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    Title: In-vitro Two Step Dissolution Study of Docetaxel Granules in Fed Media
    (2022) Kasim, Chaitanya
    Presenter: Chaitanya Kasim Authors: Chaitanya Kasim, OMS-II, Dr. Brijesh Shah, Ph.D, Dr. Xiaowei Dong, Ph.D Title: In-vitro Two Step Dissolution Study of Docetaxel Granules in Fed Media Background: Lung cancer is the leading cause of death in America amongst all cancer related deaths. The conventional treatment for lung cancer is with Docetaxel (DTX), which works by inhibiting microtubule formation and has shown to significantly slow lung cancer progression. Typical administration of DTX is based on administering high doses of chemotherapeutic drugs at low frequency; however, this treatment method yields a poor 5-year survival outcome. Specifically, DTX is administered intravenously (IV) due to its low oral bioavailability. IV administration, however, is taxing on the patient, so better therapy modalities are needed. Recent studies suggest that metronomic therapy, administering low doses of a drug at high frequency, may lead to better survival outcomes. Our lab explored in situ self-assembling nanoparticle (ISNP) granule composed of lipids and surfactant as a potential method of drug delivery for metronomic therapy. The aim of this study is to determine the optimal Lipid: Surfactant ratio and composition for high DTX drug release. Hypothesis: We hypothesize that the ISNP granule composed of 1:1 lipid: surfactant ratio will lead to the highest drug release. Methods: Previous studies have shown that ISNP granules were able to deliver significant drug concentration to lung tissue in vivo but failed to demonstrate these results in vitro. To reflect this discrepancy between in vivo and in vitro studies, our lab developed new protocols that correlated with physiological pH changes during digestion known as "Fed Media". Our lab formulated DTX ISNP granule composed of different ratios of lipid-Miglyol 812 (M) and surfactant- TPGS (T) and added to Fed Media. Samples were taken at different timepoints and drug release was measured via HPLC. We then formulated granules composed of different lipids (Cap200 and PG8 backbone) and measured its drug release. Results: The M:T 1:1 formulation led to the highest drug release. As expected, the blank granules led to a lower or similar release when compared to pure DTX powder. However, there was an interesting result, the DTX release for M:T ratio 0:1 is close to M:T 1:1. This was surprising as it showed that surfactants played an important role when prior emphasis was placed on lipids. For different lipid compositions, Cap200 is showing a higher drug release compared to PG8 backbone. Conclusion: The results validate the hypothesis that 1:1 M:T ratio will lead to the highest drug release. However, the 0:1 M:T ratio provides interesting avenues for research. The role of surfactants in improving DTX solubility needs to be explored further. One theory is that the granule formulation process might by playing a role in improving solubility. Future directions for this study include exploring different diester lipid backbones and see how it effects drug release.
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    Hormonal Contraceptive Use in Oncology Patients: Pharmacists Role in Counseling
    (2022) Obioma, Jessica
    Objective: Over 70 million women in the United States are currently using a contraceptive method. In addition, there were 1.7 million new cancer cases reported in 2018. A concise and timely conversation about contraceptive options and use is pertinent to the care of a cancer patient. Some studies have shown concerns for hormonal contraceptive use in cancer patients. The primary objective of this systematic review was to evaluate evidence on effective hormonal contraceptive use in cancer patients. A second objective was to describe pharmacist counseling points for cancer patients. Methods: A systematic review of the literature was conducted from 1975 to 2022 using PubMed with keywords such as "contraceptive use," "oncology patients," "counseling," and "role of a pharmacist." A PRISMA flow diagram was used to analyze the process. Studies that did not meet the inclusion criteria of focusing on the effects of hormonal contraceptives in cancer patients and patient counseling were excluded. Articles were summarized in a table classified by the author, year published, title, study design, intervention, pros and cons of contraceptive methods, and major findings. The quality of the articles was assessed via the Oxford for Evidence-based Medicine scale. Results: Seventy-four articles were eligible for review. The majority of studies conducted were randomized clinical trials and comparative studies. Trends in literature have shown insufficient data in regard to medication counseling on the effects of hormonal contraceptive use in cancer patients. There are 6 classes of contraceptive methods: (1) behavioral methods, (2) barrier methods, (3) estrogen-containing methods, (4) progestin-only methods, (5) intrauterine devices (IUDs), and (6) surgical sterilization. Several studies suggest the copper IUD, a highly effective, reversible, long-acting, hormone-free method should be considered a first-line contraceptive option for women with a history of hormonally mediated cancer. Women with IUDs can undergo all forms of imaging, including computed tomography and magnetic resonance imaging. Conclusion: Hormonal contraceptives are one of the most prescribed medications in the United States which provide pharmacists the opportunities to counsel and practice through state protocol or collaborative practice agreements. While pharmacists are poised to provide this service, cancer patients represent a unique population to seek contraceptive advice before and after treatment. As the pharmacist's scope of practice continues to expand, future research is needed to address the pros and cons of available contraceptives.
