Applied BioMath, LLC and Speid & Associates, Inc. Present Webinar on How a Good Regulatory and Computational Strategy Helps Avoid Common Pitfalls

CONCORD, Mass., March 5, 2018 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling, simulation, and analysis to de-risk drug research and development, today announced their collaboration with Speid & Associates, Inc. for their upcoming webinar titled "How a Good Regulatory and Computational Strategy Helps Avoid Common Pitfalls." The webinar will be held Tuesday, March 6, 2018 at 2:00 p.m. ET / 11:00 a.m. PT.

The therapeutic development process is progressively challenging. In response, there are increasingly new specialties and services in drug research and development that biotechnology and pharmaceutical companies can utilize to maximize their chances of success. These services assist with essential components to drug development, such as target product profiles (TPP) and regulatory strategies, which many companies are failing or leaving out of development programs altogether.

In this webinar, targeted toward scientists and project leaders in research and development, Dr. Lorna Speid will discuss how to develop a regulatory strategy. Dr. Speid has extensive experience working with small and large pharmaceutical companies, with an emphasis on global and international regulatory affairs, assisting companies at various stages of the drug development process. Her company, Speid & Associates, provides a full complement of services required for new chemical entities, 505(b)(2) applications, diagnostics, devices and other types of applications.

Dr. John M. Burke will parallel the examples presented by Dr. Speid with case studies on how Model-Aided Drug Invention can support and guide such a regulatory strategy. Model-Aided Drug Invention (MADI) is a mathematical modeling and engineering approach to translational medicine that aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. MADI de-risks projects, accelerates the development of best-in-class therapeutics, and reduces late stage attrition rates. This results in helping the industry save money, accelerate timelines, and make better therapeutics, ultimately improving patients' lives.

"Good regulatory and computational strategies are critical to efficiently and effectively moving drugs to the clinic, yet many projects progress without one or both," said John Burke, PhD, Co-Founder, President and CEO of Applied BioMath. "In this webinar, we will highlight the key steps to implementing solid strategies and the benefits to be gained."

Applied BioMath's services are used worldwide by pharmaceutical and biotechnology companies to better understand the desired TPP for an indication of interest, determine best-in-class properties of a clinical candidate, and identify key differentiators from competitors.

To learn more and to register for this webinar, visit www.appliedbiomath.com/webinar.

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 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

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SOURCE Applied BioMath, LLC