Applied BioMath, LLC Extends Collaboration into Phase 1 with Northern Biologics for Clinical Pharmacology Support and Semi-Mechanistic PK/PD Modeling Support in Oncology

Applied BioMath (, the industry-leader in applying mechanistic modeling, simulation, and analysis to accelerate and de-risk drug research and development, today announced an extension to their collaboration with Northern Biologics Inc. to include Phase I clinical analyses for MSC-1, their lead antibody therapeutic targeting the cytokine LIF for the treatment of cancer. This collaboration will focus on clinical pharmacology and traditional and mechanistic pharmacokinetic and pharmacodynamic (PK/PD) modeling.

Applied BioMath previously collaborated with Northern Biologics to create a human semi-mechanistic PK/PD model to support IND filing. In this next phase of the collaboration, Applied BioMath will update the previously built human semi-mechanistic PK/PD model with interim Phase 1 data to support the ongoing Phase 1 clinical study as well as provide updated optimal dosing regimen predictions to support dosing regimen selection for Phase 2 studies. Applied BioMath will additionally provide clinical pharmacology support. "Applied BioMath's models were important in establishing our Phase I dosing regimen," said Philip Vickers, PhD, CEO of Northern Biologics. "In addition, modeling efforts from Applied BioMath also informed the design of Northern Biologics' biomarker strategy. Understanding how target occupancy relates to target inhibition and efficacy will be critical for the success of the MSC-1 program moving forward."

Applied BioMath employs a rigorous fit-for-purpose model development process, referred to as Model-Aided Drug Invention (MADI), which aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. Their MADI approach employs proprietary algorithms and software that were designed specifically for mechanistic PK/PD modeling. "The mechanistic component of our modeling approach brings a biological relevance which is crucial for a model to successfully progress from preclinic into the clinic," said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "Given the increased investment as candidates progress to the clinic, teams that can continue to leverage their models to support their clinical decision-making stand to save an even higher amount of resources and budget."

About Applied BioMath

Founded in 2013, 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 Model-Aided Drug Invention (MADI) 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

Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.

Press contact:
Kristen Zannella