Cyclosporine (CsA) is a classical immunosuppressant that requires therapeutic drug monitoring to determine efficacy and adverse effects due to the individualized nature of its drug metabolism. Emerging computer technology has helped to give birth to new approaches to drug therapy. Pharmacokinetic models are used to identify covariates affecting efficacy, predict changes in cyclosporine metabolism and assist in the individualization of CsA treatment. Machine learning algorithms can be used to predict CsA concentrations and adverse events, big data mining can identify rare adverse reactions to CsA in the real world, and the application of internet-based home pharmacy services will yield long-term patient follow-up data. In the future, we will use more computer technology in combination with drug therapy to provide patients with a full range of pharmacy services.
Nanomedicine is a promising platform for drug delivery systems, offering enhanced therapeutic outcomes and reduced side effects. Nanomicelles are a class of nanoparticles that have shown great potential in delivering a wide range of therapeutics, including small molecules, proteins, and nucleic acids, to treat varied diseases and investigations. This review summarises the current state of the art in nanomedicine and its potential applications in drug delivery system. The use of Nanomicelles in topical medication delivery systems can help minimized side effects and improve patient compliance due to their improved stability and prolonged drug release capabilities. The development of stimuli-responsive micelles that can release drugs at specific conditions within the tumour microenvironment and targeted delivery strategies to enhance specificity and efficiency of gene therapy has shown promising results in terms of improved therapeutic efficacy and therapeutic efficiency. However, the presence of multidrug resistance pumps in brain cells can pose challenges in overcoming MDR mechanisms for certain drugs. These innovative approaches hold promise for enhancing the effectiveness of cancer chemotherapy in the brain and improving the prognosis for patients with brain tumours.
The integration of Artificial Intelligence (AI) technologies in Indian healthcare is set to revolutionize drug related problem (DRP) management, ensuring patient safety and optimizing healthcare outcomes. AI-driven drug discovery will enable precision medicine by tailoring treatments to individual patient profiles, genetics, and environmental factors. Medication management will be greatly improved through AI-powered applications that track and monitor patients' medication schedules, reducing adverse reactions and enhancing treatment effectiveness. AI algorithms will play a vital role in identifying potential drug interactions and safety concerns, offering real-time alerts to healthcare providers. Personalized drug prescriptions and dosage recommendations will minimize medication errors and maximize treatment efficacy. Healthcare chatbots will empower patients with accurate information, enabling them to actively manage their health and make informed decisions. AI-driven data analytics will facilitate population health management, guiding evidence-based decision-making to address public health concerns effectively. Remote healthcare services powered by AI-driven telemedicine platforms will bridge the gap between underserved populations and healthcare facilities, providing equitable access to quality care. Despite the transformative potential, challenges such as data privacy, regulatory compliance, and integration with existing healthcare infrastructure must be addressed responsibly. By embracing AI technologies collaboratively, Indian healthcare will enter an era of enhanced DRP management, leading to improved patient safety, optimized healthcare outcomes, and a more efficient and equitable healthcare system.
With the progress of digital technology and innovative drug R&D, machine learning and data-driven algorithms have been increasingly used to support the core work of pharmaceutical areas such as new drug discovery, drug reuse and drug supervision, etc. A new concept of "Smart Pharmacology" has gradually grown into a system with rich connotations and comprehensive coverage, and the related applications and industrial chain have high prospects for development. The so-called "Smart Pharmacology" mainly uses big data, cloud computing, AI, IoT, 5G, Blockchain and other forefront digital technologies to provide whole-process, information-based, intelligence-driven solutions for various scenarios in the pharmacy sectors, including new drug development, drug molecular design, hospital drug management, clinical drug decision support, modernization of traditional medicine, pharmacy informatization, drug regulation and other broad areas, with a wide range covering drug discovery, production, supply, circulation, procurement, allocation and monitoring. In fact, the emergency of smart pharmacology provides a comprehensive and optimized path for modernizing the whole life cycle management of drugs and instills new vitality into the development of modern pharmacy.
