Advancing pharmaceutical Intelligence via computationally Prognosticating the in-vitro parameters of fast disintegration tablets using Machine Learning models.

The field of Machine Learning (ML) has garnered significant attention, particularly in healthcare for predicting disease severity. Recently, the pharmaceutical sector has also adopted ML techniques in various stages of drug development. Tablets are the most common pharmaceutical formulations, with their efficacy influenced by the physicochemical properties of active ingredients, in-process parameters, and formulation components. In this study, we developed ML-based prediction models for disintegration time, friability, and water absorption ratio of fast disintegration tablets. The model development process included data visualization, pre-processing, splitting, ML model creation, and evaluation. We evaluated the models using root mean square error (RMSE) and R-squared score (R2). After hyperparameter tuning and cross-validation, the voting regressor model demonstrated the best performance for predicting disintegration time (RMSE: 21.99, R2: 0.76), surpassing previously reported models. The random forest regressor achieved the best results for friability prediction (RMSE: 0.142, R2: 0.7), and the K-nearest neighbor (KNN) regressor excelled in predicting the water absorption ratio (RMSE: 10.07, R2: 0.94). Notably, predicting friability and water absorption ratio using ML models is unprecedented in the literature. The developed models were deployed in a web app for easy access by anyone. These ML models can significantly enhance the tablet development phase by minimizing experimental iterations and material usage, thereby reducing costs and saving time.

Azacoumarin-based "turn-on" fluorescent probe for the detection and imaging of hydrogen peroxide in living cells.

Azacoumarins are a relatively unexplored group of coumarin fluorophores, despite their excellent light-emitting properties. In this report, we detail the creation and production of a fluorescent probe (PYCB) based on azacoumarin for detecting H2O2. The probe utilizes a carboxy benzyl boronic pinacol ester as the recognition unit and displays a turn-on fluorescence response at 460 nm upon exposure to H2O2. The probe shows excellent sensitivity and selectivity to H2O2, with a detection limit of 0.385 µM. PYCB also exhibited strong pH stability and selectivity for H2O2 over other reactive oxygen species (ROS). Additionally, MTT assay results demonstrated the excellent biocompatibility of PYCB in MCF-7 cell lines. Fluorescence imaging of PYCB-treated MCF-7 cells revealed enhanced blue fluorescence corresponding to varying concentrations of exogenous H2O2.

Development and comparison of machine learning models for in-vitro drug permeation prediction from microneedle patch.

The field of machine learning (ML) is advancing to a larger extent and finding its applications across numerous fields. ML has the potential to optimize the development process of microneedle patch by predicting the drug release pattern prior to its fabrication and production. The early predictions could not only assist the in-vitro and in-vivo experimentation of drug release but also conserve materials, reduce cost, and save time. In this work, we have used a dataset gleaned from the literature to train and evaluate different ML models, such as stacking regressor, artificial neural network (ANN) model, and voting regressor model. In this study, models were developed to improve prediction accuracy of the in-vitro drug release amount from the hydrogel-type microneedle patch and the in-vitro drug permeation amount through the micropores created by solid microneedles on the skin. We compared the performance of these models using various metrics, including R-squared score (R2 score), root mean squared error (RMSE), and mean absolute error (MAE). Voting regressor model performed better with drug permeation percentage as an outcome feature having RMSE value of 3.24. In comparison, stacking regressor have a RMSE value of 16.54, and ANN model has shown a RMSE value of 14. The value of permeation amount calculated from the predicted percentage is found to be more accurate with RMSE of 654.94 than direct amount prediction, having a RMSE of 669.69. All our models have performed far better than the previously developed model before this research, which had a RMSE of 4447.23. We then optimized voting regressor model's hyperparameter and cross validated its performance. Furthermore, it was deployed in a webapp using Flask framework, showing a way to develop an application to allow other users to easily predict drug permeation amount from the microneedle patch at a particular time period. This project demonstrates the potential of ML to facilitate the development of microneedle patch and other drug delivery systems.

Advancements in microneedle fabrication techniques: artificial intelligence assisted 3D-printing technology.

