Systems Pharmacology

Quantitative Systems Toxicology—Taking the Cue from Aristotle

Maria Saluta

“The whole is greater than the sum of its parts” -Aristotle This quote from the great 4th century BCE Greek philosopher and scientist has become the mantra for many endeavors, sectors, organizations, and disciplines. From biology, chemistry, and physics to agriculture, engineering, and business, it is the foundation for synergy. What is the connection between […]

Read More
Topics: Systems Pharmacology

Speaking into the Ether: Challenges of the Virtual Pharma Workplace

P Bonate, S Tannenbaum

In today’s global pharma working environment, virtual interactions are sometimes more common than live exchanges. Many people work virtually through teleconferences, video conferences, instant messaging, phone calls, and emails. Through flexible schedules and working remotely, some people spend the majority of their day without seeing or hearing their colleagues. Honing your skills Pharmacometricians are like […]

Read More
Topics: PK/PD Modeling & Simulation

Using Model Reduction to Bridge the QSP-Pharmacometrics Divide

Tom Snowden

Quantitative systems pharmacology (QSP) models are generally too large to be validated or fit in a traditional sense and they can become intractable to standard methods of analysis or even to the modeler’s own intuition. Model reduction can alleviate these issues of complexity by eliminating portions of a system that have minimal effect upon the […]

Read More
Topics: Systems Pharmacology

What are Clinical Trial Outcomes Databases? How and Why You Should Use Them

Maria Saluta

Publicly available clinical trial data represents an underutilized source of information. If properly extracted and analyzed, they provide valuable information to support drug development decisions. When you think of the volumes of public information and databases that are available to determine, for example, commercial viability of a therapeutic in development, your first inclination is—“great!” But […]

Read More
Topics: Model-based Meta-analysis, PK/PD Modeling & Simulation
Learn More LinkedIn Twitter Facebook Email