This paper presents an in-depth discussion of the development of electronic skin (e-skin) devices for transdermal drug delivery (TDD) for skin health management. E-skin devices, grounded in flexible conductive polymers, demonstrate immense potential as a versatile platform for TDD due to the adaptable properties factors. The integration of sensors and electronic components into e-skin devices seamlessly allows for real-time monitoring of skin health parameters, such as temperature, hydration, and pH levels. Additionally, e-skin devices can also realize the prospect of targeted and controlled drug delivery through the utilization of iontophoresis. This paper explores the current state-of-the-art in e-skin technology, emphasizing its applications in TDD and skin disease management. Furthermore, the paper outlines the prospective directions and prevailing challenges in this rapidly evolving domain.
Diabetes mellitus is a concern of disorder globally and which is increasing continuously. Diabetic complications lead to physical, mental and societal issues to patients. Oral medications are being prescribed but these have problems like frequent dosing, side effects and non-patient compliance. Insulin therapy is also problematic due to injectable route of delivery. Dose missing of these treatments lead to fluctuations in blood glucose levels which cause severe adverse effects. Recent developments have shown the potential of transdermal drug administration in association with nanoformulations for improving the efficacy and safety of anti-diabetic medications. Nanotechnology offers modification of size and surface characteristics of nanocarriers which enhances the drug permeation through biological barriers. Transdermal drug delivery in conjunction with nanocarriers provide enhanced permeation, improved bioavailability and sustained effect with reduction in adverse effects. This article first presents the current scenarios of diabetes mellitus and important aspects of transdermal drug delivery systems. In later sections, a detailed description (pharmaceutical and preclinical characteristics) of various nanoformulation assisted transdermal drug delivery systems (polymeric nanoparticles, ethosomes, nanostructured lipid carriers, solid lipid nanoparticles, microemulsions, liposomes, niosomes, nanoemulsions, transethosomes and transfersomes) have been reviewed. Transdermal drug delivery in conjunction with nanoformulations can be utilized for the better management and control of diabetes.
The newly identified COVID-19 variant, B.1.1.529, initially detected in South Africa, was officially designated as the “Omicron” variant by the World Health Organization on November 26, 2021. This variant has raised concerns globally. From January 17 to November 26, 2021, Public Health Ontario (PHO) Library Services conducted extensive searches of published literature and preprints using the MEDLINE database. A total of six articles and one ongoing clinical trial were identified. Data from 15 published and unpublished reports, including interim findings, were collected. The WHO, ICMR, daily updates web page, internet sources, news, and hospitalization or death data were analyzed to assess the risk associated with the Omicron variant compared to non-hospitalized COVID-19 patients. The data suggested a potential 50% increase in the risk of hospitalization or death among Omicron patients compared to previous variants. Considering the emergence of the Omicron variant, it is important to note that India has an advantage due to its extensive immunization program, which annually vaccinates approximately 2.7 crorenewborns. However, it is crucial to ensure that vaccines meet all validation requirements and regulatory frameworks before they are made available to the public.
Epigenetics is a rapidly growing field that deals with the study of heritable changes in gene expression that occur without a change in DNA sequence. DNA methylation, histone modification, and noncoding or microRNAs are the three major mechanisms of epigenetics that can best explain how genes are regulated. These processes are mediated by various enzymes such as DNA methyltransferases, histone acetyltransferases, histone deacetylases, and microRNA biogenesis enzymes. Dysregulation of these enzymes can lead to various pathological conditions, including cardiovascular diseases (CVDs). In recent years, the role of epigenetics in CVDs has gained significant attention as an important regulatory key player in the pathophysiology and therapeutics of these diseases. Epigenetics is an area of scientific study that has been instrumental in exploring the mechanisms that control gene expression. It has been observed that changes in chromatin or its packaging have a large impact on DNA accessibility, which leads to modifications in various cellular processes. DNA methylation, histone modification, and noncoding or microRNAs are the primary tools used by epigenetics to regulate these changes. A variety of enzymes responsible for DNA methylation, histone modification, and microRNAs have been found to play a critical role in the onset of various CVDs (cardiovascular diseases). Epigenetics is now regarded as an important player in the regulation of cardiovascular disease at various levels, from pathophysiology to therapeutic interventions. This article comprehensively investigates the diverse epigenetic aspects which are associated with the occurrence of cardiovascular disorders.
