immunology

Season 4, Episode 3: Peering Inside the Immune Response for Novel Antibodies with Nima Emami

Episode Contributors: Seth Bannon, Michael Chavez, Nima Emami

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!

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

Season 3, Episode 2: What boosts immune boosters? with Kevin Litchfield

First Author: Kevin Litchfield

Episode Summary: Novel drugs that boost the immune system to fight cancer have become pharma darlings in the few short years since their approval. These drugs, known as immunotherapies, have so far focused on improving T cell responses and can be used to cure a multitude of different cancer types. Yet more often than not, immunotherapies have no effect on a patient, leaving doctors guessing on whether to prescribe the drug. To find the reason why some people respond while others don’t, Kevin and his team create a huge database of sequences derived from immunotherapy-treated patients. With it, he discovers biomarkers, mutational signatures, and immune profiles that correlate to response with the hopes that one day, these measurements form a diagnostic to ensure we treat the right patients.

About the Author

  • Kevin is a group leader at University College London and performed this work in the lab of Charles Swanton at the Francis Crick Institute. Dr. Swanton and his group are experts in studying the genome instability and evolution of cancer.

  • Kevin started his career as a mathematician but was always driven to apply his skills to improving medicine.

Key Takeaways

  • Immunotherapies aim to cure cancer by “taking the breaks off” your immune system, supercharging it to attack tumors.

  • Two immunotherapies known as checkpoint inhibitors (CPI), anti-CTLA-4 and anti-PD-1, work by enhancing T cells and have recently become blockbuster drugs for the treatment of multiple different cancer types.

  • These immunotherapies don’t work in many patients and medicine has yet to understand why.

  • Kevin aggregated DNA and RNA sequencing data across multiple studies to generate a dataset that contained over 1,000 CPI treated patients who did and did not benefit from treatment.

  • With this data, Kevin discovers mutational signatures, biomarkers, and immune profiles that correlate to whether a patient will respond to treatment.

Translation

  • Kevin finds measurable signatures of a patient’s cancer that could be used to determine whether a patient should receive CPIs.

  • This retrospective analysis will need to be validated as a prospective study to determine whether Kevin’s findings actually predict response.

  • More tumor data as well as information about the patient’s genetics is being brought in to improve the accuracy of this prediction.

  • Collaborations between academics, medical centers, non-profits, and industry partners will enable the findings to make an impact on patient outcomes.

Paper: Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition