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 their participation at the 38th Annual Meeting of the Society for Immunotherapy of Cancer (SITC) occurring November 1-5, 2023 in San Diego, CA.
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| [30-October-2023] |
| CONCORD, Mass., Oct. 30, 2023 /PRNewswire/ -- 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 their participation at the 38th Annual Meeting of the Society for Immunotherapy of Cancer (SITC) occurring November 1-5, 2023 in San Diego, CA.
During the conference, Fei Hua, PhD, Vice President of Modeling and Simulation Services at Applied BioMath, will present the poster entitled, “Overcoming the dose-response prediction limitation from bench to clinic for T-cell engagers: Using Quantitative Systems Pharmacology (QSP) modeling in the development of CDR404 for solid tumors.” While T-cell Engagers (TCEs) offer a potentially very potent approach to treat cancer, they also have complex relationships between binding potency, exposure, and efficacy. These complex relationships bring challenges to drug discovery and development such as identifying optimal Kd for the drug candidate, predicting efficacious doses, and selecting dosing regimens for clinical study. Applied BioMath’s poster describes a QSP model developed to support the first-in-human trial design for CDR404, a highly potent and highly specific antibody-based T-cell engager that binds bivalently to a MAGE-A4 peptide displayed on HLA-A*02:01 on cancer cells and monovalently to CD3 on T-cells. The QSP model will become an integrated part of the clinical development program and can be updated with emerging clinical data to facilitate discovery of a safe and therapeutic dose range for CDR404. “For therapeutics with complex mechanisms of action (MoA), QSP modeling can be integral for progressing through the R&D pipeline,” said John Burke, PhD, Co-founder, President and CEO. “Particularly for TCEs, we’ve had experience where QSP modeling has tested target feasibility, optimized molecule design, predicted therapeutic index, and guided clinical trial design.” To learn more about Applied BioMath, visit www.appliedbiomath.com. 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:
SOURCE Applied BioMath, LLC |
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