Academic literature on the topic 'Master of Drug Discovery and Development'
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Journal articles on the topic "Master of Drug Discovery and Development"
Yu, Bingting, Ruslan Mamedov, Gwenny M. Fuhler, and Maikel P. Peppelenbosch. "Drug Discovery in Liver Disease Using Kinome Profiling." International Journal of Molecular Sciences 22, no. 5 (March 5, 2021): 2623. http://dx.doi.org/10.3390/ijms22052623.
Full textMartínez, Antón Leandro, José Brea, Marián Castro, Ángel García, Eduardo Santamaría, Óscar Lestón, and María Isabel Loza. "An Experience of Using a Canvas-Based Template for Blended-Learning in a Master in Drug Discovery." International Journal of Emerging Technologies in Learning (iJET) 17, no. 06 (March 29, 2022): 257–67. http://dx.doi.org/10.3991/ijet.v17i06.28149.
Full textGusev, K. A., O. A. Terenteva, D. N. Maimistov, Yu E. Generalova, K. O. Sidorov, and E. V. Flisyuk. "Development of Suppositories Silicone Molds Using Additive Technologies." Drug development & registration 11, no. 4 (November 27, 2022): 116–24. http://dx.doi.org/10.33380/2305-2066-2022-11-4-116-124.
Full textZheng, Hailin, Mati Fridkin, and Moussa Youdim. "New Approaches to Treating Alzheimer's Disease." Perspectives in Medicinal Chemistry 7 (January 2015): PMC.S13210. http://dx.doi.org/10.4137/pmc.s13210.
Full textKaizer, Alexander M., Joseph S. Koopmeiners, Michael J. Kane, Satrajit Roychoudhury, David S. Hong, and Brian P. Hobbs. "Basket Designs: Statistical Considerations for Oncology Trials." JCO Precision Oncology, no. 3 (December 2019): 1–9. http://dx.doi.org/10.1200/po.19.00194.
Full textShirakawa, Tomohiko, Takashi Toyono, Asako Inoue, Takuma Matsubara, Tatsuo Kawamoto, and Shoichiro Kokabu. "Factors Regulating or Regulated by Myogenic Regulatory Factors in Skeletal Muscle Stem Cells." Cells 11, no. 9 (April 29, 2022): 1493. http://dx.doi.org/10.3390/cells11091493.
Full textBuxton, Meredith Becker, Brian Michael Alexander, Donald A. Berry, Webster K. Cavenee, Howard Colman, John Frederick De Groot, Benjamin M. Ellingson, et al. "GBM AGILE: A global, phase II/III adaptive platform trial to evaluate multiple regimens in newly diagnosed and recurrent glioblastoma." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): TPS2579. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.tps2579.
Full textChen, Po-Ling, Tsai-Teng Tzeng, Alan Yung-Chih Hu, Lily Hui-Ching Wang, and Min-Shi Lee. "Development and Evaluation of Vero Cell-Derived Master Donor Viruses for Influenza Pandemic Preparedness." Vaccines 8, no. 4 (October 25, 2020): 626. http://dx.doi.org/10.3390/vaccines8040626.
Full textChavan, Sandeep, Sonali Tayade, Vidya Gupta, Vineeta Deshmukh, and Sadanand Sardeshmukh. "Pharmaceutical Standardization and Physicochemical Characterization of Traditional Ayurvedic Marine Drug: Incinerated Conch Shell (Shankha Bhasma)." Marine Drugs 16, no. 11 (November 15, 2018): 450. http://dx.doi.org/10.3390/md16110450.
Full textWu, Guoyu, Junyang Yi, Ling Liu, Pengcheng Wang, Zhijie Zhang, and Zhen Li. "Pseudoginsenoside F11, a Novel Partial PPARγAgonist, Promotes Adiponectin Oligomerization and Secretion in 3T3-L1 Adipocytes." PPAR Research 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/701017.
Full textDissertations / Theses on the topic "Master of Drug Discovery and Development"
Cai, Xiaoshu. "DEVELOPMENT OF COMPUTATIONAL APPROACH FOR DRUG DISCOVERY." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1465403528.
