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Includes:

Large-scale Electronic Data Capture

SAE Reporting with EDC

Improving Clinical Trial Software

CDISC and HL7 Convergence

Translational Medicine

Clinical Trials in Eastern Europe

DATA MANAGEMENTIN PHARMACEUTICALRESEARCH & DEVELOPMENT

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3D A T A M A N A G E M E N T I N P H A R M A C E U T I C A L R E S E A R C H & D E V E L O P M E N T

Contents

Embracing New Challenges Clinical Development – The New Opportunity 4Jonathan Palmer1 and Nicholas Giannasi, PhD2

1. Business Development Lead, Clinical Solutions, Europe, Middle East and Africa (EMEA), Oracle, and

2. Senior Business Development Director, Life Sciences, EMEA, Oracle

Putting the ‘e’ in R&D 5Michelle Grayson

Managing Editor, Medical Communications, Touch Briefings

Large-scale Electronic Data Capture – When Size Is Not the Only Issue 7Nicolas Schaltenbrand, PhD

Senior Director, Global Data Management, Quintiles

Electronic Safety Data Management – The Dawn of a New Era, but Are We Awake to the Consequences? 10Barry Burnstead

Director of Project Management, i3 Statprobe International

Data Integration – Business Requirements and Implications for Data Standards 12Sharon Marmaras

Director, Clinical Trial Support and Life Sciences Data Hub (LSH) Business Project Leader, Boehringer Ingelheim

The Convergence of Healthcare and Clinical Research Standards 14Pierre-Yves Lastic, PhD

Senior Director, Standards Management & Data Privacy, sanofi aventis R&D

Scaling Up Clinical Research by Expansion of Electronic Infrastructure 17Peter J van der Spek

Professor and Head, Department of Bioinformatics, Erasmus University Medical Centre

Clinical Trials Abroad – ‘Back in the USSR’ 20Vladimir V Novakovskiy, MD, PhD

Vice President of Regulatory Affairs and Quality Assurance, Congenix LLC

Optimising eClinical

Introduction

Foreword


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a report by

Jonathan Palmer1 and Nicholas Giannasi , PhD2

1. Business Development Lead, Clinical Solutions, Europe, Middle East and Africa (EMEA), Oracle, and

2. Senior Business Development Director, Life Sciences, EMEA, Oracle

The clinical development industry is entering a new era of change and

opportunity. It faces an increasing array of drivers from the commercial,

regulatory, safety and patient sectors, the like of which have never been

seen before. Billion-dollar development costs are dwarfed by multi-billion-

dollar safety withdrawals, such as that of Vioxx by Merck & Co., which

erased US$25 billion from the company’s market value overnight. In

parallel, patients are becoming more informed, and are consequently

demanding therapies that can stretch the budgets of their health providers.

In response to these pressures, the industry is embracing new techniques

and technologies at a rate of change not seen for many years. Clinical

trial timelines are under scrutiny, meaning that companies must seek new

technologies and new territories; maturing data standards are changing

the way in which data are collected, stored and analysed; realtime clinical

trial adverse event reporting is being considered against rapid electronic

data capture (EDC) adoption; and translational medicine is helping to

convert basic research to patient-focused therapies. Across the entire

value chain there is the realisation that those companies that best exploit

and mine their data as an asset, rather than just collecting and collating

it, will be the winners in the race to market dominance.

Oracle has been involved in providing solutions for the life science and

healthcare markets for more than 20 years. Our suite of six applications

for clinical trials and pharmacovigilance is used by more than 300

companies globally. The full spectrum of our solutions in discovery,

clinical development, supply chain and sales and marketing is widely used

across the industry, including by all of the top 20 global pharmaceutical

companies and top five clinical research organisations.

As the world’s leading enterprise software company, Oracle combines

leading-edge technologies with domain expertise to build market-leading

industry applications. Our Healthcare and Life Sciences Application

Engineering team is embracing new architectural approaches such as

service-oriented architectures to facilitate integration of ever-flexing

business processes and expanding virtual project teams.

With these challenges in mind, we have gathered a collection of experts

to provide some thought-provoking commentary and guidance on

emerging opportunities:

• Nicholas Schaltenbrand, Quintiles, illustrates how the industry is finally

moving from endless EDC pilots into mainstream global deployment.

• Barry Burnstead, i3 Statprobe, considers breaking down the historical

boundaries between safety and clinical data management to propose

more wide-scale usage of EDC as a platform for reporting serious

adverse events during a clinical trial.

• Sharon Marmaras, Boehringer Ingelheim (BI), describes BI’s initiative

to optimise clinical integration and reporting through a new

integration platform.

• Pierre-Yves Lastic, sanofi aventis, provides an overview of the latest

data standards initiatives between the Clinical Data Interchange

Standards Consortium (CDISC) and Health Level 7 (HL7) to aid

convergence of clinical trial and healthcare data.

• Peter van der Spek, Erasmus University Medical Centre, gives an

insight into the architecture of an enterprise platform to enable and

exploit translational medicine advances.

• Vladimir Novakovskiy, Congenix, illustrates the growing opportunities

to use broad patient populations and clinical services in Eastern

Europe.

We are extremely grateful to our authors for their contributions and

insights, and trust you will find their views stimulating and enlightening.

Oracle’s vision is to embrace these emerging approaches and maximise

benefit to all by providing an integrated platform of solutions for life

sciences and healthcare organisations to enable collaborative research

and, ultimately, drive better patient care.

We look forward to your feedback and to working in collaboration soon. ■

Embracing New Challenges Clinical Development – The New Opportunity

© T O U C H B R I E F I N G S 2 0 0 7

Jonathan Palmer is Business Development Lead for Oracle’sClinical and Pharmacovigilance Solutions across Europe, theMiddle East and Africa. He has 17 years of clinicalexperience. He began his career as a statistical programmer,then moved through the rapid growth of the contractresearch organisation (CRO) industry, ultimately beingresponsible for clinical solutions and support at Parexel. Hehas had numerous roles at Oracle and IBM, helping lifescience organisations realise benefits from implementingnew clinical technologies.

Nicholas Giannasi, PhD, is Senior Business DevelopmentDirector, Life Sciences at Oracle, responsible for the LifeSciences business in Europe, the Middle East and Africa. Beforejoining Oracle in 2006, Dr Giannasi was at GE Healthcare, aUS$15 billion unit of General Electric, where he was Head ofthe Informatics Business and Director of Business Development& Licensing Discovery Systems, as well as being a Member ofthe GE Healthcare Strategic Marketing Executive. He led aglobal team for Sales, Marketing, Support and Research andDevelopment. His career also includes success at a number ofsmaller bioinformatic companies; he was co-founder of a start-up biotech company and an advisor to investment funds. Dr Giannasi holds a PhD in Population Genetics and afirst-class Bachelor degree.

Foreword

4

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5© T O U C H B R I E F I N G S 2 0 0 7

a report by

Michel le Grayson

Managing Editor, Medical Communications, Touch Briefings

eClinical is no longer just a buzz-word, but a business and scientific reality.

An eClinical trial is defined by the Clinical Data Interchange Standards

Consortium (CDISC) as a study “in which primarily electronic processes are

used to plan, collect (acquire), access, exchange and archive data required for

conduct, management, analysis, and reporting of the trial”. Electronic data

capture (EDC) is one element of this, and the adoption of this technology to

drive forward drug research is gaining pace, championed by the

pharmaceutical industry, primary healthcare providers and regulators. The

next step, or ‘eClinical Phase II’, is to move from a data-capture-centric world

to one of data exploitation and exploration. All stakeholders have a vision of

technology convergence that will provide efficiencies in drug development,

greater patient safety and improvements in patient care. Although still in its

early stages, eClinical has the power to transform pharmaceutical research

and development, and the continuing evolution of technology will help to

advance convergence across the value chain.

Technological development continues apace, fuelled by Moore’s law –

making more power available more cheaply and in a smaller package.

Many different areas of modern living are in some way affected or

enhanced by electronic help, and the life sciences are no exception. “As

the biopharma industry grapples to cope with a variety of major

challenges confronting it – from expiring patents to adverse events to

stagnating pipelines – it must continually search for better and more

efficient technologies to speed the flow of drugs into and through clinical

trials. The cost of drug development is likely to soar to a staggering

US$2 billion per IND [investigational new drug] by 2010 unless new

technologies and strategies can turn things around,” observes Kevin

Davies, PhD, Editor in Chief of Bio-IT World.

However, for every one advance there are at least two new questions that

need to be answered. EDC means that pharma are now swimming in

deep pools of information; the next big challenge is to efficiently store

and make sense of it all.

Industry Acceptance

Last year, Cambridge Healthtech Institute (CHI) conducted a survey on the

practices, views and plans of 55 pharma directors and vice presidents –

many of whom were from top 20 firms – concerning a variety of

technologies that have an impact on clinical trials now and in the future.

According to the CHI data, half of respondents believed that EDC,

particularly electronic case report forms (eCRFs), is in routine use today

(see Figure 1). A further 28% thought EDC would be endemic by 2008.

Survey respondents indicated that advances such as the use of clinical

biomarkers and offshoring of clinical trials are in mainstream use today.

Adaptive design is still a year off, and microdosing (‘phase 0’) will not

become routine until 2010.

Putting the ‘e’ in R&D

Introduction

Figure 1: When Do You Expect the Following Clinical Technologies and Practices to be Routinely Integrated Into Clinical Trials AcrossMost Applicable Therapeutic Areas at Your Company?

0

10

20

30

40

50

60

Percentage agree

Now 2008 2010

Year

2012

BiomarkersEDC (eCRF)Adaptive designOffshoringMicrodosing

EDC = electronic data capture; eCRF = electronic case report form; Microdosing = ‘phase 0’. Source: Insight Pharma Reports, March 2006. Contact: Mike Goodman, Editor-in-Chief, [email protected]

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6 D A T A M A N A G E M E N T I N P H A R M A C E U T I C A L R E S E A R C H & D E V E L O P M E N T


Offshoring, most notably in the Asia-Pacific region, can save costs –

particularly in expensive phase III trials. There are other advantages in

terms of access to diverse and treatment-naïve patients (elaborated in the

Novakovskiy article), but with all advances there are new issues to

overcome such as legal and intellectual property (IP) problems,

understanding different national regulatory environments and standards

of care, training study personnel and coping with ethical issues.

