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Scientific Reports Jul 2022These days, many efforts have been made to increase and develop the solubility and bioavailability of novel therapeutic medicines. One of the most believable approaches...
These days, many efforts have been made to increase and develop the solubility and bioavailability of novel therapeutic medicines. One of the most believable approaches is the operation of supercritical carbon dioxide fluid (SC-CO). This operation has been used as a unique method in pharmacology due to the brilliant positive points such as colorless nature, cost-effectives, and environmentally friendly. This research project is aimed to mathematically calculate the solubility of Oxaprozin in SC-CO through artificial intelligence. Oxaprozin is a nonsteroidal anti-inflammatory drug which is useful in arthritis disease to improve swelling and pain. Oxaprozin is a type of BCS class II (Biopharmaceutical Classification) drug with low solubility and bioavailability. Here in order to optimize and improve the solubility of Oxaprozin, three ensemble decision tree-based models including random forest (RF), Extremely random trees (ET), and gradient boosting (GB) are considered. 32 data vectors are used for this modeling, moreover, temperature and pressure as inputs, and drug solubility as output. Using the MSE metric, ET, RF, and GB illustrated error rates of 6.29E-09, 9.71E-09, and 3.78E-11. Then, using the R-squared metric, they demonstrated results including 0.999, 0.984, and 0.999, respectively. GB is selected as the best fitted model with the optimal values including 33.15 (K) for the temperature, 380.4 (bar) for the pressure and 0.001242 (mole fraction) as optimized value for the solubility.
Topics: Anti-Inflammatory Agents, Non-Steroidal; Artificial Intelligence; Carbon Dioxide; Oxaprozin; Propionates; Solubility
PubMed: 35907929
DOI: 10.1038/s41598-022-17350-5 -
Clinical and Experimental Nephrology Mar 2020Dotinurad is a novel, selective urate reabsorption inhibitor, which reduces serum uric acid levels by inhibiting the urate transporter 1. The results of nonclinical... (Clinical Trial)
Clinical Trial
BACKGROUND
Dotinurad is a novel, selective urate reabsorption inhibitor, which reduces serum uric acid levels by inhibiting the urate transporter 1. The results of nonclinical studies indicated the possibility that the concomitant use of the non-steroidal anti-inflammatory drug oxaprozin affects the pharmacokinetics of dotinurad. We evaluated drug-drug interactions with respect to the pharmacokinetics and safety of dotinurad when co-administered with oxaprozin.
METHODS
This was an open-label, two-period, add-on study in healthy adult males. For a single dose of 4 mg of dotinurad with and without oxaprozin, we compared its pharmacokinetic parameters and evaluated safety.
RESULTS
This study enrolled 12 subjects, 11 of whom completed the study. The geometric mean ratio (90% confidence interval [CI]) of the urinary excretion rate of glucuronate conjugates of dotinurad after co-administration with oxaprozin compared to administration of dotinurad alone was 0.657 (0.624-0.692), while the geometric mean ratios (90% CIs) of the maximum plasma concentration and area under the plasma concentration-time curve from time zero to infinity (AUC) were 0.982 (0.945-1.021) and 1.165 (1.114-1.219), respectively. During the study, two adverse events occurred after administration of dotinurad alone and one occurred after administration of oxaprozin alone.
CONCLUSIONS
In comparison with administration of dotinurad alone, co-administration with oxaprozin was associated with a 34.3% decrease in the urinary excretion rate of the glucuronate conjugates of dotinurad, and a 16.5% increase in AUC of dotinurad. However, no clinically meaningful drug-drug interactions were observed. Administration of dotinurad alone was similar safety to co-administration with oxaprozin.
CLINICAL TRIAL REGISTRATION
ClinicalTrials.gov Identifier: NCT03350386.
Topics: Adult; Anti-Inflammatory Agents, Non-Steroidal; Benzothiazoles; Drug Interactions; Glucuronides; Humans; Japan; Male; Oxaprozin; Sulfates; Uricosuric Agents
PubMed: 32076889
DOI: 10.1007/s10157-020-01855-2 -
Bioinformation 2022Epilepsy is one of the most common neurological disorders, affecting millions of patients with a substantial economic and human burden. About 30-40% of epileptic...