The study was to develop a transdermal formulation of insulin, determine its pharmaceutical characteristics, and finally test its efficacy. In the current study - Transfersomes were selected as the carrier system for insulin. The transfersomes were produced by the hand-shaking method using soy lecithin phospholipid and sodium deoxycholate as the objective of the surfactant. The prepared transfersomes were subjected to characterization with optical microscopy and scanning electron microscope to estimate the shape and size of transfersomes respectively. In addition, the physical and drug-excipient interaction studies were carried out and the transfersomes were also studied for the insulin entrapment efficiency.
Results of the study showed the shape of the transfersomes was well defined and spherical. The mean size of transfersomes was estimated to be 130 nm The transfersomes were found to be stable over a period of four weeks. The insulin entrapment efficiency of the transfersomes was estimated to be 87.3%. The ex-vivo skin permeation study employing goat ear skin with the transfersomes hydrogel revealed that there was a slow and sustained release of insulin till 180 min. From the above study, it may be concluded that transfersomes are suitable carriers of insulin across biological membranes.
Health is crucial for personal happiness, productivity, and fulfillment. It impacts physical well-being, mental health, longevity, academic and professional success, and interpersonal relationships. It reduces healthcare costs, contributes to economic growth, and promotes community well-being. This paper explores the status of the healthcare system in rural India. Paper reviews available research and also collects data from rural hospitals. It also considers efforts by the Indian government and other organisations, such as Ayushman Bharat, which is acknowledged for its aim to strengthen primary healthcare and protect economically vulnerable populations. However, addressing these complex issues requires continuous efforts, adequate funding, and proactive measures in healthcare infrastructure, workforce development, and policy reforms. The presented data reflects rural areas' ongoing challenges, underscoring the pressing need for proper treatment and care. By prioritising the presented aspects, the healthcare landscape in rural India can witness positive transformations and ensure improved healthcare outcomes for its population. In this paper, the possible problems and solutions addressed which has been observed while visiting hospitals in rural areas of northeast India. Research findings emphasise the significance of implementing supply chain strategies in improving healthcare delivery. It concludes that the potential of Medical 4.0 applications with seven common effective findings can save numerous lives in rural areas by providing timely access to healthcare solutions.
Ficus benghalensis is the ingredient of a variety of Ayurvedic herbal formulations for the management of blood-related illnesses. In the current study, the new-fangled stem ethanol extract fractions in chloroform and methanol (CFFB & MFFB) were assessed for antiplatelet, thrombolytic and toxicity studies, as well as for phytoconstituent identification GC/MS was performed. The dried powdered stem bud was extracted with 80% ethanol and successively fractionated by chloroform and methanol (CFFB & MFFB). The anti-platelet, anti-thrombotic, and thrombolytic, activity of CFFB & MFFB were tested in ex vivo mode and toxicity of methanol fraction (MFFB) was tested in in vivo. The chief feasible marker components for antiplatelet activity recognized by GC-MS in the MFFB are Diethyl phthalate, (E)-4-(3-Hydroxyprop-1-en-1-yl)-2-methoxyphenol, 7,9-Di-tert-butyl-1-oxaspiro (4,5) deca-6,9-diene-2,8-dione and trans-Sinapyl alcohol might act as irreversible cyclooxygenase inhibitors like Aspirin. In the study, at 50 μg/mL, the antiplatelet activity of CFFB, MFFB, and aspirin was 50.41, 82.19, and 86.34%, and a substantial adjournment in clot development was observed whereas CFFB at different dosages did not exhibit significant outcome on the adjournment of clot formation, antiplatelet, and antioxidant activity. The toxicity examination of MFFB did not confirm any substantial signs of toxicity and mortality up to 1.5 g/kg, b.w and non-toxic up to 1.0 g/kg, b.w which is capable of the comportment of atherothrombotic ailments. The MFFB exhibited anti-platelet, anti-thrombotic, thrombolytic, and anti-oxidant activity, and capacity to prevent cardiovascular disorders without causing toxicity.
