Applied BioMath (www.appliedbiomath.com), the industry-leader in providing model-informed drug discovery and development (MID3) support to help accelerate and de-risk therapeutic research and development (R&D), today announced their participation at the 14th Annual World Bispecific Summit occurring October 2-4, 2023 in Boston, MA.
Fei Hua, PhD, Vice President of Modeling and Simulation Services at Applied BioMath will present, "Using Mathematical Modeling to Find a Balance Between Affinity and Avidity for an Optimal Therapeutic Window" within the Preclinical and Clinical Track on Tuesday, October 3, 2023 at 2:15pm.
In this presentation, Dr. Hua will demonstrate how mathematical modeling can help address critical design and development considerations, and predict an optimal therapeutic window for bispecific molecules. For example, with cis-binding bispecific molecules, weaker single-target binding affinity with stronger avidity is a strategy to reduce the chances of the drug binding to off-target cells, thereby increasing the therapeutic window. With multiple targets involved, binding affinities to multiple targets can be optimized and the expression levels of multiple targets need to be considered with translating from preclinical to clinical studies. Mechanistic PK/PD models can capture the biophysics of binding and avidity to guide compound selection and clinical translation.
"For complex therapeutics, such as bispecific and multispecific molecules, there are many design factors that are not always straightforward," said John Burke, PhD, Co-founder, President and CEO of Applied BioMath. "Incorporating mathematical modeling approaches provides competitive advantages, as it helps to test and generate hypotheses much more quickly than traditional methods."
To learn more about Applied BioMath, visit www.appliedbiomath.com.
About Applied BioMath
Founded in 2013, Applied BioMath's mission is to revolutionize drug invention. Applied BioMath applies biosimulation, including quantitative systems pharmacology, PK/PD, bioinformatics, machine learning, clinical pharmacology, and software solutions to provide quantitative and predictive guidance to biotechnology and pharmaceutical companies to help accelerate and de-risk therapeutic research and development. Their approach employs proprietary algorithms and software to support groups worldwide in decision-making from early research through all phases of 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 therapeutic, its best-in-class parameters, competitive advantages, patients, and the best path forward into and in the clinic to increase likelihood of clinical concept and proof of mechanism, and decrease late stage attrition rates. For more information about Applied BioMath and its services and software, visit www.appliedbiomath.com.
Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.