Full textGage, Zoe O. "Interferon, viruses and drug discovery." Thesis, University of St Andrews, 2017. http://hdl.handle.net/10023/10127.
Full textCereto, Massagué Adrià. "Development of tools for in silico drug discovery." Doctoral thesis, Universitat Rovira i Virgili, 2017. http://hdl.handle.net/10803/454678.
Full textEl cribado virtual es un método quimioinformático que consiste en la criba de moléculas bioactivas de grandes bases de datos de moléculas pequeñas. Esto permite a los investigadores ahorrarse el coste de probar experimentalmente cientos o miles de compuestos candidatos, reduciéndolos hasta cantidades manejables. Para la validación de los métodos de cribado virtual hacen falta bibliotecas de moléculas señuelo. El software DecoyFinder fue desarrollado como aplicación gráfica de fácil uso para la construcción de bibliotecas de moléculas señuelo, y fue posteriormente ampliado con los hallazgos de investigación posterior sobre la construcción i rendimiento de bibliotecas de moléculas señuelo. El Protein Data Bank (PDB) es muy útil porque proporciona estructuras tridimensionales para complejos proteina-ligando, y por tanto, información sobre como interactúan. Para los métodos de cribado virtual que dependen de ellas, es extremadamente importante su fiabilidad. VHELIBS fue desarrollado como herramienta para inspeccionar e identificar, fácil e intuitivamente, las estructuras fiables del PDB, basándose en como de bueno es su encaje con sus correspondientes mapas de densidad electrónica. Mientras que el cribado virtual intenta encontrar nuevas moléculas bioactivas para determinadas dianas, el enfoque inverso también se utiliza: a partir de una molécula, buscar dianas donde presente actividad biológica no documentada. Este cribado inverso es conocido en inglés como “in silico target fishing”, o pesca de dianas “in silico”, y es especialmente útil en el ámbito de la reutilización de fármacos. Al comenzar esta tesis, no había ninguna plataforma de “target fishing” de libre acceso, y aunque durante los años se han desarrollado algunas, en todos los casos su predicción de bioactividad es cualitativa. Por eso se desarrolló una plataforma propia de “target fishing” de libre acceso, con la implementación de un nuevo método que proporciona la primera predicción cuantitativa de bioactividad para este tipo de plataforma.
Virtual screening is a cheminformatics method that consists of screening large small-molecule databases for bioactive molecules. This enables the researcher to avoid the cost of experimentally testing hundreds or thousands of compounds by reducing the number of candidate molecules to be tested to manageable numbers. For their validation, virtual screening approaches need decoy molecule libraries. DecoyFinder was developed as an easy to use graphical application for decoy library building, and later updated after some research into decoy library building and their performance when used for 2D similarity approaches. The Protein Data Bank (PDB) is very useful because it provides 3D structures for protein-ligand complexes and, therefore, information on how certain ligands bind and interact with their targets. For virtual screening apporaches relying on these structures, it is of the utmost importance that the data available on the PDB for the ligand and its binding site are reliable. VHELIBS was developed as a tool to easily and intuitively inspect and identify reliable PDB structures based on the goodness of fitting between ligands and binding sites and their corresponding electron density map. While virtual screening aims to find new bioactive molecules for certain targets, the opposite approach is also used: starting from a given molecule, to search for a biological target for which it presents previously undocumented bioactivity. This reverse screening is known as in silico or computational target fishing or reverse pharmacognosy, and it is specially useful for drug repurposing or repositioning. When this thesis was started, there were no freely available target fishing platforms, but some have been developed during the years. However, they are qualitative in the nature of their activity prediction, and thus we set out to develop a freely accessible target fishing web service implementing a novel method which provides the first quantitative activity prediction: Anglerfish.
Acoca, Stephane. "In silico methods in drug discovery and development." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110376.
