Week 3 HW: AUTOMATION

1) Published paper

Villanueva-Cañas et al., PLOS ONE (2021) built a multi-station SARS-CoV-2 RT-qPCR testing workflow using Opentrons OT-2 robots. The core novelty is a reusable software + station architecture that makes a complex diagnostic pipeline programmable, modular, and reproducible across setups.

2) Final project automation plan

Project: “Living Ice Cream”

A temperature-responsive dessert system with:

  • Slow “breathing” surface behavior (controlled micro-gas generation)
  • Visual shift (color / glow) near melt-adjacent temperatures

Why Ginkgo automation

I’m using Ginkgo’s autonomous / cloud-lab framing as an iteration engine for high-throughput DOE: stable automation backbone, fast experimental loops, and standardized readouts for repeated screening rounds.

cover cover

What I will automate

A) “Breathing” kinetics screening (high-throughput DOE)

Goal: Find enzyme/substrate + formulation conditions that yield slow, non-violent micro-gas behavior around ~15–25°C.

DOE axes (example)

  • enzyme concentration
  • substrate concentration
  • buffer / pH
  • capsule matrix composition
  • temperature + time

Minimal pseudocode

for cond in DOE_grid:
    dispense(cond.reagents, well)
    incubate(temp=cond.temp, time=cond.time)
    readout = measure_optical_bubble_proxy_or_pressure(well)
    log(readout, cond)