Hispanic Voices Reflect and Connect in CAP Webinar

Elizabeth McMahon
0:02

Coming

up,

how

AI

is

parsing

data

on

maps

of

cancer

tumors

to

predict

patients'

response

to

therapy.

Plus,

simplifying

drug

testing.

A

new

proficiency

testing

program

keeps

labs

on

top

of

a

changing

landscape.

This

is

Path

News

Network

Daily

Edition

from

the

College

of

American

Pathologists.

I'm

Elizabeth

McMahon.

It's

Thursday,

September

3rd.

Hispanic

physicians

comprise

just

8%

of

active

pathologists,

but

this

growing

community

has

made

vital

contributions

to

the

field.

During

September's

Hispanic

Heritage

Month,

the

CAP

will

explore

perspectives

from

this

diverse

community

with

an

online

conversation

on

September

22nd.

Dr.

Cristina

Magallanes-
Hoyos,

assistant

professor

of

pathology

at

UT

Southwestern

Medical

Center,

is

one

of

the

event's

organizers.

Dr. Cristina Magallanes-Hoyos
0:59

This

is

going

to

be

an

open

conversation,

an

opportunity

to

connect,

an

opportunity

to

reflect

on

what

we

can

do

as

pathologists

to

serve

not

only

our

community,

of

course,

but

our

working

force

to

create

also

a

sense

of

community

within

ourselves

and

to

just

feel

that

we

are

all

in

this

together.

Elizabeth McMahon
1:19

She

said

Hispanic

professionals

fill

a

crucial

gap

for

patients,

pathologists,

and

the

practice.

Registration

is

not

required

for

the

webinar.

Cancer

tumors

have

unique

microenvironments.

To

understand

their

composition,

researchers

use

a

tool

called

spatial

transcriptomics

to

map

their

genes

and

genetic

expression.

But

this

technique

yields

a

large

amount

of

data,

making

it

difficult

to

identify

similarities

among

tumors

or

predict

how

they'll

grow.

Can

AI

help?

In

a

new

study

from

the

University

of

Chicago,

pathologists

used

spatial

transcriptomic

data

on

262

solid

tumors

to

develop

formulas

to

describe

tumor

cells

and

their

genetic

activity.

They

trained

AI

with

the

formulas

to

study

each

tumor's

organization

to

predict

how

non-small

cell

lung

cancer

patients

would

respond

to

immunotherapy.

The

team

hopes

the

tool

can

be

used

to

predict

a

response

to

therapy

with

any

type

of

tumor.

The

study

is

in

the

journal

Cell

Reports

Medicine.

Serum

drug

testing

detects

medications

in

the

bloodstream

and

helps

physicians

monitor

dosing.

It's

also

critical

for

detecting

toxic

drug

interactions.

As

drug

use

and

therapies

evolve,

labs

must

change

their

toxicology

testing.

The

CAP's

new

serum

drug

testing

proficiency

test

keeps

labs

current

by

updating

and

consolidating

multiple

tests

into

one.

Dr.

Adam

McShane

is

medical

director

of

the

Special

Chemistry

Laboratory

at

Cleveland

Clinic.

He

says

the

simplified

program

reflects

how

doctors

over

time

have

prescribed

different

drugs.

Dr. Adam McShane
3:35

Some

of

these

older

tests,

you

know,

the

screening

of

benzos,

for

example,

or

barbituits

and

tricyclic

depressants

in

serum

have

seen

dwindling

in

general.

And,

you

know,

the

tricyclic

depressants

being

the

first

generation

of

uh

tri

antidepressants

were,

you

know,

very

common

until

we

got

the

second

generation

in

the

mid-90s

with

the

SSRIs.

Um

and

they've

seen

a

precipitous

fall

and

maybe

a

little

bit

of

resurgence

the

last

couple

of

years

with

uh

some

off-label

use

with

uh

different

um,

you

know,

like

neuropathic

pain

and

migraine

insomnia,

things

of

that

nature.

But

overall,

the

the

prescription

of

you

know

ticklin

depressants

have

just

plummeted.

Elizabeth McMahon
4:11

The

CAP

recommends

that

labs

currently

enrolled

in

separate

serum

drug

screening

and

therapeutic

drug

monitoring

proficiency

tests

enroll

in

the

reformulated

offering.

And

finally,

many

viruses

that

affect

humans

start

in

animals.

Preventing

that

spillover

is

critical.

In

Uganda,

a

nonprofit

has

turned

to

AI

to

do

just

that.

The

journal

Nature

highlights

the

collaboration

between

the

nonprofit

Conservation

Through

Public

Health,

or

CTPH,

and

a

joint

project

between

the

EU

and

several

African

nations.

Over

a

three-year

collaboration,

CTPH

collected

samples

from

cattle

and

poultry,

tested

them

for

diseases

that

affect

humans,

and

combined

results

with

data

from

gorillas.

The

data

are

now

being

used

to

train

predictive

AI

models

to

warn

about

outbreaks.

The

effort

is

one

of

several

worldwide

using

AI

to

monitor

and

prevent

disease

outbreaks.

That's

all

for

today's

Daily

Edition.

Be

sure

to

check

the

show

notes

for

more

information

on

today's

stories,

including

the

Hispanic

Voices

webinar

and

the

new

proficiency

testing

programs.

Got

a

story

you'd

like

us

to

cover

in

the

Daily

Edition?

Write

to

us

at

stories

at

Cap.org.

We're

back

at

5

a.m.

Eastern

for

another

episode

of

the

Daily

Edition.

I'm

Elizabeth

McMahon.

Have

a

great

day.