Statistical Programing and CDISC-related

Services

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Planimeter’s (Hi)story

First yearsPlanimeter was founded in 1997 by private individuals to provide statistical services in the pharmaceutical industry especially to support clinical trial design and evaluation. The team was formed by 4 people at the beginning and we primarily concentrated on design and analysis of Phase III-IV clinical trials, post-marketing studies and epidemiological surveys.

E-business solutionsWe started our e-business activity in 2005 with preparation of our first Patient Registry. This was followed by further registries and the first e-CRF in 2006. Our e-CRF solution became internally well known and well accepted within a reasonably short time pf period. Probably the main reason of our success is that all our experience on conduction and evaluation of clinical trials were incorporated during design and implementation of the system. Our solution – equipped with a high level help-desk service – currently operates in 8 countries. Besides registries and eCRFs we also developed e-learning, dating and special CRM systems specifically build for health-care system support.

Our today activitiesMeantime Planimeter has became an internally acclaimed, full service CRO of a size of 16 employees and a similar bunch of contractors. Our today activity covers – beyond the original targets – full conduction of clinical trials and reporting - including the medical writing activities.Our strength lays in the strong mathematical background of our staff. We are experienced in both classical (parallel, cross-over, etc.) and modern (Bayesian, Adaptive, etc.) designs. Recently we are focusing on support of translational research and implementation of bioinformatics solution. Main therapeutic areas are: vascular and nervous system disorders, ophthalmology, infections, oncology, renal and urinary disorders, immunology and respiratory disorders. In 2014 Planimeter became an ISO qualified company.

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Mission and Vision

VisionOur vision is to be an internationally known and

accepted service provider in Pharmaceutical industry.

One day we would like to turn our rich knowledge and

experience in biostatistical / bioinformatical innovation.

What we do not aim at any circumstances is to be

‘leader’ in business or measurements aspects. We wish

to provide top-level services with a manufactoral taste

and comfort.

MissionOur mission is to serve as a source of expertise in

delivery classical and up-to-date biostatistical

services in pharmaceutical, biotechnology,

medical device industries world-wide, and to

promote the use of rigorous quantitative methods

in the biomedical and public health sciences. Our

approach is to capitalise on our presence and

network in Hungary and use information

technology to assist the life sciences industry in

the development of quality products, on time and

on budget, every time.

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Current activities

DM Statisticians PV Programmers

Help-desk eCRF Patient Registry Randomisation

Data Management Data Entry Systems Query management Coding

Statistical Programing CDASH / CDISC TLG – design and implementation Post-hoc analysis

Web-based solutions eCRF Patient registry Support of PV E-Learning

Post-marketing support Patient- support program eCRF Dashboard

Statistical Services and Data Management for Healthcare

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Our Team

István JánosiFounder,

Managing DirectorIstván graduated at KLTE, in Debrecen, Hungary as a mathematician in 1990. He has been working as biostatistician since then. He also manages – besides Planimeter - WEB2 Research Kft. Member of ISCB and DIA, author or co-author of several publications. Acting as statistician, data manager – on demand – and primarily as the manager of the company.

László SzakácsHead of Statistical Programming

and Medical WritingLászló has been working for Planimeter since his graduaton as a mathematician (2003). All of our recent systems (automated report generation, QA, web-based solutions, etc.) were developed or designed by him. He took full responsibility of complete management of DM and stat activities of several Phase I-IV studies.

Bíbor BalázsHead of Administration,

Key Contact ManagerBíbor joined Planimeter in 2002. She is an active member of SOP-develeper team. She takes full responsibility for all logistic issues regading data management. She is also a member of our pharmacovigilance team, she is responsible for monitoring of medical literature.

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References

Statistical Programing and CDISC-related Services

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Business Idea

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Statistical Programing Statistical Programing primarily means derivation of

Tables, Listings and Graphs (TLGs). This activity is performed with the help of SAS, so Statistical

programing practically means programing in SAS. In wider sense statistical programing covers the majority of CDISC-related tasks because SDTM and ADaM data

tables are also prepared with the help of SAS.