Microneedles (MNs) are micron-scale needles that are a painless alternative to injections for delivering drugs through the skin. MNs find applications as biosensing devices and could serve as real-time diagnosis tools. There have been numerous fabrication techniques employed for producing quality MN-based systems, prominent among them is the three-dimensional (3D) printing. 3D printing enables the production of quality MNs of tuneable characteristics using a variety of materials. Further, the possible integration of artificial intelligence (AI) tools such as machine learning (ML) and deep learning (DL) with 3D printing makes it an indispensable tool for fabricating microneedles. Provided that these AI tools can be trained and act with minimal human intervention to control the quality of products produced, there is also a possibility of mass production of MNs using these tools in the future. This work reviews the specific role of AI in the 3D printing of MN-based devices discussing the use of AI in predicting drug release patterns, its role as a quality control tool, and in predicting the biomarker levels. Additionally, the autonomous 3D printing of microneedles using an integrated system of the internet of things (IoT) and machine learning (ML) is discussed in brief. Different categories of machine learning including supervised learning, semi-supervised learning, unsupervised learning, and reinforced learning have been discussed in brief. Lastly, a brief section is dedicated to the biosensing applications of MN-based devices.

Quantitative phase contrast X-ray tomography of aluminium metal matrix composite.

The quantitative assessment of micro-structure and load-induced damages in Al-SiC metal matrix composites (MMC) is important for its design optimization, performance evaluation and structure-property correlation. X-ray Phase contrast micro-tomography is potentially used for evaluation of its 3 dimensional micro-structure manifested in the form of voids, cracks, embedded particles, and load-induced damages. However, the contrast between Al matrix and SiC particles is insufficient for their clear morphological identification and quantitative assessment. In the present study, we have proposed and applied single image-based phase retrieval as a pre-processing step to micro-tomography reconstruction for improved assessment of micro-structure and cohesion-induced damages in Al-SiC MMC. The advantages of applying different phase retrieval techniques in the enhancement of image quality and morphological quantification of SiC particles, pores and cohesion damages are discussed. It is observed that the Paganin method offers the best improvement in contrast to noise ratio for the measurement of SiC particles embedded in the Al matrix.

Cocrystals by Design: A Rational Coformer Selection Approach for Tackling the API Problems.

Active pharmaceutical ingredients (API) with unfavorable physicochemical properties and stability present a significant challenge during their processing into final dosage forms. Cocrystallization of such APIs with suitable coformers is an efficient approach to mitigate the solubility and stability concerns. A considerable number of cocrystal-based products are currently being marketed and show an upward trend. However, to improve the API properties by cocrystallization, coformer selection plays a paramount role. Selection of suitable coformers not only improves the drug's physicochemical properties but also improves the therapeutic effectiveness and reduces side effects. Numerous coformers have been used till date to prepare pharmaceutically acceptable cocrystals. The carboxylic acid-based coformers, such as fumaric acid, oxalic acid, succinic acid, and citric acid, are the most commonly used coformers in the currently marketed cocrystal-based products. Carboxylic acid-based coformers are capable of forming the hydrogen bond and contain smaller carbon chain with the APIs. This review summarizes the role of coformers in improving the physicochemical and pharmaceutical properties of APIs, and deeply explains the utility of afore-mentioned coformers in API cocrystal formation. The review concludes with a brief discussion on the patentability and regulatory issues related to pharmaceutical cocrystals.

Current Trends in API Co-Processing: Spherical Crystallization and Co-Precipitation Techniques.

Active Pharmaceutical Ingredients (APIs) do not always exhibit processable physical properties, which makes their processing in an industrial setup very demanding. These issues often lead to poor robustness and higher cost of the drug product. The issue can be mitigated by co-processing the APIs using suitable solvent media-based techniques to streamline pharmaceutical manufacturing operations. Some of the co-processing methods are the amalgamation of API purification and granulation steps. These techniques also exhibit adequate robustness for successful adoption by the pharmaceutical industry to manufacture high quality drug products. Spherical crystallization and co-precipitation are solvent media-based co-processing approaches that enhances the micromeritic and dissolution characteristics of problematic APIs. These methods not only improve API characteristics but also enable direct compression into tablets. These methods are economical and time-saving as they have the potential for effectively circumventing the granulation step, which can be a major source of variability in the product. This review highlights the recent advancements pertaining to these techniques to aid researchers in adopting the right co-processing method. Similarly, the possibility of scaling up the production of co-processed APIs by these techniques is discussed. The continuous manufacturability by co-processing is outlined with a short note on Process Analytical Technology (PAT) applicability in monitoring and improving the process.

Co-Crystallization Approach to Enhance the Stability of Moisture-Sensitive Drugs.

Stability is an essential quality attribute of any pharmaceutical formulation. Poor stability can change the color and physical appearance of a drug, directly impacting the patient's perception. Unstable drug products may also face loss of active pharmaceutical ingredients (APIs) and degradation, making the medicine ineffective and toxic. Moisture content is known to be the leading cause of the degradation of nearly 50% of medicinal products, leading to impurities in solid dose formulations. The polarity of the atoms in an API and the surface chemistry of API particles majorly influence the affinity towards water molecules. Moisture induces chemical reactions, including free water that has also been identified as an important factor in determining drug product stability. Among the various approaches, crystal engineering and specifically co-crystals, have a proven ability to increase the stability of moisture-sensitive APIs. Other approaches, such as changing the salt form, can lead to solubility issues, thus making the co-crystal approach more suited to enhancing hygroscopic stability. There are many reported studies where co-crystals have exhibited reduced hygroscopicity compared to pure API, thereby improving the product's stability. In this review, the authors focus on recent updates and trends in these studies related to improving the hygroscopic stability of compounds, discuss the reasons behind the enhanced stability, and briefly discuss the screening of co-formers for moisture-sensitive drugs.

Surfactant Assisted In Situ Synthesis of Nanofibrillated Cellulose/Polymethylsilsesquioxane Aerogel for Tuning Its Thermal Performance.

Nanofibrillated cellulose (NFC) and polymethylsilsesquioxane (PMSQ) based aerogel are prepared by the sol-gel method. The objective of this work is to study the impact of surfactant and base catalyst on the thermal and mechanical performance of the corresponding aerogel. The rheological premonitory assists in predicting the bulk properties of the aerogel. The chemical structure of the aerogel is studied by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and solid-state nuclear magnetic resonance (NMR). X-ray microtomographic (XMT) analysis confirms the homogeneous and monolithic structure of the aerogel. The lowest thermal conductivity is achieved as 23.21 mW m-1 K-1 with V-0 and HBF rating through UL-94 test. Thermal performance of aerogels is cross-verified through modeling and simulation in COMSOL multiphysics platform. The mechanical properties of aerogel are evaluated by monolithic compression test in axial and radial compression test up to 90% strain, cyclic compression loading-unloading, and reloading test, flexural test, and dynamic mechanical analysis. The time-temperature analysis has shown around 5 °C temperature difference in the middle of the room after using the aerogel panel at the exposed surface, which assists in the practical application of the synthesized aerogel panel.

Tinospora cordifolia Leaves Derived Carbon dots for Cancer Cell Bioimaging, Free radical Scavenging, and Fe3+ Sensing Applications.

Herein, we report the fabrication of Tinospora cordifolia leaves-derived carbon dots (TCLCDs) from aqueous extract of leaves as carbon source via simple, environmentally friendly, hydrothermal carbonization (HTC) technique. The synthesized TCLCDs were characterized for their physicochemical properties and further explored for in-vitro cancer cell bioimaging, radical scavenging, and metal ion sensing. The synthesized TCLCDs showed excitation-dependent emission property with maximum emission at 435 nm under the excitation of 350 nm. The High-Resolution Transmission Electron Microscopy (HRTEM) results revealed a roughly spherical shape with an average diameter of 5.47 nm. The diffused ring pattern of Selected Area Electron Diffraction (SAED) and halo diffraction pattern of X-ray diffraction (XRD) disclosed their amorphous nature. The Energy Dispersive X-ray (EDX) showed the existence of C, N, and O. The Fourier-transform infrared spectroscopy (FTIR) revealed the presence of -OH, -NH, -CN, and -CH groups. The TCLCDs showed excellent cellular biocompatibility with dose-dependent bioimaging results in melanoma (B16F10) and cervical cancer (SiHa) cell lines. Also, they exhibited excellent scavenging of free radicals with an IC50 value of 0.524 mg/mL & selective Fe3+ ion sensing with a detection limit of 0.414 µM. Further, they exerted excellent bacterial biocompatibility, photostability, and thermal stability. The overall results reflected their potential for in-vitro cancer cell bioimaging, free radical scavenging, and selective Fe3+ ion sensing.

