Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform

View ORCID ProfileChris Rackauckas, Yingbo Ma, Andreas Noack, Vaibhav Dixit, Patrick Kofod Mogensen, Simon Byrne, Shubham Maddhashiya, José Bayoán Santiago Calderón, Joakim Nyberg, Jogarao V.S. Gobburu, Vijay Ivaturi
doi: https://doi.org/10.1101/2020.11.28.402297
Chris Rackauckas
1
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Chris Rackauckas
  • For correspondence: crackauc@mit.edu crackauc@mit.edu
Yingbo Ma
2Julia Computing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andreas Noack
2Julia Computing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vaibhav Dixit
2Julia Computing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Patrick Kofod Mogensen
2Julia Computing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Simon Byrne
3Caltech
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shubham Maddhashiya
2Julia Computing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
José Bayoán Santiago Calderón
4Biocomplexity Institute & Initiative, University of Virginia, Pumas-AI, Inc.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Joakim Nyberg
5University of Uppsala
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jogarao V.S. Gobburu
6School of Pharmacy, University of Maryland, Baltimore, Pumas-AI, Inc.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vijay Ivaturi
6School of Pharmacy, University of Maryland, Baltimore, Pumas-AI, Inc.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Pharmacometric modeling establishes causal quantitative relationship between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. Recent technological advances rendered collecting real-time and detailed data easy. However, the pharmacometric tools have not been designed to handle heterogeneous, big data and complex models. The estimation methods are outdated to solve modern healthcare challenges. We set out to design a platform that facilitates domain specific modeling and its integration with modern analytics to foster innovation and readiness to data deluge in healthcare.

New specialized estimation methodologies have been developed that allow dramatic performance advances in areas that have not seen major improvements in decades. New ODE solver algorithms, such as coefficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to up to 4x performance improvements across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques and further specialize the solution process on the individual systems, allowing statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME parameter estimation see run times halved while retaining the same accuracy. Meanwhile in areas with less prior optimization of software, like optimal experimental design, we see orders of magnitude performance enhancements. Together we show a fast and modern domain specific modeling framework which lays a platform for innovation via upcoming integrations with modern analytics.

Competing Interest Statement

Pumas is a proprietary software developed by Pumas-AI Inc. Authors Rackauckas, Ma, Noack, Dixit, Mogensen, Byrne, Maddhashiya, Calderon, Nyberg, Gobburu, and Ivaturi all are or have been affiliated with Pumas-AI Inc. in the past 36 months.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted November 30, 2020.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform
Chris Rackauckas, Yingbo Ma, Andreas Noack, Vaibhav Dixit, Patrick Kofod Mogensen, Simon Byrne, Shubham Maddhashiya, José Bayoán Santiago Calderón, Joakim Nyberg, Jogarao V.S. Gobburu, Vijay Ivaturi
bioRxiv 2020.11.28.402297; doi: https://doi.org/10.1101/2020.11.28.402297
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform
Chris Rackauckas, Yingbo Ma, Andreas Noack, Vaibhav Dixit, Patrick Kofod Mogensen, Simon Byrne, Shubham Maddhashiya, José Bayoán Santiago Calderón, Joakim Nyberg, Jogarao V.S. Gobburu, Vijay Ivaturi
bioRxiv 2020.11.28.402297; doi: https://doi.org/10.1101/2020.11.28.402297

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Pharmacology and Toxicology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4383)
  • Biochemistry (9599)
  • Bioengineering (7094)
  • Bioinformatics (24865)
  • Biophysics (12615)
  • Cancer Biology (9958)
  • Cell Biology (14354)
  • Clinical Trials (138)
  • Developmental Biology (7950)
  • Ecology (12107)
  • Epidemiology (2067)
  • Evolutionary Biology (15989)
  • Genetics (10926)
  • Genomics (14743)
  • Immunology (9870)
  • Microbiology (23676)
  • Molecular Biology (9485)
  • Neuroscience (50872)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2683)
  • Physiology (4016)
  • Plant Biology (8657)
  • Scientific Communication and Education (1509)
  • Synthetic Biology (2397)
  • Systems Biology (6436)
  • Zoology (1346)