THE COLLABORATIVE ADVANTAGE OF BIOPHARMA COMPANIES … · THE COLLABORATIVE ADVANTAGE OF BIOPHARMA...

© 2017 PAREXEL INTERNATIONAL CORP.

THE COLLABORATIVE

ADVANTAGE OF

BIOPHARMA COMPANIES

AND GLOBAL SERVICE

PROVIDERS October 26, LA JOLLA, CA

Ubavka DeNoble

© 2017 PAREXEL INTERNATIONAL CORP. / 2

• Drug development trends

• The growing significance of

Genomics and biomarkers

• The importance of the real-time

data access and predictive

analytics

• How trial design complexity

impacts the service provider

• Future critical alignment elements

between biopharma and the

service provider

AGENDA


TOKYO, JAPAN

DRUG

DEVELOPMENT

TRENDS


FDA APPROVAL FOR ORPHAN DRUG

SETS RECORD AGAIN IN 2015

• Improving NAS

approval trend;

highest since 1997

• Many first-in-class

medicines

• Orphan therapy

approvals also

increasing

Sources: FDA.gov and Jefferies Report, February 2016


ONCOLOGY AND SPECIALTY DRUGS GAIN MOMENTUM

• Significant growth in approvals

for targeted oncology products in recent years

• Targeted therapies expected to make up 91% of novel

active substances (NAS) in oncology in 2016–2020

• Biopharma companies’ pipelines are shifting to oncology

and other areas of specialty medicine

– High unmet medical need

– Better margins

– Leaner operating model

• By 2020, >225 new medicines will be introduced,

one-third for cancer

• 2/3 of drug sales will be for specialty drugs vs. 1/3 currently

Sources: Citeline, Express Scripts,2013, Drug Trend Report; IMS Health

Report, 2014; JPM Healthcare Technology Report, 2013; Wells Fargo Report,

2013, PwC Specialty drug report, Fierce Biotech, DCAT, Cowen – Therapeutic

Categories Outlook (Feb 2015), Strategy& analysis Source: “Medicine Use and Spending in the U.S.: A Review of 2015 and Outlook

to 2020,” IMS Institute for Healthcare Informatics, April 2016


TAIPEI, TAIWAN

THE GROWING

SIGNIFICANCE OF

GENOMIC & BIOMARKERS


Sources: Citeline’s Trialtrove - data accessed January - April 2015

BIOMARKERS ARE INCREASINGLY BEING UTILIZED

IN STRATIFYING CLINICAL TRIALS

• 73% of all ongoing/planned trials

using biomarkers are oncology

related; 94% of all patient

reselection /stratification trials

are cancer related

• Approvals rose for programs

utilizing biomarkers for patient

selection to 25.9%, 3x higher

than development programs not

utilizing biomarkers (8.4%), per

a BioMedTracker analysis

Top sponsors of ongoing/planned oncology trials

using biosimilars to select or stratify patients

The proportion of stratified trials is increasing Percent oncology trials selecting or stratifying using biomarkers


GENOMICS ARE BECOMING MORE CRITICAL

IN DRUG DEVELOPMENT

Target Pre-

clinical Clinical Launch

Post-

Market

Differentiated Medicines

Patient Enrichment

Patient Stratification

Efficacy

Safety Target Validation

Drug Metabolism, Transport

Drug Repositioning

Target Validation

Drug Metabolism, Transport

Drug Repositioning

Differentiated Medicines

Patient Enrichment

Patient Stratification

Efficacy

Safety


REGULATORS SEEK GENOMIC INFORMATION TO

INFORM DECISION-MAKING

Definitions

SAD: single ascending dose

MAD: multiple ascending

dose

PK: pharmacokinetic

PD: pharmacodynamic

DDI: drug-drug interaction

PGx: pharmacogenomic

CYP: cytochrome P450

TQT: Thorough QT study


IDENTIFYING DRUG REPURPOSING OPPORTUNITIES

Background:

Drug repurposing can accelerate medicine

development. While in pharma, we worked

with our clinical colleagues to identify

additional indications for an existing medicine.

What we did:

Our experts conducted a comprehensive,

clinical transcriptomics analysis across

multiple dermatologic conditions.

Value we added:

Our experts identified additional dermatology

indications for this medicine, discovered

mechanistic connections between skin

diseases and generated new hypotheses

to accelerate medicine development.

