Cheap But Effective: Instituting Effective Pandemic Policies Without Knowing Who’s Infected


Cheap But Effective: Instituting Effective Pandemic Policies Without Knowing Who’s Infected
Chris Rackauckas
MIT Applied Mathematics Instructor

One way to find out how many people are infected is to figure out who’s infected, but that’s working too hard! In this talk we will look into cheaper alternatives for effective real-time policy making. To this end we introduce SafeBlues, a project that simulates fake virus strands over Bluetooth and utilizes deep neural networks mixed within differential equations to accurately approximate infection statistics weeks before updated statistics are available. We then introduce COEXIST, a quarantine policy which utilizes inexpensive “useless” tests to perform accurate regional case isolation. This work is all being done as part of the Microsoft Pandemic Modeling Project, where the Julia SciML tooling has accelerated the COEXIST simulations by 36,000x … READ MORE

How Inexact Models and Scientific Machine Learning Can Guide Decision Making in Quantitative Systems Pharmacology


Pre-clinical Quantitiative Systems Pharmacology (QSP) is about trying to understand how a drug target effects an outcome. If I effect this part of the biological pathways, how will it induce toxicity? Will it be effective?

Recently I have been pulling in a lot of technical collegues to help with the development of next generation QSP tooling. Without a background in biological modeling, I found it difficult to explain the "how" and "why" of pharmacological modeling. Why is it differential equations, and where do these "massively expensive global optimization" runs come from? What kinds of problems can you solve with such models when you know that they are only approximate?

To solve these questions, I took a step back and tried to explain a decision making scenario with a simple model, to showcase how playing with a model can allow one to distinguish … READ MORE

PuMaS.jl: Pharmaceutical Modeling and Simulation Engine


August 13 2018 in Biology, Julia, Programming | Tags: | Author: Christopher Rackauckas

Here is an introduction to a pharmaceutical modeling project which I will be releasing in the near future. More details to come.

Simulation and Control of Biological Stochasticity


Yesterday I defended my PhD thesis entitled “Simulation and Control of Biological Stochasticity”. Here’s the recording: