Nanodiamond-based berberine aquasomes for enhancing penetration across epidermis to treat psoriasis.

The use of berberine hydrochloride (BCS class III) has limited application in psoriasis, when given as topical drug delivery systems, due to low permeability in the skin layer. Hence, berberine hydrochloride-loaded aquasome nanocarriers were developed for skin targeting, particularly epidermis (primary site of psoriasis pathophysiology) and enhance the skin permeability of berberine hydrochloride. Aquasomes were formulated using the adsorption method and characterized by structural morphology TEM, % drug adsorption, drug release profile (in-vitro and ex-vivo), in-vivo efficacy study and stability study. The reduced particle size and higher surface charge of SKF3 formulation (263.57 ± 27.78 nm and -21.0 ± 0.43 mV) showed improved stability of aquasomes because of the development of higher surface resistance to formation of aggregates. The adsorption of hydrophilic berberine and the non-lipidic nature of aquasomes resulted in % adsorption efficiency (%AE) of 94.46 ± 0.39 %. The controlled first-order release behavior of aquasomes was reported to be 52.647 ± 14.63 and 32.08 ± 12.78 % in in-vitro and ex-vivo studies, respectively. In-vivo studies demonstrated that topical application of berberine hydrochloride loaded aquasomes significantly alleviated psoriasis symptoms like hyperkeratosis, scaling and inflammation, due to the reduction in the inflammatory cytokines (IL-17 and IL-23). Therefore, aquasome formulation exhibits an innovative approach for targeted application of berberine hydrochloride in the management of psoriasis.

Artificial intelligence in pharmaceutical regulatory affairs.

Artificial intelligence (AI) refers to the ability of a computer to carry out tasks associated with human intelligence, including thinking, discovering, and learning from prior experience. AI can be integrated to simplify the complexity of pharmaceutical regulatory affairs. AI tools can be applied to automate regulatory processes such as administrative work, dossier filling, data extraction, auditing, the implementation of regulations, and quality management. AI creates process links and reduces complexity, resulting in a more efficient management system. Human-AI interaction opens up new opportunities in regulatory affairs. This article explores the potential role of AI in pharmaceutical regulatory affairs.

Common chemistry, manufacturing, and control deficiencies in abbreviated new drug applications assessed by the US Food and drug administration: Hurdle to access cost-effective medicines.

To market a generic product in the United States, it must be registered in Common Technical Document (CTD) format with the US Food and Drug Administration. The Generic Drug User Fee Act went into force in 2012, to expedite the timely review of Abbreviated New Drug Applications (ANDA) by communicating potential defects in the application to the applicant through deficiency letters at different time intervals during the review cycle. This often delays product approval since these deficiencies must be resolved before the product can be approved. In the present study, a study was performed to analyze the recurrent queries for ANDA applications in the CTD quality module from 2013 to 2020, and the probable corrective and preventive action to be taken was drafted. The most frequently occurring queries were observed in the sections titled "Description of manufacturing process and process controls", "Controls of critical steps and intermediates", "Specifications (Control of drug product)", and "Stability data".

Aquasomes: Advanced Vesicular-based Nanocarrier Systems.

BACKGROUND: Aquasomes are novel trilayered non-lipoidal vesicular nanocarriers that demonstrate structural similarity to ceramic nanoparticles with theranostic activity for diseases like ovarian cancer and antigen delivery. OBJECTIVE: The objective of the present article is to highlight the multifaceted potential of aquasomes over other nanocarriers for the treatment of various treatments like hemophilia A, cancer, and hepatitis. METHODS: Aquasomes enter the target cell by modifying the surface chemistry, extending drug release. The solid core of aquasomes provides structural stability whereas their oligomeric coatings protect drugs from dehydration. This vesicular delivery system was successfully utilized for the delivery of acid-labile enzymes, antigens, vaccines, etc. The aquasomes nanocarrier exhibits a larger surface area, volume, and mass ratio that allows the drug to penetrate inside the cells and a prolonged drug release profile. Moreover, aquasomes consist of a high mechanical strength, reduced or no biodegradability during storage, and a good body response that facilitates deeper penetration into capillaries which makes them more special and interesting. RESULTS: Aquasomes are a potential alternative over other nanocarriers for insulin, antigen, and oxygen delivery. CONCLUSION: In the near future, aquasomes-based nano-drug delivery systems can be a fascinating field for research in nanotechnology.

CNN-Based LCD Transcription of Blood Pressure From a Mobile Phone Camera.

