{"686565":{"#nid":"686565","#data":{"type":"event","title":"PhD Defense by Bridget Neary ","body":[{"value":"\u003Cp\u003EIn partial fulfillment of the requirements for the degree of\u003Cbr\u003EDoctor of Philosophy in Bioinformatics\u003Cbr\u003Ein the School of Biological Sciences\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBridget Neary\u003C\/strong\u003E\u0026nbsp;\u003Cbr\u003E\u003Cbr\u003EDefends her thesis:\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBiological Insights from Predictors of Drug Response in Cancer Patients\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EMonday, December 1, 2025 at 1:00 PM\u003C\/p\u003E\u003Cp\u003EEngineered Biosystems Building (EBB),\u003C\/p\u003E\u003Cp\u003ECHOA seminar room EBB 1005\u003C\/p\u003E\u003Cp\u003EMeeting Link:\u0026nbsp;\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_MTUyNTc0ZDctYjgzOC00NDViLThjYjQtZjY1ZjUxMjQ5ZWZi%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22e7ed144a-29d0-4410-95d2-2276aac844b5%22%7d\u0022 target=\u0022_blank\u0022\u003EBridget Neary Thesis Defense | Microsoft Teams\u003C\/a\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EThesis Advisor\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Peng Qiu\u0026nbsp;\u003Cbr\u003EDepartment of Biomedical Engineering\u003Cbr\u003E\u003Cem\u003EGeorgia Institute of Technology\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee Members\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Greg Gibson\u003Cbr\u003ESchool of Biological Sciences\u003Cbr\u003E\u003Cem\u003EGeorgia Institute of Technology\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDr. Saurabh Sinha\u003Cbr\u003EDepartment of Biomedical Engineering\u003Cbr\u003E\u003Cem\u003EGeorgia Institute of Technology\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDr. Manoj Bhasin\u003Cbr\u003EDepartment of Pediatrics\u003Cbr\u003E\u003Cem\u003EEmory University\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDr. Kevin Bunting\u003Cbr\u003EDepartment of Pediatrics\u003Cbr\u003E\u003Cem\u003EEmory University\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECancer therapies show considerable variation in efficacy, even among histologically similar cancers, and while precision medicine has made great strides in addressing this fundamental challenge, current advances still only benefit a minority of patients. Extending the reach of precision medicine will require the development of clinically deployable methods of predicting therapeutic outcomes and the expansion of our mechanistic understanding of variability of therapeutic efficacy. This thesis addresses these needs through three complementary approaches. First, we identified clinically relevant transcriptomic and methylomic single- and multi-gene biomarkers of treatment response in pre-treatment primary tumors. Next, to elucidate cellular mechanisms of variability in therapeutic variability, we investigated common transcriptional patterns across patients in each cancer that were predictive of drug response. Enrichment analysis of multi-gene biomarkers and response-associated transcriptional patterns suggested upstream regulators potentially involved in cellular drug effects, and analysis of core gene sets linked known chromosomal aberrations to patient differences in therapeutic response. Finally, we developed a multi-drug response prediction model that predicted clinical drug efficacy, adapting a biologically informed neural network structured around the Gene Ontology hierarchy for model interpretability and using transfer learning to leverage large preclinical datasets to compensate for insufficient patient sample sizes. Network layer importance analysis implicated known and novel biological processes involved in response to specific drugs and in multi-drug resistance. Together, these results provide new tools for predicting cancer treatment outcomes and new insights into cellular mechanisms of drug response. This work demonstrates how identification and development of predictors of patient treatment outcomes can be leveraged for additional understanding of the underlying biology that is essential for continued development and clinical implementation of precision medicine tools with broader clinical reach.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EBiological Insights from Predictors of Drug Response in Cancer Patients\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Biological Insights from Predictors of Drug Response in Cancer Patients"}],"uid":"27707","created_gmt":"2025-11-20 21:49:12","changed_gmt":"2025-11-20 21:49:55","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-12-01T13:00:00-05:00","event_time_end":"2025-12-01T15:00:00-05:00","event_time_end_last":"2025-12-01T15:00:00-05:00","gmt_time_start":"2025-12-01 18:00:00","gmt_time_end":"2025-12-01 20:00:00","gmt_time_end_last":"2025-12-01 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Engineered Biosystems Building (EBB), CHOA seminar room EBB 1005","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}