Tellingly, more than three-quarters of CHI’s respondents had already

implemented EDC in clinical trials, or were planning to by 2009. EDC

equipment such as eCRFs and eDiaries were also popular tools in which

pharma will likely invest (see Figure 2).

Davies from Bio-IT World elaborates: “The arrival of technologies such as

EDC have had a great impact in this regard (speeding up clinical trials), in

large part because every day saved in clinical trials could translate to

US$1 million or more in drug development cost savings. But EDC is not a

solution unto itself. The integration of EDC allows other disruptive

technologies, notably adaptive trial designs, to become much more

commonly adopted across the leading pharmas.”

Putting Into Practice

There is a huge gulf between saying and doing, and implementing the

eClinical vision takes more effort and planning than simply flicking a switch.

For instance, CDISC recommends that certain issues be considered during

a technology selection process, including, among others: the hosting

environment – in-house or externally hosted; user acceptance, promoting

flexibility and accessibility; user support, again whether provided in-house

or by a third party; regulatory requirements, e.g. 21 CFR 11; cost; and

support for the standards (see the Lastic article for more information).

Partly for these reasons, companies are cautious of implementing new

technologies, with the result that the drug development industry has been

a “slow-adopter” of new technology, says Dr Ron Fitzmartin, President-elect

of the Drug Information Association (DIA) and Vice President of Informatics

and Knowledge Management at Daiichi Sankyo Pharma Development.

As an illustration, he points out that the US Food and Drug Administration’s

(FDA) Critical Path Initiative and the European Medicines Agency’s (EMEA)

Roadmap both mention the slow uptake by pharmas of technologies that

have the potential to “move clinical trials to a different level”. Two of the

main initiatives in the Critical Path are the use of biomarkers and adaptive trial

designs, neither of which can be realised without technology. “The FIREBIRD

initiative and the adoption of CDISC standards are just two examples that

show that the FDA wants to become an ‘eFDA’,” Fitzmartin adds.

According to Fitzmartin, better drug development comes from improved

processes, which can be optimised by technology, but not controlled by

it. “The core competency of pharma development is pharmaceutical

development, not information technology. So, pharma need to

understand and leverage technology, but not to build it ab initio,” he

opines. The bottom line is that, with Moore’s law dictating pace of

change, “pharma must be able to deploy new technology in six months

or fewer, otherwise the technology will have moved on”. ■

Figure 2: Please Rank the Top Three Technologies in Which Your Company Will Invest Over the Next 12 Months

0

10

20

30

40

50

60

70

Weighted number of votes

CTMS EDC Datamining

Legacydata

eSub Virtualpatient

RFIDs

3rd Choice2nd Choice1st Choice

Future technologies

CTMS = clinical trials management system; EDC = electronic data capture, including electronic diaries and case report forms; data mining includes extraction and reporting tools; legacy data =integration thereof, both structured and unstructured; eSub = structured electronic submissions; virtual patients = computational models; RFIDs – radio frequency identification tags to managethe clinical supply chain.Source: Insight Pharma Reports, March 2006. Contact: Mike Goodman, Editor-in-chief, [email protected]

EDC is not a solution unto itself.

The integration of EDC allows other

disruptive technologies, notably

adaptive trial designs, to become

much more commonly adopted...

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7© T O U C H B R I E F I N G S 2 0 0 7

a report by

Nicolas Schaltenbrand , PhD

Senior Director, Global Data Management, Quintiles

The rationale for switching from paper-based to eClinical trials is clear, as

readers of this report are, no doubt, already aware. Using an electronic

data capture (EDC) solution brings cost-efficient improvements in quality

of data and a huge reduction in database closure time. However, the

difficulties in making the transfer from paper to EDC on a large scale

should not be underestimated. Pilot studies carried out in the last five

years identified major areas where such large-scale clinical trials may

encounter problems, in particular IT, planning and the reworking of data

management processes.

While the general pace of progress since 2001 has ensured that

software issues and shortcomings in strategic planning have largely

resolved themselves, managing the wholesale procedural change in

the switch from paper to eClinical continues to offer challenges. New

processes must be controlled and integrated with those of the sponsor

organisation, on-site equipment needs to be delivered to site and

installed and investigators must be trained and given access to

software support.

Globally, paper-based systems still predominate – only 35% of studies

currently use EDC. Bringing the other 65% into the eClinical fold

depends on the ability of contract research organisations (CROs) to

answer logistical and organisational problems and provide the sponsor

organisation with a turbulence-free migration.

Integrated Approach – Hybrid Solution

One of the main criteria that must be considered by a sponsor company

when selecting an EDC solution is its ability to integrate with existing

in-house systems once the clinical trial process has finished and the

database has closed or ‘locked’. As the majority of global players in the

pharmaceutical industry have evolved their own systems – often

predating the eClinical revolution – the degree of compatibility between

the existing and incoming system will be critical.

With time-frames for clinical trials spanning decades, an EDC solution

must also be able to anticipate the arrival of new versions or systems. As

such, the CRO must provide a solution that meets current industry and

company-specific requirements, but that is also standardised enough to

allow migration or upgrading to a new solution for the next generation.

Issues Associated with Large-scale EDC

The most obvious difficulty to overcome is the sheer size of the project

that needs to be dealt with. Certain therapeutic areas require large and

complex clinical trials with long study duration and a global range of site

locations. These studies include a huge volume of concomitant

medication and potential adverse events, and in some cases can last for

many years. In areas such as oncology, long-term patient follow-up can

last anywhere between five and 10 years.

Studies of this size generate vast quantities of laboratory data that need

to be processed and analysed. Any CRO running a trial like this needs to

create a single database that consolidates all the constituent datasets –

laboratory, coded and randomisation data – into a single central

information repository that can be accessed at any time from any place

for the duration of the study.

Process and Organisational Change

The large-scale deployment of EDC involves substantial re-engineering of

the sponsor’s existing clinical data management system (CDMS). The

complexity of this operation should be duly factored in at the planning

stage of the trial, as experience has shown this undertaking to be

particularly time-intensive.

Clinical trials require that accurate records be kept of the case report form

(CRF) – which frequently extends to more than 100 pages per patient –

and of the number of visits made by the patient. It is also vital that the

data are consistent between visits. In addition, the coded terms used to

describe all conditions and adverse events must be monitored to ensure

they tally with the global library.

Large-scale Electronic Data Capture – When Size Is Not the Only Issue

Nicolas Schaltenbrand, PhD, is Senior Director of GlobalData Management at Quintiles. He has 17 years ofexperience in the pharmaceutical industry and clinicalresearch environment. Prior to joining Quintiles, Nicolasspent five years in applied research managing the designand development of data mining techniques in thebiomedical field. Following that, he performed various rolesin the pharmaceutical industry and contract researchorganisations (CROs). He joined Quintiles in 1998 asDirector of Data Management, where he is in charge of theorganisation and management of all aspects of data fromclinical studies at the Strasbourg office. In 2007, after thecompletion of a Masters degree in Business Administration,Nicolas took responsibility for the whole of Quintiles Franceas General Manager.


One of the main criteria that must be

considered by a sponsor company

when selecting an EDC solution is

its ability to integrate with existing

in-house systems…

Schaltenbrand_edit.qxp 4/6/07 5:03 pm Page 7



It is not only hardware and software that need to be considered. The

shift from paper- to web-based trials is accompanied by training

requirements for all users. Bringing investigators and other personnel

up to speed in processing information via EDC represents a top priority

for both the CRO and the client organisation.

The early years of training in EDC implementation generated higher

costs than are common now, as users three to four years ago were

much less accustomed to web-based data management. As well as

being cheaper, the learning curve is now less steep because

investigators have become more familiar with EDC systems.

Nevertheless, training of personnel is intrinsic to any long-term study,

and retraining on a yearly basis is necessary to ensure that

competencies are maintained. CROs need to consider establishing a

dedicated training group to give specific software-related training and

technical support to the investigators.

There are considerable logistical challenges in providing the

infrastructure for global deployment of EDC. In the large-scale projects

discussed here – where an EDC solution is rolled out across perhaps

45 different countries – the compatibility of logistics becomes critical.

The tasks of providing on-site equipment and establishing Internet

access in regions poorly equipped in IT infrastructure are tricky and any

CRO undertaking this kind of operation should be prepared at least for

connectivity difficulties, even if the general picture for global

connectivity is rapidly improving.

Such issues are where prior experience becomes vital in order to

understand and negotiate around potential problems, for example with

import or customs departments or perhaps with security of data or

Internet connection. A dedicated and multilingual call centre is essential

to ensure the coherence and smooth function of an EDC solution on a

global scale. Such a facility needs to be fully versed in software and

connectivity issues and able to offer support in the event that the system

experiences difficulties.

Case Study

Quintiles is one CRO with vast experience of tackling large-scale EDC

challenges. This particular case study was a large phase III trial,

comprising the study of 12,000 patients in 35 countries over a three-

year duration.

Like many large-scale EDC trials, the sponsor of this trial required a

customised solution that smoothed the migration between paper and

eClinical. The resulting hybrid solution was able to accommodate both

mechanisms for data capture – starting with paper and moving to

EDC – while allowing the speed of migration to EDC to be staggered

from site to site, albeit within the same organisation. As part of the

service, Quintiles provided the site assessment and all the computing

equipment, set up the help desk, trained the investigators and

established an electronic CRF and data cleaning process (see Figure 1).

The IT requirements for this project presented logistical challenges typical

of large-scale EDC studies. Laptop supply and Internet connectivity had to

be provided to sites in 35 countries and standard computer images were

built into the solution to facilitate database navigation and

communication between users.

