Pharmaceutical Sciences

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/21664

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    Update of Population Pharmacokinetic Model for Tenofovir (TFV) in HIV-1-Uninfected Members of Serodiscordant Couples
    (2018-03-14) Chaturvedula, Ayyappa; Mallayasamy, Surulivelrajan
    Purpose: Oral tenofovir disproxil fumarate (TDF) has demonstrated success in HIV pre-exposure prophylaxis (PrEP) among high risk groups. A population pharmacokinetic model (PoP PK) was reported by us using the Partners PrEP trial data in serodiscordant couples. The objective of current work was to update, the prior population pharmacokinetic model of tenofovir with pharmacokinetic and adherence data from the Demonstration project. Methods: Two plasma samples were collected from study subjects and their dosing data was extracted from medication event monitoring system (MEMS®) records. Data from the Demonstration project and the Partners PrEP trial were combined in the analysis. The PoP PK model developed was a two compartment model parameterized with first order absorption rate constant (Ka) and absorption lag-time (Alag), clearance (CL), central and peripheral volumes (Vc & Vp) and inter-compartmental clearance (Q). Creatinine clearance was included as covariate on CL. Exponential error was used for between-subject-variability (BSV) on parameters. Residual error was modeled as combined additive and proportional error model. Gibiansky’s correction for bio-availability was included in the model to adjust for dosing errors. Model was qualified with visual predictive check (VPC, n=1000 samples) and bootstrap procedure (n=500 iterations). NONMEM software (version 7.3) was used for modeling and R software package (version 3.4.2) was used for data management and plots. Results: A total of 1,592 TFV levels from 565 subjects were used for model development. The final fixed effect parameter estimates were: CL-47.8 L/h; Vc – 214 L; Vp – 512 L; Ka – 1.7; Q – 300 L/h and lag time was 0.69 hr. Relative standard Error (RSE) of estimates were in the range of 2 to 32% for all parameters. Final random effects parameters were BSV on clearance (23%), on Vc (76%), on Ka (79%) and on additive error (150%). RSE of random effect parameters ranged from 12 to 22%. Additive error (SD) was 19 ng/mL and proportional variability was 21% (CV). Goodness of fit plots showed that the model did not have major bias. VPC showed that the distribution of model simulated data agreed with observed data. Conclusion: Tenofovir PoP PK model was updated with the new data from demonstration project. The model will be utilized for interpreting concentration based threshold of protection using MEMS® adherence patterns and text messaging on sexual activity information available in the trial.
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    Development and characterization of in situ self-assembly nanoparticles for Oral Docetaxel
    (2018-03-14) Dong, Xiaowei; Nguyen, Tina
    Development and characterization of in situ self-assembly nanoparticles for Oral Docetaxel Purpose: Docetaxel (DTX) is a chemotherapy drug that can be used for different type of cancers. Due to polysorbate 80, the excipient in the formulation, acute hypertensivity reaction is observed after intravenous administration. The development of oral formulation for DTX has always been problematic as the bioavailability of the drug is shown to be low due to P-glycoprotein efflux transporters and the intestinal metabolism by CYP3A4 enzymes. The objective of this study is to develop novel DTX in situ self-assembly (ISNP) granules to enhance bioavailability of DTX for oral administration. Method: The novel nanoformulation of DTX was developed by nanotechnology utilizing the proportional ratio of the components of D-a-tocopheryl polyethylene glycol 1000 succinate (TPGS), Miglyol 812, Aeropearl 300 and DTX. The particle size, drug loading and drug entrapment efficiency of the nanoparticles (NPs) were characterized using high-performance liquid chromatography and Delsa Nano C Particle Size Analyzer. Results: The proportional ratio among the components, which optimized the drug loading and drug entrapment efficiency, was successfully identified. The drug loading and entrapment efficiency of DTX delivered in ISNP were 10% and 85% respectively. The particle size of DTX ISNPs was achieved to be around 150 nm with the polydispersity index less than 0.3. Conclusion: DTX ISNPs were successfully developed with the composition that delivers the optimal drug loading and drug entrapment efficiency. Novel DTX ISNPs could enhance the absorption and bioavailability of the drug for oral administration as well as reduces the risk of acute hypersensitivity reactions, which improves patient adherence and reduces hospitalization. Keywords: docetaxel, nanoparticle, oral solid dosage forms, drug loading, entrapment efficiency Tina Nguyen, PharmD Candidate: ttn0147@my.unthsc.edu Xiaowei Dong, PhD: Xiaowei.dong@unthsc.edu
