Applications of Polymers in Delivery of Biologics

Inamdar, Nazma; Mourya, Vishnukant

doi:10.1016/b978-0-12-819659-5.00016-1

Cited by 2 publications

(2 citation statements)

References 547 publications

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“…These theragnostic systems have attracted much attention in the medical, biological, and pharmaceutical fields [9]. Polyamines, commercially available as Tetronic ® , are formed by blocks of copolymers consisting of poly (ethylene oxide) (PEO) and poly (propylene oxide) (PPO) units arranged in a four-armed star shape with different hydrophilic-lipophilic balance (HBL), and molecular weight [10,11], being very attractive as drug delivery systems due to the capacity to form nanometric structures as micelles or worm-like micelles, for example, [12][13][14]. Structurally, Tetronics are similar to Pluronics ® [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

New Machine Learning Approach for the Optimization of Nano-Hybrid Formulations

et al. 2022

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Nano-hybrid systems are products of interactions between organic and inorganic materials designed and planned to develop drug delivery platforms that can be self-assembled. Poloxamine, commercially available as Tetronic®, is formed by blocks of copolymers consisting of poly (ethylene oxide) (PEO) and poly (propylene oxide) (PPO) units arranged in a four-armed star shape. Structurally, Tetronics are similar to Pluronics®, with an additional feature as they are also pH-dependent due to their central ethylenediamine unit. Laponite is a synthetic clay arranged in the form of discs with a diameter of approximately 25 nm and a thickness of 1 nm. Both compounds are biocompatible and considered as candidates for the formation of carrier systems. The objective is to explore associations between a Tetronic (T1304) and LAP (Laponite) at concentrations of 1–20% (w/w) and 0–3% (w/w), respectively. Response surface methodology (RMS) and two types of machine learning (multilayer perceptron (MLP) and support vector machine (SVM)) were used to evaluate the physical behavior of the systems and the β-Lapachone (β-Lap) solubility in the systems. β-Lap (model drug with low solubility in water) has antiviral, antiparasitic, antitumor, and anti-inflammatory properties. The results show an adequate machine learning approach to predict the physical behavior of nanocarrier systems with and without the presence of LAP. Additionally, the analysis performed with SVM showed better results (R2 > 0.97) in terms of data adjustment in the evaluation of β-Lap solubility. Furthermore, this work presents a new methodology for classifying phase behavior using ML. The new methodology allows the creation of a phase behavior surface for different concentrations of T1304 and LAP at different pHs and temperatures. The machine learning strategies used were excellent in assisting in the optimized development of new nano-hybrid platforms.

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Section: Introductionmentioning

confidence: 99%

New Machine Learning Approach for the Optimization of Nano-Hybrid Formulations

et al. 2022

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“…Recently, HP-β-CD and HPMC have been extensively used in the preparation of various formulations such as controlled-release pellets, microcapsules, matrix sustained-release tablets, and controlled-release tablets as complexing agents to enhance aqueous solubility and bioavailability of poorly water-soluble drugs. 24 This study proceeds to enhance the solubility and then bioavailability of AM. The effect of varying concentrations of the polymer has been determined with respect to in vitro drug release profiles and various other parameters.…”

Section: Introductionmentioning

confidence: 99%

Pharmaceutical and Pharmacological Evaluation of Amoxicillin after Solubility Enhancement Using the Spray Drying Technique

et al. 2022

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The dose frequency of drugs belonging to class II is usually high and associated with harmful effects on the body. The study aimed to enhance the solubility of the poorly water-soluble drug amoxicillin (AM) by the solid dispersion (SD) technique. Six different SDs of AM, F1−F6, were prepared by the spray drying technique using two other carriers, HP-β-CD (F1−F3) and HPMC (F4−F6), in 1:1, 1:2, and 1:3 drug-to-polymer ratios. These SDs were analyzed to determine their practical yield, drug content, and aqueous solubility using analytical techniques such as Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric analysis, and powder X-ray diffraction. The effect of polymer concentration on SDs was determined using aqueous solubility, in vitro dissolution, and in vivo studies. The results showed no drug−polymer interactions in SDs. Solubility studies showed that SDs based on the drug-to-polymer ratio of 1:2 (F2 and F5) were highly soluble in water compared to those with ratios of 1:1 and 1:3. In vitro dissolution studies also showed that SDs with a ratio of 1:2 released the highest drug concentration from both polymeric systems. The SDs based on HPMC confirmed the more sustained release of the drug as compared to that of HP-β-CD. All the SDs were observed as stable and amorphous, with a smooth spherical surface. In vivo studies reveal the enhancement of pharmacokinetics parameters as compared to standard AM. Hence, it is confirmed that spray drying is an excellent technique to enhance the solubility of AM in an aqueous medium. This may contribute to the enhancement of the pharmacokinetic behaviors of SDs.

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Applications of Polymers in Delivery of Biologics

Cited by 2 publications

References 547 publications

New Machine Learning Approach for the Optimization of Nano-Hybrid Formulations

New Machine Learning Approach for the Optimization of Nano-Hybrid Formulations

Pharmaceutical and Pharmacological Evaluation of Amoxicillin after Solubility Enhancement Using the Spray Drying Technique

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