Full textLes méthodes the modélisation sont devenues un outil inestimable dans le processus de découverte et de développement de nouveaux médicaments. Au cours de cette thèse va être décrit le développement et l'application de méthodes utilisés à chaque stage de la découverte et du développement de produits pharmaceutiques. Le Chapitre 2 est un aperçu sur l'utilisation de méthodes computationnelles vers le développement de deux nouveaux inhibiteurs des protéines Bcl-2, Obatoclax et ABT-737, en développement pour le traitement du Cancer. L'étude propose certains mécanismes d'ABT-737 qui expliquent ca sélectivité envers les membres de la famille Bcl-2. De plus, nous proposons un mécanisme d'attachement pour Obatoclax qui conforme aux données expérimentales. Le Chapitre suivant adresse l'utilisation du dépistage virtuel pour l'identification de nouvelles molécules mère. La Ligase de l'Edition d'ARN du Trypanosoma brucei a été choisie comme cible pour le développement de traitements contre des infections dû au Trypanosome et C35 a été identifié comme nouvel inhibiteur de l'enzyme. En outre, notre recherche démontre que l'action de C35 s'étends a l'inhibition de plusieurs enzymes nécessaires pour le mécanisme d'édition de l'ARN en plus de compromettre l'intégrité du complexe multi-protéinique qui l'effectue. Le Chapitre suivant prends regard a l'utilisation de donnes dérivant de la spectrométrie de masse pour but d'accélérer la découverte de molécules bioactives venant de sources naturelles. Nous avons développé un algorithme qui analyse les données MS/MS pour but de dériver la formule moléculaire du composé. Le nouvel algorithme a obtenu un taux de succès s'élevant à 95% sur un ensemble test de 91 molécules. Le dernier Chapitre de la thèse explore l'utilisation de simulations de dynamique moléculaire pour générer en ensemble conformationel de protéines cible pour son utilisation dans le dépistage virtuel. Les ensembles conformationel ont étés généré pour une série test obtenu d'un répertoire attitré 'Directory for Useful Decoys'. Les résultats démontrent que les ensembles conformationel dérivés de la dynamique moléculaire ont apporté des améliorations remarquables sur deux des cibles testées dû à une capacité accrue de placement approprié des molécules dans un site qui est autrement très restreint. Le dernier Chapitre de cette thèse est une discussion générale sur le travail accomplie et une proposition sur la manière dont tous les éléments sont intégrer dans un protocole de découverte et de développement de produits pharmaceutiques.
Hoffman, Benjamin. "The Genetics of Cancer in Pharmacological Drug Development." Diss., Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/212455.
Full textPh.D.
The field of cancer therapeutic development has been dominated by two research and discovery paradigms, the cytotoxicity-based or phenotype driven strategy and the target-based rational approach. This thesis describes the standardization of novel assays used in both approaches and the discoveries made using these processes. Rational drug design or the target-based approach to discovering novel anti-cancer agents requires a basic understanding of the oncogenic signals that induce uncontrolled cellular proliferation. c-MET is a proto-oncogene, linked to a number of different cancers, that encodes a receptor tyrosine kinase. As an oncogene, c-MET has been shown to transform cells in the laboratory setting and is dysregulated in number of malignancies. Thus, we sought to discover a small molecule inhibitor of c-MET kinase activity by screening a novel library of small molecules. In the second part of this dissertation, we describe the standardization of a high-throughput assay to identify putative c-MET inhibitors and the results of our screening attempt. Cytotoxicity-based screening is another validated approach that is used to discover anti-cancer agents. As a parallel program to our c-MET discovery effort, we designed a high-throughput cytotoxicity assay to identify a novel small molecule with high cytotoxic activity towards tumor cells. The result of this screen was the identification of ON015640, a novel anti-cancer therapeutic with tubulin-depolymerizing activity. Throughout the course of this project, we tried to discern the advantages and disadvantages of the two predominant paradigms in cancer therapeutic research. Both strategies require careful assay design and an acute understanding of the molecular and genetic underpinnings of cancer. While it is clear that structure-based rational drug design has its merits and its success stories, it has become increasingly clear that seeking out a desired biological effect may serve as a more effective staring point when dealing with cancers for which no clear oncogene addiction phenotype has been observed.
Temple University--Theses
Schreiber, Kimberly C. M. "Assay development for use in drug discovery against Bovine Trichomoniasis." Scholarly Commons, 2007. https://scholarlycommons.pacific.edu/uop_etds/650.
Full textMiller, Lisa Margaret. "The development of small molecule inhibitors for fibrosis drug discovery." Thesis, University of Strathclyde, 2016. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=27922.