This research investigates the potential of bioactive compounds derived from cyanobacteria as inhibitors of alpha-amylase and beta-glucosidase enzymes, which are involved in starch digestion and glucose release. The study reveals strong molecular interactions between these compounds and the enzyme active sites through docking analysis. Notably, compounds such as Abietic, Anilide, Nostocarboline, Noscomin, Tanikolide, Tubercidin, Cryptophycin, and Cyanobacteria exhibit the lowest binding energies when interacting with alpha-amylase. Among them, Noscomin demonstrates the lowest docking score and binding energy against alpha-amylase, outperforming the reference compound metformin. Similarly, these compounds also display low binding energies when interacting with beta-glucosidase. The bioactive compounds from cyanobacteria show significant potential as inhibitors of alpha-amylase and beta-glucosidase, suggesting their efficacy in managing diabetes by slowing down starch digestion and controlling glucose release. Their superior binding affinities and lower binding energies, particularly Noscomin, indicate their potential in regulating blood sugar levels by interacting effectively with these enzymes. Thus, these compounds hold promise as valuable leads for developing alpha-amylase and beta-glucosidase inhibitors, contributing to the management of diabetes. Further research is required to understand the underlying mechanisms of action and assess the bioavailability, toxicity, and pharmacological potential of these cyanobacterial compounds. This investigation provides valuable insights into the potential of cyanobacterial bioactive compounds as effective candidates for the development of novel therapeutics targeting alpha-amylase and beta-glucosidase enzymes in diabetes management.
Purpose Artificial neural network (ANN) model has been developed in prediction of serum drug concentration. The aim of this study was verifying the accuracy of ANN model in predicting vancomycin trough serum concentration in ARC adult patients.
Methods A total of 162 ARC patients (258 observations) who received vancomycin treatment (500–2000 mg) at the First Affiliated Hospital of China Medical University between Jan 2017 and Nov 2020 were included. The performance and accuracy of the ANN model was evaluated by mean absolute deviation (MAD), mean absolute percent error (MAPE), mean square error (MSE), and root mean squared error (RMSE). In addition, the vancomycin calculator and multivariable linear regressions were compared with the ANN model in predicting vancomycin concentration.
Results From results of linear regression analyses, dosage, dosage interval, age, creatinine clearance, sex, weight, total bilirubin (T-Bil), haemoglobin (HGB) and total protein (TP) were used as input variables to develop an ANN model for predicting vancomycin concentration in ARC patients. The MAPE, MSE, RMSE, MAD and R2 were 14.81%, 2.47%, 0.44%, 1.40% and 0.88%, respectively.
The ANN model might be an useful tool to predict vancomycin concentration and help modify the dosing regimen accurately and in a timely manner to improve the clinical efficacy in ARC patients. In the future, ANN model could be developed to predict serum concentration and modify dosing regimens for more types of therapeutic drugs and patients with more complex diseases.