Quality Assurance with ChiliA sophisticated Quality Assurance procedure was

developed and introduced to support the preparation of data models and the process of statistical programing.

QA can be performed with different depth depending on the Sponsor’s requests. The whole procedure is

documented within Chili, a free web-based tool, which was configured specifically for QA-purposes internally.

Data Models (CDISC)CDISC SDTM (Study Data Tabulation Model) is applied to re-structure the raw clinical data into the generally

used domains with the help of variable naming conventions. In this approach the Submission

Metadata Model is followed as far as possible. ADaM (Analysis Data Model) is used to prepare

datasets for direct reporting purposes. The activity is extended with preparation of the Define.xml and

Study Data Reviewer’s Guide.

Management support with ChiliChili is not only suitable for documentation of the QA-

procedure, it also provides environment for delegation of tasks and supervision of both the development and QA-

procedures. With granting access to the Sponsor the whole procedure can be monitored with full transparency.

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Detailed Services - Menu

CDASHClinical Data Acquisition Standards

Harmonisation – further details

SDTMMore detailed description of

our services

ADaMData models – as we apply this

approach in our everyday routine

Define.xmlDescription of our interpretation

of generation of define.xml

TLGPreparation of Tables, Listings

and Graphs

QA-proceduresBrief description of our QA-

procedures

QA in ChiliQA implemented within Chili

framework

Management with Chili Management support (development

and QA) within Chili framework

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The Clinical Data Acquisition Standards

Harmonization (CDASH) model standardizes

the way data is collected to facilitate the

generation of SDTM tables. As the primary aim

of following CDASH Guidance is to make

easier and more comfortable to transform

raw study data into SDTM domains, CDASH is

taken into consideration during CRF (and eCRF)

design.

CDASH approach is primarily applied by our Data Management Department, but being a small company

there are not strict boundaries between DM and statisticians or DM and programmers. Consequently majority of our staff including data managers, statistical

programmers and statisticians are familiar with the CDASH standards.

Similarly to the CDASH / CDISC community we are also continuously working on building our CDASH libraries and improvement of already implemented

modules.

CDASH

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SDTM

Preparation of SDTM domains is quite a well defined

procedure, which primarily means the proper application

of the guidance in case of the standard variables and

domains (e.g. sex, age or blood pressure). Due to the

nature of SDTM even the study or therapeutic area

specific variables can easily been transformed into SDTM-

compliant variables with following the naming and

formatting conventions.

As SDTM is a living concept in itself , we pay great

attention to its own development: we intensively follow

the achievements regarding development of Therapeutic

Area Data Standards (TAUGs), Metadata Submission

Guidelines (MSG) or SDTM implementation Guide for

medical devices (SDTMIG-MD).

Our services cover:

• Creation of Data Standards Library including a CRF Library, and CDASH/SDTM/ADaM Libraries

• Set-up Study Specific aggregates mapping visit information into the appropriate visit window structure

• Development of a metadata repository to enable data model compliance checking and define.xml generation

• Comparison against Study Specifications

• Validation against the Data Standards Library

• Generation of pooled analysis based on CDISC data (for ISS or ISE purposes)

• Creation of macros for ADaM dataset creation.

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SDTM and ADaM data sets are programmed according

to the associated specifications, and validated against a

series of electronic integrity checks to ensure compliance

to the models. Additional QC includes independent

verification of results.

In the Subject-Level Analysis Dataset (ADSL) only one

record is created for all subjects.

In the Basis Data Structures (BDs) one or more records

per subject are generated per analysis parameter, per

analysis time point (conditionally required).

The so called „Other” section of ADaM specifically

contains – among others – the Basic Data Structure for

Time-to-Event Analysis and Data Structure for Adverse

Event Analysis.

ADaM

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Define.XMLInformation sharing on the content of SDTM in a more or less human-readable manner led to introduction of Define.xml, which – in short – contains all SDTM data AND metadata in XML-format.