Anthocyanidins Inhibit Growth and Chemosensitize Triple-Negative Breast Cancer via the NF-κB Signaling Pathway.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Due to the lack of drug-targetable receptors, chemotherapy is the only systemic treatment option. Although chemotherapeutic drugs respond initially in TNBC, many patients relapse and have a poor prognosis. Poor survival after metastatic relapse is largely attributed to the development of resistance to chemotherapeutic drugs. In this study, we show that bilberry-derived anthocyanidins (Anthos) can inhibit the growth and metastasis of TNBC and chemosensitize paclitaxel (PAC)-resistant TNBC cells by modulating the NF-κB signaling pathway, as well as metastatic and angiogenic mediators. Anthos administered orally significantly decreased MDA-MB-231 orthoxenograft tumor volume and led to lower rates of lymph node and lung metastasis, compared to control. Treatment of PAC-resistant MDA-MB-231Tx cells with Anthos and PAC in combination lowered the IC50 of PAC by nearly 20-fold. The combination treatment also significantly (p < 0.01) decreased the tumor volume in MDA-MB-231Tx orthoxenografts, compared to control. In contrast, Anthos and PAC alone were ineffective against MDA-MB-231Tx tumors. Our approach of using Anthos to inhibit the growth and metastasis of breast cancers, as well as to chemosensitize PAC-resistant TNBC, provides a highly promising and effective strategy for the management of TNBC.

The white beam station at imaging beamline BL-4, Indus-2.

The high flux density of synchrotron white beam offers several advantages in X-ray imaging such as higher resolution and signal-to-noise ratio in 3D/4D micro-tomography, higher frame rate in real-time imaging of transient phenomena, and higher penetration in thick and dense materials especially at higher energies. However, these advantages come with additional challenges to beamline optics, camera and sample due to increased heat load and radiation damage, and to personal safety due to higher radiation dose and ozone gas hazards. In this work, a white beam imaging facility at imaging beamline BL-4, Indus-2, has been developed, while taking care of various instrumental and personal safety challenges. The facility has been tested to achieve 1.5 µm spatial resolution, increased penetration depth up to 900 µm in steel, and high temporal resolutions of ∼10 ms (region of interest 2048 × 2048 pixels) and 70 µs (256 × 2048 pixels). The facility is being used successfully for X-ray imaging, non-destructive testing and dosimetry experiments.

Exploring the potential of solid dispersion for improving solubility, dissolution & bioavailability of herbal extracts, enriched fractions, and bioactives.

Most drugs' poor aqueous solubility has emerged as a significant challenge in achieving proper therapeutic response following oral administration. Herbal drugs are being used from time immemorial to prevent, mitigate, and cure multiple diseases. However, most of the bioactives phytoconstituents possess limited aqueous solubility & poor oral bioavailability. Solid dispersion (SD) has been realised as an efficient formulation to overcome hydrophobic candidates' solubility issues and improve their oral bioavailability. The current review mainly explores the potential of SD for improving solubility, dissolution & bioavailability of herbal extracts, enriched fractions, and isolated bioactives. Hence, basics of SD, selection of excipients, need for SD of plant products, SD of plant products, selection of preparation method, the chemistry of phytoconstituent-excipient interaction, and hurdles associated with SD of herbal extract/enriched fraction were explored in this review. The SD has the potential to overcome solubility, dissolution, and oral bioavailability issues of poorly soluble phytoconstituents.

Bio-extract amalgamated sodium alginate-cellulose nanofibres based 3D-sponges with interpenetrating BioPU coating as potential wound care scaffolds.

