Formulation of water insoluble drugs

Poor water solubility and the resulting low oral bioavailability of drugs is one of the major challenges encountered by drug discovery and development scientists. Drug candidates with a solubility of less than 1 μg/ml are considered poorly soluble which show unacceptable bioavailability from conventional dosage forms. Formulation plays a major role in determining the rate and extent of absorption of such drugs. There are a number of formulation strategies that could be used to improve the bioavailability of such drugs, primarily either by increasing the dissolution rate or by presenting the drug in solution. Various approaches to enhance the solubility and dissolution rate of drugs have been already reported e.g. inclusion complexation, colloidal systems, solid lipid nanoparticles and nano-structured lipid carriers etc

The preparation of solid core drug delivery systems (SCDDS) for the biomolecular delivery

In this study a solid core drug delivery system (SCDDS) is prepared with silica as a model core, fatty acid as a shell material and supercritical fluid technology as the process. SCDDS can be developed as targeted delivery systems or as sustained/controlled release platforms. SCDDS are coated with fatty acids using supercritical fluid technology (SCFT), allowing the creation of nano-particulate and micro-particulate delivery systems. The operating conditions of low temperature and pressure used to formulate these systems make it attractive for pharmaceutical research, especially for thermo-labile or sensitive bio-materials

Functional physico-chemical, ex vivo permeation and cell viability characterization of omeprazole loaded buccal films for pediatric drug delivery

Buccal films were prepared from aqueous and ethanolic Metolose gels using the solvent casting approach (40 °C). The hydration (PBS and simulated saliva), mucoadhesion, physical stability (20 °C, 40 °C), in vitro drug (omeprazole) dissolution (PBS and simulated saliva), ex vivo permeation (pig buccal mucosa) in the presence of simulated saliva, ex vivo bioadhesion and cell viability using MTT of films were investigated. Hydration and mucoadhesion results showed that swelling capacity and adhesion was higher in the presence of PBS than simulated saliva (SS) due to differences in ionic strength. Omeprazole was more stable at 20 °C than 40 °C whilst omeprazole release reached a plateau within 1 h and faster in PBS than in SS. Fitting release data to kinetic models showed that Korsmeyer–Peppas equation best fit the dissolution data. Drug release in PBS was best described by zero order via non-Fickian diffusion but followed super case II transport in SS attributed to drug diffusion and polymer erosion. The amount of omeprazole permeating over 2 h was 275 ug/cm2 whilst the formulations and starting materials showed cell viability values greater than 95%, confirming their safety for potential use in paediatric buccal delivery

PAGER: A Framework for Failure Analysis of Deep Regression Models

Safe deployment of AI models requires proactive detection of potential prediction failures to prevent costly errors. While failure detection in classification problems has received significant attention, characterizing failure modes in regression tasks is more complicated and less explored. Existing approaches rely on epistemic uncertainties or feature inconsistency with the training distribution to characterize model risk. However, we show that uncertainties are necessary but insufficient to accurately characterize failure, owing to the various sources of error. In this paper, we propose PAGER (Principled Analysis of Generalization Errors in Regressors), a framework to systematically detect and characterize failures in deep regression models. Built upon the recently proposed idea of anchoring in deep models, PAGER unifies both epistemic uncertainties and novel, complementary non-conformity scores to organize samples into different risk regimes, thereby providing a comprehensive analysis of model errors. Additionally, we introduce novel metrics for evaluating failure detectors in regression tasks. We demonstrate the effectiveness of PAGER on synthetic and real-world benchmarks. Our results highlight the capability of PAGER to identify regions of accurate generalization and detect failure cases in out-of-distribution and out-of-support scenarios

Melting behaviour of triblock polymers (poloxamers) in supercritical CO2

Carbon dioxide (CO2) is the most commonly used SCF because of the relatively mild operating conditions (31.1°C and 72.8 bar) and easily tuneable properties. Moreover, the ability of CO2 to act as a solvent and solute has made it highly desirable in the field of excipient processing, particle formation and drug encapsulation. The dissolution of CO2 is known to affect glass transition or melting temperature of polymers and fats [1]. In this work, the effect of the dissolution of liquid (l.CO2) or supercritical (sc. CO2) was studied on the melting point of various poloxamers (Pluronic™ F77, F127, F38, F68, F108) at the pressure ranging from 70 to 250 bar in a supercritical phase monitor. The treated and untreated samples were analysed by X-ray diffraction (XRD), scanning electron microscopy (SEM) and differential scanning calorimetry (DSC)

Conversion of sustained release omeprazole loaded buccal films into fast dissolving strips using supercritical carbon dioxide (scCO2) processing, for potential paediatric drug delivery

This study involves the development of thin oral solvent cast films for the potential delivery of the proton pump inhibitor, omeprazole (OME) via the buccal mucosa for paediatric patients. OME containing films were prepared from ethanolic gels (1% w/w) of metolose (MET) with polyethylene glycol (PEG 400) (0.5% w/w) as plasticiser, and L-arginine (l-arg) (0.2% w/w) as a stabilizer and dried in an oven at 40 °C. The blank and drug loaded films were divided into two groups, one group was subjected to supercritical carbon dioxide (scCO2) treatment and the other group untreated. The untreated and scCO2 treated films were then characterised using differential scanning calorimetry, thermogravimetric analysis, scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, hydration (swelling), mucoadhesion and in vitro drug dissolution studies. Treatment of the solvent cast films with scCO2 caused significant changes to the functional and physical properties of the MET films. The original drug loaded MET films showed a sustained release of OME (1 h), whereas scCO2 treatment of the formulations resulted in fast dissolving films with > 90% drug release within 15 min

