Search results for: drug regimens

Authors: Aly Kassem, Eman Sapet, Eman Abdelbaset, Hosam Mahmoud

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Objective: Hypertension is an important public health challenge being one of the most common worldwide disease-affecting human. Our aim is to study the clinical characteristics, therapeutic regimens, treatment compliance, and risk factors in a sector of of hypertensive patients at Sohag City. Subject and Methods: A cross sectional study; conducted in Sohag city; it involved 520 patients; males (45.7 %) and females (54.3 %). Their ages ranged between 35-85 years. BP measurements, BMI, blood glucose, Serum creatinine, urine analysis, serum Lipids, blood picture and ECG were done all the studied patients. Results: Hypertension presented more between non-smokers (72.55%), females (54.3%), educated patients (50.99%) and patients with low SES (54.9%). CAD presented in (51.63%) of patients, while laboratory investigations showed hyperglycaemia in (28.7%), anemia in (18.3%), high serum creatinine level in (8.49%) and proteinuria in (10.45%) of patient. Adequate BP control was achieved in (49.67%); older patients had lower adequacy of BP control in spite of the extensive use of multiple-drug therapy. Most hypertensive patients had more than one coexistent CV risk factor. Aging, being a female (54.3%), DM (32.3%), family history of hypertension (28.7%), family history of CAD (25.4%), and obesity (10%) were the common contributing risk factors. ACE-inhibitors were prescribed in (58.16%), Beta-blockers in (34.64%) of the patients. Monotherapy was prescribed for (41.17%) of the patients. (75.81%) of patients had regular use of their drug regimens. (49.67%) only of patients had their condition under control, the number of drugs was inversely related to BP control. Conclusion: Hypertensive patients in Sohag city had a profile of high CV risks, and poor blood pressure control particularly in the elderly. A multidisciplinary approach for routine clinical check-up, follow-up, physicians and patients training, prescribing simple once-daily regimens and encouraging life style modifications are recommended. Anti hypertensives, hypertension, elderly patients, risk factors, treatment compliance.

Keywords: anti hypertensives, hypertension, elderly patients, risk factors, treatment compliance

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Thomas Geninatti, Bruno Giacomo, Alessandro Grattoni

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Nanofluidic devices have been investigated for over a decade as promising platforms for the controlled release of therapeutics. The nanochannel drug delivery system (nDS), a membrane fabricated with high precision silicon techniques, capable of zero-order release of drugs by exploiting diffusion transport at the nanoscale originated from the interactions between molecules with nanochannel surfaces, showed the flexibility of the sustained release in vitro and in vivo, over periods of time ranging from weeks to months. To improve the implantable bio nanotechnology, in order to create a system that possesses the key features for achieve the suitable release of therapeutics, the next generation of nDS has been created. Platinum electrodes are integrated by e-beam deposition onto both surfaces of the membrane allowing low voltage (<2 V) and active temporal control of drug release through modulation of electrostatic potentials at the inlet and outlet of the membrane’s fluidic channels. Hence, a tunable administration of drugs is ensured from the nanochannel drug delivery system. The membrane will be incorporated into a peek implantable capsule, which will include drug reservoir, control hardware and RF system to allow suitable therapeutic regimens in real-time. Therefore, this new nanotechnology offers tremendous potential solutions to manage chronic disease such as cancer, heart disease, circadian dysfunction, pain and stress.

Keywords: nanochannel membrane, drug delivery, tunable release, personalized administration, nanoscale transport, biomems

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Authors: Anushka Naidoo, Veron Ramsuran, Maxwell Chirehwa, Paolo Denti, Kogieleum Naidoo, Helen McIlleron, Nonhlanhla Yende-Zuma, Ravesh Singh, Sinaye Ngcapu, Nesri Padayatachi