Specific to this project was a particularly high provisioning rate: 40% of

sites required computers and 20% needed Internet connection to be

set up. This, coupled with poor IT infrastructure or governmental

obstruction in some countries, led to significant delays in providing

Internet access to particular sites. Similar delays were also experienced

with the customs service of certain countries in the delivery of on-site

EDC Clinical Study

Site Assessment

Order/delivery Site Provisioned Equipment

Support & Helpdesk

Hosting StudySet-up

eCRF Design

MonitorTraining

InvestingTraining

Site Switch to EDC Solution

Paper Process

User Acceptance

Test

April July Sep Oct Jan

Go liveJune June

Figure 1: Example of Processes Necessary for a Large-scale EDC Project

A dedicated and multilingual call centre

is essential to ensure the coherence

and smooth function of an EDC

solution on a global scale.



Large-scale Electronic Data Capture – When Size Is Not the Only Issue

equipment. As part of the provisioning, Quintiles provided a

multilingual helpdesk, available 24 hours a day and seven days a week,

to support EDC software and connectivity. The volume and type of calls

received provided valuable feedback for Quintiles on the range of issues

that users encountered (see Figure 2).

To resolve the software, connectivity and user account issues identified

in this trial, Quintiles also set up a study web portal designed to

complement the helpdesk and allow the end-user to submit account

requests and password resets via email. The study web portal also

served as a second point of access to information on the clinical trials.

General study documents – such as protocol and eCRFs – were made

available to users, who could also access performance metrics and a

study contact database that included all the people connected with

the EDC solution.

On a more functional level, the study web portal allowed users to review

patient listings prior to the patients’ arrival at a hospital or medical centre.

Thus, staff were able to anticipate and prepare in advance of a visit. Last

but not least, the study web portal gave easy access to patient profiles

for use in medical review (see Figure 3).

Summary

The benefits of deploying a fully integrated paper and EDC solution as

described above are clear-cut. The traditional paper-based process and

electronic data collection via Internet can all be implemented within a

single database where all information can be viewed in parallel by

multiple team members. Furthermore, a central point of access to all

patient listings and study documents is available via the web study

portal. The hybrid system obviates the risk of paper loss – all images are

available online – improves the cleaning process and provides easy

access for data review.

We have reached a tipping point in the deployment of EDC. More than

one-third of trials now use EDC, and the next two to three years will see

rapid expansion across the rest of the sector. It is vital that CROs

understand the issues and take the needs of the sponsors into account in

order to ease the migration from paper to eClinical. ■

Figure 2: Sample of Problems Encountered by Users (From Helpdesk Log)

User account 45% Software 5%

OC RDC 16%

Hardware 4%

General 10%

Connectivity 20%

Figure 3: Study Portal

The traditional paper-based process

and electronic data collection via

Internet can all be implemented within

a single database where all information

can be viewed in parallel by multiple

team members.

ASP Quick-start Services for Oracle Life Sciences Suite

Hosting • Site Assessment and Provisioning • Helpdesk • Support


a report by

Barry Burnstead

Director of Project Management, i3 Statprobe International

The enthusiasm of both the pharmaceutical industry and regulatory

authorities to adopt new technologies such as electronic data capture

(EDC) systems and electronic patient diaries is a powerful reason to

change the established practices of collecting safety data. This article

examines the pressures and opportunities for safety data management in

the brave new world of eClinical development. Specifically, it will address

the question: ‘Will single-source serious adverse event (SAE) data

collection via EDC become the industry norm?’

Safety data on pharmaceutical products are collected during clinical

testing and continue to be collected after the product is on the market.

Each pharmaceutical company needs a pharmacovigilance department to

record all SAEs, while the team undertaking clinical testing will

concentrate on all AEs that occur during their trials. Traditionally, clinical

trial results were recorded on paper in a case report form (CRF), to be

collected weeks later. This process was not fast enough for the

pharmacovigilance team, who need to report deaths within seven days of

their being recorded and SAEs within 15 days. Thus, there was a

separate, fax-based system for reporting SAEs for pharmacovigilance

purposes, and management of safety data was effectively performed by

two operations in parallel, albeit with contrasting objectives.

For many years these two operations co-existed harmoniously, inasmuch

as pharmacovigilance and clinical data management barely

acknowledged each other’s existence. This dual system required that the

common SAE data in the two databases be tediously reconciled – a

sobering reminder that the industry had created two sources and

independent procedures to handle the SAE information from a clinical

trial. Nevertheless, it appeared to work.

So what has changed? The drive to accelerate data acquisition and

improve data management led to the development of new technology.

EDC was one result, and it has taken more than a decade to become

established. However, recognition of its wider impact has been even more

pedestrian: pharmacovigilance operations have continued with their paper

and fax solution for acquiring SAE data. What has become clear, however,

is the fact that clinical data management operations using EDC are

potentially receiving notification of an SAE before pharmacovigilance, and

with better quality and transmission success rate than the faxing

procedure. It has therefore dawned on the safety departments that they

are vulnerable to becoming non-compliant with regulatory reporting time-

frames while remaining blissfully unaware of this.

Yet nothing that is being implemented is revolutionary. An automated

e-mail alert whenever an SAE is reported via EDC might effectively

address the compliance concern, but it fails to eliminate redundancy and

obviate the generation of conflicting data. Continuous SAE reconciliation,

automated SAE reconciliation and e-mail alerts are laudable responses to

the advent of EDC. However, the present situation cries out for more

courageous intervention and radical process improvement.

One Source Fits All

Herald the arrival of single-source SAE information. The safety mavericks

among us have recognised how the functionality of EDC can be as

beneficial to the collection of our own SAE data as it is for clinical trial

information. For example:

• the quality of SAE data can be enhanced by use of instantaneous

dynamic data checks, which can send out an alert when data lie out

of plausible ranges;

• data can be transferred into the safety database within 24 hours,

enabling the more complex checks developed for the safety database

to be run sooner and for queries to be presented back to the site at

the start of the next working day;

• the tedious task of SAE reconciliation is eliminated and, along with it,

any queries that are presented back to the site weeks or sometimes

months after the event, which all too frequently compromise rather

than enhance data quality; and

• as it is a new communication medium, EDC can ensure that important

safety information – and advice on how to report it – can be conveyed

to the whole investigator community if necessary.

Above all, the most eye-catching benefit is the fact that data are collected

once only. Nevertheless, there is a distinct lack of enthusiasm to embrace

EDC from the pharmacovigilance world, despite the fact that it is a more

efficient means of capturing information at the investigator site. Perhaps

there is a political or cultural divide between the two operations?

Electronic Safety Data Management – The Dawn of a New Era, but Are We Awake to the Consequences?

© T O U C H B R I E F I N G S 2 0 0 7

Barry Burnstead is the Director of Project Management inthe international division of i3 Statprobe, Phase Forward. Hehas worked in the pharmaceutical industry for over 30 years,beginning at Beecham Pharmaceuticals, working initially ‘atthe bench’ before establishing a Statistics and DataManagement Department to support worldwide early-phaseclinical trials. He remained at the company following itsmerger with SmithKline French. Since leaving, Barry hasbeen involved in the contract research organisation (CRO)business, even co-founding his own CRO in Germany. InAugust 1999, he joined Domain Pharma as a SeniorBusiness Consultant, expanding his role to cover the globalimplementation of safety systems for five major companiesand, after Phase Forward acquired Domain, becoming globalHead of Programme Management. Mr Burnstead is also anactive member of the Drug Information Association (DIA)and recently received a Lifetime Membership Award inrecognition of his contributions. He is also a member of theEuropean Clinical Data Interchange Standards Consortium(CDISC) co-ordinating committee.


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Electronic Safety Data Management – The Dawn of a New Era, but Are We Awake to the Consequences?

Opportunity knocks for the ‘pharmacovigilantes’. One company going for

first-mover advantage is GlaxoSmithKline (GSK). Speaking at the Drug

Information Association (DIA) EuroMeeting (26–28 March 2007 in Vienna,

Austria), GSK’s Director of the Case Management Group announced that

for the company’s research operation, capture of SAE information via EDC

has moved from pilot mode into production. This means that GSK has had

to refine its business practices for capturing all safety information required,

both for expedited reporting and for inclusion within the clinical report.

Pharmacovigilance gained responsibility for the safety data area within

EDC, and could specify the data to be transferred to the safety database.

Working rules have been established and political sensitivities addressed,

but have not been allowed to dictate. The benefits of dynamic on-line

checking of SAE data are emphasised. True single-sourcing of SAE data

eliminates reconciliation and ensures that no conflicting information is

submitted to the competent authorities and the European Agency for

the Evaluation of Medicinal Products (EMEA). The process is illustrated in

Figure 1. GSK is to be congratulated on achieving a harmonious business

solution that will deliver increased efficiency.

Reading the Signals

All of this effort, both technical and political, can be justified on the

grounds of efficiency in SAE data collection, yet further associated benefits

exist. There is a lot of pressure on drug developers to cut costs, and one of

the ways in which this can be done is to ensure that ineffective, poor or

dangerous drugs are identified as early in the development cycle as possible

to prevent any more time or money being lavished on them. This has

focused attention on the clinical trials (CT) database. Collecting all SAE

information via EDC and then loading it into a catch-all clinical data

management system (CDMS) will actually lead to an enrichment of the

content of the CT database. An aggregated CT database would hold all the

data associated with the investigational medicinal product (IMP) and would

therefore be used for running algorithms to detect early safety signals. In

fact, this environment could ultimately support continuous signal detection.

The benefits of a single-source electronic safety data collection system do

not end there. There is a further, less obvious regulatory perspective. For

several years now, the US Food and Drug Administration (FDA) has asked

to have access to the raw clinical data for clinical study evaluation

purposes. In the paper world this was simply a case of providing access

to the CRFs. So well established was this process that the first response

to EDC was simply to translate the requirements directly and recreate the

CRF as a pdf file. Current activity is focused on CDISC’s study data

tabulation model (SDTM), which is a recognised format for submitting

electronic information to the FDA, and effectively replaces the CRF

listings. One should recognise that the FDA is the only agency requiring

the raw clinical data and hence the only agency to take a specific interest

in this particular CDISC model.

