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 ongoing collaboration with Monte Rosa Therapeutics to develop a cellular systems pharmacology model for cereblon (CRBN)-based molecular glue degraders (MGDs) targeting GSPT1. The model will be used to predict and explain CRBN-based GSPT1 target degradation in various cellular disease settings and to answer mechanistic questions.
"We chose to work with Applied BioMath based on their scientific expertise across various modalities and disease areas," said Sharon Townson, PhD, Chief Technology Officer at Monte Rosa Therapeutics. "Our hope is that the cellular systems pharmacology model we develop will accelerate our understanding of small molecule MGDs and we look forward to leveraging this advantage."
Applied BioMath employs a rigorous fit-for-purpose model development process which quantitatively integrates knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. Their approach employs proprietary algorithms and software that were designed specifically for systems pharmacology model development, simulation, and analysis. "A fit-for-purpose mechanistic model allows our partners to gain better insight into their therapeutic's mechanism of action in various disease conditions more quickly than with traditional experimental approaches," said John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "Monte Rosa Therapeutics is doing novel work and we're excited to partner with them on this project."
To learn more about Applied BioMath's solutions, visit https://www.appliedbiomath.com/our-solutions.
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, visitwww.appliedbiomath.com.
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