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Research Interests
Molecular Imaging Agent Design – Significant advances have been made in understanding the molecular basis of many diseases including cancer, cardiovascular disease, autoimmune disorders, Alzheimer’s disease, and numerous others. Molecular imaging agents have the potential to translate this knowledge into making earlier and more accurate diagnoses and better monitoring of treatment outcomes. The broad research goal of the lab is to understand the transient distribution of imaging agents based on molecular properties (such as size, target affinity, lipophilicity, plasma clearance, etc.) in order to efficiently generate novel compounds. A mechanistic understanding of distribution also enables predictive scaling from animal models to the clinic for more efficient translation. Towards this goal, the lab uses a joint theoretical and experimental approach, applying fundamental chemical engineering principles, to utilize models while developing new imaging agents and measuring their properties and distribution.
Quantitative Pharmacology – Therapeutic molecules must reach their intended target for efficacy in disease treatment. Mathematical models developed for imaging agents also apply to therapeutic distribution, often delivered in a pseudo-steady state fashion (such as repeated oral dosing). Using sophisticated in vivo microscopy techniques and multi-scale mathematical modeling, the distribution of therapeutics is investigated from the organ level down to the tissue, cellular, and subcellular length scale. The results can be paired with pharmacodynamic studies to maximize therapeutic efficacy. Mathematical models developed from these experimental studies will become increasingly important as the distinction between small molecule drugs and macromolecule biologics decreases for many new therapeutics with novel properties.
Molecular Imaging Agent Design – Significant advances have been made in understanding the molecular basis of many diseases including cancer, cardiovascular disease, autoimmune disorders, Alzheimer’s disease, and numerous others. Molecular imaging agents have the potential to translate this knowledge into making earlier and more accurate diagnoses and better monitoring of treatment outcomes. The broad research goal of the lab is to understand the transient distribution of imaging agents based on molecular properties (such as size, target affinity, lipophilicity, plasma clearance, etc.) in order to efficiently generate novel compounds. A mechanistic understanding of distribution also enables predictive scaling from animal models to the clinic for more efficient translation. Towards this goal, the lab uses a joint theoretical and experimental approach, applying fundamental chemical engineering principles, to utilize models while developing new imaging agents and measuring their properties and distribution.
Quantitative Pharmacology – Therapeutic molecules must reach their intended target for efficacy in disease treatment. Mathematical models developed for imaging agents also apply to therapeutic distribution, often delivered in a pseudo-steady state fashion (such as repeated oral dosing). Using sophisticated in vivo microscopy techniques and multi-scale mathematical modeling, the distribution of therapeutics is investigated from the organ level down to the tissue, cellular, and subcellular length scale. The results can be paired with pharmacodynamic studies to maximize therapeutic efficacy. Mathematical models developed from these experimental studies will become increasingly important as the distinction between small molecule drugs and macromolecule biologics decreases for many new therapeutics with novel properties.
研究兴趣
论文共 102 篇作者统计合作学者相似作者
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Ian Nessler,Baron Rubahamya,Anna Kopp, Scott Hofsess,Thomas M. Cardillo, Nalini Sathyanarayan, Jennifer Donnell,Serengulam V. Govindan,Greg M. Thurber
MOLECULAR CANCER THERAPEUTICSno. 3 (2024): 343-353
Anna Kopp, Jiakun Guan, Colette Johnston, Steven Vance, James Legg, Laurie Galson-Holt,Greg M. Thurber
The AAPS Journalno. 4 (2024): 1-13
Pharmaceutical Researchno. 6 (2024): 1-12
The AAPS journalno. 4 (2024): 68-68
Ian Nessler, Baron Rubahamya, Anna Kopp, Scott Hofsess,Thomas M. Cardillo, Nalini Sathyanarayan, Jennifer Donnell,Serengulam V. Govindan,Greg M. Thurber
crossref(2024)
Science advancesno. 22 (2024): eadk1894-eadk1894
Anna Kopp, Shujun Dong, Hyeyoung Kwon,Tiexin Wang,Alec A Desai,Jennifer J Linderman,Peter Tessier,Greg M Thurber
bioRxiv : the preprint server for biology (2024)
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAno. 11 (2024): e2311726121-e2311726121
Anna Kopp, Hyeyoung Kwon,Colette Johnston, Steven Vance,James Legg, Laurie Galson-Holt,Greg M. Thurber
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