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Background: Despite efforts to introduce new drugs and shorter drug regimens for drug-susceptible tuberculosis (TB), the standard first-line treatment has not changed in over 50 years. Rifampicin, isoniazid, and pyrazinamide are critical components of the current standard treatment regimens. Some studies suggest that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic (PK) variability independent of adherence to treatment. Wide between-patient pharmacokinetic variability for rifampin, isoniazid, and pyrazinamide has been reported in prior studies. There may be several reasons for this variability. However, genetic variability in genes coding for drug metabolizing and transporter enzymes have been shown to be a contributing factor for variable tuberculosis drug exposures. Objective: We describe the pharmacokinetics of first-line TB drugs rifampicin, isoniazid, and pyrazinamide and assess the effect of genetic variability in relevant selected drug metabolizing and transporter enzymes on pharmacokinetic parameters of isoniazid and rifampicin. Methods: We conducted the randomized-controlled Improving retreatment success TB trial in Durban, South Africa. The drug regimen included rifampicin, isoniazid, and pyrazinamide. Drug concentrations were measured in plasma, and concentration-time data were analysed using nonlinear-mixed-effects models to quantify the effects of relevant covariates and single nucleotide polymorphisms (SNP’s) of drug metabolizing and transporter genes on rifampicin, isoniazid and pyrazinamide exposure. A total of 25 SNP’s: four NAT2 (used to determine acetylator status), four SLCO1B1, three Pregnane X receptor (NR1), six ABCB1 and eight UGT1A, were selected for analysis in this study. Genotypes were determined for each of the SNP’s using a TaqMan® Genotyping OpenArray™. Results: Among fifty-eight patients studied; 41 (70.7%) were male, 97% black African, 42 (72.4%) HIV co-infected and 40 (95%) on efavirenz-based ART. Median weight, fat-free mass (FFM), and age at baseline were 56.9 kg (interquartile range, IQR: 51.1-65.2), 46.8 kg (IQR: 42.5-50.3) and 37 years (IQR: 31-42), respectively. The pharmacokinetics of rifampicin and pyrazinamide was best described using one-compartment models with first-order absorption and elimination, while for isoniazid two-compartment disposition was used. The median (interquartile range: IQR) AUC (h·mg/L) and Cmax (mg/L) for rifampicin, isoniazid, and pyrazinamide were; 25.62 (23.01-28.53) and 4.85 (4.36-5.40), 10.62 (9.20-12.25) and 2.79 (2.61-2.97), 345.74 (312.03-383.10) and 28.06 (25.01-31.52), respectively. Eighteen percent of patients were classified as rapid acetylators, and 34% and 43% as slow and intermediate acetylators, respectively. Rapid and intermediate acetylator status based on NAT 2 genotype resulted in 2.3 and 1.6 times higher isoniazid clearance than slow acetylators. We found no effects of the SLCO1B1 genotypes on rifampicin pharmacokinetics. Conclusion: Plasma concentrations of rifampicin, isoniazid, and pyrazinamide were low overall in our patients. Isoniazid clearance was high overall and as expected higher in rapid and intermediate acetylators resulting in lower drug exposures. In contrast to reports from previous South African or Ugandan studies, we did not find any effects of the SLCO1B1 or other genotypes tested on rifampicin PK. However, our findings are in keeping with more recent studies from Malawi and India emphasizing the need for geographically diverse and adequately powered studies. The clinical relevance of the low tuberculosis drug concentrations warrants further investigation.

Keywords: rifampicin, isoniazid pharmacokinetics, genetics, NAT2, SLCO1B1, tuberculosis

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Authors: Meenu Mehta, Munish Garg

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The use of oral anticancer drugs from AYUSH system of medicine is widely increased among the society due to their low cost, enhanced efficacy, increased patient preference, lack of inconveniences related to infusion and they provide an opportunity to develop chronic treatment regimens. However, oral delivery of these drugs usually laid down by the limited bioavailability of the drug, which is associated with a wide variation. As most of the cytotoxic agents have a narrow therapeutic window and are dosed at or near the maximum tolerated dose, a wide variability in the bioavailability can negatively affect treatment result. It is estimated that 40% of active substances are poorly soluble in water. The improvement of bio-availability of drugs with such properties presents one of the greatest challenges in drug formulations. There are several techniques reported in literature. Among all these Self Emulsifying Drug Delivery System (SEDDS) has gained more attention due to enhanced oral bio-availability enabling a reduction in dose. Thus, SEDDS anticancer drugs will have the increased bioavailability and efficacy. These dosage form will provide societal benefit in a cost-effective manner as compared to other oral dosage forms. Present study reflects on the formulation strategies as SEDDS for oral anticancer agents of AYUSH system for enhanced bioavailability with proven efficacy by cancer cell lines.

