜结束后，关闭镀膜机，当腔室重新加压后取出样品台 (参见注 15)。

3.6.2 Scanning Electron Microscopy 扫描电子显微镜操作

1. Run the TM3030 software and evacuate the microscope (Note the blue LED for EVAC/AIR). 启动 TM3030 软件并对显微镜进行排气操作（注意 EVAC/AIR 的蓝色 LED 灯）。

2. When the sample is ready, repressurize the system and open the sample chamber. 当样品准备好后，重新加压系统并打开样品腔室。

3. Place the stub on the specimen holder by screwing it to the stick followed by placing the specimen holder on the black stage. 将样品台固定在样品架上，并将样品架放置在黑色平台上。

4. Adjust the height of the specimen holder by loosening the two screws that hold them at the bottom. Tighten the screws once the position is fixed (see Note 16). 调整样品架的高度，通过松开底部的两颗螺丝调整位置，调整好后固定螺丝 (参见注 16)。

5. Place the specimen holder in the microscope chamber. Adjust the position in such a way that the crosshair (+) is aligned with the tip of the triangle. Evacuate the chamber and capture the data. 将样品架放入显微镜腔室，调整位置，使十字准线（+）与三角形尖端对齐。排气腔室并开始数据采集。

6. Set the observation view, magnification, adjust brightness and contrast, autofocus the image, and select slow scanning speed. 调整视图，放大倍数，调整亮度和对比度，自动对焦图像，并选择慢速扫描。

7. Capture the image when it is wholly focused and stop data acquisition (Fig. 8). 当图像完全对焦时，捕捉图像并停止数据采集（图 8）

8. Take out the sample after repressurizing the chamber. 当腔室重新加压后，取出样品。

Fig. 8 Representative scanning electron microscopy image of spray-dried siRNA-loaded lipidoid-polymer hybrid nanoparticles, microscopic magnification 2000×

3.7 Solid State Properties 固态性质

The solid state properties of the dry powders are characterized using X-ray powder diffraction (XRPD).

干粉的固态性质通过 X 射线粉末衍射（XRPD）进行表征。

3.7.1 Sample Preparation and Loading

1. Turn on the X-Ray Powder Diffractometer and start the program “Data Collector.” 打开 X 射线粉末衍射仪并启动程序“Data Collector”。

2. Create a new program with an absolute scan, change the detector value to X’Celerator, enter the details as shown in Table 7, and save the program. 创建一个新的绝对扫描程序，将检测器值改为 X’Celerator，输入表[7]()中的详细信息，并保存程序。

3. On the instruments tab toward the left of the screen, double-click on Sample Changer: Changer PW3065/00 (15 positions) and click on Reset button.在屏幕左侧的仪器选项卡上，双击“Sample Changer: Changer PW3065/00（15 个位置）”，然后单击重置按钮。

4. In the same tab, head over to X-ray tab and enter 45 kV for tension and 10 mA for the current. 在同一选项卡中，进入 X 射线选项卡，输入电压为 45 kV，电流为 10 mA。

5. Distribute the spray-dried TNF-α siRNA-loaded LPNs and mannitol evenly on the aluminum sample holders. 将喷雾干燥的 TNF-α siRNA 载 LPNs 和甘露醇均匀分布在铝制样品托盘上。

6. Load the sample holders into the magazine. The positions are numbered from 1 to 15 (top to bottom). 将样品托盘加载到样品更换器中。位置从 1 到 15 编号（从上到下）。

7. Place the magazine in the sample changer such that the two alignment holes at the bottom go directly into the alignment pins. 将样品更换器放置在样品更换器中，使底部的两个对齐孔直接进入对齐销。

8. The numbered side should face toward the operator, i.e., toward the glass door, away from the goniometer. 编号的一面应面向操作员，即面向玻璃门，远离测角仪。

9. Adjust the power of the generator to 45 kV and 40 mA. 将发电机功率调整到 45 kV 和 40 mA。

10. Open the program, click on Measure, select the saved program, and click OK to start the measurement. 打开程序，点击“Measure”，选择保存的程序，然后点击确定开始测量。

11. Ensure that the shutter is closed, turn down the voltage to 40 kV, and the current to 10 mA. 确保快门关闭，将电压调低至 40 kV，电流调低至 10 mA。

12. Run the X’Pert High Score Plus program and open the XRDML file. 运行 X’Pert High Score Plus 程序并打开 XRDML 文件。

13. Click on the Treatment tab and determine the background. 点击“Treatment”选项卡并确定背景。

14. Subtract the background and accept the changes. 减去背景并接受更改。

15. The diffractograms can be exported as they are. The anchor scan data can be copied, if needed, to plot in other programs. 衍射图可以按原样导出。如果需要，可以复制锚定扫描数据，以在其他程序中绘制。

16. Diffractograms from the two sample types can be compared for crystallinity and amorphization based on the peaks obtained. The spray-dried LPNs are crystalline, as intense peaks are observed (Fig. 9). Some of the crystallinity of spray-dried mannitol is lost, which may indicate amorphization due to the LPNs. 可以比较两种样品的衍射图以确定结晶性和非晶化。喷雾干燥的 LPNs 表现为晶态，因为观察到强烈的衍射峰（图 9）。部分喷雾干燥甘露醇的结晶性丧失，这可能表明由于 LPNs 的存在导致了非晶化。