Polygonum Cuspidate (P. cuspidatum) is a traditional topical preparation of Chinese medicine. The aim of this study was to develop HPLC fingerprints for P. cuspidatum Powder and P. cuspidatum Ointment, as well as to determine the total stilbene and total anthraquinone contents in them. A XB-C18 column (250 mm × 4.6 mm, 5 μm) was used with a mobile phase consisting of 0.1% phosphoric acid solution-acetonitrile and a gradient elution. The flow rate was 1.0 ml/min and the detection wavelength was 286 nm. The column temperature was 30 °C and injection volume was 10 μl. The similarity evaluation system for chromatographic fingerprint of traditional Chinese medicine (2012 edition) was employed to confirm the common peaks at 13 batches of samples and to assess the similarity. The study revealed that 20 common peaks were identified in both P. cuspidatum powder and P. cuspidatum ointment, with a similarity greater than 0.95. Amongst them, seven components were attributed and confirmed, which were identified as polydatin, resveratrol, emodin-8-glucoside, aloe-emodin, rhein, emodin and physcion. Under the established conditions of the chromatography, quantitative analysis of six components could be well separated, and had a good linearity and linear range, the precision, repeatability and stability were good. The method's efficacy in assessing the quality of P. cuspidatum powder and P. cuspidatum ointment is validated, and it can be employed for quality control purposes.
This study assessed Lavandula stoechas flower extract's impact on Isoprenaline-induced myocardial necrosis in rats. Five groups of five rats each were used. Group I received 1 ml/kg normal saline orally for 13 days, Group II received 10 ml/kg normal saline orally, Group III received 200 mg/kg Lavandula stoechas extract orally, Group IV received 400 mg/kg Lavandula stoechas extract orally, and Group V received 10 mg/kg Metoprolol orally. On days 14 and 15, Group I received 0.5 ml/kg subcutaneous normal saline, and Groups II to V received 85 mg/kg Isoprenaline subcutaneously. On day 16, rats were weighed, and cardiac blood samples were collected. Serum was analyzed for total protein, triglycerides, and cardiac enzymes (cardiac injury markers). Rats were sacrificed, and heart tissues were histologically examined.
Results showed significant serum marker enzyme reductions (p < 0.01) in Lavandula stoechas-treated rats. Total protein and triglyceride levels (p < 0.01) decreased, and heart weight-to-body weight ratio (p < 0.05) decreased in Lavandula stoechas-treated rats. Histopathology confirmed the extract's protective effect.
In conclusion, Lavandula stoechas flower extract offers protection against Isoprenaline-induced myocardial infarction in rats.
Prostate cancer is a common malignant tumor in men and early diagnosis and treatment are crucial for the survival rate of patients. This study aimed to establish a machine learning-based prostate cancer prediction model to help physicians accurately identify high-risk patients. This study performed a retrospective analysis using prostate cancer patient data from the MIMIC-IV database. First, the data was cleaned and preprocessed, including imputing missing values, handling outliers, and feature selection. Then, prediction models were established using machine learning algorithms (including logistic regression, support vector machine, deep neural networks, XGBoost, LightGBM and CatBoost) and evaluated using cross-validation and ROC curve analysis. We screened out 1975 patients diagnosed with PC and 11,745 patients diagnosed with BPH based on ICD codes. However, among the BPH patients, 467 were also diagnosed with PC, so we excluded these patients. The LightGBM machine learning model outperformed the other models in distinguishing patients with PC [LightGBM vs. CatBoost vs. XGBoost vs. DNN vs. SVM vs. LR; area under the curve (AUC): 0.93 vs. 0.91 vs. 0.89 vs. 0.86 vs. 0.70 vs. 0.68, respectively]. The LightGBM model had a sensitivity of 86%, specificity of 85% at the best cut-off value. The model was capable of predicting whether a patient has prostate cancer based on their clinical features (including age, Laboratory test, etc.) and had a high level of accuracy and stability. The machine learning-based prostate cancer prediction model established in this study has some clinical application value and can help physicians accurately identify high-risk patients, providing more precise prevention and treatment plans for patients.