Keywords: anticancer agents, AYUSH system, bioavailability, SEDDS

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Authors: Rasha Ahmadi

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In December 2019, a coronavirus, currently identified as SARS-CoV-2, produced a series of acute atypical respiratory illnesses in Wuhan, Hubei Province, China. The sickness induced by this virus was named COVID-19. The virus is transmittable between humans and has caused pandemics worldwide. The number of death tolls continues to climb and a huge number of countries have been obliged to perform social isolation and lockdown. Lack of focused therapy continues to be a problem. Epidemiological research showed that senior patients were more susceptible to severe diseases, whereas children tend to have milder symptoms. In this study, we focus on other possible side effects of COVID-19 and more detailed treatment strategies. Using bioinformatics analysis, we first isolated the gene expression profile of patients with severe COVID-19 from the GEO database. Patients' blood samples were used in the GSE183071 dataset. We then categorized the genes with high and low expression. In the next step, we uploaded the genes separately to the Enrichr database and evaluated our data for signs and symptoms as well as related medication regimens. The results showed that 138 genes with high expression and 108 genes with low expression were observed differentially in the severe COVID-19 VS control group. Symptoms and diseases such as embolism and thrombosis of the abdominal aorta, ankylosing spondylitis, suicidal ideation or attempt, regional enteritis were observed in genes with high expression and in genes with low expression of acute and subacute forms of ischemic heart, CNS infection and poliomyelitis, synovitis and tenosynovitis. Following the detection of diseases and possible signs and symptoms, Carmustine, Bithionol, Leflunomide were evaluated more significantly for high-expression genes and Chlorambucil, Ifosfamide, Hydroxyurea, Bisphenol for low-expression genes. In general, examining the different and invisible aspects of COVID-19 and identifying possible treatments can help us significantly in the emergency and hospitalization of patients.

Keywords: phenotypes, drug regimens, gene expression profiles, bioinformatics analysis, severe COVID-19

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Authors: Selamawit Hirpa, Girmay Medhin, Belaineh Girma, Muluken Melese, Alemayehu Mekonen, Pedro Suarez, Gobena Ameni

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Worldwide, there were 650,000 multi-drug resistant tuberculosis (MDR-TB) cases in 2010. Ethiopia is 15th among the 27 MDR-TB high-burden countries. A case control study was conducted at St. Peter Hospital and five health centers in Addis Ababa. Cases were MDR-TB patients who were in treatment at St. Peter Hospital during the study period. Controls were patients who were on first-line anti-TB treatment and were registered as cured or having completed treatment in the period 9 April 2009– 28 February 2010, in five health centers. A structured interview questionnaire was used to assess factors that could potentially be associated with the occurrence of MDR-TB. Factors that were significantly associated with MDR-TB: drug side effects during first-line treatment (adjusted odds ratio (AOR): 4.5, 95% CI; 1.9 - 10.5); treatment not directly observed by a health worker (AOR = 11.7, 95% CI; 4–34.3); and retreatment with the Category II regimen (P = 0.000).

Keywords: adherence to TB treatment, MDR-TB, TB treatment, TB treatment regimens

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Authors: Deepika Bhaskar, Neena Wadehra, Megha Gulati, Aruna Narula, R. Vishnu, Gunjan Katyal

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With drug resistance becoming widespread in Plasmodium falciparum infections, development of the alternative drugs is the desired strategy for prevention and cure of malaria. Three drug targets were selected to screen promising drug molecules from the GSK library of around 14000 molecules. Using an in silico structure-based drug designing approach, the differences in binding energies of the substrate and inhibitor were exploited between target sites of parasite and human to design a drug molecule against Plasmodium. The docking studies have shown several promising molecules from GSK library with more effective binding as compared to the already known inhibitors for the drug targets. Though stronger interaction has been shown by several molecules as compare to reference, few molecules have shown the potential as drug candidates though in vitro studies are required to validate the results.

Keywords: plasmodium, malaria, drug targets, in silico studies

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Authors: Sara Ataei, Molouk Hadjibabaie, Shirinsadat Badri, Amirhossein Moslehi, Iman Karimzadeh, Ardeshir Ghavamzadeh

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Purpose: To assess the pattern and probable risk factors for moderate and major drug–drug interactions in a referral hematology-oncology ward in Iran. Methods: All patients admitted to hematology–oncology ward of Dr. Shariati Hospital during a 6-month period and received at least two anti-cancer or non-anti-cancer medications simultaneously were included. All being scheduled anti-cancer and non-anti-cancer medications both prescribed and administered during ward stay were considered for drug–drug interaction screening by Lexi-Interact On- Desktop software. Results: One hundred and eighty-five drug–drug interactions with moderate or major severity were detected from 83 patients. Most of drug–drug interactions (69.73 %) were classified as pharmacokinetics. Fluconazole (25.95 %) was the most commonly offending medication in drug–drug interactions. Interaction of sulfamethoxazole-trimethoprim with fluconazole was the most common drug–drug interaction (27.27 %). Vincristine with imatinib was the only identified interaction between two anti-cancer agents. The number of administered medications during ward stay was considered as an independent risk factor for developing a drug–drug interaction. Conclusions: Potential moderate or major drug–drug interactions occur frequently in patients with hematological malignancies or related diseases. Performing larger standard studies are required to assess the real clinical and economical effects of drug–drug interactions on patients with hematological and non-hematological malignancies.