Routine blood pressure (BP) measurement in pregnancy is commonly performed using automated oscillometric devices. Since no wireless oscillometric BP device has been validated in preeclamptic populations, a simple approach for capturing readings from such devices is needed, especially in low-resource settings where transmission of BP data from the field to central locations is an important mechanism for triage. To this end, a total of 8192 BP readings were captured from the Liquid Crystal Display (LCD) screen of a standard Omron M7 self-inflating BP cuff using a cellphone camera. A cohort of 49 lay midwives captured these data from 1697 pregnant women carrying singletons between 6 weeks and 40 weeks gestational age in rural Guatemala during routine screening. Images exhibited a wide variability in their appearance due to variations in orientation and parallax; environmental factors such as lighting, shadows; and image acquisition factors such as motion blur and problems with focus. Images were independently labeled for readability and quality by three annotators (BP range: 34-203 mm Hg) and disagreements were resolved. Methods to preprocess and automatically segment the LCD images into diastolic BP, systolic BP and heart rate using a contour-based technique were developed. A deep convolutional neural network was then trained to convert the LCD images into numerical values using a multi-digit recognition approach. On readable low- and high-quality images, this proposed approach achieved a 91% classification accuracy and mean absolute error of 3.19 mm Hg for systolic BP and 91% accuracy and mean absolute error of 0.94 mm Hg for diastolic BP. These error values are within the FDA guidelines for BP monitoring when poor quality images are excluded. The performance of the proposed approach was shown to be greatly superior to state-of-the-art open-source tools (Tesseract and the Google Vision API). The algorithm was developed such that it could be deployed on a phone and work without connectivity to a network.

A Real-Time Eating Detection System for Capturing Eating Moments and Triggering Ecological Momentary Assessments to Obtain Further Context: System Development and Validation Study.

BACKGROUND: Eating behavior has a high impact on the well-being of an individual. Such behavior involves not only when an individual is eating, but also various contextual factors such as with whom and where an individual is eating and what kind of food the individual is eating. Despite the relevance of such factors, most automated eating detection systems are not designed to capture contextual factors. OBJECTIVE: The aims of this study were to (1) design and build a smartwatch-based eating detection system that can detect meal episodes based on dominant hand movements, (2) design ecological momentary assessment (EMA) questions to capture meal contexts upon detection of a meal by the eating detection system, and (3) validate the meal detection system that triggers EMA questions upon passive detection of meal episodes. METHODS: The meal detection system was deployed among 28 college students at a US institution over a period of 3 weeks. The participants reported various contextual data through EMAs triggered when the eating detection system correctly detected a meal episode. The EMA questions were designed after conducting a survey study with 162 students from the same campus. Responses from EMAs were used to define exclusion criteria. RESULTS: Among the total consumed meals, 89.8% (264/294) of breakfast, 99.0% (406/410) of lunch, and 98.0% (589/601) of dinner episodes were detected by our novel meal detection system. The eating detection system showed a high accuracy by capturing 96.48% (1259/1305) of the meals consumed by the participants. The meal detection classifier showed a precision of 80%, recall of 96%, and F1 of 87.3%. We found that over 99% (1248/1259) of the detected meals were consumed with distractions. Such eating behavior is considered "unhealthy" and can lead to overeating and uncontrolled weight gain. A high proportion of meals was consumed alone (680/1259, 54.01%). Our participants self-reported 62.98% (793/1259) of their meals as healthy. Together, these results have implications for designing technologies to encourage healthy eating behavior. CONCLUSIONS: The presented eating detection system is the first of its kind to leverage EMAs to capture the eating context, which has strong implications for well-being research. We reflected on the contextual data gathered by our system and discussed how these insights can be used to design individual-specific interventions.

Garcinol Exhibits Anti-Neoplastic Effects by Targeting Diverse Oncogenic Factors in Tumor Cells.

Garcinol, a polyisoprenylated benzophenone, is the medicinal component obtained from fruits and leaves of Garcinia indica (G. indica) and has traditionally been extensively used for its antioxidant and anti-inflammatory properties. In addition, it has been also been experimentally illustrated to elicit anti-cancer properties. Several in vitro and in vivo studies have illustrated the potential therapeutic efficiency of garcinol in management of different malignancies. It mainly acts as an inhibitor of cellular processes via regulation of transcription factors NF-κB and JAK/STAT3 in tumor cells and have been demonstrated to effectively inhibit growth of malignant cell population. Numerous studies have highlighted the anti-neoplastic potential of garcinol in different oncological transformations including colon cancer, breast cancer, prostate cancer, head and neck cancer, hepatocellular carcinoma, etc. However, use of garcinol is still in its pre-clinical stage and this is mainly attributed to the limitations of conclusive evaluation of pharmacological parameters. This necessitates evaluation of garcinol pharmacokinetics to precisely identify an appropriate dose and route of administration, tolerability, and potency under physiological conditions along with characterization of a therapeutic index. Hence, the research is presently ongoing in the dimension of exploring the precise metabolic mechanism of garcinol. Despite various lacunae, garcinol has presented with promising anti-cancer effects. Hence, this review is motivated by the constantly emerging and promising positive anti-cancerous effects of garcinol. This review is the first effort to summarize the mechanism of action of garcinol in modulation of anti-cancer effect via regulation of different cellular processes.