Full textHatherley, Rowan. "Structural bioinformatics studies and tool development related to drug discovery." Thesis, Rhodes University, 2016. http://hdl.handle.net/10962/d1020021.
Full textYamaura, Kei. "Novel methods for drug discovery and development using ligand-directed chemistry." 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/217177.
Full textPilger, Jens. "Development and application of NMR methods for challenges in drug discovery." Doctoral thesis, Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2013. http://hdl.handle.net/11858/00-1735-0000-0015-C6E8-4.
Full textBooks on the topic "Master of Drug Discovery and Development"
Dikshit, Madhu, ed. Drug Discovery and Drug Development. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8002-4.
Full textRang, H. P., and Raymond Hill. Drug discovery and development. 2nd ed. Edinburgh: Elsevier, 2012.
Find full textDrug discovery and development. 2nd ed. Edinburgh: Elsevier, 2012.
Find full textChorghade, Mukund S., ed. Drug Discovery and Development. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0471780103.
Full textO’Donnell III, James J., John Somberg, Vincent Idemyor, and James T. O’Donnell, eds. Drug Discovery and Development. Third edition. | Boca Raton, Florida : CRC Press, 2019. |: CRC Press, 2019. http://dx.doi.org/10.1201/9781315113470.
Full textChorghade, Mukund S., ed. Drug Discovery and Development. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470085223.
Full textWilliams, Michael, and Jeffrey B. Malick, eds. Drug Discovery and Development. Totowa, NJ: Humana Press, 1987. http://dx.doi.org/10.1007/978-1-4612-4828-6.
Full textPoduri, Ramarao, ed. Drug Discovery and Development. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-5534-3.
Full textS, Chorghade Mukund, ed. Drug discovery and development. Hoboken, N.J: Wiley, 2006.
Find full textLiu, Xinyong, Peng Zhan, Luis Menéndez-Arias, and Vasanthanathan Poongavanam, eds. Antiviral Drug Discovery and Development. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0267-2.
Full textBook chapters on the topic "Master of Drug Discovery and Development"
Turner, J. Rick. "Drug Discovery." In New Drug Development, 21–34. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6418-2_3.
Full textWashburn, William N. "Chapter 3. SGLT2 Inhibitors in Development." In Drug Discovery, 29–87. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735322-00029.
Full textFilipski, Kevin J., Benjamin D. Stevens, and Jeffrey A. Pfefferkorn*. "Chapter 4. Glucokinase Activators in Development." In Drug Discovery, 88–108. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735322-00088.
Full textMacchiarulo, Antonio, Antimo Gioiello, and Roberto Pellicciari*. "Chapter 10. TGR5 Agonists in Development." In Drug Discovery, 270–305. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735322-00270.
Full textPerni, Robert B., Vipin Suri, Thomas V. Riera, Joseph Wu, Charles A. Blum, George P. Vlasuk, and James L. Ellis*. "Chapter 13. SIRT1 Activators in Development." In Drug Discovery, 366–402. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735322-00366.
Full textBourbeau, Matthew P. "Chapter 16. ACC Inhibitors in Development." In Drug Discovery, 464–500. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735322-00464.
Full textDemong*, Duane E., and M. W. Miller. "Chapter 15. Glucagon Receptor Antagonists in Development." In Drug Discovery, 429–63. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849735322-00429.
Full textYing, Weiwen. "CHAPTER 6. Discovery and Development of Ganetespib." In Drug Discovery, 180–97. Cambridge: Royal Society of Chemistry, 2013. http://dx.doi.org/10.1039/9781849739689-00180.
Full textMitscher, Lester A., and Apurba Dutta. "Contemporary Drug Discovery." In Drug Discovery and Development, 103–28. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0471780103.ch3.
Full textSolon, Eric G. "Chapter 6. Autoradiography in Pharmaceutical Discovery and Development." In Drug Discovery, 309–42. Cambridge: Royal Society of Chemistry, 2011. http://dx.doi.org/10.1039/9781849732918-00309.
Full textConference papers on the topic "Master of Drug Discovery and Development"
Miftahof, R., and N. Akhmadeev. "Mathematical modeling in drug discovery and development." In BIOMED 2007. Southampton, UK: WIT Press, 2007. http://dx.doi.org/10.2495/bio070301.