Watching the Detectives

In a new move (March 2007), the FDA’s Center for Drug Evaluation and

Research (CDER) and Center for Biologics Evaluation and Research (CBER)

have launched a search for five partners to participate in an operational

data model (ODM) XML transfer pilot. ODM was developed as a means

of transferring complete databases, with the key being that it is platform-

independent. This request essentially confirms the FDA’s interest in

metadata and audit trails, covering all the SAE information in the

database and any changes that have been made to it. One might

speculate on the motives behind the FDA’s interest: why would it wish to

view all these data? Perhaps the FDA wishes to:

• import the whole of the study data into its new database, Janus;

• inspect audit trails to assess consistency and objectiveness; and

• ultimately be reassured of the authenticity of the data.

What are the ramifications of this request? Access to the source data

offers the assessors greater confidence about any SAEs and their

collection than is currently supplied via the pharmacovigilance route. This

is because the data in an ODM file will expose quite different information

than an E2B file. For example, a user might change the Medical Dictionary

for Regulatory Activities (MedDRA) coding of an SAE, and this change will

be recorded in the audit trail and be immediately available to the

assessor. Such changes can now be assessed for consistency and absence

of bias, which are very difficult to detect in individual case summary

reports and product safety update reports.

Other important pieces of information are the date stamps, which will

provide unequivocal evidence of when these data were received in

the sponsor database. This places pressure on pharmacovigilance

departments to ensure they report within the statutory timeframes. One

can speculate on motive and paranoia sets in, but a sponsor ultimately

wishes to submit quality data that cannot be challenged.

Whatever the purposes and consequences of an ODM XML file may be,

it raises the spectre of data consistency and a need for pharmacovigilance

to be aware of new information on an SAE provided in ODM of which

they may have been blissfully unaware. One can speculate on the

consequences of authorities uncovering conflicting data on an SAE

occurring within a trial, but it is reasonable to assume that confidence is

undermined and the likelihood of an audit is increased.

Personally, I see the FDA’s interest in ODM XML as bringing further

pressure upon the pharmaceutical industry to adopt single sourcing of

SAE information. EDC offers the best medium for this. The pot of gold at

the end of the rainbow is the promise of casting SAE reconciliation into

the history books forever. The electronic era has placed the two

independent processes for SAE data collection under the spotlight, and

to answer the opening question: yes, single-source SAE data collection is

the obvious solution. Dual SAE data recording will be judged to have

become a luxury that drug development can no longer afford. ■

EDC Database

SafetyDatabase

eSubmissionof ICSR

ODM XMLfile

Query resolution

Report1. Transfer an E2B

file equivalent

3. Query resolution

2. Query transfer

Routine EDCchecking process

SITESAE

Ultimately a paperlessprocess from site to

regulatory submission

Figure 1: Single Sourcing of SAE Data

Burnstead_edit.qxp 4/6/07 4:54 pm Page 11

a report by

Sharon Marmaras

Director, Clinical Trial Support and Life Sciences Data Hub (LSH) Business Project Leader, Boehringer Ingelheim

The integration, analysis and reporting of data collected in clinical

trials is one of the critical paths in drug development. Challenges

arrive from integrating data from multiple sources. Furthermore, the

analysis of this data must be controlled and must deliver reproducible

results. Data from clinical trials are captured, cleaned, processed,

reported and archived using appropriate computerised tools. These

tools support various aspects of the research process, such as trial

design, data entry, source document tracking, data cleaning, analysis

and reporting.

Problems arise when multiple data sources need to be shared. Often,

problems linked to sharing data between different systems are

addressed by several one-to-one links between the various systems. This

results in considerable maintenance effort and version dependencies.

Typically, data transformation and reporting programs are developed by

copying files from a file system, which are then edited, possibly trial by

trial. Managing version control and the testing cycle is a major challenge

in such an environment. Accordingly, integrating data across the

systems is time-consuming. Because data are dispersed, end-users

cannot access crucial information without the involvement of a

technically skilled person. Such delays during regulatory submission

preparation are very costly.

Boehringer Ingelheim (BI) currently uses Oracle Clinical (OC) as its

clinical data management system (CDMS) to perform clinical data

management functions. Data in OC are depicted in a relational

structure, which does not implicitly support reporting, but does allow

flexible study set-up and data entry. However, in OC it is difficult to

handle cross-trial data and to perform the sophisticated data

transformations required for statistical analysis. Reporting and analysis

are currently supported by an SAS-based system developed in-house,

CARE (Clinical data Analysis and Reporting Environment). CARE was

developed to reduce global programming effort within BI, by providing

a standard environment for generating the tables, listings and figures

for clinical trial reports. CARE promotes a harmonised SAS environment

across the corporation, through standardised OC database structures,

SAS data libraries, a library of standard SAS programs and the use of an

SAS-based report appendices generator (RAGe) to apply headers,

footers and a table of contents to the SAS output. Using CARE, data

managers and statisticians create their own tables, listings and figures

for the reporting and analysis of clinical data. The analysed data are

then collated and published using Documentum®.

The Life Sciences Data Hub

BI needed a solution where data could be loaded by end-users from a

variety of sources (e.g. OC, SAS), where programs and reports could be

built from a library of re-usable standards, and all authorised users could

easily access the data they required. In addition, the automation of some

of the process would be an extra benefit.

To achieve this, BI wanted to establish a unified environment for

clinical data building, analysis and reporting at a global, cross-trial and

individual trial level – effectively, a central global repository for data,

which would integrate data from multiple sources and help to move

BI’s processes in the direction in which the industry is headed in terms

of eClinical development.

BI put out a set of user requirements that the company felt were

essential from the system and put up several requests for proposals to

different groups. BI’s main considerations were for a central global

repository that allowed users to be able to work in a secure location. BI

also wanted to integrate SAS (the skill-set of the organisation) to

promote the use of standards and reusability by use of library functions.

BI also wanted its medical personnel to be able to review data easily with

a user-friendly interface – the current data management system is often

considered too complicated for non-technical personnel. The new system

also needed to support regulatory requirements such as US Food and

Drug Administration (FDA) 21 CFR part 11 compliance. Other key

requirements identified by BI included:

• enabling a configurable workflow, e.g. to support users in the

validation of programs;

• facilitating the import/export of data, together with associated

metadata and programs, to send to regulatory authorities and

contract research organisations (CROs); and

• providing archiving functions.

BI had originally contracted a company to build a customised system.

However, Oracle approached BI with a view to building a tier 1 product

in collaboration with a partner from the pharmaceutical industry. A

consortium was formed – the current partners being BI, Oracle and

IBM – and development began on the Life Sciences Data Hub (LSH) in

2000. The LSH is not intended to specify the standard reporting

programs, but to provide an interface for creating, maintaining and

running these programs. BI will develop standard programs in parallel.

Data Loading

To allow clinical data reporting in the LSH, the data needs to be made

available from the external source systems by loading them into the LSH.

Loading data is handled through predefined adapters. Adapters for OC,

Oracle tables, SAS datasets and ASCII files are shipped with LSH. Data

loading may be accomplished by physically copying data into LSH or by

just defining views onto the source system. There are two components to

Data Integration – Business Requirements and Implications for Data Standards

© T O U C H B R I E F I N G S 2 0 0 7


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Data Integration – Business Requirements and Implications for Data Standards

loading data – the metadata that describe the structure of the data to be

loaded, and the actual data source supplying data to LSH. After loading

the clinical data, together with the metadata, into the LSH, they can be

further processed and transformed within the LSH to prepare analysis

datasets, to perform data building for reporting or to combine them

across trials to build a project database.

Programs in LSH are created to transform, analyse and report data. The

LSH’s interactive development environment (IDE) allows users to write

program logic (i.e. source code) for data transformation and reporting

programs in the IDE, and to save source code files in LSH for re-use.

Reporting Data

One of the primary goals of LSH is clinical data reporting, which is

accomplished with the use of report sets. Company standard templates

will be available for standard reports, such as clinical trial reports and

other internal review reports. At BI, programs for analysing and reporting

clinical data are developed in the SAS IDE in the same way as programs

for data transformations. For other reporting purposes, e.g.

administrative reporting, Oracle Reports might be used.

Visualisations provide easy and user-friendly access to data for data

visualisations and exploratory data snooping by non-programmers. The

LSH allows users to view data using tools such as Oracle Discoverer or

other commercially available review tools. BI intends to use a

visualisation tool as a review tool for clinical personnel during the

conduct of clinical development.

A validation life-cycle can be defined for all programs developed in LSH.

For example, a program may move through these statuses: under

development, ‘in test’ and in production. The validation life-cycle is

customisable and will be adapted to match BI’s development process. All

output is labelled with the validation status of the program that produced

it in order to make it obvious on which validation status an output is

based. All changes to data and metadata are audited.

The Benefits of Data Integration

After the first implementation phase to bring the LSH into production at

BI, we intend to integrate further BI systems into the LSH with the goal

of establishing an integrated reporting environment for a wide spectrum

of data generated in clinical development.

In terms of business benefits, having one central global data repository

will be the biggest benefit. As a global company, with clinical studies

running all over the world, data can be in several locations. With the LSH

we can put all data in one place, which gives BI the opportunity to reuse

programs, further facilitate the use of standards and reduce cost and time

for the development of programs.

The LSH will be able to pull data from the database that you may be

working in, together with data from multiple trials, which will enable

reporting on one substance or one indication. Furthermore, there is the

potential to integrate administrative trial data with clinical data or

integrate drug safety data with clinical data.

In essence, the LSH is one security concept, one central application.

Although the LSH has only been running in non-production mode since

March 2006, in terms of the maintenance effort it has definitely been

easier for BI’s administrative people.

No major issues have been encountered with data integration. However,

the reporting components of the LSH still need additional refinement and

we are still working towards improving certain aspects of functionality

and the user interface. BI is working very closely with Oracle on

recommendations for improvements. In addition, Oracle plans the

development of an improved interface to Documentum, which will satisfy

the needs of the company.

While it is still too early to comment about real benefits – BI has yet to

run a pilot study on real data – several simulations, run for proof-of-

concept purposes, have demonstrated that the benefits that could be

realised include improved quality and speed of summary information,

facilitating the reuse of standards.

Essentially, the LSH has the potential to introduce significant

improvements in efficiency, which in turn can reduce time and cost for

drug development. The integration of multiple data sources also

increases the knowledge across the company. As a company BI has been

promoting standards for some time. As such, the LSH will provide the

opportunity to introduce a stricter standardisation of data.