Atopic Dermatitis Psoriasis Acne

Drug Discovery Today (2014) 19 (9): 1364-71

PAREXEL Genomic Medicine

can advise clients on lifecycle

management strategies


BERLIN, GERMANY

THE IMPORTANCE

OF THE REAL-TIME

DATA ACCESS AND

PREDICTIVE

ANALYTICS


DESCRIPTIVE – REPORTING

PREDICTIVE – SIMULATION

INVESTIGATIVE – DIAGNOSTIC

What happened? What could happen? Why did it happen?

CAPITALIZING ON REAL-TIME DATA


Speed and Simplify Your Journey to Market

NOVEL

TECHNOLOGY

INDUSTRY

STANDARDS

EXPERT

SERVICES

THE SOLUTION


LEVERAGE OF SMAC TECHNOLOGIES

IMPACT CLINICAL DEVELOPMENT PLATFORM

About How We Interact Patients

Sites

Clinical Services Teams

About Big Data and Analytics Access to Digitized Information

Combined Insight

Right Decisions

Social Mobile Analytics Cloud

END TO END CLINICAL PROCESS

CONVERGENCE

Patient Reported Outcomes

Randomization

Trial Supply

Management

Clinical Trial

Management

System

Electronic

Data Capture Protocol

Deviations

Site

Start-Up Regulatory

Platform Imaging Data-Driven

Monitoring

Country

Allocation


Moving from transactional

to transformational

BENEFITS TO THE BUSINESS

DRIVE DOWN

COSTS ACCELERATE

DEVELOPMENT

TIMES

PEOPLE,

PROCESS &

TECHNOLOGY

IMPROVE

COMPLIANCE

Make better

decisions faster

Reduce monitoring

costs while

enhancing quality

Focus on your

core competency

Turning data

into knowledge


BOSTON, MASSACHUSETTS

HOW TRIAL DESIGN

COMPLEXITY IMPACTS THE

SERVICE PROVIDER


INCREASING TRIAL COMPLEXITY

• Major shift in

business mix

toward more

complex studies

(e.g., oncology)

• Patients for

targeted indications

more difficult to find

• Specialized centers

with internal IRBs*

delay startup

$194

*Institutional Review Boards

Source: Medidata PICAS database score for therapeutic areas: high>70, medium= 20-70, low<20


CLINICAL DEVELOPMENT OPTIMIZATION

EXECUTE

SUBMIT

START-UP

DESIGN

Commercialization and Outcomes Plan

Regulatory Strategy

Quantitative Clinical Development

Risk Assessment

Protocol

Optimization

Clinical Study Report Approved

Country and Site

Selection

Last Subject Last Visit (LSLV)

First Subject First Visit (FSFV)

First Protocol Approval

End-to End Data Standards and Trial Master Storage

= PAREXEL Optimization Innovations

DYNAMIC PLANNING

DYNAMIC PLANNING

Regulatory and Ethical Approval

Investigator Grants and

Contracts

Study Training

Clinical Trial Logistics

Site Regulatory

Documentation

Critical Path

Management

Recruitment and Retention

Adaptive

Monitoring

Data Surveillance

Payments

Trial Management

and Analytics

Imaging and

Spirometry

Data Management / Statistics Aggregation

Regulatory

Services

Clinical Study Report

Cross Data Analysis

Publications

Study Transparency /

Disclosure


PROTOCOL OPTIMIZATION - HOW DOES THIS WORK?

OUR GOAL

Help clients develop

multiple study designs

in order to find

the optimal one.

1

2

4

Standard

Building

Blocks in

Every Study

Considerations

for Each

Building

Block

Leverage

30 Years of

PAREXEL

Experience

& Data

Interrogate

Relevant

Building

Blocks

Scenarios

that assist

Clients

with trade-

off

decisions

3

5

A

B

C

D

E


DATA-DRIVEN INSIGHTS TO YIELD

CONSENSUS ON ACCEPTABLE RISK

THE PHILOSOPHY BEHIND BETTER INFORMED

DECISION MAKING

THE BIG DATA

ENGINE

INVESTIGATOR

& PATIENT VOICE

CLIENT

DISCUSSIONS

& ACTIONABLE

DECISIONS

PREDICTIVE

ANALYTICS

Bringing in

the Investigator

& Patient Voice

The Power to Identify

the “right countries,

sites & patients”

