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Abstract: Artificial intelligence (AI) speeds up the drug development process and reduces its time, as well as the cost which is of enormous importance in outbreaks such as COVID-19. It uses a set of machine learning algorithms that collects the available data from resources, categorises, processes and develops novel learning methodologies. Virtual screening is a successful application of AI, which is used in screening huge drug-like databases and filtering to a small number of compounds. The brain’s thinking of AI is its neural networking which uses techniques such as Convoluted Neural Network (CNN), Recursive Neural Network (RNN) or Generative Adversial Neural Network (GANN). The application ranges from small molecule drug discovery to the development of vaccines. In the present review article, we discussed various techniques of drug design, structure and ligand-based, pharmacokinetics and toxicity prediction using AI. The rapid phase of discovery is the need of the hour and AI is a targeted approach to achieve this.

PurposeThis paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach.Design/methodology/approachThe present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation.FindingsThe findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week.Research limitations/implicationsThe implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain.Originality/valueThe novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations.

The most promising class of heterocyclic compounds in medicinal chemistry are those with the quinolin-2-one nucleus. It is a versatile heterocyclic molecule that has been put together with numerous pharmaceutical substances and is crucial in the creation of anticancer medications. In this view, the present research work deals with design, synthesis, and characterization of various analogous of quinolin-2-one nucleus and evaluation of their anticancer activity against MCF-7 cells (adenoma breast cancer cell line). Fourteen new compounds have been synthesised using suitable synthetic route and are characterized by FTIR

Breast cancer is a major health concern as it is the second leading cause of death from cancer. There are several well-known risk factors that contribute to breast cancer. Despite the various treatment options available, complete cure is still difficult due to heterogenicity of BC subtypes. As a result, identifying BC subtypes is critical for determining the optimal treatment approach. Over the last several years, new drugs targeting particular therapeutic targets have resulted in significant advances in the treatment of breast cancer. Nonetheless, resistance to treatment is the “major” issue, and a significant increase in survival rates has been the main focus for researchers. The purpose of this review article is to provide a broad overview of the molecular basis of drug resistance in breast cancer, as well as a detailed assessment of current treatment options, potential new treatment methods for drug-resistant breast cancer and repurposed drugs used for treatment. The possibility of non-cancer drugs being studied for breast cancer in the future, as well as the obstacles and bottlenecks of drug repurposing, is also highlighted. Finally, we go through present problems and future prospects in drug-resistant breast cancer therapy.

Drug repurposing opens new avenues in cancer therapy. Drug repurposing, or finding new uses for existing drugs, can substantially reduce drug discovery time and costs. Cheminformatics, genetics, and systems biology advances enable repositioning drugs. Clinical usage of PD-1/PD-L1 blocking has been approved because of its efficacy in improving prognosis in select groups. The PD-1/PD-L1 axis was considered to represent a mechanism for tumour evasion of host tumour antigen-specific T-cell immunity in early preclinical research. The expression of PD-L1 in cancer cells causes T lymphocytes to become exhausted by transmitting a co-inhibitory signal. A better understanding of how PD-L1 is regulated in cancer cells could lead to new therapeutic options. In this view, the study was aimed to repurpose the existing FDA-approved drugs as a potential PD-L1 inhibitor through e-Pharmacophore modelling, molecular docking and dynamic simulation. e-Pharmacophore screening retrieved 324 FDA-approved medications with the fitness score ≥ 1. The top 10-docked FDA candidates were compared with IN-35 (Clinical trial candidate) for its interaction pattern with critical amino acid residues. Mirabegron and Indacaterol exhibited a greater affinity for PD-L1 with docking scores of - 9.213 kcal mol

Background: Bioactive compounds obtained from natural sources like plants, algae, mushrooms and marine have become of utmost importance in the pharmaceutical, food and cosmetic industries. Many bioactive chemicals have been found to have health-promoting characteristics, including antioxidant, antidiabetic, antibacterial, and anticancer activities. Extraction of these bioactive chemicals from natural sources is difficult since they are present in extremely low concentrations inside the cell. Methods: The complete cropping of bioactive compounds from natural sources depends on several physicochemical parameters such as solvent, solvent concentration, temperature, pressure, time, etc., and they play a crucial role in determining the efficiency of extraction. Furthermore, these factors are not inherently connected to one another, but when they are combined, they change not just the extraction efficiency but also the process cost. As a result, the physicochemical parameters must be properly adjusted in order to increase the extraction efficiency as well as the biological characteristics of isolated molecules. Results: The article provides a thorough examination of several extraction strategies, as well as the mechanism and concepts that underpin them. Also, the review highlights the impact of various physicochemical parameters on the effective extraction of bioactive compounds from natural sources to meet the standards of industrial requirements. Conclusion: Many of the tests have been conducted at the laboratory level; as a result, recommendations for scaling up the extraction process have been provided in order to assess the performance of small-scale to large-scale industrial operations.