Keywords: drug–drug interactions, hematology–oncology ward, hematological malignancies

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Authors: Pimporn Thongmuang

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The import value of antimicrobial drugs reached approximately fifteen million Baht in 2010, considered as the highest import value of all modern drugs, and this value is rising every year. Antimicrobials are considered the hazardous drugs by the Ministry of Public Health. This research was conducted in order to investigate the past knowledge of drug use and Antimicrobial drug use behavior. A total of 757 students were selected as the samples out of a population of 1,800 students. This selected students had the experience of Antimicrobial drugs use a year ago. A questionnaire was utilized in this research. The findings put on the view that knowledge gained by the students about proper use of antimicrobial drugs was not brought into practice. This suggests that the education procedure regarding drug use needs adjustment. And therefore the findings of this research are expected to be utilized as guidelines for educating people about the proper use of antimicrobial drugs. At a broader perspective, correct drug use behavior of the public may potentially reduce drug cost of the Ministry of Public Health of Thailand.

Keywords: drug use knowledge, antimicrobial drugs, drug use behavior, drug

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Authors: Mohand Yaghi, O. Kehinde

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Background: For the diagnosis of prostate cancer Trans-rectal prostate biopsy (TRPB) is used commonly, the procedure is associated with infective complications. There is evidence that antibiotics (ABx) decrease infective events after TRPB, but different regimens are used. Aim: To systematically review different regimens of prophylactic oral antibiotics in TRPB. Design: Medline, Embase, Clinical trials site, and Cochrane library were searched, experts were consulted about relevant studies. Randomized clinical trials (RCT) conducted in the last twenty years, which investigated different oral antibiotic regimens in TRPB, and compared their efficacy to reduce infectious complications were analyzed. Measurements: Primary outcomes were bacteriuria, urinary tract infection (UTI), fever, bacteremia, sepsis. Secondary outcomes were hospitalization rate, and the prevalence of ABx-resistant bacteria. Results: Nine trials were eligible with 3012 patients. Antibiotics prevented bacteriuria (3.5% vs. 9.88%), UTI (4.46% vs. 9.75%), and hospitalization (0.21% vs. 2.13%) significantly in comparison with placebo or no treatment. No significant difference was found in all outcomes of the review between the single dose regimen and the 3 days. The single dose regimen was as effective as the multiple dose except in Bacteriuria (6.75% vs. 3.25%), and the prevalence of ABx-resistant bacteria (1.57% vs. 0.27%). Quinolones reduced only UTI significantly in comparison with other antibiotics. Lastly, Ciprofloxacin is the best Quinolone to prevent UTI, and hospitalization. Conclusion: it is essential to prescribe prophylactic Antibiotics in TRPB. No conclusive evidence could be claimed about the superiority of the multiple or the 3 days regimens to the single dose regimen. Unexpectedly, ABx-resistant bacteria was identified more often in the single dose cohorts.

Keywords: infection, prostate cancer, sepsis, TRPB

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Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Shannon Glaspy, Gerald Boon, Jack Lambert

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Studies on AE of highly active antiretroviral therapy (HAART) in children and adolescents are rare. The aim of this study is to observe the frequency of treatment limiting adverse drug reactions against years on ARVs and specific ARV regimen. Methods: A retrospective cohort study was conducted in East London, South Africa. All patient files in the pediatric (0 – 18 years) ARV cohort were examined, selecting only those patients started on HAART. ARV regimen changes explicitly due to AE, age on ARV treatment onset, age of AE onset, and gender were extrapolated. Eligible subjects were obtained from patient folders, anonymized and cross-referenced with data obtained from electronic records. A total of 1120 patients [592 male (52.9%) and 528 female (47.1%)] were charted by incidence and year. Additional information was extrapolated in cases where the patient experienced lipodystrophy and lipoatrophy to include the number of years on ARVs prior to the onset of the AE. Results: Of the 1120 HIV infected children of the hospital cohort, a total of 105 (9.37%) AE (53.3% male) observed were deemed eligible for the study due to completeness of medical history and agreement between electronic records and paper files. The AE cited were as follows: lipoatrophy 62 (5.53% of all subjects), lipodystrophy 27 (2.41%), neuropathy 9 (0.8%), anemia 2 (0.17%), Steven Johnsons Syndrome 1 (0.08%), elevated LFTs 1 (0.8%), breast hypertrophy (0.08%), gastritis 1 (0.08%) and rash 1 (0.08%). The most prevalence ARV regimens associated with the onset of the AE are: D4T/3TC/EFV 72 cases (64.86% of all AE), D4T/3TC/LOPr 24 cases (21.62%). Lipoatrophy and lipodystrophy combined represent 84.76% (89 cases) of all adverse events documented in this cohort. Within the 60 cases of lipoatrophy, the average number of years on ARVs associated with an AE is 3.54, with 14 cases experiencing an AE between 0-2 years of HAART. Within the 29 cases of lipodystrophy, the average number of years on ARVs associated with an AE is 3.89, with 4 cases experiencing an AE between 0-2 years on HAART. The regimen D4T/3TC/EFV is associated with 43 cases (71.66%) of lipoatrophy and 21 cases (72.41%) of lipodystrophy. D4T/3TC/LOPr is associated with 15 cases (25%) of lipoatrophy and 7 cases (24.14%) of lipodystrophy. The frequency of AE associated with ARV regimens could be misrepresented due to prevalence of different 1st line regimens which were not captured in this study, particularly with the systematic change of 1st line drugs from D4T to ABC in 2010. Conclusion: In this descriptive study we found a 9.37% prevalence of AE were significant enough to be treatment limiting among our cohort. Lipoatrophy accounted for 59.04% of all documented AE. Overall, D4T/3TC/EFV was associated with 64.86% of all AE, 71.66% of lipoatrophy cases and 72.41% of lipodystrophy cases.

Keywords: ARV, adverse events, HAART, pediatric

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Authors: Keaghan Brown

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The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

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Authors: Farzad Jalilian, Mehdi Mirzaei Alavijeh, Fazel Zinat Motlagh

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Social support is an important benchmark of health for people in avoidance conditions. The main goal of this study was to determine the three kinds of social support (family, friend and other significant) to drug cessation among male addicts, in Kermanshah, the west of Iran. This cross-sectional study was conducted among 132 addicts, randomly selected to participate voluntarily in the study. Data were collected from conduct interviews based on standard questionnaire and analyzed by using SPSS-18 at 95% significance level. The majority of addicts were young (Mean: 30.4 years), and with little education. Opium (36.4%), Crack (21.2%), and Methamphetamine (12.9%) were the predominant drugs. Inabilities to reject the offer and having addict friends are the most often reasons for drug usage. Almost, 18.9% reported history of drug injection. 43.2% of the participants already did drug cessation at least once. Logistic regression showed the family support (OR = 1.110), age (OR = 1.106) and drug use initiation age (OR = 0.918) was predicting drug cessation. Our result showed; family support is a more important effect among types of social support in drug cessation. It seems that providing educational program to addict’s families for more support of patients at drug cessation can be beneficial.

Keywords: drug cessation, family support, drug use, initiation age

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Authors: Temesgen Geremew

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Functionalized nanoparticles have emerged as a revolutionary platform for drug delivery, offering significant advantages over traditional methods. By strategically modifying their surface properties, these nanoparticles can be designed to target specific tissues and cells, significantly reducing off-target effects and enhancing therapeutic efficacy. This targeted approach allows for lower drug doses, minimizing systemic exposure and potential side effects. Additionally, functionalization enables controlled release of the encapsulated drug, improving drug stability and reducing the frequency of administration, leading to improved patient compliance. This work explores the immense potential of functionalized nanoparticles in revolutionizing drug delivery, addressing limitations associated with conventional therapies and paving the way for personalized medicine with precise and targeted treatment strategies.

Keywords: nanoparticles, drug, nanomaterials, applications

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Authors: Adegoke Yinka Adebayo

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An understanding of the critical product attributes that impact on in vivo performance is key to the production of safe and effective medicines. Thus, a key driver for our research is the development of new basic science and technology underpinning the development of new pharmaceutical products. Research includes the structure and properties of drugs and excipients, biopharmaceutical characterisation, pharmaceutical processing and technology and formulation and analysis.