Summary

BI envisages that the LSH will help to:

• increase the quality and speed of summary information available for

decision points;

• reduce the time and cost of the drug development process by

supporting the use of company standards and the sharing/re-use of

user programs;

• automate and facilitate company validation efforts;

• increase drug development knowledge by integrating multiple

company data sources;

• transform data to information;

• increase knowledge of our drugs.

LSH will close the gap between the collection and tracking of clinical data

and the submission of the analysed data to regulatory agencies, and

when the LSH is a part of the company’s reporting process, we expect to

see a significant improvement in efficiency. Currently, the learning curve

is fairly steep and that curve needs to be brought down, either through

improving the graphical user interface of the system or through the

development of training materials. Finally, BI plans to go into pilot phase,

with a live study, in September 2007. ■

Originally published in The eClinical Equation: Delivering the Vision,

Touch Briefings/IBM, 2006.

Visualisations provide easy and user-

friendly access to data for data

visualisations and exploratory data

snooping by non-programmers.

Marmaras_edit3.qxp 5/6/07 12:04 pm Page 13

a report by

Pierre-Yves Last ic , PhD

Senior Director, Standards Management & Data Privacy, sanofi aventis R&D

Most individuals involved in the collection, validation, coding, transfer,

analysis, reporting and archiving of data from clinical trials are generally

aware of the existence of the standards developed by the Clinical Data

Interchange Standards Consortium (CDISC).1 In fact, most people

working in clinical research across the world use these standards on a

daily basis, or at least specifications derived from or inspired by them. It

is fair to say that the majority of these people are unaware of Health Level

Seven (HL7)2 standards. On the other hand, software developers working

on hospital information systems routinely implement HL7 specifications,

but know CDISC only from hearsay. However, there is a growing

community of healthcare and clinical research professionals working with

a foot in each world. If you are not yet among them, here are a few

answers to frequently asked questions.

Where Do HL7 and CDISC Come From?

HL7 is one of several standards-developing organisations (SDOs)

accredited by the American National Standards Institute for the

healthcare arena, and has just celebrated its 20th birthday. It was born at

a time when information systems used in healthcare were not linked with

each other. This meant that patients admitted to a hospital filled in paper

forms that clerks entered into the administration system. The patient

received a printout and took it to another department, where staff would

perform the examinations and write these results on other paper forms

that would eventually be entered in a different computer. A similar

process occurred at the pharmacy and involved yet another form, which

would be attached to all the forms from the hospital; the whole paper

stack would then be filed to the insurance company for reimbursement.

Similar systems still operate in many countries. Nevertheless, growing

healthcare costs have driven a huge optimisation effort and, as bytes are

easier to move than physical forms, electronic messages are progressively

replacing paper-carrying patients. HL7 plays an important role in this

process as it has defined sets of standardised messages to carry bits of

administrative, financial and clinical information between independent

computer systems on a variety of hardware and software environments.

HL7 has also developed specifications for documents, leading the way

towards the implementation of electronic medical records. Above all,

during these 20 years of continuous improvement, HL7 has put in place

a standards development and maintenance methodology that can cope

with the extremely complex processes that are the norm in healthcare.

CDISC is only half as old as HL7. It started as a volunteer group within the

Drug Information Association (DIA) in 1997 and was incorporated in

1999. Most of the original CDISC members worked as statisticians, data

managers or programmers in biopharmaceutical companies, contract

research organisations or software providers, yet they faced a number of

similar business problems:

• agreeing about data exchange formats with development partners,

clinical research organisations and central laboratories, then spending

considerable amounts of time and resources to check and clean the

exchanged data;

• redefining internal data formats and database organisation with each

merger or acquisition;

• customising software systems to accommodate different data

models; and

• transforming and reorganising clinical study data from different

sources to be able to prepare integrated summaries of safety

and efficacy.

On the other side of the fence, the US Food and Drug Administration

(FDA) was confronted with the need to analyse data from thousands of

clinical trials, all formatted differently.

These different business cases led CDISC to develop several models: an

XML model called the operational data model (ODM) dealing with the

acquisition, validation, transfer and archival of clinical data; the LAB

model specifically for the exchange of data from central laboratories; a

submission data model (SDM; now called the submission data tabulation

model, SDTM) defining the format and organisation of raw data

submitted to the FDA for review and analysis; and an analysis data model

(ADaM) documenting the analysis process.

The Different Models

A partnership between HL7 and CDISC makes a lot of sense. HL7 can

provide proven methodology and know-how from the healthcare side,

while CDISC can contribute expertise in the clinical research domain.

The Convergence of Healthcare and Clinical Research Standards

© T O U C H B R I E F I N G S 2 0 0 7

Pierre-Yves Lastic, PhD, is Senior Director of StandardsManagement & Data Privacy at sanofi-aventis R&D. Afterworking for several years as an Assistant Professor at theUniversity of Bayreuth, he moved to the pharmaceuticalindustry where he spent 17 years in different managementpositions in the field of clinical research, leading clinical datamanagement, biostatistics, clinical operations andinformation management, first with Ciba-Geigy(Switzerland), then with Synthélabo, Sanofi-Synthélabo andsanofi-aventis (France). Dr Lastic is a member of the Boardof Directors of the Clinical Data Interchange StandardsConsortium (CDISC) and of the International PharmaceuticalPrivacy Consortium (IPPC). He studied biology, computersciences and languages in France and Germany and holds aPhD in biology from Bayreuth University, Germany.


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The Convergence of Healthcare and Clinical Research Standards

Therefore, together with the FDA, CDISC and HL7 created the Regulated

Clinical Research Information Management (RCRIM) technical

committee3 to provide a framework for common developments.

However, early attempts to harmonise HL7 and CDISC models faced

difficulties. To begin with, HL7 develops messages. By nature, a message

is transient: it contains a piece of information extracted from one place

to be delivered to another before disappearing. This is perfectly suitable

for personal medical records that consist of various documents such as

clinical examinations, laboratory results, X-rays, videos, etc. However, it

does not provide for easy access across patients or structured data

domains. CDISC, on the other hand, is built around well-defined clinical

trial protocols with strict data structures, and development is driven by

the need to use technology to improve the efficiency of the heavily

regulated clinical trial process.4

Of the CDISC models, ODM is designed to comply with good clinical

practice regulations – for example, audit trails and electronic signatures

are built in – while SDTM allows easy review and analysis across studies

and across patients – for example the ability to pool all adverse events

from several drugs of the same class, or verify the exposure of a certain

patient population to a drug across several studies.

The only CDISC model that was easily translated into an HL7 model was

the LAB model, because its primary use is the transfer of data from a

central laboratory to a clinical research database: in other words, a

message. Currently, the LAB model can be implemented in four different

ways: as a CDISC XML file, an ASCII flat file, an SAS data set or an HL7

v3.0 message.

Bringing Them All Together

The goal of information standardisation is the interoperability of

computer systems, i.e. the possibility for one computer system to

adequately process data from another system without human

intervention. The prerequisites for interoperability are known as ‘the four

pillars of interoperability’:5

1. a common reference information model;

2. unambiguously defined data types;

3. a robust mechanism to bind domain-specific terminologies; and

4. a formal top-down message development process.

Following this, a domain analysis model was developed for clinical

research that is compliant with the HL7 reference information model

(RIM). This clinical model, which eventually became the biomedical

research integrated domain group (BRIDG) model with the

participation of the US National Cancer Institute (NCI), supports the

first pillar of interoperability between hospital information systems

and systems used in clinical research and in regulatory agencies.

Data types used should follow or be translated into the HL7 v3.0

specifications.

Terminology is also an area that needs to be standardised. This is handled

by two HL7 technical committees (Vocabulary and Modelling &

Methodology), while the vocabulary itself is either drawn from existing

domain-specific terminologies – e.g. systemised nomenclature of human

medicine (SNOMED),6 logical observation identifiers, names and codes

(LOINC),7 digital imaging and communications in medicine (DICOM),8

medical dictionary for regulatory activities (MedDRA),9 etc. – or

developed within the RCRIM Vocabulary Working Group using the

enterprise vocabulary services from the NCI.10 The entire development

process is supported by a number of HL7 v3.0 tools to assist developers

in building compliant interchange structures.

Given that CDISC and HL7 develop models and specifications, not

programs, putting all four pillars in place is only a signal for the software

development work to begin; there are still plenty of issues to be resolved.

This is common for all projects that aim to link electronic medical records

with clinical research systems.

Real-life Applications

The interconnection of patient hospital records and clinical research

systems faces many issues: privacy, security, non-matching patient

identification numbers, FDA regulatory compliance (e.g. 21 CFR part 11),

etc. These have been reviewed and analysed several times, as can be

found in the references.11,12

One of the most appealing solutions to these issues is the Single Source

Project,13 which aims to have a one-time collection of data that are

subsequently rendered into multiple formats/systems using CDISC and

HL7 standards. Single Source was tested in a CDISC proof-of-concept trial

that led to the co-development of a new methodology, or integration

profile, with the Integrating the Healthcare Enterprise (IHE) initiative.14

Called Retrieve Form for Data-capture (RFD), this profile enables any

electronic health record (EHR) to retrieve data-capture forms from many

external systems.

RFD was recently demonstrated at the Interoperability Showcase at the

Healthcare Information and Management Systems Society (HIMSS) 2007

Annual Meeting.15 Similarly, the US National Cancer Institute (NCI) and

Oracle collaborate on the electronic Data Collection Instrument (eDCI)

project to develop a method of transferring the definitions and

functionality of data capture forms from the data dictionary of a clinical

data management system into an EHR.16

The Single Source approach was also recently tested at the European

Hospital Georges Pompidou in Paris with promising results.17 Data were

shown to be imported into existing EHR and electronic data capture

(EDC) systems using HL7 and CDISC standards, and work continues on

semantic integration of both sides.

Looking Ahead

All of these pilot projects show that progress is being made. For example,

HL7 v3.0 and CDISC ODM have been stable for years; the BRIDG model

Given that CDISC and HL7 develop

models and specifications, not

programs, putting all four pillars of

interoperability in place is only a

signal for the software development

work to begin…




allows data to be shared between the patient-care and research worlds;

and IHE facilitates the move from standards specifications to practical

solutions. The question now is, will we soon be feeding clinical trial

databases from hospital records?

