Applied BioMath, LLC to Present at Bio-IT World Conference & Expo
John Burke, PhD, Co-founder, President and CEO of Applied BioMath will present "Applied BioMath Assess - An Early Feasibility Assessment Tool for Biotherapeutics" within the Software Applications and Services track on Tuesday, September 21st at 10:30 a.m.
CONCORD, Mass., Sept. 14, 2021 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying systems pharmacology and mechanistic modeling, simulation, and analysis to de-risk drug research and development today announced their participation at the Bio-IT World Conference & Expo occurring virtually and in Boston, MA September 20-22, 2021.
John Burke, PhD, Co-founder, President and CEO of Applied BioMath will present "Applied BioMath Assess™ - An Early Feasibility Assessment Tool for Biotherapeutics" within the Software Applications and Services track on Tuesday, September 21st at 10:30 a.m. ET. In this presentation, Dr. Burke will demonstrate Applied BioMath Assess*, an interactive, web-based application that helps assess the difficulties and risks in developing a therapeutic very early-on. Dr. Burke will explain how Applied BioMath Assess can help project teams answer questions such as:
- How does affinity impact target inhibition? Will it impact TMDD if membrane bound?
- How does dosing interval impact success criteria?
- How does target expression, especially in the site of action, impact design criteria?
- How to think about therapeutic index prior to Lead Generation?
"Applied BioMath Assess provides rational go/no-go guidance while also helping project teams manage their resources efficiently," said Dr. Burke. "Our software has an exciting roadmap and will continue to evolve as we add new drug modality models and tools to best inform therapeutic R&D."
Additionally, Sharvari Gujja, Senior Principal Scientist, Bioinformatics at Applied BioMath will present a poster titled, "Leveraging ML/AI Tools for Robust Identification of Potential Biomarkers in Drug Response." The poster provides an overview of Applied BioMath's open source, easy-to-use and flexible command line interface (CLI) to access the state-of-the-art Machine Learning and Deep Learning frameworks to build predictive models for assessing cancer drug response using gene expression data from The Cancer Genome Atlas Program (TCGA) and Genomics of Drug Sensitivity in Cancer (GDSC).
To learn more about Applied BioMath, visit https://www.appliedbiomath.com/.
*Patent pending
About Applied BioMath
Founded in 2013, Applied BioMath's mission is to revolutionize drug invention. Applied BioMath uses mathematical modeling and simulation to provide quantitative and predictive guidance to biotechnology and pharmaceutical companies to help accelerate and de-risk drug research and development. Their approach employs proprietary algorithms and software to support groups worldwide in decision-making from early research through clinical trials. The Applied BioMath team leverages their decades of expertise in biology, mathematical modeling and analysis, high-performance computing, and industry experience to help groups better understand their candidate, its best-in-class parameters, competitive advantages, patients, and the best path forward into and in the clinic. For more information about Applied BioMath and its services, visit www.appliedbiomath.com.
Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.
Press contact:
Kristen Zannella
[email protected]
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SOURCE Applied BioMath, LLC
