Capgemini-下一代臨床開發(fā)-推動(dòng)臨床藥物開發(fā)的成功和上市時(shí)間（英）-2024.1

NEXT-

GENER

ATIONCLINICAL

DEVELOPMENTDriving

success

and

time-to-marketin

clinical

drug

developmentThe

clinical

drug

development

market

is

teeming

with

innovation,

including

cell

and

gene

therapies,

digitaltherapeutics,

personalized

medicine

and

biomarkers,

and

the

integration

of

drugs

and

medical

devices.However,despite

these

breakthroughs,

many

life

sciences

organizations

are

not

able

tofully

capitalize

on

theadvancements.A

dramatic

increase

in

the

number

of

clinical

trials,

compounded

bythe

intricacies

of

new

therapeutic

platforms,increased

regulatory

constraints,

and

intensi?ed

competition,

has

created

unprecedented

complexity

for

lifesciences

organizations.

As

a

result,

the

drug

development

success

rate

remains

stubbornly

low,with

just

10-15%of

new

treatments

making

it

tomarket.In

this

article,

weexplore

one

keyelement

of

the

development

cycle—the

clinical

trial—and

how

the

emergenceof

powerful

new

digital

and

data

capabilities,

as

well

as

new

trial

designs,

can

help

companies

increase

programe?ciency,

speed,

and

access,

driving

outcomes

for

both

the

business

and

patients.What

is

anext-generation

clinical

development?Anext-generationclinicaltrialisaprojectthatleveragesadvanceddigitalanddatacapabilities,includingAIandgenerativeAI,

to

managemultipledatasources,enablenewdesignformats,andunlocknewanalysismethods.The

value

of

next-generation

clinical

development2+

years>15%20%

to

50%15%

to

20%Reduction

intime

to

marketProbably

ofsuccessDrug

pipeline

valueincreaseReduce

cost2NEXT-GENERATION

CLINICAL

DEVELOPMENTBREAKING

THROUGH

THE

CHALLENGESOF

BREAKTHROUGH

INNOVATIONSDespite

the

life

sciences

industry’s

collective

focus

on

bringing

new,

proven

medicines

topatients

quickly,

clinicaltrials

remain

a

costly

and

time-consuming

process.

In

today’s

landscape,

teams

contend

with

the

age-old

industrychallenges

of

recruitment

and

supply

chain

optimization

as

well

as

those

stemming

from

new

medical

innovations,competition

from

emerging

players

and

a

exponential

increase

in

data.Most

clinical

trial

challenges

relate

to

one

of

three

main

dimensions:AccessSpeedE?ectiveness?

Only5%

ofeligiblepatientshave

accessto

aclinicaltrial.?

Theaverageclinicaltriallasts6-10

years.?

Overallcostfordrugdevelopmentisbetween$1-2

billion.?

Recruitingadiversesetofpatientsremainsacorechallenge.?

Digitaltoolsarenotbeingusedto

theirfullpotentialto

enableend-to-endintegrationthatwouldacceleratetheentireprocess.?

Highcostisto

largedegreedrivenby

low

probabilityofsuccess(PoS)3NEXT-GENERATION

CLINICAL

DEVELOPMENT3

STEPS

TO

ENABLING

NEXT-

GENCLINICAL

TRIALSIn

the

world

of

clinical

trials,

so

much

is

changing

and

yet

one

thing

remains

the

same:

toadvance

the

healthcareindustry

and

improve

patient

outcomes

through

research

and

innovation.To

overcome

the

current

challenges

within

the

life

sciences

landscape,

companies

must

reevaluate

and

adapt

long-standing

traditional

clinical

trial

practices

tomakethem

more

e?cient,

engaging,

and

accessible.

Werecommendcompanies

take

the

following

three

actions

toenable

next

generation

clinical

trial

operations:1Integrate

and

simplifytraditional

clinical

trial

processes

to

accelerate

processexecution

and

data

?ows

across

the

whole

value

chain.When

evaluating

the

e?ciency

and

e?ectiveness

of

a

clinical

trial,

organizations

must

consider

three

distinct,

butinterconnected,

elements:The

processThe

supporting

organizationData

and

the

enabling

technologyIn

reviewing

these

dimensions,

companies

are

likely

tosee

that

there

are

obstacles

toe?ciency

and

e?ectivenessthat

are

common

across

all

three

areas.For

example,

one

common

challenge

related

toclinical

trial

operation

stems

from

data

silos,

which

are

often

theresult

of

disparate

systems

or

legacy

applications.