Effective Strategy

Planning by

Understanding Risk

Turning Data

Into Knowledge


TAIPEI, TAIWAN

FUTURE CRITICAL

ALIGNMENT

ELEMENTS BETWEEN

BIOPHARMA AND THE

SERVICE PROVIDER


BIOPHARMA

FACE ENORMOUS

PRESSURES • Demonstrating proof-of-concept

• Creating Target Product Profiles

with endpoints that support

regulatory approval

• Identifying the right partner for

protocol design, site selection and

data collection/integrity

• Managing ever-changing regulatory

and reimbursement landscapes

80%

PERCENT OF R&D ORIGINATED

OUTSIDE THE TOP 25

PHARMACEUTICAL COMPANIES


Whether you seek to license

your compound, reach proof-of-

concept, or enter the clinic

and commercialize, the PAREXEL

BioPharm Unit’s flexible model

will help you extract maximum value

from your compound or portfolio by:

• Enhancing internal capabilities

• Helping reach faster go/no-go

decisions

• Increasing compound value by

demonstrating PoC and understanding

regulatory and reimbursement

landscape

• Accelerating study start-up and

site selection

• Ensuring logistical planning and

execution is integrated into the entire

trial process

KEY ELEMENTS FOR

SUCCESS


BENEFITS OF

PARTNERING

To reach your goals faster, the

PAREXEL BioPharm unit:

• Assigns a senior PAREXEL executive

to lead a dedicated team

• Develops a strategy to minimize

complexity, accelerate timelines,

and reduce fixed costs

• Designs commercialization solutions to

accelerate development, substantiate

value and vet evidence

• Provides access to sites and patients

across Europe, Asia and the Americas

• Differentiates your company and

compound in the eyes of potential

investors and partners

• Helps you derive the most value from

your compound


ONGOING VIRTUALIZATION OF BIOPHARMA INDUSTRY

• Small-to-midsize companies,

including virtual companies, rely

heavily on outsourced services:

• Executing clinical trials

• Expanding regulatory and commercial

capabilities

• Managing cost and time to market

• Large, established companies

increasingly willing to extend the

range & breadth of outsourced

services:

• Regulatory

• Commercial

• Clinical IT

Virtualization of Biopharma


ACCELERATED REGULATORY PATHWAYS

Drug Pipelines and Specialty Products

• 64% used

at least one

accelerated

pathway

• More than a third

used multiple

accelerated

pathways


INDEXED GROWTH IN HEALTHCARE SPENDING,

GDP AND WAGES IN FOUR COUNTRIES

Note: Index on basis of local currency Sources: BCG Analysis; OECD Health Data 2009; EIU, GBE (Gesundheitsberichterstattung des Bundes),

CMS, INSEE, Office for National Statistics UK; All data indexed to 100

HEALTHCARE SPENDING OUTPACES GDP AND WAGES

Importance of Payers

• Healthcare spend growing at an unsustainable pace

• Limited objective data on value

• Biopharmaceutical companies face external pressures to reduce drug costs

• Biopharmaceutical products help bend cost curve down

100

150

200

250

300

350

19921997200220072012

100

150

200

250

300

350

19921997200220072012

100

150

200

250

300

350

19921997200220072012

100

150

200

250

300

350

19921997200220072012

Healthcare Spending

GDP

Wages


REAL-WORLD EVIDENCE PLATFORM

Patient Population

from Secondary

Data Assets

Phases

I-III

Post-Approval

Research

Patient Population from Clinical Trials

Approv

al

• Advances in computing power to integrate real-world data

• Allows study of heterogeneous patient populations beyond those studied in clinical trials

• Age groups

• Patient lifestyle variance

• Disease progression

• Compliance


PERSONALIZED MEDICINES ARE BECOMING

MORE AVAILABLE

Adapted from Pharmaceutical Research and Manufacturers' Association (PhRMA):

Value of Personalized Medicine (2015)

138 FDA approved

drugs with

biomarker

information on their

label

138 FDA approved

drugs with

biomarker

information on their

label

20% of FDA

approvals in 2014

were for targeted

therapies

20% of FDA

approvals in 2014

were for targeted

therapies


55% OF PERSONALIZED MEDICINES ARE WITHIN

ONCOLOGY/HEMATOLOGY AND PSYCHIATRY


MARKET DRIVERS INFLUENCING NEED FOR GENOMIC MEDICINE

SERVICES

Decision Maker Decision Drivers

Clients Looking for information to drive drug development

decision making

Regulators Seek pharmacogenomic information to understand who

will benefit or be harmed by the drug

Payers Want companies to demonstrate value over current

medicines

Patients Want medicines that work for them and don’t cause

side effects


INTEGRATED MULTI-OMICS APPROACHES FOR NOVEL

TARGET DISCOVERY

PAREXEL Genomic Medicine can help clients select and validate drug targets.

