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 a collaboration with Xilio Therapeutics. Applied BioMath will continue work on semi-mechanistic pharmacokinetic/pharmacodynamic models to support Xilio development programs. "We previously collaborated with Applied BioMath to develop our in vitro and in vivo systems math models," said Jennifer O'Neil, PhD, Vice President, Translational Oncology at Xilio Therapeutics. "We look forward to extending this collaboration to utilizing these systems pharmacology models for FIH dose predictions and IND support."
Applied BioMath employs a rigorous fit-for-purpose model development process which aims to quantitatively integrate 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. "The mechanistic nature of our systems modeling makes it ideal for translating from in vitro to in vivo and human models, and for aiding in critical thinking," said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "We often work with our collaborators to help them predict FIH starting dose and efficacious dose and to prepare the PK section of their IND filing."
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.