There is no simple answer to that question. It will certainly take 10 or

even 20 years before we are able to run a multinational, multicentre

clinical trial in which the clinical trial database is populated by the

information systems of the hundreds of hospitals in all the different

countries involved. That would require all these systems to be HL7 RIM-

compliant, which cannot be achieved quickly. Many efforts are being

made to harmonise laws and regulations internationally, but it is a

lengthy process. Even within the EU, national interpretations of the same

directives are often a barrier to efficient clinical trials. When it comes to

accessing patient records from hospitals and general practitioners, a

possible solution seems even further away.

However, there are some areas where practical solutions are only a few

years away:

• For many years, clinical pharmacology units have used their own

proprietary systems to manage the clinical data of volunteers. The

implementation of HL7/CDISC-compliant standards could lower the

costs of a phase I trial by 20–30% by eliminating the source-data

verification steps and thus reducing the number of monitoring visits.

• In oncology, organisations such as the NCI or the European Organisation

for Research and Treatment of Cancer18 sponsor hundreds of clinical

trials that are run in their hospital networks. Such organisations will be

leading hospital-research interoperability within a few years.

• The development of biomarkers that, like medical images, will need

to be shared between hospitals, sponsors and regulatory reviewers

will also be a strong driver for this kind of interoperability.

In conclusion, given that EDC in clinical trials took 15 years to take off,

one can expect that healthcare-research interoperability will need a

generation to establish itself. Nevertheless, this process has already

started and will be a hot topic for the decade to come. ■

1. Clinical Data Interchange Standards Consortium,http://www.cdisc.org

2. Health Level Seven, http://www.hl7.org3. Regulated Clinical Research Information Management Technical

Committee,http://www.hl7.org/Special/committees/rcrim/rcrim.htm

4. Clinical Data Interchange Standards Consortium, ElectronicSource Data Interchange (eSDI) Group, Leveraging the CDISCStandards to facilitate the use of Electronic Source Data withinClinical Trials, Version 1.0, 20 November 2006,http://www.cdisc.org/eSDI/eSDI.pdf

5. Mead CN, Data Interchange Standards in Healthcare IT—Computable Semantic Interoperability: Now Possible but StillDifficult, Do We Really Need a Better Mousetrap?, J Healthc InfManag, 2006;20(1),http://www.himss.org/ASP/publications_jhim_issue.asp?issue=1/1/2006

6. Systematized nomenclature of medicine,http://www.snomed.org/

7. Logical Observation Identifiers Names and Codes,http://www.regenstrief.org/medinformatics/loinc/

8. Digital Imaging and Communications in Medicine,http://medical.nema.org/

9. Medical Dictionary for Regulatory Activities,http://www.meddramsso.com/MSSOWeb/index.htm

10. National Cancer Institute Enterprise Vocabulary Services,http://evs.nci.nih.gov/

11. Bleicher P, Integrating EHR with EDC: When Two WorldsCollide, Applied Clinical Trials, 2 March 2006,http://www.actmagazine.com/appliedclinicaltrials/article/articleDetail.jsp?id=310798

12. Donovan H, EHR & EDC: Tomorrow’s Technology Today,Applied Clinical Trials, 1 February 2007,http://www.actmagazine.com/appliedclinicaltrials/article/articleDetail.jsp?id=401624

13. The Single Source Project,http://www.cdisc.org/single_source/about.html

14. Integrating Healthcare Enterprise (IHE), http://www.ihe.net/

15. Healthcare Information and Management Systems Society(HIMSS) Annual Meeting,http://www.himss07.org/general/handouts.aspx

16. Kacher D, eDCI Project Report, CDISC Interchange, Bethesda,27 September 2006,http://www.cdisc.org/publications/interchange2006/session6/DonKachercdisc_edci_report.pdf

17. El Fadly N, Bousquet C, Daniel C, Facing the semantic issues inaligning HL7 CDA templates and CDISC ODM – An experimentin cardio-vascular radiology, CDISC Interchange, Bethesda, 27September 2006,http://www.cdisc.org/publications/interchange2006/session6/Pierre-YvesLasticEHR-EDCintegrationatHEGP-pyl-CDISCInterchange2006.pdf

18. European Organisation for Research and Treatment of Cancer,http://www.eortc.be/


Erasmus University Medical Centre (MC) provides advanced medical care

for three million people in the south-western part of The Netherlands,

making it the largest centre of its kind in the country. Care is organised

in three clinical branches: the General Hospital, the Sophia Children’s

Hospital and the Daniel den Hoed Oncology Centre. Erasmus MC has

achieved excellence in many areas, including cardiovascular diseases,

oncology, paediatrics, genetics and cell biology, human reproduction,

endocrinology, microbiology and virology, immunology, hepatology and

(micro-)surgery. It is among the top research institutes in The Netherlands

and participates in several nationally and internationally recognised

biobank initiatives. Research activities range from fundamental

biomedical research, patient-related research and epidemiology to public

healthcare policy and management.

Over recent decades, progress in molecular biology, chemistry and

imaging technology has provided the life sciences and healthcare

sectors with the opportunity – and the challenge – to use

unprecedented volumes of data across the entire spectrum of clinical

activities. High-throughput sequencing, such as that used in the

Human Genome Project, has provided complete genetic sequences of

growing numbers of organisms. DNA chip (or microarray) technologies

are responsible for the growth of hundreds of thousands of gene

expression and single-nucleotide polymorphism (SNP) data points on a

daily basis. Advances in proteomics are now creating a similar flood of

data on the biology of proteins. Novel in vivo molecular imaging

techniques allow visualisation of the molecular pathways that

underpin the aetiology of cardiovascular disease, neurological

disorders and, last but not least, cancer. This all requires a state-of-the-

art information and communication technology (ICT) infrastructure. To

this end, Erasmus MC’s department of bioinformatics has selected

several institutes with which to work, including US-based Windber

Research Institute (WRI) and Walter Reed Army Medical Center and

London-based Imperial College for tissue banking and data

warehousing of clinical, molecular and imaging information.

Evidence-based Therapy

Today, most diseases are diagnosed after clinical symptoms start to

manifest. Therapy is considered successful if symptoms are reduced,

but, in general, current interventions and pharmaceuticals tend to deal

with diseases at too late a stage of development. In future, novel

diagnostic technologies will allow for earlier and much more

individualised detection and treatment, and probably even prevention

in certain cases. With pressures on the pharmaceutical industry to cut

costs, yet also replace blockbuster drugs coming off patent, and with

insurance companies trying to force hospitals to run more cost-effective

operations and reduce the cost of expensive drugs, this could be an

improvement for all concerned.

Such changes will be driven by molecular diagnostic detection and a

greater understanding of biological changes at genetic and cellular

levels, which will enable therapy to target the cause of disease rather

than simply the symptoms. Biomarkers are molecular indicators that

have recently risen in importance as potential diagnostic tools. Tests can

be developed based on technologies such as proteomics,

transcriptomics and genetics to look for specific biomarkers that

support medical decision-making. For clinicians, biomarkers will play an

increasingly important role in diagnosing and tailoring a medication or

dose to that which is more likely to work for that patient’s particular

pathology. In addition, biomarkers can be used to rapidly detect

pharmacological effect, allowing new candidate drugs to demonstrate

efficacy more quickly in smaller trials. Evidence-based, personalised

therapy necessarily results in a rapid expansion of data, collected from

diagnosis, prognosis and prediction of treatment efficacy through to

administration of therapy.

The Data Explosion

Scientists in life sciences and clinical research have to deal with huge

datasets, which are then analysed and interpreted in the context of

data from internal biobanks, external sources of biomedical

knowledge and electronic medical records. These days, relating

clinical data to molecular biology data represents a critical part of

clinical research; however, this is a minefield of consent

documentation and privacy regulation. In order to make sense of the

landscape, Erasmus MC has developed computational tools and a

relational database architecture that provides shared functionality and

tools for sample acquisition, tracking, workflow management and

data analysis. While there is no universal way to integrate and analyse

biomolecular microarray or proteomics data, consistent and

reproducible methodologies are needed to analyse the vast

amounts of data obtained. Moreover, these methodologies need to

be cost-effective and also validated for clinical diagnostic decision-

making processes.

17© T O U C H B R I E F I N G S 2 0 0 7

a report by

Peter J van der Spek

Professor and Head, Department of Bioinformatics, Erasmus University Medical Centre

Scaling Up Clinical Research by Expansion of Electronic Infrastructure

Peter J van der Spek is Professor and Head of theDepartment of Bioinformatics at Erasmus University MedicalCentre (MC), one of the largest medical centres in TheNetherlands. He runs a neuroscience research programmethat provides the biological and technological basis for thebioinformatics group at Erasmus MC, concentrating on theway in which the genome as a whole contributes to theevolution, development, structure and function of the brain.Dr van der Spek has six years of pharmaceutical experiencefrom Akzo-Nobel and Johnson & Johnson and holds severalinternational academic appointments in Japan, Australiaand the US. He obtained his doctoral degree in 1995 in the field of molecular carcinogenesis by cloning cancerpredisposition genes.


VanderSpek_edit.qxp 4/6/07 4:58 pm Page 17



Storage and Database Development

To reach these demanding goals, Erasmus MC has set up a translational

medicine partnership with the WRI, which hosts one of the world’s

largest biobanks. The WRI biobank contains DNA and serum samples

from US army soldiers and their family collected through six different

medical centres across the US. Both Erasmus and WRI biobanks

co-develop on a similar Oracle-based framework.

Within this framework, programmers and analysts collaborate to

integrate clinical, histopathological, imaging, genomic, proteomic and

pharmacogenomic knowledge. This datamodel is based on Oracle 10g,

which has bioinformatics functionalities and is used for storage and

integration to support high-throughput sample processing in both clinical

and research environments. Enhancements for Oracle 11 are jointly

developed for improved digital imaging and communications in medicine

(DICOM) support for medical images.