At

?rst

glance,

this

would

be

considered

a

technology

challenge.However,

it

becomes

an

organizational

issue

since

it

often

means

that

teams

are

unable

toshare

data

with

oneanother,or

that

the

data

is

of

limited

use

since

it

is

not

in

a

standard

format.

This

not

only

creates

pockets

ofine?ciency,

but

can

also

contribute

topoor

decision-making

since

teams

do

not

have

visibility

into

other

areasof

the

process.

This

a?ects

the

overall

e?ciency

and

e?ectiveness

of

the

process

itself.By

evaluating

these

three

areas

individually

and

interdependently,

organizations

can

identify

and

eliminate

corechallenges

that

are

hindering

overall

performance.

In

so

doing,

organizations

are

able

tocreate

a

more

agile

andresilient

process,

which

accelerates

process

elements,

optimizes

resources,

and

often

lowers

costs.We

have

recently

helped

a

global

pharma

in

setting

up

their

uni?ed

clinical

platform

with

end-to-end

data

?ow

fromProtocol

toSubmission

and

secondary

analysis

addressing

these

three

areas

and

through

high

value

process

stepsprioritization.

This

has

led

tosigni?cant

time

reduction

in

system

setup

(50

to75%)

and

database

lock

(50%).4NEXT-GENERATION

CLINICAL

DEVELOPMENT2Enable

a

multi-modal

approach

to

accommodate

new

engagement

forms,platforms,and

data

sources.Given

the

challenges

in

today’s

landscape

around

patient

access

and

diversity

of

participants,

companies

mustrethink

traditional

trial

design

and

execution

strategies

and

instead

consider

how

touse

technology

and

alternativeengagement

methods

toreach

a

wider

range

of

patients,

often

across

a

broader

geography.For

example,

instead

of

relying

exclusively

on

on-site

trials

where

patients

must

frequently

visit

a

hospital

or

otherfacility,

they

can

consider

developing

a

hybrid

trial,

which

would

allow

participants

tocomplete

some

trial

activityfrom

their

home

through

telehealth

applications

and

remote

data

capture

from

connected

health

devices.Taking

a

multi-modal

approach

requires

trial

operators

tocollect,

process,

integrate

and

analyze

a

wider

variety

ofdata

sources.

These

can

include

traditional

clinical

data,

as

well

as

patient-reported

outcomes,

digital

biomarkers,connected

device

data,

genomic

data,

and

more.While

this

increases

the

complexity

of

the

trial,

it

provides

the

company

with

a

far

better

understanding

ofresults,

as

well

as

patient

engagement

and

behavior.This

data

can

be

used

tofurther

re?ne

and

adapt

the

patientexperience

toensure

consistent,

correct

participation

and

reduce

the

risk

of

drop

o?.We

have

been

supporting

a

large

pharma

company

with

hybrid

trials

scaling,

simplifying

the

experience

for

everyonewith

a

uni?ed,

easy-to-use

solution

for

patients

and

sites

while

reducing

patient

burden

bycollecting

patient

datafrom

home,

increasing

statistical

power

using

innovative

endpoints

and

improving

outcomes

with

remote

patientmonitoring.3Enable

self-learning

and

insight-driven

clinical

trials

to

acceleratedecision-making

and

shiftfrom

reactive

to

proactive.Finally,

pharmaceutical

companies

must

be

able

tomonitor

the

execution

of

the

clinical

trial

and

proactively

addressissues

as

they

arise.

This

is

done

byleveraging

advanced

technologies

tomonitor

KPIs

across

di?erent

domains.One

example

for

self-learning,

that

wehave

achieved

with

one

of

our

clients,

is

connecting

the

clinical

control

towerthat

monitors

trial

execution

with

a

feedback

loop

toprotocol

design.

This

way,

new

protocols

can

be

AI

generatedusing

live

experience

especially

on

the

operational

dimension

(e.g.

milestones,

best

recruiting

sites,

etc.)

and

also

onthe

medical

dimension

(e.g.

best

end

points).Another

example

is

clinical

supply

chain

operations

which

represent

one

of

the

biggest

challenges

in

clinicaldevelopment,

aside

from

participant

recruitment.

In

most

cases,

the

products

used

in

a

clinical

trial

are

not

availablevia

a

pharmacy

or

store.

