is led by world class pioneers at the intersection of data science and the life sciences, with extensive experience in applying machine learning to a range of biological problems and data sets.
As Vice President of High-throughput Biology Aj is responsible for producing high-quality data sets to use in for machine learning-based target and drug discovery. He leads insitro’s wet lab activities (bio-data factory) which consists of functional genomic, disease modeling, automation/process engineering and proteomic teams.
Ajamete has spent over 28 years in both industry and academia, working in the areas of proteomics, genomics, and stem cell biology. Before joining insitro, Aj led the early target discovery team at Novartis Institutes for Biomedical Research in the Neuroscience unit. His team efforts have led to the discovery of multiple new disease targets and the development of better predictive preclinical models. He conducted his postdoc with Dr. Randy Moon at University of Washington/Howard Hughes Medical Institute on Wnt-signaling. While in Randy’s lab, he conducted one of the first ever genome-wide RNAi screens and studied the role of Wnt-signaling in human disease and stem cell biology. He did his graduate work at University of Wisconsin-Madison in Dr. Bill Sugden’s lab where he studied virology, immunology, and oncology.
In his free time, Aj enjoys traveling, kayaking, sailing, biking, making whiskey and most of all his family.
DRUG-seq: A Miniaturized High-Throughput Transcriptome Profiling Platform for Drug Discovery. Ye C, Ho DJ, Neri M, Yang C, Kulkarni T, Randhawa R, Henault M, Mostacci N, Farmer P, Renner S, Ihry R, Mansur L, Gubser Keller C, McAllister G, Hild M, Jenkins J, and Kaykas A. In Press, Sept; 2018 Nat. Comm.
p53 inhibits CRISPR-Cas9 engineering in human pluripotent stem cells. Ihry RJ, Worringer KA, Salick MR, Frias E, Ho D, Theriault K, Kommineni S, Chen J, Sondey M, Ye C, Randhawa R, Kulkarni T, Yang Z, McAllister G, Russ C, Reece-Hoyes J, Forrester W, Hoffman GR, Dolmetsch R, Kaykas A. Nat Med. 2018 Jul;24(7):939-946.
A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development. Yao Z, Mich JK, Ku S, Menon V, Krostag AR, Martinez RA, Furchtgott L, Mulholland H, Bort S, Fuqua MA, Gregor BW, Hodge RD, Jayabalu A, May RC, Melton S, Nelson AM, Ngo NK, Shapovalova NV, Shehata SI, Smith MW, Tait LJ, Thompson CL, Thomsen ER, Ye C, Glass IA, Kaykas A, Yao S, Phillips JW, Grimley JS, Levi BP, Wang Y, Ramanathan S. Cell Stem Cell. 2017 Jan 5;20(1)
Genetic Ablation of AXL Does Not Protect Human Neural Progenitor Cells and Cerebral Organoids from Zika Virus Infection. Wells MF, Salick MR, Wiskow O, Ho DJ, Worringer KA, Ihry RJ, Kommineni S, Bilican B, Klim JR, Hill EJ, Kane LT, Ye C, Kaykas A*, Eggan K.* Cell Stem Cell. 2016 Dec 1;19(6):703-708. *Co-corresponding author
Functional genomic analysis of the Wnt-wingless signaling pathway. DasGupta R*, Kaykas A*, Moon RT, Perrimon N. Science. 2005 May 6;308(5723):826-33. *Co-first authors
Albert utilizes different automation technologies to ensure quality data generation from many of insitro’s scientific processes. This includes integrating specific assays onto automation, onboarding tools for efficient execution, and maintaining an environment for seamless research operations.
After graduating with his B.S. in Biochemistry and Philosophy from Wisconsin-Madison he started at Abbott Laboratories as an Associate Scientist focusing on instrument and assay validation for their diagnostics platform. After working in a big company environment, he joined Transcriptic, where he helped w/ assay integration and automation.
In his free time, Albert enjoys watching the NBA and trying out different banana bread recipes.
Eric utilizes microscopy to extract quantitative information from cells. His research is focused on developing in situ genomics technologies through a combination of bioengineering, optics, and image analysis. As a member of the functional genomics team, Eric is dedicated to delivering novel assays and datasets to further insitro’s drug discovery pipeline.
Eric earned his Ph.D. in biophysics from Caltech where he developed a new generation of microscopes capable of capturing transcriptomic information from human cells and tissue. Following graduation he transitioned to a postdoc in bioengineering at UCSF/Stanford where he developed synthetic biology tools using CRISPR screens.
In his free time Eric enjoys bicycles, hiking, and spending time with his family.
As the Head of Process Engineering, John is responsible for leading the development and deployment of lab automation for high-throughput, effective production of high-quality data sets to use in machine learning. John’s team also will focus on building out the tools and capabilities for implementing operational excellence across all of insitro’s laboratories.
Prior to joining insitro, John spent the last 20 years designing, building and managing automation solutions across biotech and pharmaceutical industries. He has significant expertise with early-stage startups, helping to develop, implement and support automation technologies as they scale. John has an M.Eng. in Systems Engineering from Penn State University.
He is an avid outdoor enthusiast who enjoys backpacking, road biking, landscape photography, and travel.
As Disease Modeling Scientist, Max is focused on using pluripotent stem cells, CRISPR, and a range of differentiation and transcriptomics approaches to model human diseases in in vitro platforms. Max and his team will model devastating human diseases using the relevant cell types, and will produce high-throughput / high-quality imaging and transcriptomic datasets for insitro’s machine learning platform to mine for phenotypes.
Max is an engineer by training, gaining a B.S. in Engineering Mechanics and Astronautics and a Ph.D. from the Materials Science Program of the University of Wisconsin – Madison. By combining dry lab engineering with wet lab disease modeling, Max has frequently used the newest technologies to gain insights into the mechanisms by which various genetic diseases affect human health. Max spent his time in graduate school developing micropatterned differentiation techniques and computational analysis tools to improve stem-cell-based heart modeling methods. Prior to joining insitro, Max spent 4 years as a postdoc in the Novartis Neuroscience department, where he developed single cell characterization platforms to discover disease mechanisms of tuberous sclerosis, uncovered novel mechanisms of disease progression in certain dementias, and conducted genome-wide screens to elucidate potential Zika virus receptors.
Max’s free time is spent with his border collie, Coda, along with playing piano/guitar, and poorly-but-enthusiastically playing various sports.
Owen spent four and a half years as a member of Dr. Jonathan Weissman’s Lab at UCSF, where he supported the development RNAi-based and CRISPR-based mammalian genome-scale functional genomics screening platforms, successfully identifying new targets for grants and publications. He cloned and maintained ultracomplex shRNA/sgRNA screening libraries as well as generated stable cell lines with gene repression or activation. Additionally, he conducted numerous functional genomic screens in cancer cell lines challenged by various toxins, drugs, and chemicals.
After his time at UCSF, he spent two and a half years at Driver, where he developed NGS assays and validated tumor-normal and cfDNA manual assays under CAP and CLIA guidelines. He also had fun acquiring a new set of skills in converting these manual assays into fully automated processes.
As part of the Functional Genomics team at insitro, Tina generates libraries for screening using the latest molecular biology techniques.
Tina spent the last thirteen years working in all facets of yeast strain engineering, first at Amyris and then at Lygos and Calico. She received a B.S. in Chemical Engineering from UC-Berkeley and was an undergraduate researcher in the Keasling lab.
Tina used to play ice hockey but now focuses her energy into knitting or crocheting toys for her three kids.