Keywords: drug discovery, drug development, drug delivery

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Authors: S. Niamkaeo, O. Robert, O. Chaowalit

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In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

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Authors: Afsaneh Ghorbanzadeh, Afshin Farahbakhsh, Zakieh Bayat

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The drug capsulation was used for release and targeted delivery in determined time, place and temperature or pH. The DOX nanocapsules were used to reduce and to minimize the unwanted side effects of drug. In this paper, the encapsulation methods of doxorubicin (DOX) and the labeling it by the magnetic core of iron (Fe3O4) has been studied. The Fe3O4 was conjugated with DOX via hydrazine bond. The solution was capsuled by the sensitive polymer of heat or pH such as chitosan-g-poly (N-isopropylacrylamide-co-N,N-dimethylacrylamide), dextran-g-poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) and mPEG-G2.5 PAMAM by hydrazine bond. The drug release was very slow at temperatures lower than 380°C. There was a rapid and controlled drug release at temperatures higher than 380°C. According to experiments, the use mPEG-G2.5PAMAM is the best method of DOX nanocapsules synthesis, because in this method, the drug delivery time to certain place is lower than other methods and the percentage of released drug is higher. The synthesized magnetic carrier system has potential applications in magnetic drug-targeting delivery and magnetic resonance imaging.

Keywords: drug carrier, drug release, doxorubicin, iron oxide NPs

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Authors: Farzad Jalilian, Mehdi Mirzaei Alavijeh

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Background: Substance addiction is one of the major worldwide problems that destroys economy, familial relationships, and the abuser’s career and has several side effects; in the meantime drug injection due to the possibility of shared use of syringes among drug users could have multiple complications to be followed. The purpose of this study was to determine the prevalence of drug injection among male prisoners in Kermanshah city, the west of Iran. Methods: In this cross-sectional study 615 male prisoners were randomly selected to participate voluntarily in the study. Participants filled out a writing self-report questionnaire. Data were analyzed by the SPSS software (ver. 21.0) at 95% significant level. Results: The mean age of respondents was 31.13 years [SD: 7.76]. Mean initiation age for drug use was 14.36 years (range, 9-34 years). Almost, 39.4 % reported a history of drug use before prison. Opium (33.2%) and crystal (27.1%) was the most used drug among prisoners. Furthermore, 9.3 % had a history of injection addiction. There was a significant correlation between age, crime type, marital status, economic status, unprotected sex and drug injection (P < 0.05). Conclusion: The low age of drug abuse and the prevalence of drug injection among offenders can be as a warning for responsible; in this regard, implementation of prevention programs to risky behavior and harm reduction among high-risk groups can follow useful results.

Keywords: substance abuse, drug injection, prison, Iran

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Authors: Christi Jackson, Chuka Onaga

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Introduction: We report a case of delayed diagnosis of extra-pulmonary INH-mono-resistant Tuberculosis (TB) in a South African patient with drug-resistant HIV. Case Presentation: A 36-year old male was initiated on 1st line (NNRTI-based) anti-retroviral therapy (ART) in September 2009 and switched to 2nd line (PI-based) ART in 2011, according to local guidelines. He was following up at the outpatient wellness unit of a public hospital, where he was diagnosed with Protease Inhibitor resistant HIV in March 2016. He had an HIV viral load (HIVVL) of 737000 copies/mL, CD4-count of 10 cells/µL and presented with complaints of productive cough, weight loss, chronic diarrhoea and a septic buttock wound. Several investigations were done on sputum, stool and pus samples but all were negative for TB. The patient was treated with antibiotics and the cough and the buttock wound improved. He was subsequently started on a 3rd-line ART regimen of Darunavir, Ritonavir, Etravirine, Raltegravir, Tenofovir and Emtricitabine in May 2016. He continued losing weight, became too weak to stand unsupported and started complaining of abdominal pain. Further investigations were done in September 2016, including a urine specimen for Line Probe Assay (LPA), which showed M. tuberculosis sensitive to Rifampicin but resistant to INH. A lymph node biopsy also showed histological confirmation of TB. Management and outcome: He was started on Rifabutin, Pyrazinamide and Ethambutol in September 2016, and Etravirine was discontinued. After 6 months on ART and 2 months on TB treatment, his HIVVL had dropped to 286 copies/mL, CD4 improved to 179 cells/µL and he showed clinical improvement. Pharmacy supply of his individualised drugs was unreliable and presented some challenges to continuity of treatment. He successfully completed his treatment in June 2017 while still maintaining virological suppression. Discussion: Several laboratory-related factors delayed the diagnosis of TB, including the unavailability of urine-lipoarabinomannan (LAM) and urine-GeneXpert (GXP) tests at this facility. Once the diagnosis was made, it presented a treatment dilemma due to the expected drug-drug interactions between his 3rd-line ART regimen and his INH-resistant TB regimen, and specialist input was required. Conclusion: TB is more difficult to diagnose in patients with severe immunosuppression, therefore additional tests like urine-LAM and urine-GXP can be helpful in expediting the diagnosis in these cases. Patients with non-standard drug regimens should always be discussed with a specialist in order to avoid potentially harmful drug-drug interactions.