Enhanced cancer treatment remains as one of the focused areas for researchers around the world. Hence, the progress in this direction will be a challenge and an opportunity in, inter-disciplinary field to mitigate the suffering of millions in the upcoming decades. As we see, cancer death rate has also progressively increased despite the current impressive treatment regimens but also due to the non-availability of vaccines and the re-occurring of cancer in substantially recovered patients. Currently, numerous treatment strategies like surgical removal of solid tumors followed by radiation with a combination of immunotherapy/chemotherapy by the researchers and clinicians are routinely being followed. However, recurrence and distant metastasis often occur following radiation therapy, commonly due to the generation of radio-resistance through deregulation of the cell cycle, cell death, and inhibition of DNA damage repair mechanisms. Thus, chemotherapeutic/immunotherapeutic treatment systems have progressed remarkably in the latest years owing to destroying tumors, noninvasive, and affordable charge of therapy. But, traditional chemotherapeutic approaches target the DNA of mutated and normal healthy cells, resulting in a significantly increased risk of toxicity and drug resistance. Thus, many receptors targeted therapies are in the developmental phase of discovery. Cancer cells have a specialized set of surface receptors that provide potential targets for cancer therapeutics. Cell surface receptor-dependent endocytosis is well a known major mechanism for the internalization of macromolecular drugs. This review emphasizes the recent development of several surface receptors mediated cancer-targeting approaches for the effective delivery of various therapeutic formulations.

In the present work, novel 3-(4-(5-(substituted phenyl)-3-phenyl-4,5-dihydro-1H-pyrazole-1-carbonyl)phenylimino)-1-(substitutedmethyl)indolin-2-one derivatives were obtained via the reaction of 4-(1-(substituted methyl)-2-oxoindolin-3-ylideneamino) benzohydrazide with appropriate aromatic chalcone. The synthesized compounds were investigated for their in silico chemokine/CXCR6 inhibitory activity. The most effective chemokine inhibitors were also evaluated for their in vivo antiinflammatory activity. The 3-(4-(5-(4-Chlorophenyl)-3-phenyl-4,5-dihydro-1H-pyrazole-1-carbonyl) phenylimino)-1-(morpholino methyl) indolin-2-one (5a) derivative showed significant chemokine inhibition with eleven amino acid interaction as compared with standard Acetaminophen whereas Celecoxib, Diclofenac, Indomethacin, Naproxen, Ibuprofen, Aspirin showed less amino acid interaction. Based on the theoretical study reports the in vivo antiinflammatory activity was performed for the 3-(4-(5-(substituted phenyl)-3-phenyl-4,5-dihydro-1H-pyrazole-1-carbonyl)phenylimino)-1-(substitutedmethyl)indolin-2-one (5a-5l). The observed results of in vivo study indicate that the compounds 5a, 5c exhibited significant antiinflammatory activity.

Background: Cervical cancer is one of the leading causes of female death, with a mortality rate of over 200,000 per year in developing countries. Despite a decrease in cervical cancer occurrences in developed countries over the last decade, the frequency of the disease in developing nations continues to rise at an alarming rate, particularly when it is linked to the human papillomavirus (HPV). With just a few highly invasive conventional therapies available, there is a clear need for novel treatment options such as nanotechnology-based chemotherapeutic drug delivery. Current limitations: Traditional anticancer therapy is limited by poor drug potency, non-specificity, unwanted side effects, and the development of multiple drug resistance (MDR), leading to a decrease in long-term anticancer therapeutic efficacy. An ideal cancer therapy requires a personalized and specialized medication delivery method capable of eradicating even the last cancer cell responsible for disease recurrence. Purpose: Nanotechnology provides effective drug delivery mechanisms, allowing it to serve both therapeutic and diagnostic purposes. Nanotechnology-based formulations are widely used to accurately target the target organ, maintain drug load bioactivity, preferentially accumulate the drug at the target location, and reduce cytotoxicity. Future perspectives: The key benefits of this drug delivery are that it improves pharmacological activity, solubility, and bioavailability and reduces toxicity in the target tissue by targeting ligands, allowing for new innovative treatment methods in an area that is desperately required. The goal of this review is to highlight possible research on nanotechnology- based delivery systems for cancer detection and treatment.

