IPIRA Startups

TL Revolution delivers the next generation of data analysis tools with superior precision, reliability, and ease of use to pharma, FDA, and beyond. Data analysis drives mission-critical decisions, but hasn’t kept up with proven advances in statistics. Biased and imprecise analyses lead to wrong conclusions and significant loss of time and money. The company's software encapsulates expertise in super learning and TMLE to proved state-of-the-art machine learning and robust causal inference.

The company was co-founded by UC Berkeley Professor in Biostatistics and...

Azalea Therapeutics is an early-stage biotech startup on a mission to revolutionize genomic medicines. By designing vehicles that enable cell-specific delivery inside the body, the company aims to unlock precision therapeutics for genetic diseases and unleash the promise of cellular-based therapies. The company's co-founders include Jennifer Doudna, a Nobel Laureate in Chemistry and UC Berkeley Professor of Biochemistry, Biophysics and Structural Biology, with Postdocs and a PhD student from her lab: CEO/CSO Jennifer Hamilton (PhD, 2018-2023); Founding Scientist Connor...

Pow.Bio provides intelligent fermentation services for industrial and synthetic biology. The company's services combine continuous fermentation with advanced control methodology to quickly optimize the fermentation process and deliver high yields at low cost. The scale runs from 1-100 liter capacity for bacteria, yeast, and filamentous fungi. The first-of-its-kind fermentation technology solves the capacity problem of bioproduction with high-performance continuous fermentation that can run for hundreds of hours. This holy grail of biology offers an order of magnitude step...

The next decade is going to see a biotech revolution fueled by three technologies: ability to read DNA (sequencing), ability to write DNA (synthesis), and computational systems that predict what DNA to read and write. With sequencing and synthesis being mainstream now, 20n provides the computational systems that predict DNA design for novel industrial biotech and health applications. At 20n, we are taking a fresh look at turning biological data into information. We approach it as a big data learning problem, and bring to bear techniques from machine learning, distributed...