Keywords: drug-resistance, HIV, line probe assay, tuberculosis

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Authors: Jay Ananth

Abstract:

The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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Authors: Nishank Raisinghani

Abstract:

Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi

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Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.

Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements

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Authors: Arpa Petchsomrit, Namfa Sermkaew, Ruedeekorn Wiwattanapatapee

Abstract:

Oil entrapped floating alginate beads of curcumin were developed and characterized. Cremophor EL, Cremophor RH and Tween 80 were utilized to improve the solubility of the drug. The oil-loaded floating gel beads prepared by emulsion gelation method contained sodium alginate, mineral oil and surfactant. The drug content and % encapsulation declined as the ratio of surfactant was increased. The release of curcumin from 1% alginate beads was significantly more than for the 2% alginate beads. The drug released from the beads containing 25% of tween 80 was about 70% while a higher drug release was observed with the beads containing Cremophor EL or Cremohor RH (approximately 90%). The developed floating beads of curcumin powder with surfactant provided a superior drug release than those without surfactant. Floating beads based on oil entrapment containing the drug solubilized in surfactants is a new delivery system to enhance the dissolution of poorly soluble drugs.

Keywords: alginate, curcumin, floating drug delivery, oil entrapped bead

Procedia PDF Downloads 358

Authors: Romasa Qasim, G. M. Sayedur Rahman, Nahid Hasan, M. Shazzad Hosain

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Millions of people worldwide suffer from Hepatitis C, one of the fatal diseases. Interferon (IFN) and ribavirin are the available treatments for patients with Hepatitis C, but these treatments have their own side-effects. Our research focused on the development of an orally taken small molecule drug targeting the proteins in Hepatitis C Virus (HCV), which has lesser side effects. Our current study aims to the Pharmacophore based drug development of a specific small molecule anti-viral drug for Hepatitis C Virus (HCV). Drug designing using lab experimentation is not only costly but also it takes a lot of time to conduct such experimentation. Instead in this in silico study, we have used computer-aided techniques to propose a Pharmacophore-based anti-viral drug specific for the protein domains of the polyprotein present in the Hepatitis C Virus. This study has used homology modeling and ab initio modeling for protein 3D structure generation followed by pocket identification in the proteins. Drug-able ligands for the pockets were designed using de novo drug design method. For ligand design, pocket geometry is taken into account. Out of several generated ligands, a new Pharmacophore is proposed, specific for each of the protein domains of HCV.

Keywords: pharmacophore-based drug design, anti-viral drug, in-silico drug design, Hepatitis C virus (HCV)

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Authors: V. Balamuralidhara

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The aim of the present work was to develop Paclitaxel loaded polyacrylamide grafted guar gum nanoparticles as pH responsive nanoparticle systems for targeting colon. The pH sensitive nanoparticles were prepared by modified ionotropic gelation technique. The prepared nanoparticles showed mean diameters in the range of 264±0.676 nm to 726±0.671nm, and a negative net charge 10.8 mV to 35.4mV. Fourier Transformed Infrared Spectroscopy (FT-IR) and Differential Scanning Calorimetry (DSC) studies suggested that there was no chemical interaction between drug and polymers. The encapsulation efficiency of the drug was found to be 40.92% to 48.14%. The suitability of the polyacrylamide grafted guar gum ERN’s for the release of Paclitaxel was studied by in vitro release at pH 1.2 and 7.4. It was observed that, there was no significant amount of drug release at gastric pH and 97.63% of drug release at pH 7.4 was obtained for optimized formulation F3 at the end of 12 hrs. In vivo drug targeting performance for the prepared optimized formulation (F3) and pure drug Paclitaxel was evaluated by HPLC. It was observed that the polyacrylamide grafted guar gum can be used to prepare nanoparticles for targeting the drug to the colon. The release performance was greatly affected by the materials used in ERN’s preparation, which allows maximum release at colon’s pH. It may be concluded that polyacrylamide grafted guar gum nanoparticles loaded with paclitaxel have desirable release responsive to specific pH. Hence it is a unique approach for colonic delivery of drug having appropriate site specificity and feasibility and controlled release of drug.