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    Summary of a Novel, Non-opioid Local Anesthetic for Post-surgical Pain Relief
    (2022) Kieltyka, Hunter; Hearn, Elizabeth
    Purpose: Introducing Zynrelef (bupivacaine/meloxicam) as a new post-surgical medication to relieve pain provides an alternative to opioid use. In recent years, the opioid epidemic has been the cause of numerous overdoses and addictions. By utilizing non-opioid pain relief, we can help combat the ever-growing opioid crisis. Bupivacaine has been utilized for years as a post-operative local anesthetic, working by competitively inhibiting voltage-gated Na+ channels, causing the muscles nearby to relax. However, the inflammation process that occurs after surgery prevents some absorption of local anesthetics, thereby reducing the efficacy of pain relief. Zynrelef is a novel bupivacaine combination product with the addition of meloxicam, a non-steroidal anti-inflammatory drug (NSAID). Meloxicam inhibits COX enzymes, ultimately reducing the inflammatory response. When combined with bupivacaine, the NSAID action enhances the response of the local anesthetic, producing more efficacious pain relief. Additionally, Zynrelef's irrigation application is a novel technique for local pain relief. By irrigating instead of injecting, the inflammatory response and site pain brought on by the injection will be avoided. Clinical trials have shown reduced pain intensities over a 72-hour period in post-operative patients who were administered combination Zynrelef irrigation compared to bupivacaine HCl injection. While the clinical efficacy of Zynrelef is well-documented, the purpose of this study is to compare the cost-effectiveness of Zynrelef irrigation versus another bupivacaine product, Exparel injection. Methods: A drug formulary monograph of Zynrelef was created by thoroughly researching information about its drug class, indications for use, pharmacology, dosing, pharmacokinetics, drug interactions, and clinical efficacy. Once the basis of the drug was established, the precautions, administration options, adverse effects, availability, and cost were compared with Exparel. Results: In bunionectomy, herniorrhaphy, and total knee arthroplasty procedures, Zynrelef scored the lowest on the pain-intensity scale over a 72-hour period and had the largest percentage of patients who did not request additional opioid therapy compared to bupivacaine HCl and saline placebo. Zynrelef is administered via a needle-free single-dose viscous solution instillation available in both 7- and 14-mL vials, opposed to Exparel's single-dose infiltration injection available in either 10- or 20-mL vials. The average wholesale price of Zynrelef amounts to $267.50 (14-mL) and $135.50 (7-mL), and Exparel equates to $344.20 (20-mL) and $189.37 (10-mL). Conclusion: Zynrelef results in more efficacious pain relief and reduced opioid usage compared to bupivacaine HCl and saline placebo. Additionally, the use of the irrigation administration could curb the site pain and inflammation associated with injections, eliminating additional need for anti-inflammatories and local anesthetics. Lastly, when comparing the cost, Zynrelef shows to be slightly more expensive per dose over a three-day (72-hour) period, but the benefits of adding meloxicam were proven to reduce usage of opioid medications and increase alleviation of pain. A future study that considers potential cost savings from eliminating needles for injection and reducing post-operative opioid prescribing would be beneficial.
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    Development of a Machine Learning Model to Design Target-specific Ligands
    (2022) Mathew, Ezek; Liu, Jin; Wang, Duen-Shian; Liu, Kevin
    Background: As the estimated cost required to bring a drug to market ranges from $314 million to $2.8 billion, drug discovery is undoubtedly a lengthy and expensive process. Additionally, completion of Phase 3 trials does not guarantee FDA approval. For most drugs, the probability of receiving FDA approval ranges from 9% to 14%, depending on the time period. Therefore, researchers have turned to machine learning (ML) to decrease the burden of drug discovery for multiple targets. In the central nervous system (CNS), the metabotropic glutamate receptor subtype 2 (mGlu2) and metabotropic glutamate receptor subtype 3 (mGlu3) play various roles in normal physiology. Therefore, ligands of these receptors pose potential for the treatment of various pathologies, such as Alzheimer's disease, schizophrenia, and other neurological disorders. Currently, no literature exists referencing a machine learning model that is capable of distinguishing drug ligands based on their affinity to mGlu2 or mGlu3. To fill this gap in knowledge, we will design a machine learning algorithm capable of making associations across the entire data set, identifying patterns that the human eye cannot detect. Methods: We utilized a dataset which included two dimensional (2D) images of drug ligands belonging to two classes, mGlu2 or mGlu3. The images were resized, then converted into grayscale and subsequently processed as a numerical NumPy array with their associated labels. Convolutional Neural Network (CNN) and Functional API architecture were tested to determine the optimal model. Hyperparameter optimization occurred throughout this process. Results: The CNN and Functional API both reached 100% accuracy within 20 epochs, successfully classifying ligands as mGlu2 or mGlu3 based on 2D structure alone. However, the Functional API reached 100% accuracy in under 5 epochs, yielding superior performance when compared to the CNN. Conclusion: While the CNN is one of the most popular ML architectures for image classification, the Functional API can perform a similar role. As datasets expand, it may be beneficial to consider more efficient models, especially for image classification in the realm of drug discovery.