Brain tumor is an abnormal growth of mass of cells in (or) around the brain. Brain tumors can be malignant (cancerous) or being non-cancerous. It is the most common malignant primary intracranial tumors of central nervous system. Brain tumor can affect brain function if they grow large enough to press on surrounding nerves, blood vessels and tissues. Only one third of tumors formed in the brain are formed as cancerous cells. Brain tumors release molecular information to the circulation. Liquid biopsies collect and analyse tumor component in the body fluid and there is an increasing interest in investigation of liquid biopsies as substitute from tumor markers. Tumor-derived biomarkers include nucleic acids, proteins and tumor-derived extracellular vesicles that accumulate in blood (or) cerebrospinal fluid. Circulating biomarkers like O-6-methylguanine DNA methyl transferase, epidermal growth factor, isocitrate dehydrogenase, circulating tumor cells, circulating cell free micro RNAs, circulating extracellular vesicles plays and important role in causing a cancer. Brain tumor can be treated by surgery, radiation therapy (or) targeted therapy. Radiation therapy is often given afterwards. As a consequence, the most recent review reviewed the present state of research with the hopes of discovering a new brain tumor inhibitor that may be used to treat advanced malignancies.

The main focus of present study is to optimize the extraction parameters for maximum yield of biomass, β-carotene and chlorophyll content and their antioxidants from Kappaphycus alvarezii by response surface methodology (RSM) along with adaptive neuro-fuzzy inference system (ANFIS). Central composite rotatable design of RSM was applied to optimize the effect of microwave-assisted extraction (MAE) parameters. In this way, four parameters, such as methanol concentration (X1: 65–80%), microwave power (X2: 15–20%), radiation induced temperature (X3: 45–60 °C) and radiation exposure time (X4: 7.5–15 min) at five levels were selected. Optimal conditions were found as X1 = 80%, X2 = 20%, X3 = 45 °C and X4 = 12.5–14.5 min, under this condition, % yield of biomass (y1) = 86.231–87.212%, β-carotene and chlorophyll content (y2) = 77.348–82.841 mg/gm, %DPPHsc (y3) = 69.362–72.768%, %ABTSsc (y4) = 66.282–70.621%, FRAP (y5) = 62.654–64.381 μg mol (Fe(II))/g has been obtained. Also, optimized values of MAE parameters were compared and verified with ANFIS. Further, the major bioactive compounds present in the optimally obtained extract of K. alvarezii was identified through FTIR, gas chromatography-mass spectrum and HPLC.

The following study was done to assess the glucose utilizing efficiency of Indoloquinoxaline derivative incorporated keratin nanoparticles (NPs) in 3T3-L1 adipocytes. Indoloquinoxaline derivative had wide range of biological activities including antidiabetic activity. In this view, Indoloquinoxaline moiety containing N, N-dimethyl (3-fluoro-6H-indolo [3,2-b] quinoxalin-6-yl) methanamine compound was designed and synthesized, and further it is incorporated into keratin nanoparticles. The formulated NPs, drug entrapment efficiency, releasing capacity, stability, and physicochemical properties were characterized by various spectral analyzer and obtained results of characterizations were confirmed the properties of NPs. The analysis of mechanism underlying the glucose utilization of NPs was examined through molecular docking with identified target, and observed in silico study reports shown strong interaction of NPs in the binding pockets of AMPK and PTP1B. Based on the in silico screening, the formulated NPs was performed for in vitro cellular viability and glucose uptake studies on 3T3-L1 adipocytes. Interestingly, 40 μg of NPs displayed 78.2 ± 2.76% cellular viability, and no cell death was observed at lower concentrations. Further, the concentration dependent glucose utilization was observed at different concentrations of NPs in 3T3-L1 adipocytes. The results of NPs (40 μg) on glucose utilization have revealed eminent result 58.56 ± 4.54% compared to that of Metformin (10 μM) and Insulin (10 μM). The identified results clearly indicated that Indoloquinoxaline derivative incorporated keratin NPs significantly increased glucose utilization efficiency and protect the cells against the insulin resistance.