In this work, sodium alginate (SA) based "all-natural" composite bio-sponges were designed for potential application as wound care scaffold. The composite bio-sponges were developed from the aqueous amalgamation of SA and cellulose nanofibres (CNFs) in bio-extracts like Rice water (Rw) and Giloy extract (Ge). These sponges were modified by employing a simple coating strategy using vegetable oil-based bio-polyurethane (BioPU) to tailor their physicochemical and biological properties so as to match the specific requirements of a wound care scaffold. Bio-sponges with shared interpenetrating polymeric network structures were attained at optimized BioPU coating formulation. The interpenetration of BioPU chains within the sponge construct resulted in the formation of numerous micro-networks in the interconnected microporous structure of sponges (porosity ≥75%). The coated sponge showed a superior mechanical strength (compressive strength ~3.8 MPa, compressive modulus ~35 MPa) with appreciable flexibility and recoverability under repeated compressive loading-unloading cycles. A tunable degradation behaviour was achieved by varying BioPU coating concentrations owing to the different degree of polymer chain entanglement within the sponge construct. The physical entanglement of BioPU chains with core structural components of sponge improved their structural stability by suppressing their full fragmentation in water-based medium without affecting its swelling behaviour (swelling ratio > 1000%). The coated sponge surface has provided a suitable moist-adherent physical environment to support the adhesion and growth of skin cells (HaCaT cells). The MTT (3-(4,5-dimethyl thiazolyl-2)-2,5-diphenyltetrazolium bromide) assay and hemolytic assay revealed the non-toxic and biocompatible nature of coated sponges in vitro. Moreover, no signs of skin erythema or edema were observed during in vivo dermal irritation and corrosion test performed on the skin of Sprague Dawley (SD) rats. Our initial observations revealed the credibility of these sponges as functional wound care scaffolds as well as its diverse potential as a suitable substrate for various tissue engineering applications.

Magnetopriming effects on arsenic stress-induced morphological and physiological variations in soybean involving synchrotron imaging.

This study investigates the effect of static magnetic field (SMF) pre-treatment in ameliorating arsenic (As) toxicity in soybean plants in relation to growth, photosynthesis and water transport through leaf venation. Soybean (Glycine max variety JS-9560) seeds pre-treated with SMF (200 mT for 1 h) were grown in four levels of arsenate-polluted soil (As(V); 0, 5, 10 and 50 mg kg-1 ) in order to find out the impact of magnetopriming on plant tolerance against As toxicity. Quantitative image analysis of soybean leaf venation showed a narrowing in the width of midrib with increasing As(V) contamination in non-primed seeds. The morphological variations are also supported by the physiological parameters such as reduction in efficiency of photosystem II, plant performance index, stomatal conductance and photosynthetic rate in the presence of As(V) for non-primed seeds. However, remarkable increase was observed in all the measured parameters by SMF pre-treatment at all the concentrations of As(V) used. Even for the highest concentration of As(V) (50 mg kg-1 soil), SMF pre-treatment caused significant enhancement in plant height (40%), area of third trifoliate leaves (40%), along with increase in width of the midrib (17%) and minor vein (13%), contributing to increase in the water uptake, that resulted in higher primary photochemistry of PSII (12%), performance index (50%), stomatal conductance (57%) and photosynthetic rate (33%) as compared to non-primed ones. Consequently, magnetopriming of dry seeds can be effectively used as pretreatment for reduction of As toxicity in soybean plants.

Esterified superhydrophobic nanofibrillated cellulose based aerogel for oil spill treatment.

The present work aims towards the structuring of a physically cross-linked aerogels based on nanofibrillated cellulose (NFC) and polyvinyl alcohol (PVA), i.e., NFC/PVA aerogels for oil spillage cleanup. Highly porous (98%) NFC/PVA aerogels having both meso-micro pores were achieved by freeze drying technique. To impart super-hydrophobicity to the composite aerogel, a simple dip coating process was adopted using stearic acid chloride (SAC) solution. The SAC conjugated aerogels combined both superhydrophobic and oleophilic characteristics showed a contact angle of ∼159° and ∼0° with water and oil respectively. FESEM and X-ray microtomography images revealed a self-assembled 3D porous cellular structure of the aerogels. The prepared aerogels were found to be very efficient in separating a series of oil/water mixtures and various organic solvents with excellent selectivity and recyclability. Absorption capacity of the aerogels was at least 35 times higher than their dry weight. Simple mechanical squeezing method was adopted for repetitive uses.