Rather,

companies

are

manufacturing

speci?c,

investigational

products,

often

in

smallquantities

that

are

then

shipped

toa

hospital

or,

in

the

case

of

a

hybrid

trial,

possibly

directly

tothe

home

of

theparticipant.

These

kits

are

often

extremely

expensive

toproduce

and

may

have

speci?c

parameters

around

howthe

package

must

be

stored

or

shipped.

This

means

that

any

unexpected

delay

or

disruption

within

the

supply

chaincould

potentially

destroy

products

that

cannot

be

easily

replaced.One

of

the

core

components

of

a

next-generation

clinical

trial

is

an

intelligent

supply

chain.

An

intelligent

supplychain

is

an

integrated,

collaborative,

responsive

ecosystem

that

leverages

advanced

digital

technologies,

includingcloud

and

AI,

toprovide

end-to-end

visibility

of

the

entire

value

chain,

enable

the

frictionless

?ow

of

informationamong

partners,

and

seamlessly

orchestrate

all

stakeholders.5NEXT-GENERATION

CLINICAL

DEVELOPMENTDownload

our

related

paper,

Resilient

and

Sustainable

Life

Sciences

SupplyChains:Goodforbusiness.Good

forpatients,tolearn

more

about

how

an

intelligent

supply

chain

canhelp

your

business

unleash

the

power

of

your

supply

chain

data

to

improve

e?ciency,

avoiddisruptions

and

manage

delays.Creating

a

better

patient

experience

–

and

better

results–

with

next-genclinicaltrials10-20%25%10-30%50-75%Improved

patientretentionReduced

patientrecruitment

timesImprove

patientsatisfactionReduce

systemsetup

time6Resilient&SustainableLifeSciencesSupplyChains6NEXT-GENERATION

CLINICAL

DEVELOPMENTWhile

next-generation

clinical

trials

represent

a

signi?cant

opportunity

for

life

sciences

organizations,

their

abilitytodeliver

value

tothe

business

and

patients

is

based

on

several

underlying

factors:CLEAN

DATA

FOUNDATION?Ensure

access

tohigh-quality,

clean,

complete,

and

timely

data

toinform

decision-making

and

enable

proactiveoperations.?Establish

robust

clinical

data

hubs,

data

lakes,

or

data

mesh

architectures

for

e?cient

data

management.DEMOCRATIZED

DATA?Ensure

all

relevant

members

of

the

clinical

team

can

access

the

data

they

need

tomakeaccurate,

timely,and

informed

decisions.??Enable

self-service

data

exploration

and

self-learning

toempower

users.Enable

robust

data

dashboards

that

o?er

timely,

complete,

accurate

data,

in

a

digestible

and

accessibleformat,

from

all

relevant

domains.MODELING

AND

SCENARIO

PLANNING?Leverage

data

and

advanced

technologies,

such

as

digital

twins,

toperform

simulations

and

what-if

scenariostoimprove

operations

and

de-risk

certain

elements.?Use

data

toinform

mitigation

plans

toproactively

address

key

issues.PATIENT-CENTRICITY

AND

HUMAN-CENTRIC

DESIGN???Develop

mechanisms

tomonitor

patient

behavior

throughout

the

patient

journey

and

identify

points

offriction

or

stress.Design

clinical

trial

protocols

that

are

reasonable

and

intuitive,

helping

toensure

patients

remain

engagedand

active

throughout

the

trial

period.Leverage

remote

data

capture,

connected

health

devices,

and

telemedicine

applications

toenable

hybridor

other

non-traditional

formats

toincrease

trial

accessibility,

diversity,

and

engagement.7NEXT-GENERATION

CLINICAL

DEVELOPMENTTAKING

THE

NEXT

STEP

TOWARDNEXT-

GEN

CLINICAL

DEVELOPMENTInnovation

promises

tousher

in

a

new

era

of

opportunity

for

life

sciences

companies.

However,

it

will

also

add

newlevels

of

complexity

tothe

development

process,

heightening

the

need

tosolve

core

challenges

related

toaccess,speed

and

e?ectiveness.As

the

clinical

landscape

becomes

both

more

complex

and

more

competitive,

now

is

the

time

toembrace

thetransformative

strategies,

advanced

digital

and

data

capabilities,

and

innovative

trial

designs

that

will

enable

a

truenext-gen

clinical

trial

function—driving

success

and

time-to-market

across

the

drug

development

lifecycle.8NEXT-GENERATION

CLINICAL

DEVELOPMENTAuthorsDavid

GhesquieresGlobal

O?er

Lead