About This Project

We have been making open-source PCR machines for decade. 1st generation thermal cycler NinjaPCR was released in 2013. Super fast PCR machines (video1, video2) in 2016 and 2017. During Covid pandemic 2020-2023, we developed $220 qNinja: 2nd generation qPCR (RT-PCR) and $45 qLAMP. Now let us start 3rd generation dNinja, Digital PCR (dPCR). dPCR is 1,000 times more sensitive than qPCR and essential to liquid biopsy for noncomunicable diseases that caused 74% of global death in 2019.

Ask the Scientists

What is the context of this research?

PCR tests are far more sensitive than antigen or -body tests, and are the only way to detect disease before becoming infectious. qPCR and dPCR make millions of fluorescent copies of target DNA which allow optical sensors to detect positive or negative results in real time. Due to their simplicity, qPCR and dPCR are mainly used for PCR tests and we open-sourced qPCR as $220 qNinja. By splitting the solution into tens of thousands of micro spaces before qPCR, dPCR is 1,000 times more sensitive than qPCR to mutation. That is necessary for liquid biopsy to detect DNA of minor mutations like cancer released from the tumor into the bloodstream. Patients can be monitored by picking 10-20ml (0.3-0.6oz) of blood without getting tissue surgically.

What is the significance of this project?

This is the world's first challenge to make open-source dPCR. dNinja will be most user-friendly and drastically cheaper than any other dPCR machines in the market. Almost everyone has no access to qPCR nor dPCR simply because it is pricy as $20k-200k and skill is needed to use it. qPCR can detect most of infectious diseases but 74% of global death comes from noncomunicable diseases. Liquid biopsy covers all of top 7 causes (heart disease, stroke, pulmonary disease, cancer, Alzheimer, diabetes, kidney disease) and dPCR is essential tool for them.

What are the goals of the project?

Our goal is to make well-documented open-source dPCR as we did with PCR and qPCR. As described in Methods and Lab Note, we start assembling a microscope, XY stage, and custom solder stencil to count positive/negative colors of qPCR solution in micro holes using deep learning model trained to detect and track holes with YOLOv8 and ByteTrack. Then we evaluate the device by calculating Poisson corrected concentration of custom standard DNA oligos with known concentration. A DIY guide will be written to make from scratch. dNinja kits and hard-to-make parts will be distributed at our online store with a detailed assembly guide.

As an extended goal, we will make a commercial model of dNinja to get FDA license for medical devices as we are working with qPCR and qLAMP.