Current work

I’m currently bootstrapping the pre-clinical stages of developing a drug. With my savings from graduate school, I’m designing new small molecule drugs, synthesizing them, and generating in vivo safety and efficacy data in support of a disease with unmet need.

This might seem impossible. Drug developers spend millions of dollars, if not significantly more, getting a drug to clinical trials. How am I cutting these costs by several orders of magnitude?

The short answer is that most of the expensive studies that drug developers run prior to clinical trials are simply not needed. By aggressively cutting out all such unnecessary experiments, and with careful selection of which disease to treat (whose nature determines the amount of required data), it’s possible to generate the data needed for a drug to enter clinical trials at a tiny fraction of the usual cost.

If you’d like to chat about this project in more detail and/or collaborate, then please reach out to me at douglasyao2 [at] gmail.com.

Past work

Compressed Perturb-seq

I invented a new genomics assay called “compressed Perturb-seq.” This is a ten-fold cheaper version of standard “Perturb-seq,” which involves modifying the DNA of cells using CRISPR then reading out changes in the mRNA expression levels of all ~20,000 expressed genes for each cell using single-cell RNA-sequencing.
Original publication: Yao et al. 2023, Nature Biotechnology.
Editorial highlights of the technology in Nature Biotechnology and Nature Genetics.
Blog post, Twitter thread, and video (credit to Julia Bauman) that summarize the paper in non-technical terms.

Mediated expression score regression

I invented a new statistical framework and inference method to quantify how much genetic effect on a given disease “flows” through gene expression measurements in large human populations.
Original publication: Yao et al. 2020, Nature Genetics.
Technical blog post, non-technical blog post, and Twitter thread that summarize the paper.

Other

I wrote this paper on cancer genomics when I was an undergrad: Yao et al. 2019, Scientific Reports.