Eryney Marrogi

I got an early start in science as a high school student working with Miriam Poirier and Jing Huang at the National Cancer Institute. In addition to falling in love with biology and medicine, I got to contribute to basic biology projects focused on determining the carcinogenic effects of the HIV drug AZT, and later on specific genes involved in osteosarcoma.

• Perinatal exposure of patas monkeys to antiretroviral nucleoside reverse-transcriptase inhibitors induces genotoxicity persistent for up to 3 years of age. The Journal of Infectious Diseases, 2013.
• A RUNX2-mediated epigenetic regulation of the survival of p53 defective cancer cells. PLOS Genetics, 2016.
• cFOS-SOX9 axis reprograms bone marrow-derived mesenchymal stem cells into chondroblastic osteosarcoma. Stem Cell Reports, 2017.

As an undergraduate student at Virginia Tech, I had the privilege of working in George Church’s lab on engineering mosquitoes with gene drives to eradicate malaria. The work ultimately did not pan out in achieving our goal, a sustainable gene drive that can continuously propagate, but we did build a population suppression system.

• CRISPR-mediated germline mutagenesis for genetic sterilization of Anopheles gambiae males. Scientific Reports, 2024.
• Engineering gene drive docking sites in a haplolethal locus in Anopheles gambiae. Scientific Reports, 2025.

As part of this project, I also worked alongside mosquito expert Flaminia Catteruccia at Harvard. It’s here that I ironically got my first exposure to machine learning by building an image detection model. I additionally contributed to work investigating basic mosquito biology.

• OocystMeter, a machine-learning algorithm to count and measure Plasmodium oocysts, reveals clustering patterns in the Anopheles midgut. bioRxiv, 2025 (preprint).
• A mating-induced reproductive gene promotes Anopheles tolerance to Plasmodium falciparum infection. PLOS Pathogens, 2020.

Continuous monitoring devices are necessary if we are to advance the current goals of AI in health and biology. The continuous glucose monitor (CGM) exists because of a natural enzyme we could ingeniously apply to an engineered system, but unfortunately nothing similar exists for other compounds. I worked at Caltech with Anand Muthuswamy under the advising of Henry Lester on applying frontier protein language and structure models towards the design of novel continuous monitors beyond the glucose monitor.

This work was part of a larger effort to create a new Focused Research Organization oriented on making new wearable devices.

Papers in process.