Morphological characteristics and microstructure of kidney stones using synchrotron radiation µCT reveal the mechanism of crystal growth and aggregation in mixed stones.

Understanding the mechanisms of kidney stone formation, development patterns and associated pathological features are gaining importance due to an increase in the prevalence of the disease and diversity in the presentation of the stone composition. Based on the microstructural characteristics of kidney stones, it may be possible to explain the differences in the pathogenesis of pure and mixed types of stones. In this study, the microstructure and distribution of mineral components of kidney stones of different mineralogy (pure and mixed types) were analyzed. The intact stones removed from patients were investigated using synchrotron radiation X-ray computed microtomography (SR-µCT) and the tomography slice images were reconstructed representing the density and structure distribution at various elevation planes. Infrared (IR) spectroscopes, X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to confirm the bulk mineral composition in the thin section stones. Observations revealed differences in the micro-morphology of the kidney stones with similar composition in the internal 3-D structure. Calcium oxalate monohydrate stones showed well-organised layering patterns, while uric acid stones showed lower absorption signals with homogenous inner structure. Distinct mineral phases in the mixed types were identified based on the differential absorption rates. The 3-D quantitative analysis of internal porosity and spatial variation between nine different types of stones were compared. The diversity among the microstructure of similar and different types of stones shows that the stone formation is complex and may be governed by both physiological and micro-environmental factors. These factors may predispose a few towards crystal aggregation and stone growth, while, in others the crystals may not establish stable attachment and/or growth.

Milk exosomes - Natural nanoparticles for siRNA delivery.

Gene-silencing with targeted siRNAs has great potential as a therapeutic approach for various diseases including cancer. However, intracellular delivery of siRNA is challenging. We used bovine milk exosomes as a novel system for siRNA delivery. First, we demonstrated that exosomes can deliver endogenous RNA payloads into recipient cells. Next, we loaded siRNA against specific genes including VEGF, EGFR, AKT, MAPK, and KRAS. We utilized 5'-32P-labeled siKRAS as a tracer and found exosome loading with siRNA could be variable. We demonstrated that the siRNA of loaded exosomes is stable and resist degradation. Our results indicated that siRNAs against target genes ranged from 2 to 10-fold knockdown in expression levels in various cancers. Since mutated KRAS has been implicated in the development of various cancers including lung cancer, we tested a mutant-allele specific siRNA against KRASG12S, in A549 cells. We observed a dose-dependent anti-proliferative activity against A549 cells treated with exosomes carrying siKRASG12S. We observed significant inhibition of A549 tumor xenografts in animals treated with folic acid-functionalized exosomes carrying siKRAS. In summary, milk-derived exosomes represent a viable natural nano-carrier for the delivery of siRNA for therapeutic application against cancer.

Morphological and micro-tomographic study on evolution of struvite in synthetic urine infected with bacteria and investigation of its pathological biomineralization.

Pathological biomineralization in the urinary system leads to urolithiasis. Formation of kidney stones involves a series of events during which they undergo morphological and mineralogical changes. We investigated the mineralization of biogenic struvite (in vitro) and examined the transformation of distinct interior and exterior structure of struvite. In vitro crystallization of struvite was performed in the presence of two bacteria that were originally isolated from the kidney stone patients. Morphological evaluation was carried out using SR-µCT as well as FESEM, XRD and FT-IR. Characteristic internal 3-D morphology and porosity of the stones were studied. For comparison, patient derived struvite stones were used. From the results obtained, we report that the presence of bacteria enhances the crystallization process of struvite in vitro. A series of time-resolved experiments revealed that struvite crystals experienced a significant morphologic evolution from pin pointed structure to X-shaped and tabular morphologies. These X-shaped and unusual tabular habits of struvite resembled biogenic morphologies of struvite. SR-µCT showed similarities between the patient derived and the in vitro derived struvite crystals. In conclusion, these experiments revealed that the bacteria play a major role in the specific morphogenesis of struvite and can able to control the nucleation, modulate crystalline phases, and shape of the growing crystal.