Proposal for an Open Software Development Life Cycle

Posted by Marc Gastonguay on Sep 16, 2019 2:31:04 PM

The confluence of several factors, including: the growing recognition of the value of quantitative approaches to decision-making in drug development, advancements in numerical methods and analytics, and democratization of modern software engineering, has led to the emergence of multiple pharmacometrics-related software tools, both commercially and publicly licensed. A rigorously managed, high-quality, software development practice is central to reliable and reproducible scientific application and regulatory compliance for these tools. Professional software development best practices should typically be outlined in a Software Development Life Cycle (SDLC) policy or procedure, but the extent of guidance, consistency of methods, adherence to procedures, completeness of quality documentation, and execution rigor vary greatly across software development organizations or teams.

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Topics: Methodology, Tools, and Computation, Open Science

ISoP Regional QSP Day 2019

Posted by Marc Gastonguay on Jul 17, 2019 11:41:15 AM

Metrum Research Group scientists participated in the first International Society of Pharmacometrics (ISoP) Regional Quantitative Systems Pharmacology (QSP) Day on July 16, 2019. 

The meeting, which included podium presentations, a poster session, and opportunities for discussion and networking, highlighted several examples of the application of QSP methods in drug development. Particularly notable topics included: the integration of transcriptomics and systems pharmacology models, challenges with calibration of virtual patients in QSP models, and the use of QSP as a scaffold for bridging from well studied therapeutic indications to related but somewhat less understood indications.

Madeleine Gastonguay, of MetrumRG and University of Connecticut, presented the poster "Development of an open-source physiologically-based pharmacokinetic model to predict maternal-fetal exposures of CYP450-metabolized drugs". The open science philosophy, exemplified in this work, resonated with attendees and was also highlighted by several of the conference speakers.

Special thanks goes to the meeting organizers, the ISoP QSP Special Interest Group (ISoP QSP SIG), and hosts, Bristol-Myers Squibb (BMS), for a well organized event and an energizing, thought-provoking day.

Pictures from the event below.

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Topics: Methodology, Tools, and Computation, Open Science

Torsten: Stan Functions for Pharmacometrics Applications

Posted by William R. Gillespie on Aug 13, 2018 9:57:48 AM

Bill Gillespie, Ph.D., gave a presentation on "Torsten: Stan functions for pharmacometrics applications" at the "Stan for Phamacometrics" event in Paris, France on July 24, 2018. You can view the presentation here.

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Topics: Methodology, Tools, and Computation

Bayesian Data Analysis Using Stan/Torsten for Pharmacometric Applications

Posted by William R. Gillespie on May 17, 2018 4:37:37 PM

William Gillespie, Ph.D. presented at the Midwest Biopharmaceutical Statistics Workshop on May 15, 2018. See presentation here

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Topics: Methodology, Tools, and Computation, Bayesian

Modeling methods for analyzing tumor dynamic data from basket trials

Posted by Alanna S. Ocampo-Pelland on Oct 18, 2017 9:01:02 AM

Poster presented by Alanna S. Ocampo-Pelland and Jonathan L. French at ACoP8. See the poster here

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Topics: Methodology, Tools, and Computation, Oncology, Open Science

Cloud Computing at ACoP

Posted by Tim Bergsma on May 31, 2017 3:54:23 PM

by Tim Bergsma

Already widely received in the finance community, cloud computing is gaining acceptance in the pharmaceutical industry as well. At this year’s American Conference on Pharmacometrics, Metrum Research Group staff presented a poster on the topic, and helped lead a related panel discussion.

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Topics: Methodology, Tools, and Computation

Adding Sinew to Roxygen Skeletons

Posted by Yoni Sidi on May 31, 2017 3:52:45 PM

For new developers, getting a package ready for building and submitting to CRAN is an expletive-filled, head-scratching experience to say the least. Trying to figure out the basics of what goes in depends and what goes in imports is a lost afternoon most of us would like back. Once that is understood, filling in relevant information to each field is a mundane task even for a well polished package developer. The out-of-the-box roxygen skeleton supplied by RStudio gives the bare bones road map of what should be part of function documentation:

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Topics: Methodology, Tools, and Computation

PaSiPhIC Conference

Posted by Jonathan French on May 31, 2017 3:51:13 PM

Recently, I was asked to speak at this year’s PaSiPhIC conference about different approaches to meta-analysis. As I was putting together my presentation, I began to wonder: How can we best leverage traditional meta-analysis methods in a model-based drug development framework?

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Topics: Methodology, Tools, and Computation

Metrum Research Group Presents at Bio-IT World 2012

Posted by Jeffrey Hane on May 31, 2017 3:47:52 PM
Jeff Hane of MetrumRG and Adam Kraut of The BioTeam presented details of MetrumRG’s ground-breaking infrastructure in the cloud at Bio-IT World 2012 (Boston, MA). The talk, ‘Building A Scalable Pharmacometrics Platform in the Cloud’, was delivered in the Cloud Computing Track on April 25. Grab your copy of the slide deck today.
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Topics: Methodology, Tools, and Computation, Metrum News

What Decisions Benefit from Model-Based Meta-Analysis (MBMA)?

Posted by Jeffrey Hane on May 31, 2017 3:47:13 PM

The primary rationale for model-based meta-analysis (MBMA) is to improve decision-making by better leveraging prior information from multiple sources. Decision-makers generally attempt to consider such prior information, but it is usually done in a relatively qualitative manner, and each individual decision-maker is usually aware of only a subset of the prior information. MBMA seeks to make the process more quantitative and comprehensive. The process and results of MBMA may be made visible (aka transparent) to the decision-makers. The end result is that the decision-makers are better informed, and they can contribute their knowledge to the modeling process leading to better, more trusted models and model-based inferences.

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Topics: Methodology, Tools, and Computation

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