Full textSathiaseelan, Allimalar, Chong Seng Shit, and Tsun-Thai Chai. "ANTI-BIOFILM ACTIVITY OF FERMENTED SOYBEAN TEMPEH EXTRACTS AND FRACTIONS AGAINST ORAL PRIMARY COLONIZER BACTERIA." In International Conference on Drug Discovery & Development. The International Institute of Knowledge Management (TIIKM), 2018. http://dx.doi.org/10.17501/icddd.2017.1101.
Full textRansom, John T., Bruce S. Edwards, Frederick W. Kuckuck III, Alex Okun, David K. Mattox, Eric R. Prossnitz, and Larry A. Sklar. "Flow cytometry systems for drug discovery and development." In BiOS 2000 The International Symposium on Biomedical Optics, edited by Daniel L. Farkas and Robert C. Leif. SPIE, 2000. http://dx.doi.org/10.1117/12.384201.
Full textIbáñez Antolín, Ane. "Applications of Machine Learning in drug discovery and development." In MOL2NET'21, Conference on Molecular, Biomedical & Computational Sciences and Engineering, 7th ed. Basel, Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/mol2net-07-11234.
Full textBednar, Bohumil. "Development of Optical Imaging Biomarkers and Applications in Drug Discovery and Development." In Biomedical Optics. Washington, D.C.: OSA, 2010. http://dx.doi.org/10.1364/biomed.2010.bma2.
Full textMomtahen, Shadi, Furat Al-Obaidy, and Farah Mohammadi. "Machine Learning with Digital Microfluidics for Drug Discovery and Development." In 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE). IEEE, 2019. http://dx.doi.org/10.1109/ccece.2019.8861842.
Full textKumazawa, Shigenori. "Bioactive compounds in bee propolis for drug discovery." In 2ND BIOMEDICAL ENGINEERING’S RECENT PROGRESS IN BIOMATERIALS, DRUGS DEVELOPMENT, AND MEDICAL DEVICES: Proceedings of the International Symposium of Biomedical Engineering (ISBE) 2017. Author(s), 2018. http://dx.doi.org/10.1063/1.5023948.
Full textKhalil, Iya. "Abstract SY14-03: Inferring causality for oncology drug discovery and development." In Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/1538-7445.am2011-sy14-03.
Full textChandra, Rini, Mohammed Javed, Bulla Rajesh, B. S. Sanjeev, and Shahnawaz Khijmatgar. "Target-less Drug Discovery Pipeline using Feature Driven Development (FDD) model." In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021. http://dx.doi.org/10.1109/bibm52615.2021.9669585.
Full textHait, William N. "Abstract IA-12: Oncology drug discovery and development in the 21st century." In Abstracts: First AACR International Conference on Frontiers in Basic Cancer Research--Oct 8–11, 2009; Boston MA. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/0008-5472.fbcr09-ia-12.
Full textReports on the topic "Master of Drug Discovery and Development"
Wirth, Dyann F. New Strategies for Drug Discovery and Development for Plasmodium Falciparum. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada375802.
Full textWang, Yanming. InVivo Imaging of Myelination for Drug Discovery and Development in Multiple Sclerosis. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada580016.
Full textEfange, Simon, and Deborah C. Mash. Drug Development and Conservation of Biodiversity in West and Central Africa: Performance of Neurochemical and Radio Receptor Assays of Plant Extracts Drug Discovery for the Central Nervous System. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada474867.
Full textJarron, Matthew, Amy R. Cameron, and James Gemmill. Dundee Discoveries Past and Present. University of Dundee, November 2020. http://dx.doi.org/10.20933/100001182.
Full textCytryn, Eddie, Mark R. Liles, and Omer Frenkel. Mining multidrug-resistant desert soil bacteria for biocontrol activity and biologically-active compounds. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598174.bard.
Full textShpigel, Nahum, Raul Barletta, Ilan Rosenshine, and Marcelo Chaffer. Identification and characterization of Mycobacterium paratuberculosis virulence genes expressed in vivo by negative selection. United States Department of Agriculture, January 2004. http://dx.doi.org/10.32747/2004.7696510.bard.
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