
Peering Inside the Immune Response for Novel Antibodies with Nima Emami
06/08/22 • 54 min
Episode Summary:
Antibodies are one of the greatest tools we have in our therapeutic arsenal and have transformed the way we treat cancer and autoimmunity. But we still largely develop these drugs using guess and check methods, massively slowing down the process. However, our own B cells are constantly making new antibodies against the pathogens and diseases we routinely suffer from, creating a gold mine of drugs floating around inside all of us. We just need to find them! Recognizing this challenge, Nima and his team at Avail Bio have leveraged their deep experience in computation and systems immunology to build a platform that massively screens the antibody repertoire of patients who have successfully cleared a disease. With it, they find ready-to-deploy antibody drugs that could treat everything from cancer to autoimmunity and even reprogram our own immune system!
Search Keywords: fifty years, bio, translation, antibodies, B cells, cancer, autoimmunity, immunology, avail bio, nima emami
Episode Notes:
About the Guest
Nima Emami is the CEO & co-founder of Avail Bio. He received a PhD in Bioinformatics from the UCSF Cancer Center, and studied Bioengineering, Electrical Engineering and Computer Science at UC Berkeley.
Key Takeaways
The immune system contains a massive diversity of antibodies that hold clues on how to fight disease. Avail has developed a platform to discover and develop these antibodies for cancer and autoimmune disease.
Companies that spin out of universities can pair with accelerators early on to both raise funding and make progress with a small amount of capital. The most challenging part of pulling IP out of a university is speed. Public universities that generate many spinouts are often overwhelmed with the amount of inventions disclosed concurrently, which lengthens the time required for tech transfer.
Avail’s platform combines synbio, machine learning and genomics to both discover and validate targets, and ultimately translate those targets into drugs. Failure of clinical stage programs in cancer trials can be traced back to the failure of mouse models to faithfully recapitulate the cancer biology or the immunobiology that we see in humans.
The future that Avail hopes to create is one where drugs developed using their platform will reach patients, thereby changing the drug discovery paradigm to be more data-driven.
Impact
The platform that Avail is building peers inside the human immune response to find and develop novel antibodies to cure cancer and autoimmune disease.
Company: Avail Bio
Episode Summary:
Antibodies are one of the greatest tools we have in our therapeutic arsenal and have transformed the way we treat cancer and autoimmunity. But we still largely develop these drugs using guess and check methods, massively slowing down the process. However, our own B cells are constantly making new antibodies against the pathogens and diseases we routinely suffer from, creating a gold mine of drugs floating around inside all of us. We just need to find them! Recognizing this challenge, Nima and his team at Avail Bio have leveraged their deep experience in computation and systems immunology to build a platform that massively screens the antibody repertoire of patients who have successfully cleared a disease. With it, they find ready-to-deploy antibody drugs that could treat everything from cancer to autoimmunity and even reprogram our own immune system!
Search Keywords: fifty years, bio, translation, antibodies, B cells, cancer, autoimmunity, immunology, avail bio, nima emami
Episode Notes:
About the Guest
Nima Emami is the CEO & co-founder of Avail Bio. He received a PhD in Bioinformatics from the UCSF Cancer Center, and studied Bioengineering, Electrical Engineering and Computer Science at UC Berkeley.
Key Takeaways
The immune system contains a massive diversity of antibodies that hold clues on how to fight disease. Avail has developed a platform to discover and develop these antibodies for cancer and autoimmune disease.
Companies that spin out of universities can pair with accelerators early on to both raise funding and make progress with a small amount of capital. The most challenging part of pulling IP out of a university is speed. Public universities that generate many spinouts are often overwhelmed with the amount of inventions disclosed concurrently, which lengthens the time required for tech transfer.
Avail’s platform combines synbio, machine learning and genomics to both discover and validate targets, and ultimately translate those targets into drugs. Failure of clinical stage programs in cancer trials can be traced back to the failure of mouse models to faithfully recapitulate the cancer biology or the immunobiology that we see in humans.
The future that Avail hopes to create is one where drugs developed using their platform will reach patients, thereby changing the drug discovery paradigm to be more data-driven.
Impact
The platform that Avail is building peers inside the human immune response to find and develop novel antibodies to cure cancer and autoimmune disease.
Company: Avail Bio
Previous Episode

Powering the Biocomputing Revolution with LatchBio
Episode Summary
Imagine if every graphics design company built its own version of Photoshop in-house. That’s exactly what’s happening today in biology research. Ten-fold increases in data every two years are forcing every biology team to build out their own, in-house bioinformatics stack to store, clean, pipe, and manage the massive volumes of data generated by their experiments. All that work has to happen even before teams can analyze the results! Recognizing this obstacle to high-throughput biology research, Alfredo, Kenny and Kyle built LatchBio to bring the modern computing stack to biotech. By uniting wet lab experiments with dry lab processing, storage, and analyses, LatchBio is democratizing access to top-notch bioinformatics and empowering biologists to derive relevant insights from their data that can move our world forward. Tune in to learn more about their journey from Berkeley dropouts to entrepreneurs building no-code tools to power the biocomputing revolution.
About the Team
- Alfredo Andere, CEO, was born in Mexico City and raised in Guadalajara, Mexico. He majored in Computer Science and Electrical Engineering and minored in Math at UC Berkeley before dropping out to co-found LatchBio.