Background: Eltrombopag, the first TPO-RA approved for the treatment of ITP, resulted in rapid and sustained increases in platelet counts, significant reductions in bleeding events and concomitant medications, and an acceptable tolerability profile. This study aimed to explore the current status of ITP treatment with eltrombopag as the target drug and the utilization of medical resources from the perspective of hospitals.
Methods: Data collection was based on two parts: real-world data and expert interviews. Real-world data of outpatients with ITP who received second-line treatment or other treatment from 1 year before to 1 year after eltrombopag admission were collected to analyze the current status of non-first-line treatment in ITP outpatients. Ten specialist physicians were interviewed to collect parameters such as efficacy, safety, and medical cost of ITP treatment regimens.
Result: The real-worlddata showed that among non-first-line treatment, market share of second-line treatment was lower than that of other treatment before the admission of eltrombopag, and the market share of second-line treatment was the higher than that of other treatment after the admission of eltrombopag in both adult and pediatric ITP patients. After the admission of eltrombopag, the annual outpatient drug-related treatment costs for adults with ITP increased by ￥13717.05, and the annual outpatient drug-related treatment costs for children with ITP increased by ￥7762.90. The results of expert interviews showed that more patients switched from other treatment to second-line treatment after the admission of eltrombopag in clinical. Eltrombopag demonstrated superior efficacy, safety and higher adherence in second-line treatment.
Conclusions: The new oral TPO-RA drugs have improved the treatment options for ITP patients, and more patients accept eltrombopag for non-first-line treatment. After eltrombopag admission, the annual outpatient drug-related treatment costs increased for both adult and pediatric patients. Nevertheless, by reason of advantages of its efficacy, tolerance, medication adherence and other aspects, eltrombopag has become an important drug in the non-first-line treatment of ITP.Additional comprehensive research is needed to verify the results.
Oral thrush, also known as candidiasis, is one of the most common parasitic infections of the human mouth. A 35-year-old female patient complaining of breathlessness, cough, and fever. She was prescribed azithromycin 500 mg po (per os; by mouth, orally), co-trimoxazole 160 mg + 800 mg po, and Paracetamol 500 mg po t.d.s. After 10 days, she visited a tertiary care hospital complaining of severe oral thrush, itching, white bumps over her cheeks and tongue, and difficulty swallowing. She stopped taking solid food due to severe pain. Her laboratory tests revealed that her haemoglobin was -6.8 g/dl (12–16 g/dl) and her erythrocyte sedimentation rate was 45 mm/h. Due to a side effect of the antibiotics, she had very bad mouth thrush. To the best of our knowledge, this is the first reported case of oral candida inducing a patient after treatment with the anti-candida drugs, and it suggests that this side effect should be taken into account when prescribing these antibiotics.
Guillain-Barre syndrome is an autoimmune disorder with the most common clinical presentation of neuromuscular paralysis. Here we have reported a rare case of GBS in a 60-year-old male patient admitted to the male medicine ward with a chief complaint of weakness in B/L upper limb and B/L lower limb from 5 -7 days. Laboratory investigation of biochemistry analysis shows CSF protein (161mg/dl), neutrophils (91%), and S.Urea (44.0 mg/dl). Radiological investigation CT scan of the brain shows atrophic changes and MRI cervical spine -shows cervical spondylosis with compression myelopathic changes at C4, and C5 level and multilevel disc herniation and bulges. Nerve conduction studies of all four limbs were also performed by sampling from the median, ulnar, peroneal, tibial, and sural nerves. It shows B/L Upper and Lower limb (sensor + motor) demyelinating polyneuropathy. more prevalent in the upper limb than in the lower limbs. After being admitted, the patient received treatment that included antibiotics, analgesics, muscle relaxants, multivitamins, and other supportive measures. Intravenous immunoglobulin infusion was started due to the patient's symptoms steadily getting worse, and soon after that, things started to get better for the patient.