Erasmus MC is implementing a secure ICT framework to permit the

integration of disparate data using validated capabilities from Inforsense

and Oracle (as illustrated in Figure 1). Inforsense technology has been

successfully applied by the pharma industry as well as by academia,

including the US National Cancer Institute. The research data warehouse

infrastructure project will create a platform where clinicians and scientists

from different institutions (both public and private) active in translational

medicine can work collaboratively with access to the decision support

engine’s knowledge extraction tools.

In hospitals, traditional workflows involve biologists/technicians

performing laboratory tests and then passing the results to the clinician for

use in medical decision-making, with little interaction between the two

groups. In part, it has been difficult to take advantage of this junction

because it requires an understanding that spans both domains. One way

to gain an overview of both the biomedical and clinical disciplines is to

visualise the information. Capturing and integrating multidisciplinary

knowledge, data, scripts and encoding calculations leads to knowledge

retention and best practices (e.g. good laboratory practice).

There are many potential ways in which the process of bringing diverse

molecular and clinical data together can go wrong; therefore, standards

are required for data acquisition. The bioinformatics department at

Erasmus MC plays a bridging role in these multidisciplinary interactions

and oversees the management of molecular and clinical data.

Clinical Decision-making

Erasmus MC has invested extensively in developing advanced

computational and laboratory/clinical information management

systems to collect, process, organise and visually present huge

amounts of relevant biomedical data. Translating basic research into a

form that has clinical utility requires a unifying IT platform that lets the

researchers themselves access, integrate and analyse information from

multiple data sources and make use of diverse tools to derive the

knowledge needed. Unfortunately, the IT infrastructures currently

used in academic hospitals are often inflexible and disparate – being

kept in ‘silos’ – thus hindering rather than helping such decision-

makers. Instead of providing support for dynamic and iterative thought

processes, most such ‘solutions’ end up either restricting innovation or

else rigidly dictating how users can develop their ideas and turn them

into practical solutions.

As well as focusing on their own data, researchers have to simultaneously

consider other sources of information such as from the scientific literature

and patent databases. Text-mining tools and Google Scholar, for

instance, can be helpful in understanding background information on

biomedical topics. Business intelligence tools provide the ideal framework

for placing scientific data in context, and there are various software tools

and enterprise solutions that can be used to mine data from gene/protein

databases for in silico biology applications, from the analysis of pathways

of disease and disease risk to protein–protein interaction studies.

Unravelling the genetic information encoded in the DNA of human cells

has led to a rapid progression in the understanding of the roles of our

genes in health and disease. Erasmus MC has made important

contributions to this field, and has multiple platforms for high-quality

gene and protein expression research, transgenic facilities and DNA

analysis capacity to study SNPs in population studies of more than

Figure 1: Secure ICT Framework to Permit the Integration ofDisparate Data Using Validated Capabilities from Inforsense andOracle

Virtual private database

LDAP user management

Importer(cached)

Encoded SNPdata (cached)

Userspace exportreport (cached)

Userspace exportreport 2 (cached)

Userspace exportreport 3 (cached)

SNP metadata (cached)

Patient metadata (cached)

Single sign-on

Figure 2: 3-D Virtual Reality Centre used to Examine (Molecular) Imaging Modalities



Scaling Up Clinical Research by Expansion of Electronic Infrastructure

25,000 individuals. Further progress now requires the introduction of

even more advanced IT that can cope with the enormous quantities of

data involved. Alongside delivering services and technology to all

medical disciplines in Erasmus MC, the department of bioinformatics

runs a research programme of its own, providing the biomedical and

technological basis for such activities. It concentrates on the way the

whole genome contributes to the evolution, development, structure and

function of the brain. It involves analysis of gene expression in brain

cells, combining genomics, proteomics, imaging and cytogenetic data to

identify genes associated with neurological disorders (see Figure 2).

Progressive Research

The research data warehouse helps scientists with their biomarker

discovery activities and enables them to easily access content from their

desktop and provide an integrated knowledge base for drug and disease

biomarkers. Erasmus MC currently implements an ‘-omics’ analytical

processing platform in which scientists are given support for statistical

methods and experimental design. To ensure that data are of the highest

quality possible, we are developing a standard operating procedure for

quality assessment. This will guarantee the best experimental accuracy

and reproducibility of expression microarrays, DNA SNP chip analyses and

proteomics and metabolomics data, whether the data are from Erasmus

MC or from our external collaborators.

For example, there are many methods that can differentiate between

diseased and/or treated patients. However, to ensure the analytical

validity of such a selection process requires proper estimation of

performance. A test that measures many analytes but with too few

patients can easily derive biomarkers that are not based on biology, but

that arise because of random variations. Many published studies

inadequately estimate future biomarker performance and fail to test

statistical significance using the class permutation test.

Our aim is to develop an ensemble approach to optimise classification

within a patient cohort using existing methods such as linear

discriminates, support vector machines, random forest and neural

nets. Within this framework we plan to explore the relationship

between sample size, outcome, methods, validation and parameters

for optimal patient stratification. These methods are part of our

biobank and biomarker activities in collaboration with the Erasmus MC

department of haematology to develop novel superior molecular

diagnostic and prognostic solutions in the field of acute myeloid

leukaemia (AML). Novel and existing methods will be used to define

whether the gene expression pattern (e.g. known pathways, specific

areas of the genome or clusters from a cluster analysis) over the whole

group of genes is related to a clinical outcome.

In parallel, we explore the topological properties of transcriptional

network and apply different approaches to inferring causal associations

among genes by integrating genotypic and expression data – a

necessary first step in reconstructing pathways associated with complex

traits. Our aim is to demonstrate core functional modules making up

the transcriptional networks that are readily identified in these data and

that are coherent for several core biological processes associated with

disease traits.

Skyline Diagnostics has developed an AML gene signature1 that will be

used to diagnose AML subtypes. Crosslinks, an Erasmus MC spin-out

company, will develop a robust software platform that is compliant with

the FDA’s 21 CFR part 11 guidelines that regulate the security and

reliability of electronic data for the diagnosis of AML. This will provide

secure access to the diagnostic application, maintain an audit trail and

ensure high availability of the data from the diagnostic site to the data-

analysis and management centre.

Conclusion

With the flood of data across all biomedical disciplines in large multi-

disciplinary environments such as Erasmus MC, information visualisation

is emerging as a critical component of discovery, diagnostic care and

clinical decision-making processes.

Evidence-based, personalised treatment strategies require a new class of

visualisations that are capable of displaying various data types collected

from multidisciplinary knowledge and interactions between clinicians and

supporting staff. The ability to use visualisations to cross domains and

data types provides the ability to integrate analyses and support fast,

effective clinical decisions.

With the fast-growing amounts of raw data, information and

knowledge, the need for infrastructure grows exponentially. Clinical data

need to be coupled with electronic medical records, internal biobanks

and external public domain databases. This requires a secure, scalable

research data warehouse infrastructure that needs to be developed and

maintained. Creating awareness with government, healthcare authorities

and insurance companies is important since the biomedical informatics

field progresses rapidly; also, the average budget that hospitals have to

spend on ICT is around 3% of its total budget, in contrast to the banking

industry, which invests an impressive 11%. ■

1. Valk PJ, Verhaak RG, Beijen MA, et al., Prognostically useful gene-expression profiles in acute myeloid leukemia, N Engl J Med, 2004;350(16):1617–28.

Bird’s-eye View of Erasmus MC

The city of Rotterdam selects and supports activities such as those described above throughits strategic Economic Vision 2020.


© T O U C H B R I E F I N G S 2 0 0 720

The drug development services industry constitutes a significant and

growing portion of all pharmaceutical and biotechnology drug

development activity. Sponsor companies in the life sciences industry

are continually striving for more efficient and cheaper ways to bring

compounds to market. Conducting work in countries outside the US

and Western Europe is one strategy to help reduce costs and is

becoming increasingly common, particularly for clinical trials. Here are

some illustrative facts:

• the total cost of bringing a new product to market is estimated to be

US$800–1,000 million;

• only one in five commercial products will generate a profit;

• the number of US Food and Drug and Drug Administration (FDA)-

sanctioned ‘offshore’ trials increased from 1,000 in 1991 to 7,000 in

2000; and

• the percentage of new drug application (NDA) submissions to the FDA

that include data generated from offshore trials has increased

dramatically over the last five years.

Of the various locations, Russia and ‘Russian-speaking’ countries are

particularly attractive to the sponsor companies. This is because of

Russia’s clinical trials authorisation (CTA) system and its healthcare

system, including the available investigators and subject population. This

last factor is perhaps the most important: the enormous enrolment

potential offers a solution to the competition for clinical trial patients in

North America and Western Europe.

Furthermore, Russia has a large number of big, highly specialised

hospitals that could have been specifically designed for clinical research.

These medical centres may have modest interiors, but this does not

preclude their clinicians from carrying out quality work.

Large-scale clinical trials have been conducted in Russia since 1989.

However, back then when interest first arose, regulators and the medical

research community were largely unaware of good clinical practice

(GCP) and clinical trials were not governed by any regulations – anyone

could do anything. There was the constitution of the USSR, which

protected the rights of patients, but that was it; ethics committees had

yet to be established. Things have changed drastically, and nowadays

there is a system of national regulations for drug development and

clinical research, with clinical trials being approved in a similar way to in

the West.

In 1999, the official text of the International Conference on

Harmonisation (ICH) GCP standards was published in Russian. In the

same year, the Russian-language version of the GCP standards – National

Standard OST 42-511-99, a close translation of ICH GCP – became a part

of national regulations on clinical research.

Nowadays, the legal basis to conduct clinical trials in Russia is governed

by the 1998 Federal Law on Drugs. The regulatory basis for conducting

clinical trials in Russia is the 2005 National Standard of the Russian

Federation 52379-2005 Good Clinical Practice, a translation of the GCP

E6 guideline. The Russian Ministry of Health and Social Development

also regulates the process by means of various Orders and Instructions,

all of which have been developed in correspondence with the law and

national standards.

The Federal Service for Supervision in the Sphere of Health Care and

Social Development has direct control in the field. This regulatory

body grants the CTA and reports to the Russian Ministry of Health and

Social Development.

