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 AAPS 2022 PharmSci 360 occurring October 16-19, 2022 in Boston, MA.
Fei Hua, PhD, VP of Modeling & Simulation Services at Applied BioMath will present Early Feasibility Assessment of Biotherapeutics Dosing Requirements during the Rapid Fire Session: Rapid Discovery of Therapeutics: Past Experience and Computational Approaches on Monday, October 17, 2022 at 3:15 p.m. In this presentation, Dr. Hua will provide an overview of Early Feasibility Assessment (EFA) and how this approach can be applied in drug discovery to help predict clinical effective dose for biotherapeutics where pharmacokinetic (PK) or pharmacodynamic (PD) data might not be available.
Applied BioMath recently published a manuscript about the ability of EFA to make accurate predictions of clinical effective doses for nine approved biotherapeutics and the impact this approach can have on early drug discovery decisions for novel therapeutics.
"For complex therapeutics, there are many factors that can impact feasibility, which are not always straightforward or intuitive," said John Burke, PhD, Co-founder, President and CEO at Applied BioMath. "EFA can help project teams be more efficient in the early drug discovery stage by quickly making portfolio decisions, prioritizing experiments, and generating hypotheses."
In addition to the presentation, Applied BioMath will also present the following posters at the conference:
- Systematic In Silico Analysis of Clinically Tested Drugs for Reducing Amyloid-Beta Plaque Accumulation in Alzheimer's disease
- A Computational Semi-mechanistic Pharmacology Model of ATG101- a PD-L1/4-1BB Bispecific Antibody for Treatment of Solid Tumors
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.