LINCOLN, Mass., April 14, 2017 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced a collaboration with Northern Biologics focused on traditional and mechanistic pharmacokinetic and pharmacodynamics (PK/PD) modeling for a biotherapeutic candidate in oncology.
Applied BioMath will utilize a hybrid modeling approach leveraging both traditional PK/PD models as well as semi-mechanistic PK/PD models to support the IND. Applied BioMath will develop models for mouse, cynomolgus monkey, and humans with cancer, the latter of which will be used to aid the prediction of first-in-human (FIH) doses. "Incorporating known disease mechanisms and drug mechanism of action (MOA) into traditional PK/PD models significantly increases the fidelity of the model to the actual biological system," said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "This results in more accurate predictions which is critical for progressing drugs into the clinic." In the future, the translated human model can be updated with emerging clinical PK/PD data to further refine the model and aid in clinical decision making.
Northern Biologics will use Applied BioMath's models to strengthen their understanding of the parameters that will determine optimal dosing paradigms. "Guidance from these modeling efforts will help us provide biological insights that will ensure we design our clinical trial to measure the most appropriate biomarkers at the right time and enable the highest likelihood of success," said Jeanne Magram, PhD, CSO of Northern Biologics. "This provides confidence in our thought processes, has the potential to shorten project timelines and reduce cost while accelerating our candidate through R&D and into the clinic."
About Applied BioMath
Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, helps biotechnology and pharmaceutical companies answer complex, critical Go/No-go decisions in R&D. Applied BioMath leverages biology, proprietary mathematical modeling and analysis technology, high-performance computing, and decades of industry experience to help groups better understand their candidate, its best-in-class parameters, competitive advantages, and the best path forward. Our involvement shortens project timelines, lowers cost, and increases the likelihood of a best-in-class drug. We provide clarity to complex situations, answer otherwise unanswerable questions, and our approach, when validated in the clinic, is 10x more accurate than traditional methodologies.
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SOURCE Applied BioMath, LLC