Table 7Configuration for absolute scan measurement program for measuring X-ray powder diffraction

Fig. 9 Representative X-ray powder diffraction patterns of spray-dried mannitol (black) and siRNA-loaded lipidoid-polymer hybrid nanoparticles (blue). Both samples exhibit similar diffraction patterns, which reflect their crystalline nature

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4 Notes 注释

1. Calculations of the amounts and volumes used in formulating TNF-α siRNA-loaded LPNs. An example of the calculations for a formulation with an L5 content of 15% (w/w) and an L5:TNF-α siRNA weight ratio of 15:1 is provided belowTNF-α siRNA 载 LPNs 制剂的计算示例。以 L5 含量为 15%（w/w）、L5:TNF-α siRNA 质量比为 15:1 的配方为例：

   (a) 最终批次重量（mg） = L5 重量（mg）+ PLGA 重量（mg）= 15 mg。

   (b)L5 含量 (占总批次重量的 15% w/w) =

   15100×15=2.25 mg。

   (c) PLGA 重量（mg） = 最终批次重量（mg）− L5 重量（mg）= 15 − 2.25 = 12.75 mg。

   (d) TNF-α siRNA 储备液浓度 = 18 mg/mL。

   (e) TNF-α siRNA 量（mg） =

   115×2.25=0.15 mg。

   (f)TNF-α siRNA 体积（μL） =0.1518=0.0083 mL=8.3 μL。

2. I-optimal designs (also referred to as IV or Integrated Variance) provide lower average prediction variance across the region of experimentation. I-optimality is desirable for response surface methods (RSM) where prediction is important. I-最佳设计 (I-optimal designs) 或称为 IV（集成方差）设计，在实验区域内提供较低的平均预测方差。I-最佳设计对于响应面方法（RSM）尤其适用，尤其当预测至关重要时

3. When a model is selected in Design-Expert® software, make sure to go through all the evaluation parameters, especially lack of fit and aliasing. Correct the model by excluding specific terms from the equation. Design-Expert® 软件中的模型选择，确保评估所有参数，特别是拟合缺失和别名效应。可以通过从方程中排除特定项来修正模型。

4. All responses may not be significant and should be carefully analyzed when evaluating the statistical parameters. 响应结果分析，并非所有响应都显著，评估统计参数时需仔细分析。

5. Care should be taken while constructing these plots and interpreting data. The OOS may appear to be dynamic when responses are added/removed, criteria are modified, data is over-fitted, and/or the model is aliased. This can result in questionable data quality. 图形构建和数据解释应谨慎。当添加/删除响应、更改标准、过度拟合数据或模型别名时，OOS（超过规范）可能会表现出动态变化，影响数据质量。

6. The goal is set to “minimize” for the PDI to aim for a monodisperse formulation. PDI（多分散指数）目标设置为“最小化”，以期获得单分散配方。

7. The desirability displays values between 0 and 1, the latter being a highly desirable condition. However, it may be misinterpreted because the desirability function is entirely dependent on how close the upper and lower limits are set in the QTPP. The goal of optimization is how well the set conditions meet the goals rather than achieving a high desirability. 理想度（Desirability）值 介于 0 和 1 之间，1 为高度理想状态。需注意的是，理想度函数依赖于在 QTPP 中设置的上下限。优化的目标是确保设定条件尽可能达到目标，而非单纯追求高理想度。

8. Make sure that the entire content remains at the bottom of the vial with sufficient headspace for effective evaporation. 确保内容物位于瓶底，且留有足够空间进行有效蒸发。

9. It is essential to mix by pipetting because vortexing usually results in liquid spill or loss in the caps, which affects the true yield of the process. 混合时需通过移液器进行，因为涡旋搅拌通常会导致液体溢出或盖内损失，影响产率。

10. The inner layer of the collection vial is coated with a hydrophobic material and using hard tools may scratch the surface, resulting in loss of the product. The true yield is calculated as the sum of powder lost during the spray drying and the transfer from the collection vial to the storage vial. 收集瓶的内层涂有疏水材料，使用硬工具可能会刮伤表面，导致产物损失。真正产率的计算包括喷雾干燥过程中和从收集瓶转移到储存瓶时丢失的粉末总量。

11. Consider that the tiny hook of the thermogravimetric instrument needs to grab the pan. If the bow is bent, restructure it carefully with a pair of tweezers to bend it in a vertical direction so that the bow is directed outside. 热重仪的小钩子需要抓住盘子，若弓形部件弯曲，需用镊子小心矫正，使弓形朝外。

12. Do not get the sample on the bow or overload the pan. The weighing will be done automatically. 不要将样品放在弓形部件上或过量加载盘子，称重将自动完成。

13. Only put a tiny amount of powder on the carbon tape and spread it as a single layer. 在碳胶带上只需放置少量粉末，并将其均匀铺展为单层。

14. The instrument will be properly turned on if the vacuum in the glass chamber is reached, which is evidenced by a tight seal between the O ring and glass tube. 设备在玻璃室达到真空状态时已正确启动，此时 O 形圈与玻璃管之间应形成密封。

15. The lid can be opened very easily when the chamber has repressurized. Do not force the lid to open. 当腔室重新加压后，盖子可轻松打开，切勿强行打开盖子。

16. The height should be adjusted in such a way that the specimen holder is placed just beneath the cylindrical metal bar on top.调整高度，以使样品托盘位于上方圆柱金属杆下方。