Background:

While working in pharma, we partnered

with pre-clinical scientists to develop

and implement a multi-omics strategy to

discover novel, specific drug targets in

the IL23 pathway.

What we did:

Our experts supported multi-omics

strategy design and applied cutting-

edge methodologies (e.g., causal

reasoning, advanced network analysis)

to analyze, integrate, and interpret the

multi-omics experimental findings.

Value we added:

In close collaboration with our bench

scientist colleagues, we discovered

novel drug targets that are validated in

follow-up experiments.

-300 -200 -100 0 100 200 300

Comp.1 [25.66%]

-200

-150

-100

-50

0

50

100

150

200

Co

mp

.2 [

12

.25

%]

Transcriptomics: IL23 vs IL12 Proteomics: IL23 vs. IL12

Integrated Multi-omics Network

Causal Reasoning & Inference

Novel Target Candidates

J Immunol (2014) 192: 2527-8

EBI Immunogenomics Conference 2015


ADME GENETICS EXPLAINS EXPOSURE DIFFERENCES

• In a Phase I drug-drug interaction study, a

subset of healthy volunteers had elevated

levels of Drug X when administered with the

client’s medicine.

• Drug X is primarily metabolized by CYP2B6.

Our experts assessed genetic variation in

the CYP2B6 gene to determine if genetic

variants leading to reduced CYP2B6

enzyme activity might account for increased

exposure of Drug X.

• The poor metabolizer CYP2B6 *6/*6

genotype was associated with elevated

exposure of Drug X. The client’s medicine

did not impact Drug X exposure; however,

Drug X increased metabolism of the client’s

medicine (data not shown) so dose

adjustments of the client’s medicine are

recommended.

Drug X plasma concentrations over time by

CYP2B6 genotype


QUANTITATIVE CLINICAL DEVELOPMENT

• Model based development is critical to take the right steps to get into IND –

pave the way for successful Phase I (the right data without surprises)

A fit-for-purpose modeling tool, always

Create definable value in early development

Cost avoidance, focus only on what is truly needed

Enhancement of pharmacology data with focus on exposure response, occupancy

Clear definition of “target” or “candidate”

Establishing high-confidence stopping rules, eliminating clouded judgment

Successful modeling helps sponsors create optimal Proof-of-Principle and

Proof-of-Concept studies, delivering more valuable data earlier in

development cycle

Exposure to Target

Binding to Target

Expression of Pharmacology


YEAREND CASH AT SMALL/MIDSIZED BIOPHARMA ($ IN BILLIONS)

SMALL AND MIDSIZED CLIENTS

$33 $38

$48

$62

$78

2011 2012 2013 2014 2015

• Despite recent slowdown in funding, smaller biopharma companies have about $78 billion of cash

• Industry as a whole has approximately $350 billion of cash

• New business from segment remains strong

• Willing and ready to deploy capital

Grow the Core Source: Chestnut Partners


DATA CAPTURE

& MANAGEMENT

Typical challenges

• Timely availability of a data capture

framework prior to first patient in

• Cost effectively capture data

• Leveraging ‘real time’ clinical data

PAREXEL® solution

Robust technology platform and

infrastructure supporting large trials

Allow rapid study-build process with

design specification generation

DataLabs closely integrated with

Data-Driven Monitoring to improve

study oversight

16,000+ SUBJECTS ENROLLED IN

1,900+SITES

Customer results:

Largest study


SOURCE DATA

VERIFICATION &

SOURCE DATA REVIEW Typical challenges

• Capturing, reviewing and analyzing

patient data in timely manner

• Managing multiple source of information

• Reporting and exporting of data

• Inspection ready SDV and SDR

PAREXEL® solution

Focus SDV within EDC to

critical elements

Efficiently document SDR in CTMS

via customizable checklists

Dashboard view of site and patients

Improved patient data surveillance

enhances data quality safety

20% SDV & SDR THRESHOLD

for some studies

Customer results:


PAYMENT MANAGEMENT

Typical challenges

• Effective control and management of

contracts and trial budgets

• Greater visibility into committed costs

vs. projected budgets

• Projecting under/over spend areas

throughout the process

PAREXEL® solution

Dynamically forecast and adjust

spend in real time

Easy generation of proposed payments

for hundreds of sites at once

Straightforward interfacing with

Accounts Payable systems

880,000+ SUBJECTS ENROLLED IN

25,000+ STUDIES

Customer results: Impact CTMS


INVESTIGATOR

PERFORMANCE

Typical challenges

• Lengthy study start-up times

• Difficulty selecting and managing

investigators

• Maintenance of investigator database

impairs planning and study timelines

PAREXEL® solution

Reduce the cost and risk of clinical

trial study start-up

Have confidence that you are using

the right investigators in your study

Expedite site selection and

patient recruitment

380,000+SITES IN

70+ COUNTRIES

Customer results: Impact CTMS


DATA DRIVEN

MONITORING Typical challenges

• Addressing cost pressure without

compromising data quality

• Regulatory pressure

• Maximizing the value of limited

resources

• Timely ability to monitor quality

and safety issues

PAREXEL® solution

Reduce costs by assessing workload

to drive site visits

Enhances study data integrity and

scientific credibility

Predictability of outcomes that

withstand regulatory scrutiny

10-25% reduction in

Customer results:

STUDY MONITORING COSTS


TRIAL TRACKING

& MANAGEMENT

Typical challenges

• Site recruitment takes too long

• Large number of global sites

and patients

• Lack of centralized information

management for Clinical Operations

PAREXEL® solution

Timely access to enrollment

and milestones

Track submissions, approvals

and the study start-up process

Focus on the sites that need

attention with on-screen filtering

and drill-through to action items


EXAMINING RULE BASED VS MODEL BASED DESIGN ACCRUAL NUMBER FOR ILLUSTRATIVE PURPOSES ONLY

1 2 3 4 5 6 7

3

3

3

3 3(15) 40

8 9

T Accrual = 55

No data on

treatment effect

3

3

3

3

3 7 (16)

5 LBM+ | 5 LBM-

+ 15 LBM-

+ 10 LBM+ + 20(?) LBM

T Accrual = 35 T Accrual = 55

Data on treatment

effect + LBM

Biomarker

No MTD

DLT?

Exploring safety

~$43K/Pat*

$2.4M

OBD

All Tox

Enrichment data

Reduced timeline

Exploring efficacy

Reduce P2b $$

~$55K/Pat*

$3.1M

Timeline in Months

* Operation fees only

Rule

Based

Model

Based


WELL POSITIONED FOR PHASE IIB

1 2 3 4 5 6 7

3

3

3

3

3 7 (16)

5 LBM+ | 5 LBM-

+ 15 LBM-

+ 10 LBM+ + 20(?) LBM

T Accrual = 35

8 9

T Accrual = 55

Data on treatment

effect + LBM

Biomarker

• Reduce timeline to acquire efficacy data

• Reducing risk of 2b design with defined patient enrichment

• Increase Investigator interest in 2b (improved enrolment)

• Reduce $ Investment for Phase 2b and time to Phase 3

OBD

All Tox

Enrichment data

Exploring Efficacy

~$55K/Pat

$3.1M

Prospective

hypothesis testing

Confirm LBM

Response rate


REGULATORS SEEK GENOMIC INFORMATION TO

INFORM DECISION-MAKING

FDA, EMA and PMDA have all recognized the importance of genomic sampling in clinical

trials: – published guidance to industry on pharmacogenomics

– ICH guideline E18 on genomic sampling and management of genomic data has been released for

public consultation

Graphic courtesy of:

Issam Zineh

Office of Translational Sciences

CDER

U.S. Food and Drug Administration


DRUG DEVELOPMENT

CHALLENGES

• Clinical studies are becoming

more complex

• Cycle times too long

• Cost pressure

• Lack of real-time and standardized

data and analytics


PHASE III FAILURES

Source: Korieth, Karyn.. “Facing protocol amendments head-on.” The CenterWatch Monthly 23.4 (April 2016): 1-13. Print

Success Rates by Phase,

2010 vs. 2011 vs. 2012 vs. 2013 (lead and secondary indications)

Approximately

40% fail!


