WEBVTT

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Myeloid cells are part of
the innate immune system.

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These are the most abundant
cells we find in circulation,

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in blood as well as in tissues.

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So we study them because they're
involved in all processes.

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They're the first responders,

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but they don't leave when things
go out of control, they stay,

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and we think they're primary
drivers of the disease

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and instruct other cells
as well to drive disease.

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We study infectious, inflammatory
and autoimmune disease in the lab,

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and we're trying to understand how immune
cells drive pathologies and disease.

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And the focus primarily is myeloid cells.

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So we study monocytes,
macrophages and neutrophils,

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and we study how these cells drive disease.

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We follow them to the course of a disease.

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Trying to find more human relevant models
where we watch a disease progress,

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learn from it, then go back and perturb it

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and learn from that perturbation and
try to gain a better understanding

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so that we can make better
drugs treating disease.

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So conceptually we start with human data.

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So we pick a disease.

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It could be fibrosis.

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It could be cancer.

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It could be infectious disease.

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We did a lot of work with SARS-CoV-2
infection in COVID-19.

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We start with the human data

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and based on this observational data,

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we make a hypothesis that we are going
to test in a mouse model.

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We have something called humanized mice.

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This work was pioneered by my mentor
Richard Flavell two decades ago,

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and I have been building on it
to improve the types of cells we have.

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The unique aspect of this mouse is it has genes,

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human genes that are necessary
for human immune system to develop.

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On top of a human immune system,

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we have also provided
tissue cells to these.

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So they have a liver that is humanized.

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We have humanized the lung.

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We have humanized the intestine,
and we have humanized the skin.

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So now we have a system
where we can study human cells

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in the context of any type of disease.

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We study them, we start perturbing or
identifying networks that are driving

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and we block those networks.

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We take them out of the equation
and see if they matter.

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If they don't matter,

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then we go back to the human data
and try to come up with better hypotheses.

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If they matter, we still go
back to the human data

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and see if there is any sign there that
you know, encourages us to keep working.

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So, I do basic science,

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but I hope that one day

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findings that we found in the lab
are gonna help someone.

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So before something is a candidate
for drug development,

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we need to study it in a human
relevant system, hence our mice,

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and do this iterative work where
we go back and forth with human data,

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mouse model, human data, mouse model
and gain a true mechanistic understanding.

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And once we have a strong candidate

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after really hard work,
then we try to take it to clinic,

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and I think the way we're doing our research

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will allow us to go to clinic
with better candidates

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and also maybe make it faster

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so that what we find on the bench doesn't
take 20 years for it to go to clinic.