News

Each February, Metrum Research Group raises awareness for our fight against rare diseases. We kicked off February by highlighting a few of these rare diseases, sharing the effects of the diseases, and the hope MetrumRG's work efforts provide.

Over the course of the last decade, a variety of methods have been proposed for fitting pharmacometric models to outcomes with constrained pharmacodynamic scales. One approach is to model the residual distribution as a Beta distribution (methods that employ this strategy are referred to broadly as "Beta regression" methods.) There are several reasons why one might choose to NOT use Beta regression in pharmacometrics: 

A remote workforce inspired creativity as Metrum Research Group found ways to remain committed to our mission to fight disease through community outreach. Employee efforts over the past several months have included food and toy donations, an employer-match of employee donations to Direct Relief for COVID-19 efforts, and support for the Alzheimer’s Association and the Lupus Foundation of America. MetrumRG employees also had the opportunity to continue support for the National Society of Black Engineers by reviewing resumes and conducting mock interviews with students. 

Metrum Research Group is excited to be a founding sponsor of the recently launched Connecticut chapter of Women In Bio (WIB).  WIB is a national organization supporting diversity and inclusion for women in the life sciences. Founded in 2002, WIB’s mission is to educate, engage, and empower women from the classroom to the boardroom. The organization’s pillars are Young Women In Bio’s STEM programming, the Boardroom Ready program, The Entrepreneur Center, and WIB’s growing Mentorship community.

When the world changed in March due to the Coronavirus pandemic, and many people began to feel disconnected, MetrumRG stepped up to keep our team members engaged with each other and with our mission to improve health and defeat disease. Since we could not partake in our normal outreach efforts of collecting food, working on a Habitat for Humanity project, or even just sharing a meal together, creativity came into play. 

MetrumRG is proud to continue to be an educational resource for our community by offering open, free pharmacometrics training through a variety of mediums. The range of courses and training content, as listed here: metrumrg.com/courses/ includes a series of courses that were intended to progress from introductory through more advanced topics according to "MI" course number, e.g., MI210 (intro to pharmacometrics modeling and simulation) would be completed prior to MI212 (intermediate/advance topics), etc.

We have since added several "special topic" courses. In general, these are likely best done after completing the "MI" courses.

We also encourage individuals to periodically check our github site (github.com/metrumresearchgroup) -- we often post our workshop materials to this site.  For example, the hand-outs/slides for the two workshops we taught at ACoP10 (Fall 2019) have been posted here:

Metrum Research Group's Cellar Office OPen-EDUcation in Pharmacometrics (“COOPED UP”) webinar series will be kicking off next month! These webinars will feature a range of topics, discussed in vignette formats, to share with our community the same training and development in which our staff routinely engages.

In my first post in this series, I proposed a “starter kit” for developing a statistical argument. This “starter kit” included considerations related to both the direction of effects (“[Is] the association directionally consistent with known mechanistic accounts (e.g. based on enzymology)?”) and the magnitude of effects (“Does the association have a magnitude that is consequential in some practical sense?”). In this post, I argue that “significance language” can play a valuable role in discussing the estimated direction of effects, even if supplementary approaches are needed to address more complex questions about magnitude.

In my previous post, I proposed a “starter kit” for developing a statistical argument. An essential ingredient in this “starter kit” was the identification of the context of inquiry as being confirmatory, explanatory, or something in between. In this post, I propose several criteria for defining a confirmatory context, and I suggest principles for using the language of “statistical significance” when confirmatory contexts do not obtain.