Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced an extension of their collaboration with Zymeworks Inc. for quantitative systems pharmacology (QSP) support for antibody drug conjugate therapeutics intended for the treatment of cancer.
Applied BioMath has supported Zymeworks previously for GLP toxicology studies and first-in-human dose predictions for IND filings. This extension of their collaboration will update the previously built QSP model with new clinical data to analyze and predict dose escalations and inform internal decisions about next steps in clinical trials. "One of the benefits of our modeling approach is that we can easily evolve our model as new data is produced to continue to support the project team throughout R&D," said John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "We prioritize an accurate representation of the disease biology specifically for this reason, so that the model translates well from early development to the clinic."
"We are pleased to extend our collaboration with Applied BioMath," said Gerry Rowse, PhD, Senior Director, Therapeutics Preclinical Development, Zymeworks. "The mechanistic modeling work the Applied BioMath team continues to perform significantly contributes to our R&D efforts and decision making processes. We look forward to continuing our working relationship with them as we advance our programs into clinical trials."
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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