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    The Stability of Quetiapine Fumarate 10 mg/mL Compounded Oral Suspension in Ora-Blend and Ora-Sweet Vehicles Over Time at Two Temperatures
    (2018-03-14) Gervase, Melissa; Evans, Jason; Dong, Xiaowei; Tran, Jennie
    Purpose: Quetiapine fumarate (QF) is an atypical antipsychotic agent that is used off-label for the treatment of delirium in critically-ill children. QF is commercially available as immediate and extended-release tablets for oral administration. Although there is a published 40 mg/ml compounded suspension, this is not suitable for small doses, and there is no stability data available for QF compounded suspension. Therefore, the objective of this study was to evaluate the stability of 10 mg/mL QF compounded oral suspension in Ora-Blend (OB) vehicle and Ora-Sweet (OS) vehicle by analyzing drug contents, dissolved drug in selected vehicles, pH, visual appearance and odor at two temperatures up to 90 days. Methods: QF compounded suspensions (10 mg/mL) were prepared from QF commercial tablets in either OB or OS vehicle and were stored in plastic amber bottles at either 22°C or 2°C. At day 0, 7, 60 and 90, three bottles from each condition were used to prepare samples for the high-performance liquid chromatography (HPLC) analysis that was developed and validated. The drug contents were measured by directly mixing QF suspension with MeOH:H20 (v/v) and diluting the supernatant with MeOH after centrifugation to a detectable concentration for HPLC analysis. To measure dissolved QF, QF suspension was centrifuged and then QF in the supernatant was measured by HPLC. pH was measured by a pH meter, and physical characteristics were analyzed based on the changes in color and odor. Results: The QF drug contents in OB and OS for 90 days were not significantly different compared to day 0 at two temperatures. QF in OB remained dissolved over time at two temperatures, whereas QF in OS was precipitated out at day 7 and 90. The pH of both OB and OS preparations was consistent from day 0 to day 90. There were no significant differences in visual appearance or odor for both OB and OS preparations overtime at two temperatures. Conclusions Based on the results of drug contents, dissolved drug, pH and physical characteristics, QF compounded suspensions in OB were stable at two temperatures for up to 90 days. Compared to OS, OB is the better vehicle to prepare QF compounded suspensions. Keyword: Quetiapine fumarate, Stability testing, HPLC, Pediatrics
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    Probing protein allostery through residue perturbation maps
    (2018-03-14) Ahuactzin, Emilio; Liu, Jin; Hayatshahi, Hamed
    Protein allostery has been well accepted to be an intrinsic feature of all dynamic proteins. A perturbation at one site of the protein could distantly affect another site. The residues involved in these sites are considered as allosteric residues. Here, we argue that all residues in a protein are allosteric residues. We used hybrid models including molecular dynamics simulations and machine learning components to investigate whether a single or multiple properties of protein residues are changed upon ligand binding in PDZ3 domain. Also, we tried to understand whether various residues are affected similarly or in different ways when the ligand is bound. Our deep neural networks and random forests trained with different residue properties of molecular dynamics trajectories revealed that not only many properties of residues are affected upon ligand binding, but also each residue is affected through perturbation of its various properties, which makes the residue distinguishable from other residues. In other words, upon perturbation, different properties of each residue are affected at distinct extents, demonstrating that all residues are allosteric residues. According to our findings in this model protein, we defined a “residue perturbation map” as a two-dimensional map that fingerprints a protein based on the extent of perturbation in different properties of all its residues in a quantitative fashion. This “residue perturbation map” provides a novel way to systematically describe the protein allosteric effects of each residue upon perturbation.