Epilepsy is one of the most common neurological disorders, affecting millions of patients with a substantial economic and human burden. About 30-40% of epileptic patients remain un-treated after the therapeutic option. Genetic or idiopathic epilepsy count about 40% of total epilepsy patients, showing a maximum percentage for drug-resistant epilepsy. Since the last century basic approach to understanding disease progression and drug discovery has been through the prism, exploring all possible causes and treatment options. Here we report about the gene expression-based drug repositioning study for epilepsy. Epilepsy gene expression data was retrieved from the Gene Expression Omnibus database, while drugs-associated gene expression data was retrieved from the Connectivity map (CMAP). The study predicted309 drug compounds which can alter genetic epilepsy-mediated gene signature using an in-house developed R-script. These compounds were docked against identified epilepsy targets- Voltage-gated sodium channel subunit α2 (Nav1.2); GABA receptor α1-β1; and Voltage-gated calcium channel α1G (Cav3.1)using Carbamazepine, Clonazepam, and Pregabalin as standard drugs, respectively. Twenty-one predicted drug compounds showed better binding affinity than respective standards against the selected epileptic receptors. Among these drug compounds, Ergocalciferol, Oxaprozin, Flunarizine, Triprolidine and Cyproheptadine have been previously reported for anti-epileptic activities and can be potential hits to target idiopathic epilepsy.
PubMed: 37654844
DOI: 10.6026/97320630018845 -
Scientific Reports Jul 2022Accurate specification of the drugs' solubility is known as an important activity to appropriately manage the supercritical impregnation process. Over the last decades,...
Accurate specification of the drugs' solubility is known as an important activity to appropriately manage the supercritical impregnation process. Over the last decades, the application of supercritical fluids (SCFs), mainly CO, has found great interest as a promising solution to dominate the limitations of traditional methods including high toxicity, difficulty of control, high expense and low stability. Oxaprozin is an efficient off-patent nonsteroidal anti-inflammatory drug (NSAID), which is being extensively used for the pain management of patients suffering from chronic musculoskeletal disorders such as rheumatoid arthritis. In this paper, the prominent purpose of the authors is to predict and consequently optimize the solubility of Oxaprozin inside the COSCF. To do this, the authors employed two basic models and improved them with the Adaboost ensemble method. The base models include Gaussian process regression (GPR) and decision tree (DT). We optimized and evaluated the hyper-parameters of them using standard metrics. Boosted DT has an MAE error rate, an R2-score, and an MAPE of 6.806E-05, 0.980, and 4.511E-01, respectively. Also, boosted GPR has an R2-score of 0.998 and its MAPE error is 3.929E-02, and with MAE it has an error rate of 5.024E-06. So, boosted GPR was chosen as the best model, and the best values were: (T = 3.38E + 02, P = 4.0E + 02, Solubility = 0.001241).
Topics: Anti-Inflammatory Agents, Non-Steroidal; Humans; Machine Learning; Oxaprozin; Propionates; Solubility
PubMed: 35908085
DOI: 10.1038/s41598-022-17440-4 -
British Journal of Clinical Pharmacology Mar 1985A series of 42 healthy male and female volunteers aged 21 to 89 years received a single 1200 mg oral dose of oxaprozin. Kinetics were determined from multiple plasma...
A series of 42 healthy male and female volunteers aged 21 to 89 years received a single 1200 mg oral dose of oxaprozin. Kinetics were determined from multiple plasma oxaprozin concentrations measured by h.p.l.c. during 14 days after the dose. Peak plasma oxaprozin concentrations were reached between 3 and 6 h after dosage the majority of subjects, probably reflecting slow absorption from the gastrointestinal tract. Elimination also was slow with a mean half-life of 59 h (range 36 to 92 h). Owing in part to extensive protein binding (mean free fraction 0.0023%), oxaprozin distribution was limited, with apparent volume of distribution averaging 0.25 l/kg. Apparent volume of distribution declined with increasing age, probably reflecting the reduction in lean mass relative to total weight that occurs in the elderly. Total apparent oxaprozin clearance declined with age in men (r = -0.58, P less than 0.01), but was not significantly related to age in women (r = -0.25, NS). This is consistent with the previously described gender-specific reduction in hepatic oxidizing capacity association with increasing age. Thus oxaprozin is a slowly eliminated nonsteroidal anti-inflammatory agent that should be suitable for once daily or every other day administration.
Topics: Adult; Age Factors; Aged; Anti-Inflammatory Agents; Chromatography, High Pressure Liquid; Female; Half-Life; Humans; Kinetics; Male; Middle Aged; Oxaprozin; Propionates; Sex Factors
PubMed: 3986088
DOI: 10.1111/j.1365-2125.1985.tb02656.x -
Journal of Andrology 1989To evaluate the influence of indomethacin and oxaprozin on reproductive function in healthy young men, 34 volunteers with normal semen parameters were recruited. In a... (Clinical Trial)
Clinical Trial Randomized Controlled Trial
Indomethacin and oxaprozin lower seminal prostaglandin levels but do not influence sperm motion characteristics and serum hormones of young healthy men in a placebo-controlled double-blind trial.