- Kyle Giffin, COO, attended UC Berkeley to study Cognitive Neuroscience and Data Science before dropping out to found LatchBio.
- Kenny Workman, CTO, started engaging in molecular biology research when he was 15, first at local community colleges as a lab hand and then at MIT and UC Berkeley over successive summers. Prior to co-founding LatchBio, he worked at Asimov and Serotiny as a Software and Machine Learning Engineer.
Key Takeaways
- After hundreds of interviews with biotech leaders to discover pain points around managing data, the founders developed the LatchAI platform.
- Common biology analyses require piping gigabytes/terabytes of data, meaning data storage and retrieval require programming expertise.
- Although scientists may be experts in biological theory and wet lab experimentation, programming expertise is scarce. Biologists must rely on limited computational analysts to process and visualize their data; thus, access to bioinformaticians is a bottleneck in the scientific discovery process.
- On the flip side, bioinformaticians are often hampered by repetitive analysis tasks, preventing them from innovating new computational methods.
- Recognizing this disconnect between biologists and bioinformaticians, Alfredo, Kenny, and Kyle launched LatchBio: an end-to-end biocomputing platform to allow both wet lab and dry lab scientists to get back to what they’re trained to do - science!
- The team recently launched their SDK - a Python native developer toolkit - to bridge the divide between the computationally literate bioinformaticians and the no-code savvy biologists.
- The goal of Latch is to become the universal cloud computing platform for academic research and industry biotech.
Impact
- The no-code platform that LatchBio is building is bringing the modern computing stack to biotech, streamlining data analysis so scientists can focus on solving the world’s biggest problems with biology.
Company: LatchBio
Next Episode

Illuminating Biological Context with Josie Kishi
Episode Summary:
Technologies like next-generation sequencing allow us to understand which RNA transcripts and proteins are expressed in biological tissues. However, it’s often equally important to understand how cells or molecules are positioned relative to one another! Whether it be a cell changing its shape, an organelle ramping up a metabolic process, or a DNA molecule traveling across the nucleus, understanding spatial context is critical. Current approaches for spatial sequencing are limited by cost, complicated equipment, sample damage, or low resolution. Recognizing this challenge, Josie and team developed Light-seq, a cheap and accessible method to combine sequencing and imaging in intact biological samples. Not only is the method inexpensive, but Light-seq can also achieve unprecedented spatial resolution by using light to add genetic barcodes to any RNA, allowing scientists to determine exactly where sequencing should occur with extreme precision. By helping researchers to understand spatial context, Light-seq-driven insights may illuminate cancer, neurodegeneration, and autoimmunity.
Episode Notes:
About the Author
- Following her lifelong passion for computer programming, Josie studied Computer Science at Caltech and worked as a software engineering intern at Google. At Caltech, a biomolecular computation course introduced her to the field of biomolecular programming. Josie was quickly excited about the intersection of computers and biology and its potential to bring about positive change in the world. She pursued this interest in her graduate studies in the Wyss Institute for Biologically Inspired Engineering at Harvard, where – as first a postdoctoral fellow, and then the Technology Development Fellow – she developed platform technologies for DNA-based imaging and sequencing assays.
Key Takeaways
- Next-generation sequencing is a powerful technology to read the transcriptomic state of biological tissues by surveying the RNA transcripts present.
- However, it’s important to understand not only what is being expressed but where this expression occurs! The spatial arrangement, structure, and interactions between molecules are critical to define the functions of biological systems.
- By linking imaging with -omics profiling, the field of spatial biology seeks to understand molecules like RNAs in their 2D and 3D contexts.
- Unfortunately, currently available spatial transcriptomics methods are limited in their ability to select individual cells with complex morphologies, require expensive instrumentation or complex microfluidics setups to the tune of several $100K, and often damage the samples.
- Further, rare cells are often missed due to lower sequencing throughput, even though they may be critical for biological activity.
- Recognizing this challenge, Josie and her collaborators developed Light-seq, a new, cheap, and accessible approach for single-cell spatial indexing and sequencing of intact biological samples.
- Using light-controlled nucleotide crosslinking chemistry, Light-seq can correlate multi-dimensional and high-resolution cellular phenotypes – like morphology, protein markers, spatial organization) – to transcriptomic profiles across diverse sample types.
- In particular, using the biological equivalent of photolithography, Light-seq can add genetic barcodes to any RNA by shining light on it, allowing scientists to control exactly where sequencing should occur with extreme precision – up to the subcellular level.
- Light-seq can operate directly on the sample: the method does not require cellular dissociation, microfluidic separation/sorting, or custom capture substrates or pre-patterned slides.
- Samples used for Light-seq remain intact for downstream analysis post-sequencing.
- Josie evaluated Light-seq on mouse retinal sections to barcode three different cell layers and study the rare dopaminergic amacrine cells (DACs).
Impact
- Josie created a cheap, accessible, and powerful tool for scientists to perform spatial sequencing at unprecedented resolution without requiring expensive or complicated setups.
- By enabling new advances in spatial biology, Light-seq has the potential to help biologists discover biomarkers for disease, measure on and off target effects of therapeutic candidates, and illuminate poorly understood biological mechanisms where understanding spatial context makes all the difference.
Author: Josie Kishi
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