PHASE III FAILURES

- Recent PAREXEL analysis,

we collected and evaluated

data on 38 Phase III failures

from mid-2012 through 2015

from a variety of publicly

available sources

- Failed to meet primary or

secondary efficacy endpoints

- Phase III trials that failed due

solely to safety issues are

not included

- These 38 failed trials

collectively enrolled nearly

150,000 patients


ADAPTIVE DESIGNS

How could these designs reduce amendment & failure risk?

Prospectively planned opportunity to revisit initial assumptions based on

interim data –

e.g., Drop a dose arm that is ineffective or adapt sample size

based on observed treatment effect differences

TRADITIONAL DESIGN (CARGO) ADAPTIVE DESIGN (PASSENGER)


HOW DO WE FIND THE RIGHT INVESTIGATIVE SITES?

A COMPREHENSIVE PICTURE OF THE INVESTIGATOR AND SITE LANDSCAPE

SITE PERFORMANCE DATA IN THE BROADEST SENSE

EXPERIENCE

ENROLLMENT

RESPONSIVENESS

DATA QUALITY

PATIENT POPULATION

INVESTIGATOR VOICE

DIAGNOSTICS


A SEA OF DATA

Imaging

Geo Profiling

Clinical Trial

Data

IRB

Lab Data

Audits

Validation of

instruments

IVRS

Surveys

CTMS


• Master the

datasets − Investigator

− Study

− Site

• Get the right sites,

countries and

patients for your

study

INTERNAL &

EXTERNAL

DATASETS INCREASED STUDY

PREDICTABILITY

TURNING

DATA INTO

KNOWLEDGE

• Gain real

insights

NORMALIZE

THE DATA

• Compare to the

median performance

on the same study

in the same country

IDENTIFYING SIGNALS FROM THE NOISE


Filter for Best Sites in Japan

ACCESSIBLE DATA

REGIONAL AND COUNTRY HEAT MAPS WITH SITE LEVEL DRILL-DOWN


Electronic Health Records (EHR) Insights

Early identification of potential issues with protocol inclusion

and exclusion criteria will enable a risk based approach to

feasibility and clinical trial management

Most Challenging

Eligibility Criteria

Independent

Criteria Impact

Number of Record

Queries 18,536 (100%)

Criteria 1 16,152 (87%)

Criteria 2 17,996 (97%)

Criteria 3 5,795 (32%)

Potential patient

population

for study

18,536

16,152

15,612

2,871

Identifying the impact certain criteria

will have on the patient pool allows

management of risk sharing

DO THE PATIENTS EXIST?


CLINICAL TRIAL INTELLIGENCE

MAGNITUDE

OF EXISTING

TRIAL DATA

Competitive

site landscape

Industry

benchmark

data

Study and drug

pipelines

Previous study

outcomes

Study duration

and timelines


•Analyze conversations

•Understand and advise clients

•Engage patients and/or influencers

•Understand Sentiment – assess what is said, whether good, bad or neutral

DIGITAL LISTENING is Data Collected in Real-time via Social Media

to Support Better Decision-Making

NEWS FORUMS BLOGS

Key Benefits

Develop strategies to mitigate

potential challenges

Accurate insight into

patient/medical staff

experiences

Target bloggers/tweeters to

push information

Cost effective

Global reach

What We Learn from Digital Listening: Examples

TWITTER

Patients speak openly about

illnesses, conditions and drugs on

social media

Understanding Patient Perceptions

Tracking Top Physicians and Patient Influencers

Social media influencers range

from top doctors to recent cancer

survivors to authors and more

DIGITAL LISTENING: PROVIDES UNCENSORED INSIGHT

55


COUNTRY DECISION MAKING SUPPORTED BY PREDICTIVE ANALYTICS

A data-driven approach to country selection takes into account key parameters

to gain a better awareness of the risks associated with country selection

DATA-DRIVEN

ALLOCATION SELECT THE

RIGHT COUNTRIES

Identify the most desirable

countries from the beginning

Validate protocol feasibility with

local clinical operations

RESULTS

STRATEGY

TRANSPARENCY

Increase quality of country

selection

Use the data to drive allocation

of countries

Enforce indication and protocol

specific assessment

Increase predictability of country

performance

Allow efficient and effective

conversations on country

allocation

Increase sponsor confidence in

country selection capabilities

RESULTS RESULTS


RISK ASSESSMENT

Feasibility will never be perfect. There will always be risk in the delivery of clinical trials.

