Applied BioMath, a leader in applying mechanistic mathematical modeling, simulation, and analysis to de-risk therapeutic research and development, announced a collaboration with Checkpoint Therapeutics, Inc., for semi-mechanistic pharmacokinetic and pharmacodynamic (PK/PD) modeling in advanced metastatic solid tumors.
"Applied BioMath's modeling approach will be an important predictor of optimal dosing regimens to support potential future registration clinical trials for our immuno-oncology and targeted product candidates," said James F. Oliviero, president and CEO of Checkpoint Therapeutics. "We look forward to working with Applied BioMath as we advance our product candidates through clinical development in support of potential FDA approvals."
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. In this collaboration, Applied BioMath will leverage MADI to predict optimal dosing regimens for Checkpoint Therapeutics' product candidates based on in vitro functional, in vivo efficacy, and preclinical toxicology data, as well as Phase 1 PK data.
"Our modeling approach incorporates all relevant available data which increases the model's fidelity to the biology of the drug and disease," said John Burke, PhD, co-founder, president, and CEO of Applied BioMath. "Due to our model's loyalty to the biology, they have proven to generate highly accurate predictions as drugs progress into and through the clinic."
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.
Checkpoint Therapeutics, Inc. (Checkpoint) is a clinical-stage, immuno-oncology biopharmaceutical company focused on the acquisition, development and commercialization of novel treatments for patients with solid tumor cancers.