Klasifikasi Penentuan Jenis Obat Menggunakan Algoritma Decision Tree

Classification is a technique that can be used for prediction, where the predicted value is a label. The classification of drug determination aims to predict the type of drug that is accurate for patients with the dataset that has been obtained. The data used in this study are data from the patient's medical records based on the symptoms of the disease but the type of medicine is not yet known. The data set used comes from kaggle.com which is then presented in the form of a decision tree with a mathematical model. To complete this research, a classification method is used in data mining, namely the decision tree. The decision tree method is used to find the relationship between a number of candidate variables, so that it becomes a classification target variable by dividing the data into 70% data testing and 30% training data. The results obtained from this study are in the form of rules and an accuracy rate of 96.36% as well as the recall and precision values ​​of each type of drug using a multiclass configuration matrix.

Molecularly Imprinted Electrochemical Sensor-Based Fe2O3@MWCNTs for Ivabradine Drug Determination in Pharmaceutical Formulation, Serum, and Urine Samples

Ivabradine hydrochloride (IVR) is a medically important drug because of its ability to lower the heart rate. Techniques reported for IVR determination were expensive, laborious, besides being of poor selectivity. In this study, iron oxide @ carbon nanotube (Fe2O3@MWCNTs) nanocomposite and molecularly imprinted polymer (MIP) were synthesized and used in the fabrication of carbon paste electrodes (CPEs) for the potentiometric detection of IVR in biological and pharmaceutical samples. CPEs of the best sensor were formulated from graphite (41 wt%) as a carbon source, MIP (3 wt.%) as an ionophore, Fe2O3@MWCNTs (5 wt%) as a modifier, and nitrophenyl octyl ether (NPOE, 51 wt.%) as a conductive oil so-called plasticizer. The best sensor exhibits a Nernstian slope (response) of 56 mV decade–1 within the IVR concentration range from 1.0 × 10–3 M to 9.8 × 10–8 M with high selectivity against interfering species (ascorbic, maltose, glucose, lactose, dopamine, glycine) over those reported earlier. The use of Fe2O3@MWCNTs together with MIP in the electrode formulation was found to improve the limit of detection (LOD) from 630 to 98 nM along with high reversibility, a short response time of 30 s, and a good lifetime of more than 2 weeks. The sandwich membrane (SMM) method was used to quantify the H-bonding complexing strength of the MIP binding sites for IVR with Log βILn = 11.33. The constructed sensors were successfully applied for the IVR determination in blood serum, urine, and commercial formulations (Savapran®) with high sensitivity.

Rapid sensitive bioscreening of remdesivir in COVID-19 medication: Selective drug determination in the presence of six co-administered therapeutics

The widespread coronavirus 2019 (COVID-19) pandemic, attributed to the severe acute respiratory syndrome coronavirus-2, has resulted in global lockdowns and excess mortality. Remdesivir (RM) is the first and only antiviral drug that the US Food and Drug Administration (FDA) has approved so far for COVID-19. The treatment protocol involves multidrug combinations, basically depending on RM, in addition to antimicrobials, antipyretics, corticosteroids, and anticoagulants. This study develops and validates sensitive and selective RM screening in spiked human plasma in the presence of commonly co-administered drugs. Hydroxychloroquine, azithromycin, paracetamol, dexamethasone, and anticoagulants (rivaroxaban and edoxaban) have been detected simultaneously with RM in the same biological matrix. Separation has been efficiently achieved by simple reversed phase HPLC with dual detectors. Diode array detector and fluorimetric detection have been used to compare their sensitivity and selectivity. Both assays have been validated according to bioanalytical FDA validation parameters. Chromatographic separation and quantitation of RM along with concomitant drugs instantly bioscreen COVID-19 multiple therapy medication in 10 min run time. Furthermore, the proposed in vitro study takes the lead for prospective testing of possible drug–drug interactions that alter the pharmacokinetic profiles of drugs.