Reducing risk to an acceptable level is the goal.

Undis

covere

d

Kn

ow

led

ge

What We

Do Know

What We

Don’t Know

What We

Suspect

Feasibility

Fe

as

ibil

ity

Undiscovered

Knowledge

What We

Do Know

What We

Don’t Know

What We

Suspect

Feasibility allows us to maximize what we know, firm up what we suspect, and minimize what we don’t know


ADAPTIVE TRIAL DESIGN CAN POTENTIALLY REDUCE

COST OF FAILURE

• About 50%

of Phase III

trials fail

• Average cost

of $20 M makes

it an expensive

problem

• Root cause

attributed to

traditionally rigid,

inflexible design

• Adaptive trial

design (ATD)

allows to

revisit initial

assumptions

and change

course


REAL-TIME DATA AND PREDICTIVE ANALYTICS

TRANSFORMING STUDY EXECUTION

Actionable

Information

Data Driven

Interventions

Silo’ed

Systems

Data Aggregation

Data Driven Interventions

Modelling Normality

Strategic Planning

Adaptive Trials

Proactive Interventions

Raw

Data

Alerts

# People/Study

Monitored

Valu

e

Maturity

Reso

urc

e r

eq

uir

ed

Modelling

Normality

Anomaly

Detection

Proactive

Decisions


DATA-DRIVEN FEASIBILITY REQUIREMENTS

Medical

Imaging

RTSM /

IRT CTMS EDC

A Single Intelligence Platform

Site Forecast

Patient Feasibility

Survey

Digital Listening

TURNING DATA INTO KNOWLEDGE

External Data

Sources

DATABASE 1

DATABASE 2

DATABASE 3

DATABASE 4

UNDERPINNING BIG

DATA ENGINE

PREDICTIVE

ANALYTICS

Country Allocation

Study

Optimization

Site

Optimization

Analysis and

Scenario Modeling +

Visualization

Power to identify the “right countries, right sites, right

patients”

Risk

Management

What We

Do Know

What

we Risk

EHR INSIGHTS

UNDERSTANDING

RISK

Decisions based on

consensus of

acceptable risk

Investigator

Surveys

Pre-Screening

Platform

CRO

Supporting Solutions

INVESTIGATOR AND

PATIENT VOICE


THE IMPACTS

COSTS?

The average cost to

develop and gain

marketing approval

for a new prescription

medicine, a process

often lasting longer than

a decade, is now

$2.56 billion dollars.*

* Tuft CSDD Outlook 2015

DELAYS?

On average, 2-3

protocol amendments

can delay a trial by

2 months, with each

amendment adding

$500,000 in

additional costs.*

* Tufts May 12, 2014, International

Journal of Environmental Research

And Public Health.

CHURN?

A big factor

contributing to delay

is the 'churn rate’

among investigators.

In some estimates,

over 50% of

investigators have

only completed

one study.

HOW TO MITIGATE THESE

CHALLENGES WITH BETTER

DATA- DRIVEN DECISIONS


INDUSTRY CHALLENGES

Site landscape

is highly

fragmented

with variable

performance

40% of

participating

Investigators

never conduct

another FDA

regulated study

About 30% of

sites don’t

enroll a single

patient

Studies don’t

meet their

enrollment

timelines 80%

of the time

Source: CenterWatch Reports


POSITIVE TREND IN FDA APPROVALS CONTINUES

FIPCOs defined as companies with annual R&D spend of $500 million or over. SEBPCO defined as companies with annual R&D of less than $500 million.

Sources: www.fda.gov. Pink Sheets 2010 -2015. PAREXEL Biopharmaceutical R&D Statistical Sourcebook 2016/2017. Michael Lanthier, Kathleen L. Miller, Clark Nardinelli

and Janet Woodcock; “An Improved Approach To Measuring Drug Innovation Finds Steady Rates Of First-In-Class Pharmaceuticals, 1987-2011,” Health Affairs, 32, no.8

(2013):1433-1439

• Growth in the number of approvals is observed for orphan drugs

18

24 26

21

30

39

27

41

45

0

10

20

30

40

50

2007 2008 2009 2010 2011 2012 2013 2014 2015

Total Orphan First-in-class Breakthroughs

NME Approvals


THANK YOU


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