Keywords: colon targeting, polyacrylamide grafted guar gum nanoparticles, paclitaxel, nanoparticles

Procedia PDF Downloads 315

Authors: Temesgen Sidamo, Prakruti S. Rao, Eleni Akllilu, Workineh Shibeshi, Yumi Park, Yong-Soon Cho, Jae-Gook Shin, Scott K. Heysell, Stellah G. Mpagama, Ephrem Engidawork

Abstract:

The fluoroquinolones (FQs) are used off-label for the treatment of multidrug-resistant tuberculosis (MDR-TB), and for evaluation in shortening the duration of drug-susceptible TB in recently prioritized regimens. Within the class, levofloxacin (LFX) and moxifloxacin (MXF) play a substantial role in ensuring success in treatment outcomes. However, sub-therapeutic plasma concentrations of either LFX or MXF may drive unfavorable treatment outcomes. To the best of our knowledge, the pharmacokinetics of LFX and MXF in Ethiopian patients with MDR-TB have not yet been investigated. Therefore, the aim of this study was to develop a population pharmacokinetic (PopPK) model of levofloxacin (LFX) and moxifloxacin (MXF) and assess the percent probability of target attainment (PTA) as defined by the ratio of the area under the plasma concentration-time curve over 24-h (AUC0-24) and the in vitro minimum inhibitory concentration (MIC) (AUC0-24/MIC) in Ethiopian MDR-TB patients. Steady-state plasma was collected from 39 MDR-TB patients enrolled in the programmatic treatment course and the drug concentrations were determined using optimized liquid chromatography-tandem mass spectrometry. In addition, the in vitro MIC of the patients' pretreatment clinical isolates was determined. PopPK and simulations were run at various doses, and PK parameters were estimated. The effect of covariates on the PK parameters and the PTA for maximum mycobacterial kill and resistance prevention was also investigated. LFX and MXF both fit in a one-compartment model with adjustments. The apparent volume of distribution (V) and clearance (CL) of LFX were influenced by serum creatinine (Scr), whereas the absorption constant (Ka) and V of MXF were influenced by Scr and BMI, respectively. The PTA for LFX maximal mycobacterial kill at the critical MIC of 0.5 mg/L was 29%, 62%, and 95% with the simulated 750 mg, 1000 mg, and 1500 mg doses, respectively, whereas the PTA for resistance prevention at 1500 mg was only 4.8%, with none of the lower doses achieving this target. At the critical MIC of 0.25 mg/L, there was no difference in the PTA (94.4%) for maximum bacterial kill among the simulated doses of MXF (600 mg, 800 mg, and 1000 mg), but the PTA for resistance prevention improved proportionately with dose. Standard LFX and MXF doses may not provide adequate drug exposure. LFX PopPK is more predictable for maximum mycobacterial kill, whereas MXF's resistance prevention target increases with dose. Scr and BMI are likely to be important covariates in dose optimization or therapeutic drug monitoring (TDM) studies in Ethiopian patients.

Keywords: population PK, PTA, moxifloxacin, levofloxacin, MDR-TB patients, ethiopia

Procedia PDF Downloads 84

Authors: M. Rahimnejad, B. Vahidi, B. Ebrahimi Hoseinzadeh, F. Yazdian, P. Motamed Fath, R. Jamjah

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In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

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Authors: D. R. Rama Brahma Reddy, A. Vijaya Sarada Reddy

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Nanoparticles represent a promising drug delivery system of controlled and targeted drug release. They are specially designed to release the drug in the vicinity of target tissue. The aim of this study was to prepare and evaluate polymethacrylic acid nanoparticles containing Zidovudine in different drug to polymer ratio by nanoprecipitation method. SEM indicated that nanoparticles have a discrete spherical structure without aggregation. The average particle size was found to be 120 ± 0.02 - 420 ± 0.05 nm. The particle size of the nanoparticles was gradually increased with increase in the proportion of polymethacrylic acid polymer. The drug content of the nanoparticles was increasing on increasing polymer concentration up to a particular concentration. No appreciable difference was observed in the extent of degradation of product during 60 days in which, nanoparticles were stored at various temperatures. FT-IR studies indicated that there was no chemical interaction between drug and polymer and stability of drug. The in-vitro release behavior from all the drug loaded batches was found to be zero order and provided sustained release over a period of 24 h. The developed formulation overcome and alleviates the drawbacks and limitations of Zidovudine sustained release formulations and could possibility be advantageous in terms of increased bio availability of Zidovudine.

Keywords: nanoparticles, zidovudine, biodegradable, polymethacrylic acid

Procedia PDF Downloads 583