Effect of pressure on the melting point of pluronics in pressurized carbon dioxide

The melting points of Pluronic F-77, F-127, F-68, F-38, and F-108 were investigated in pressurized CO2 between a pressure range of 2.0–50.0 MPa. Unprocessed and CO2-processed Pluronic samples were analyzed by differential scanning calorimetry (DSC) and powder X-ray diffraction (PXRD). A melting point depression in the range of 18.1 (± 0.5 K) to 19.3 (± 0.3 K) was observed for all Pluronics studied in this work. The melting point of Pluronics in pressurized CO2 was found to be independent of their molecular weight and poly(propylene oxide) [PPO] content. Analysis by DSC and PXRD revealed that CO2 processing had no impact on the morphology of Pluronics

Alteration in the histology of gonads and hormone levels of fish Channa punctatus on exposure to 17-α ethynylestradiol

It has been demonstrated that effluents discharged from sewage treatment facilities allow synthetic estrogens, widely employed in contraceptives and other pharmaceutical applications, to reach the aquatic environment. One of the most biologically active xenoestrogens in the aquatic environment is the synthetic hormone 17-α ethynylestradiol(EE2), raisingreproductive issues in the fish population. The present study chose Channa punctatus fish to study the effects of EE2 on gonad histology and the calculation of estrogen and testosterone levels. The experimental setting was separated into four groups, with Group I as control with 0 ng/L of EE2. The other three groups viz., Group II to IV, had 5 ng/L, 10 ng/L, and 20 ng/L concentrations of EE2, respectively, and samples were obtained after the durations of 7, 14, 21, and 28 days. The findings showed that as 17-α ethynylestradiol concentrations increased, testosterone levels decreased from 10.88±0.24 ng/dL to 4.91±0.24 ng/dL,while estrogen levels increased from 42.7±2.22 pg/mL to 120.18±4.54 pg/mL. The number percentage of primary growth oocytes, previtellogenic oocytes and vitellogenic oocytes in the histology of ovary decreased from 28.45±1.42 to 10.43±0.47; 16.22±0.81 to 3.15±0.16 and 14.81±0.89 to 2.14±0.11 respectively while in testis, the number percentage of spermatogonia, spermatocytes decreased from 21.4±0.86 to 15.1±0.68 and 97.1±3.88 to 54.2±3.25. In contrast, the percentage of mature spermatids increased from 20.8±0.94 to 40.2±2.41. Since synthetic estrogens adversely affect aquatic animals, especially fish, they should be treated properly before releasing them into the aquatic environment.

Determination of mycophenolic acid in human plasma by ultra performance liquid chromatography tandem mass spectrometry

AbstractA simple, sensitive and high throughput ultra performance liquid chromatography tandem mass spectrometry method has been developed for the determination of mycophenolic acid in human plasma. The method involved simple protein precipitation of MPA along with its deuterated analog as an internal standard (IS) from 50µL of human plasma. The chromatographic analysis was done on Acquity UPLC C18 (100mm×2.1mm, 1.7µm) column under isocratic conditions using acetonitrile and 10mM ammonium formate, pH 3.00 (75:25, v/v) as the mobile phase. A triple quadrupole mass spectrometer operating in the positive ionization mode was used for quantitation. In-source conversion of mycophenolic glucuronide metabolite to the parent drug was selectively controlled by suitable optimization of cone voltage, cone gas flow and desolvation temperature. The method was validated over a wide concentration range of 15–15000ng/mL. The mean extraction recovery for the analyte and IS was >95%. Matrix effect expressed as matrix factors ranged from 0.97 to 1.02. The method was successfully applied to support a bioequivalence study of 500mg mycophenolate mofetil tablet in 72 healthy subjects

SplitEE: Early Exit in Deep Neural Networks with Split Computing

Deep Neural Networks (DNNs) have drawn attention because of their outstanding performance on various tasks. However, deploying full-fledged DNNs in resource-constrained devices (edge, mobile, IoT) is difficult due to their large size. To overcome the issue, various approaches are considered, like offloading part of the computation to the cloud for final inference (split computing) or performing the inference at an intermediary layer without passing through all layers (early exits). In this work, we propose combining both approaches by using early exits in split computing. In our approach, we decide up to what depth of DNNs computation to perform on the device (splitting layer) and whether a sample can exit from this layer or need to be offloaded. The decisions are based on a weighted combination of accuracy, computational, and communication costs. We develop an algorithm named SplitEE to learn an optimal policy. Since pre-trained DNNs are often deployed in new domains where the ground truths may be unavailable and samples arrive in a streaming fashion, SplitEE works in an online and unsupervised setup. We extensively perform experiments on five different datasets. SplitEE achieves a significant cost reduction ($>50\%$) with a slight drop in accuracy ($<2\%$) as compared to the case when all samples are inferred at the final layer. The anonymized source code is available at \url{https://anonymous.4open.science/r/SplitEE_M-B989/README.md}.Comment: 10 pages, to appear in the proceeding AIMLSystems 202