Obtaining a CTA requires parallel favourable decisions from the federal

Ethics Committee and the Scientific Centre for the Evaluation of the

Products for Medicinal Use (a federal state institution, or FSI). In

general, it does not take more than 60 days to obtain a CTA after

submission, including import and export licences.

a report by

Vladimir V Novakovskiy , MD , PhD

Vice President of Regulatory Affairs and Quality Assurance, Congenix LLC

Clinical Trials Abroad – ‘Back in the USSR’


Vladimir Novakovskiy, MD, PhD, is Vice President ofRegulatory Affairs and Quality Assurance at Congenix, a contract research organisation (CRO) specialising inconducting clinical trials in Russia and countries of theCommonwealth of Independent States (CIS). Congenixprovides comprehensive solutions for the pharmaceuticaland life sciences industries using its own experiencecombined with the advantages of ‘Russian-speaking’countries. In his 10 years’ working in clinical research, Dr Novakovskiy has served in a variety of positions in CROs, starting with CRA at the Moscow office of Quintiles.Dr Novakovskiy holds a medical degree from St PetersburgMedical University. He also has a PhD in medicine,specialising in recombinant cytokines.

Russia has a large number of big,

highly specialised hospitals that

could have been specifically designed

for clinical research.

Novakovskiy_edit.qxp 4/6/07 3:38 pm Page 20



The Russian Medical System

Russia ranks highly among other Eastern European countries on the

availability of basic medical resources for conducting clinical trials (see

Table 1).

At present, most clinical trial work is conducted in Moscow and

St Petersburg owing to their better infrastructures, larger populations

and the presence of major research centres in these two cities; well-

equipped academic sites located to the east – from the Ural Mountains

in Siberia to the Far East, which is rich in natural gas and oil resources –

remain largely underused.

The ‘Soviet’-structured centralised healthcare system in Russia and the

countries of the former USSR consists of large medical institutions, many

of which specialise in different therapeutic areas. These institutions, both

general and specific, have large patient pools from which to draw,

making enrolment in clinical trials very easy for the patient and rapid for

the sponsor.

Despite the fact that many medical procedures that in the West might be

performed in an outpatient setting require a stay in hospital in Russia, these

additional hospital costs do not add significantly to the trial expenses.

Moreover, this additional level of attention is helpful in informing the

subjects of their obligations and providing the opportunity to closely

monitor and instruct them early on, thus helping to facilitate compliance.

The Russian People

Russia is a country with access to experienced, motivated and compliant

investigators, for several reasons. First, taking part in a global project

gives them an opportunity to interact, directly or indirectly, with the

international medical community from which they were almost entirely

excluded during the Soviet era. Second, Russian clinicians are

scientifically curious; the pioneering essence of a new drug always

presents an additional incentive for them. Third, most investigators are

eager to become familiar with new quality standards and

methodological approaches. This is why the GCP concept is normally

readily accepted by clinicians, even those with no prior practical

experience with the guidelines.

Recruitment rate is fast in Russia: on average 2–4 months ahead of

sites in more developed parts of the world. Patients in Russia are both

eager to participate and extremely compliant. Given the overall

healthcare situation in Russia, it is not difficult to understand why

patient enrolment continues to be so strong.

Many patients in Russia require specific treatments that are usually

beyond their reach. Participation in a clinical trial is a good opportunity

for them to receive appropriate long-term treatment because it offers

free access to the best medical facilities, the best diagnostic methods,

the best physicians and, potentially, the best medications.

Typically, the treatment provided in clinical research is better than the

standard of care available through the national health services. The

fact that trial protocol often calls for complete physical assessments

and personal interaction with the investigator may in itself be an

incentive to join a trial. Combined with the additional lure of Western

medicines and therapies, it is easy to see why the prospective patients

are excited to participate.

The only requirement of the patients is to be compliant, which they

consider more than acceptable. The high general level of education with

no illiteracy means that most people understand the nature of research

and the need to follow treatment regimens. In addition, Russian people

exhibit a greater respect for authority compared with those in the West

and have a more settled way of life. This all leads to higher acceptance

rates, more disciplined patients, increased compliance with physician

instructions, low drop-out rates and high follow-up rates.

Data Quality

Despite rumours and existing prejudice, Russia remains a solid and

reliable arena for conducting clinical trials. Cases of fraud in general

have been found to be much less frequent than in the US. In addition,

the European Forum for GCP (EFGCP) supports initiatives for

developing better conditions for clinical trials in and around Europe,

Table 1: Medical Resources in Selected Eastern European Countries

Country Major Cities Physicians Medical Hospital Beds per 1,000 Universities per 1,000 Inhabitants Inhabitants

Czech Republic 1 3.4 5 8.6

Hungary 1 3.6 4 8.4

Latvia 0 3.2 2 8.7

Lithuania 0 3.8 2 9.2

Russia 13 (9) 4.2 55 13.1

(European part)

Slovak Republic 0 3.2 3 8

Ukraine 5 4.6 18 10.4

Source: The Informer newsletter, June 2003, Imform GmbH.

Table 2: Summary of FDA Inspections Performed in EasternEuropean Countries between 1 January 1994 and 31 March 2002

Country Number ofInspections Observations

NAI VAI OAICzech Republic 2 1 3 0

Croatia 2 0 4 0

Hungary 6 2 8 0

Poland 5 4 1 0

Romania 1 1 0 0

Russia 6 4 7 0

Slovenia 1 1 0 0

Total 23 13 23 0

NAI = no action indicated; VAI = voluntary action indicated (objectionable conditions found,but justifying only local measures and not any further regulatory action; any correction is leftto the investigator to take voluntarily); OAI = official action indicated.Source: www.fda.gov

Recruitment rate is fast in Russia: on

average 2–4 months ahead of sites in

more developed parts of the world.




and since 2000 has been supporting efforts in Russia to conduct trials

to world-quality standards, thus paving the way for today’s sponsors

from the research-based pharmaceutical industry to place their studies

in the region with confidence. FDA audit data suggest that data

quality in Russia is at least as good as that from other regions around

the world (see Table 2).

These days more than 100 foreign pharmaceutical companies are

accredited in Russia, mostly located in Moscow. The international

companies that do not have representation in Russia still conduct clinical

trials there through third-party organisations. Many major contract

research organisations (CROs) have opened offices there, and there are

several local CROs, including Congenix, LLC (see Figure 1).

The number of clinical trials conducted in Russia has increased

considerably over the past 10 years, and this trend continues with on

average close to 100 new trials being approved every year. Interestingly,

the number of trials outsourced to specialised CROs is also growing,

allowing international companies to benefit from local resources,

intelligence and expertise (see Figure 2). There was a slight decline in the

number of clinical trials approved between 2003 and 2004, which can be

attributed to the increase in the number of mergers in the worldwide

healthcare sector at that time. Post-integration companies focus on

internal reorganisation, thus we see an increase in the number of trials in

2005 as these new entities resume normal operations.

Driving the Growth in Clinical Trials

When clinical trials first came to Russia, foreign pharmaceutical

companies had no representatives in the country; therefore, they started

work through local groups of researchers. The first group was based in

the Research Institute of Cardiology in St Petersburg and the first CROs

began to appear around 1990.

There are currently around 10 domestic CROs in Russia, with Congenix

one of the most advanced. The main difference between Russian CROs

and CROs in other countries is that in Russia all clinical research associates

(CRAs) are medical doctors. A CRO is able to pay much higher wages than

government-owned medical institutions, and can therefore select the

best, most highly experienced professionals. Many CRAs speak fluent

English, which helps a great deal in communication between investigators

and sponsors in terms of monitoring, reporting and so on. Russian CRAs

are trained in GCP, and many are also members of international

professional organisations such as the Drug Information Association (DIA)

and the Association of Clinical Research Professionals (ACRP).

The role that these groups played in shaping the clinical research market

in Russia cannot be underestimated. They translated GCP guidelines and

introduced them to regulators, medical professionals and the

community; they implemented the most reliable communication

technologies; they established data management systems; and they

implemented modern methods of statistical analysis. In short, they

Figure 1: Companies Involved in Clinical Trials in Russia

0

20

40

60

55%

37%

25%

35%

2000-2003 2004 2005

21%

29%

42%46%

10%

80

Local pharmaceutical and biotechnology companies

International pharmaceutical and biotechnology companies

Contract research organisations

Source: www.regmed.ru

A CRO is able to pay much higher

wages than government-owned

medical institutions, and can

therefore select the best, most

highly experienced professionals.


created comprehensive standard operating procedures (SOPs) and

invented effective project management technology.

Russian CROs provide the full spectrum of services, including regulatory

submissions, medical monitoring, project management, handling clinical

trial supplies, reporting, medical writing and so forth. However, only a

few of them can provide the data management and biostatistics services

in accordance with the highest international standards. Therefore, the

active work of software producers such as Oracle in the Russian market

is of fundamental importance.

In summary, by outsourcing drug development activities to local Russian

CROs, pharmaceutical, biotechnology and generic drug companies can

reduce their fixed costs and investment in infrastructure and focus their

resources on sales and marketing, drug discovery and other areas in

which they can best differentiate themselves. ■

01992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

(Q1–3)

50

100

150

200

250

Figure 2: Number of International Clinical Trials Approved in Russia

Source: www.regmed.ru




Oracle Applications

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Clinical Business Development, Europe, Middle East & AfricaJonathan Palmer

Clinical Solutions Director, EMEA

[email protected]

Gilbert Bellachen

Clinical Solutions Director, EMEA

[email protected]

Life Science Solutions, Europe, Middle East & AfricaNick Giannasi

Life Sciences Senior Director, EMEA

[email protected]

Clinical Business Development, North AmericaMichele Becci

Life Sciences Industry Director, North America

[email protected]


Clinical Trial Management(Siebel Clinical)

Term Classification/Dictionary Management(Oracle Thesaurus Management System)

Clinical Integration, Warehousing & Reporting(Oracle Life Sciences Data Hub)

Electronic Data Capture(Oracle Remote Data Capture)

Clinical DataManagement System

(Oracle Clinical)

PharmacovigilanceReporting & Call Centre(Oracle Adverse EventReporting System)

Oracle Life Sciences Suite – Clinical Development & Pharmacovigilance Applications

Contacts

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Clinical Trials in Eastern Europe


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