Applied BioMath (www.appliedbiomath.com), the industry-leader in providing model-informed drug discovery and development (MID3) support to help accelerate and de-risk therapeutic research and development (R&D), today announced they have been awarded a grant to develop a simulation platform to facilitate the prediction of optimal dose, therapeutic window, and best dosing strategy of Immunocytokines.
Immunocytokines (ICs) are a promising class of cytokine-based therapeutics with potential applications in diseases such as rheumatoid arthritis (RA), psoriasis, and cancer. However, achieving an adequate therapeutic window is complicated because of the potentially high risk of toxicity due to off-target effects. The simulation platform will help reduce IC drug development risks, accelerate timelines, and reduce late stage attrition by efficiently screening for molecules with high likelihood of clinical success.
"We are excited to develop the first computational platform model in the IC field to include both pro- and anti-inflammatory immune responses to quantitatively address the critical question of how to balance efficacy and safety," said Raibatak Das, PhD, Senior Principal Scientist at Applied BioMath and the principal investigator on the grant. "The model is also designed to make the platform disease agnostic and applicable for dose predictions in a variety of clinical applications from cancer to autoimmune disorders." The simulation platform will be accessible via an interactive web-based user interface to foster effective communication among multidisciplinary R&D project teams, and help identify optimal molecular characteristics, dosing strategies, and guide selection criteria for clinical trials.
"We are excited to combine our expertise in QSP modeling, experience with IC modeling, and proprietary high-performance computing (HPC) analysis tools to optimize IC drug development for more efficacious and safer treatment for patients," said John Burke, PhD, Co-founder, President and CEO of Applied BioMath.
The grant referenced in this press release is supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number R44AI177133. The content is solely the responsibility of Applied BioMath, LLC and does not necessarily represent the official views of the National Institutes of Health.
About Applied BioMath
Founded in 2013, Applied BioMath's mission is to revolutionize drug invention. Applied BioMath applies biosimulation, including quantitative systems pharmacology, PKPD, bioinformatics, machine learning, clinical pharmacology, and software solutions to provide quantitative and predictive guidance to biotechnology and pharmaceutical companies to help accelerate and de-risk therapeutic research and development. Their approach employs proprietary algorithms and software to support groups worldwide in decision-making from early research through all phases of 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 therapeutic, its best-in-class parameters, competitive advantages, patients, and the best path forward into and in the clinic to increase likelihood of clinical concept and proof of mechanism, and decrease late stage attrition rates. For more information about Applied BioMath and its services and software, visit www.appliedbiomath.com.
Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.
Press contact:
Kristen Zannella
kristen.zannella@appliedbiomath.com