LINCOLN, Mass., May 2, 2016 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced that the National Institutes of Health (NIH) has awarded a $1.5M grant to Applied BioMath to enhance the company's proprietary tools and algorithms for analyzing nonclinical data and mechanisms and predicting clinical PKPD for biologics.
"Critical segments of biotherapeutics development, from lead identification to preclinical and clinical development, are largely unserved with respect to systems approaches. This award validates the need for more technology applications in this space, and demonstrates the NIH's support that Applied BioMath's technology is best served to do that."
Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath
Systems modeling has increasingly been adopted throughout drug R&D to help reduce late stage failures and accelerate time to market for best-in-class therapeutics. Due to the complexity and nonlinearity of biotherapeutics and disease, mechanistic systems approaches are best suited to increase certainty in nonclinical and translational human predictions. Applied BioMath's proprietary technology clarifies such complexities, thus enabling our partners to develop better, faster, less expensive biotherapeutics.
About Applied BioMath
Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug invention and development, helps biotechnology and pharmaceutical companies answer complex, critical Go/No-go decisions in R&D. Applied BioMath leverages biology, proprietary technology, high-performance computing, and decades of industry experience to help groups better understand human disease and their candidate, its best-in-class parameters, competitive advantages, and the optimal 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.
Applied BioMath and the Applied BioMath logo are trademarks of Applied BioMath, LLC.
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SOURCE Applied BioMath
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