Claudia Zhang ’24

Acuimmune, Los Angeles, CA

For eight weeks, I worked for the immunology research startup Acuimmune in Los Angeles. This startup specializes in bioinformatics and proteomics and work regarding vaccine development. I was drawn to Acuimmune’s work for several reasons: bioinformatics incorporates machine learning and computer science—a field which I have little experience in but am interested in exploring; the ability to conduct research remotely allows for a larger team to work despite Covid policies; and working for a startup is very different from the academia research I am used to.

Preparing cells for a plate map under
the hood.

During my internship at Acuimmune, I worked on two projects: a modeling project that predicts patients’ immune responses to various compounds and a project that worked to develop a personalized lung cancer vaccine. The modeling project was more data-driven: much of my time was spent gathering, compiling, and organizing data from previous experiments and relevant literature reviews. For the remote portion of the vaccine project, I used the Immune Epitope Database (IEDB) to identify antigenic portions of cancer proteins and evaluated their responses using data from various in vitro and in vivo assays. The most effective epitopes were then developed into a potential vaccine and prepared for in vitro testing at the wet lab in California.

I learned several lab techniques, including how to maintain cancerous cell cultures, peripheral blood mononuclear cell (PBMC) extraction from donated blood, cell plating, and Luminex assay preparation. Daily work in the lab consisted of feeding THP-1 (human monocytic cells), counting cells in each culture flask, designing plate maps for future experiments, and collecting cell supernatants at specified time intervals for ongoing experiments. To collect data for the modeling project and lung cancer, THP-1 and PBMC cells were challenged with various compounds and their supernatants (with relevant cytokines) were collected at different time intervals. The cells were challenged with the bioinformatics designed lung cancer epitope and whole carcinoembryonic antigen (CEA) protein, and cells’ responses were then measured using a Luminex assay and the data was collected.

All-in-all, my internship at Acuimmune taught me valuable dry and wet lab skills and expanded my knowledge of immunology. Bioinformatics was an incredibly interesting field to delve into: traditional vaccine design involves sequencing the entire genome of the target organism and using a method of trial-and-error to determine effective epitopes. However, bioinformatics circumvents this—predictive technology is combined with traditional lab techniques, greatly increasing efficiency. In a time where Covid-19 continues to be a global issue, techniques that streamline vaccine development are essential.

I would like to thank the generous support that Williams has provided me, in particular, the ’68 Center for Career Exploration and the Petersen Family. Your support has allowed me to work alongside brilliant mentors and peers and experience a new type of research. Through my internship, I was able to meet many wonderful mentors and peers who were all dedicated to their work and eager to teach others. The various experiences I had at Acuimmune are all incredibly valuable and will certainly help me in the future, whether I end up working in academia or industry.