To evaluate the influence of indomethacin and oxaprozin on reproductive function in healthy young men, 34 volunteers with normal semen parameters were recruited. In a randomized double-blind design, 12 men were treated with placebo, 12 received 600 mg/day of oxaprozin and 10 took indomethacin 25 mg t.i.d. This treatment phase lasted for 14 days after which a follow-up period extended for another 10 weeks. Sperm counts, percentage of motile and normally formed sperm cells, sperm velocity, linearity, lateral head displacement and beat frequency were evaluated by computerized image analysis once before treatment and at weekly intervals during the rest of the study. Prostaglandin levels in seminal plasma were significantly reduced after 2 weeks of treatment and remained suppressed for at least 2 additional weeks. In spite of this long lasting impairment of physiologic prostaglandin concentrations, no changes in any of the measured parameters were detectable when compared with the placebo group. Basal levels of testosterone, estradiol, LH, FSH, TSH and prolactin were unchanged. The response of hypophyseal hormones to a combined GnRH/TRH test before, during and after the treatment also was not affected. Overall, no negative influence of indomethacin or oxaprozin treatment on male reproductive function could be found in healthy volunteers. Since the active treatment phase was only 14 days, one can only speculate about long term effects of the tested drugs on reproductive parameters in men.
Topics: Adult; Anti-Inflammatory Agents, Non-Steroidal; Double-Blind Method; Estradiol; Follicle Stimulating Hormone; Humans; Indomethacin; Luteinizing Hormone; Male; Oxaprozin; Pituitary Hormones, Anterior; Prolactin; Propionates; Prostaglandins; Random Allocation; Semen; Sperm Motility; Spermatozoa; Testosterone; Thyrotropin
PubMed: 2497096
DOI: 10.1002/j.1939-4640.1989.tb00071.x -
Molecules (Basel, Switzerland) Sep 2022Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO) for particle engineering. SCCO has great potential...
Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO) for particle engineering. SCCO has great potential for application as a green and eco-friendly technique to reach small crystalline particles with narrow particle size distribution. In this paper, an artificial intelligence (AI) method has been used as an efficient and versatile tool to predict and consequently optimize the solubility of oxaprozin in SCCO systems. Three learning methods, including multi-layer perceptron (MLP), Kriging or Gaussian process regression (GPR), and k-nearest neighbors (KNN) are selected to make models on the tiny dataset. The dataset includes 32 data points with two input parameters (temperature and pressure) and one output (solubility). The optimized models were tested with standard metrics. MLP, GPR, and KNN have error rates of 2.079 × 10, 2.173 × 10, and 1.372 × 10, respectively, using MSE metrics. Additionally, in terms of R-squared, they have scores of 0.868, 0.997, and 0.999, respectively. The optimal inputs are the same as the maximum possible values and are paired with a solubility of 1.26 × 10 as an output.
Topics: Artificial Intelligence; Carbon Dioxide; Machine Learning; Oxaprozin; Solubility
PubMed: 36144490
DOI: 10.3390/molecules27185762 -
International Journal of Molecular... Sep 2022Fatty acid mimetics (FAM) are bioactive molecules acting through the binding sites of endogenous fatty acid metabolites on enzymes, transporters, and receptors. Due to...
Fatty acid mimetics (FAM) are bioactive molecules acting through the binding sites of endogenous fatty acid metabolites on enzymes, transporters, and receptors. Due to the special characteristics of these binding sites, FAMs share common chemical features. Pharmacological modulation of fatty acid signaling has therapeutic potential in multiple pathologies, and several FAMs have been developed as drugs. We aimed to elucidate the promiscuity of FAM drugs on lipid-activated transcription factors and tested 64 approved compounds for activation of RAR, PPARs, VDR, LXR, FXR, and RXR. The activity screening revealed nuclear receptor agonism of several FAM drugs and considerable promiscuity of NSAIDs, while other compound classes evolved as selective. These screening results were not anticipated by three well-established target prediction tools, suggesting that FAMs are underrepresented in bioactivity data for model development. The screening dataset may therefore valuably contribute to such tools. Oxaprozin (RXR), tianeptine (PPARδ), mycophenolic acid (RAR), and bortezomib (RAR) exhibited selective agonism on one nuclear receptor and emerged as attractive leads for the selective optimization of side activities. Additionally, their nuclear receptor agonism may contribute relevant and valuable polypharmacology.
Topics: Fatty Acids; PPAR delta; Receptors, Cytoplasmic and Nuclear; Retinoid X Receptors; Signal Transduction; Transcription Factors
PubMed: 36077469
DOI: 10.3390/ijms231710070