Determination of Antidepressants in Human Plasma by Modified Cloud-Point Extraction Coupled with Mass Spectrometry

Cloud-point extraction (CPE) is rarely combined with liquid chromatography coupled to mass spectrometry (LC–MS) in drug determination due to the matrix effect (ME). However, we have recently shown that ME is not a limiting factor in CPE. Low extraction efficiency may be improved by salt addition, but none of the salts used in CPE are suitable for LC–MS. It is the first time that the influences of a volatile salt—ammonium acetate (AA)—on the CPE extraction efficiency and ME have been studied. Our modification of CPE included also the use of ethanol instead of acetonitrile to reduce the sample viscosity and make the method more environmentally friendly. We developed and validated CPE–LC–MS for the simultaneous determination of 21 antidepressants in plasma that can be useful for clinical and forensic toxicology. The selected parameters included Triton X-114 concentration (1.5 and 6%, w/v), concentration of AA (0, 10, 20 and 30%, w/v), and pH (3.5, 6.8 and 10.2). The addition of 10% of AA increased recovery twice. For 20 and 30% (w/v) of AA, three phases were formed that prolonged the extraction process. The developed CPE method (6% Triton X-114, 10% AA, pH 10.2) was successfully validated through LC–MS/MS simultaneous determination of 21 antidepressants in human plasma. The linearity was in the range of 10–750 ng/mL (r2 > 0.990).

Smartphone Digital Image Using for Determination of DCH by a Diazotization Reaction

Background: Simple, sensitive, and economic colorimetric device based on a smartphone digital image coupled with Color Grab™ application was developed for DCH drug determination. The method is based on the diazotization reaction of benzocaine with DCH drug to get an orange azo dye. Methods: Variable parameters such as volumes of reagents, the internal walls and ambient light have been analyzed and optimized. From the optimized conditions, a calibration curve was created by the effective intensity (IG) of an orange azo dye, a correlation of determination is 0.999 and limit of detection 0.808 mg/L. Results: The results of the Smartphone method were statistically compared with the reference method using a t-test and found to be a good agreement. Conclusion: This method requires neither solvent extraction and temperature control, also it has achieved an extensive linear range and low limit of detection compared with different methods reported in the literature.

Comparison of Various Chromatographic Systems for Identification of Vortioxetine in Bulk Drug Substance, Human Serum, Saliva, and Urine Samples by HPLC-DAD and LC-QTOF-MS

Background: Determination of psychotropic drugs in clinical study is significant, and the establishment of methodologies for these drugs in biological matrices is essential for patients’ safety. The search for new methods for their detection is one of the most important challenges of modern scientific research. The methods for analyzing of psychotropic drugs and their metabolites in different biological samples should be based on combining a very efficient separation technique including high-performance liquid chromatography (HPLC), with a sensitive detection method and effectively sample preparation methods. Objective: Retention, peaks symmetry and system efficiency of vortioxetine on Hydro RP, Polar RP, HILIC A (with silica stationary phase), HILIC-B (with aminopropyl stationary phase), and ACE HILIC-N (with polyhydroxy stationary phase and SCX columns were investigated. Various mobile phases containing methanol or acetonitrile as organic modifiers and different additives were also applied to obtained optimal retention, peaks shape, and systems efficiency. The best chromatographic procedure was used for simultaneous analysis of vortioxetine and its metabolites in human serum, urine and saliva samples. Methods: Analysis of vortioxetine was performed in various chromatographic systems: Reversed phase (RP) systems on alkylbonded or phenyl stationary phases, hydrophilic interaction liquid chromatography (HILIC), and ion-exchange chromatography (IEC). Based on the dependence of log k vs the concentration of the organic modifier, log kw values for vortioxetine in various chromatographic systems were determined and compared with calculated log P values. Solid phase extraction (SPE) method was applied for sample pre-treatment before HPLC analysis. HPLC-QTOF-MS method was applied for confirmation of presence of vortioxetine and some its metabolites in biological samples collected from psychiatric patient. Conclusions: Differences were observed in retention parameters with a change of the applied chromatographic system. The various properties of stationary phases resulted in differences in vortioxetine retention, systems’ efficiency, and peaks’ shape. Lipophilicity parameters were also determined using different HPLC conditions. The most optimal systems were chosen for the analysis of vortioxetine in biological samples. Both serum and urine or saliva samples collected from patients treated with vortioxetine can be used for the drug determination. For the first time, vortioxetine was detected in patient’s saliva. Obtained results indicate on possibility of application of saliva samples, which collection are non-invasive and painless, for determination and therapeutic drug monitoring in patients.