Hannah Le, who works as a Product Manager at LatchBio, is spearheading the creation of an inclusive bioinformatics platform designed to help scientists leverage sophisticated tools for analyzing biological data. This initiative aims to propel progress in medical research and pharmaceuticals.
In the last twenty years, bioinformatics has offered crucial understanding of the fundamental processes at the molecular level of life. The advent of high-throughput sequencing techniques has turned biology into a discipline heavily reliant on data analysis, impacting areas such as customized healthcare solutions and drug creation. Nonetheless, numerous researchers still find it difficult to handle and decipher the extensive datasets produced.
Biological information exceeds the total amount of textual content, visuals, video materials, and even space-related data. Every experimental study produces huge volumes of such data, frequently necessitating significant computing resources for effective processing.
Tools similar to AlphaFold, capable of predicting protein structures within hours rather than decades, showcase the promise of artificial intelligence in bioinformatics. Nonetheless, accessing these technologies frequently necessitates specific infrastructural support, rendering them out of reach for numerous scientists. This barrier underscores the importance of developing user-friendly platforms that streamline biologists' ability to utilize computational assets.
LatchBio, a startup located in California, seeks to eliminate these technical obstacles by providing a cloud-based bioinformatics platform. This approach enables researchers to manage, work with, and examine extensive biological data sets without needing skills in DevOps or having access to costly equipment.
Hannah Le, hailing from Ho Chi Minh City, showed a keen interest early on in blending biology with technology. Academically talented, she achieved top honors as the valedictorian in the High School for the Gifted entrance examination in 2015. Continuing her education in Toronto, Canada, Hannah immersed herself in scientific investigations at the University of Toronto, where she participated in multiple research initiatives.
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Hannah Le, who leads product development at LatchBio. The photo is provided courtesy of Hannah. |
Her passion for computational biology intensified during her time at the Hospital for Sick Children, where she contributed to creating a database aimed at pinpointing uncommon genetic variations. This resource simplified the process of diagnosing genetic conditions, resulting in a paper published in Human Mutation.
Move from researcher role to product leadership position
In 2022, Hannah became LatchBio’s initial product manager. In just two years, she was promoted to Head of Product, overseeing a team of nine engineers and working closely with the go-to-market and customer success departments. Her aim is to expand LatchBio into a prominent bioinformatics tool.
Hannah cited her desire to address the difficulties encountered by biologists handling extensive genomic datasets as her reason for joining LatchBio. Despite the availability of sophisticated technologies like AlphaFold, single-cell RNA sequencing, and spatial transcriptomics, these resources frequently necessitate skills in cloud computing and GPU utilization. She aims to connect this divide by ensuring these powerful tools become available to a wider community of researchers.
Hannah stated that at LatchBio, they develop instruments which assist scientists in transforming raw data into valuable biological knowledge with maximum efficiency. The process of scientific examination can be divided into five essential stages: storing data, organizing metadata, performing computations, conducting analyses, and visualizing outcomes.
Every step comes with distinct technical hurdles like managing complex cloud infrastructures and dealing with sluggish processing speeds. To simplify this process, LatchBio consolidates various elements into one unified system: Latch Data handles expandable storage needs; Latch Registry organizes metadata efficiently; Latch Workflows automatize data handling; Latch Pods manage computation jobs; and Latch Plots facilitate visual representation of data.
Various firms have incorporated LatchBio into their processes. As an example, ElsieBio, a machine learning-focused biotech firm that was bought by GSK, expanded its computational investigations with this tool. Similarly, AtlasXOmics, which specializes in spatial epigenomics, uses LatchBio for the effective handling of extensive ATAC-seq data sets.
Hannah anticipates a change in the way biological research is carried out. Historically, researchers would develop hypotheses and then test these ideas via extensive lab work. However, with today’s advanced computational resources, they can initially examine RNA and DNA datasets, thereby fine-tuning their hypotheses prior to performing actual experiments. This method speeds up the process of discovering new drugs and boosts overall research productivity.
Although wet laboratory experiments continue to be essential, computational tools allow scientists to concentrate on the most promising research paths, thereby decreasing the time needed for significant discoveries.
With biological research becoming more data-heavy, the requirement for robust and accessible bioinformatics solutions keeps increasing. Thanks to contributors like Hannah, platforms such as LatchBio are enabling global scientists to utilize computational biology effectively without needing deep technical skills.
LatchBio is contributing to the advancement of genomic research, proteomics, and drug development by making bioinformatics tools more readily available.
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