The Standard content of define.XML is :

• Data Metadata (TOC)• Variable Metadata• Variable Value Level Metadata• (Computational Algorithms)• Controlled Terminology/Code Lists• Annotated CRF• Optional: Supplemental Data

Definition Document.

Computational algorithms can also be stored within define.xml framework.

Further advantage of Define.XML: Content can be checked (validated) with define.XML checker programs (e.g. http://www.pharmasug.org/proceedings/2013/AD/PharmaSUG-2013-AD19.pdf).

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TLGTables, Listings and Graphs are defined in the Statistical Analysis Plan with the

help of Table Shells. Theoretically table shells defines the outputs with character

precision (in case of Tables and Listings).

Planimeter developed a highly sophisticated SAS-macro set which is able to deliver

the required outputs with very high flexibility. What is the best in our solution that

the macro set can be adjusted through an interface which does not require

programing knowledge. So if no new template is required, the outputs can be put

together simply in a text-editor.

While each study requires some further development of our SAS macro set,

greater and greater part of tables, listings and graphs can be used in off-the-shelf

manner. Today we are generally cover a typical clinical study with pre-defined

outputs in 65-85%.

The advantage of this high coverage is that our TLG generation costs can be

decreased reasonably proportionally with the decrease in work-load.

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Quality Assurance ProceduresSteps establishing quality during development phase

• Application of programing conventions

• Commenting and segmenting

• Application of continuously developed macros in TLG-derivation

• Double programming on demand

• TLG-derivation in a three-stage method: development, testing, production

• Complete and transparent documentation of the whole activity (code development and QA)

• Continuous development of standardization according to international standards and guidelines.

Steps establishing quality during QA phase

• Code and output review

• Checking of the applied filtering and sorting in the database s

• Checking of program codes for programming conventions

• Checking log files for errors, notes, messages

• Comparison of the results against the table shells

• Checking of titles, notes, remarks, and spelling.

In case of any discrepancy notification of the programmer and detailed

description of the finding. Response: programmer’s action: fixing the bug or

explanation of the discrepancy. In case of data error notification of project

manager. In case of specification issue notification of the study statistician.

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QA in Chili

Chili (https://www.chiliproject.org/) is a free, web-based tool which perfectly fits the demand of managing and documenting of QA-procedures of statistical programing.

Adjustment of the application starts with role definition and set-up of user authorizations.

This is followed by the description of all the potential tasks (the program codes themselves) and finally with the assignment of the tasks to the users (programmers).

When a task is indicated as „ready for validation” the assignments skips to the dedicated QA-person responsible for the specific task.

Not only the work-flow can be commanded within Chili, it also provides area for showing the actual status of a specific program.

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Management with Chili

Chili is a perfect tool of monitoring

both the program development

procedure and the QA-activities.

Monitoring can be applied at task-level,

when all the activities related with one

specific task are tabulated.

Summary tables of arbitrary sets of

tasks can also be created.

With suitable authorization the

Sponsor can follow the development

and QA-procedure without any

additional effort in real-time.

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E-business solutions

Automated Business Data Reporting

There are many data sources (e.g. IMS) which make possible of

preparation of regular reports. Although the same task should be

repeated, sometimes this repetition is not supported within the original software framework. We are able to transform regular data into regular reports with a maximal flexibility.

Patient Support ProgramPatient Support Programs are to

incorporate information collected by usual eCRFs extended with

further study-specific activities of an enrolled subject, like

communication with call-center, patient organisations, dietitians,

running a Diary of rating the different services on regular basis.

E-learning SystemOur e-Learning system has two

roles. First, trains the materials as the

name says. If we consider the SOP-system as a potential material to train/learn, then we arrive to our second task: to provide a job- or

role-dependent delegation of SOPs to be studied to specific 'students'.

Medical Information System

Aim of Medical Information System is to collect, document and manage all potential AE-related information

reaching a pharma headquarter independently of the

communication channel (web, telephone, CRA, trial, etc.). The

system delegates the tasks, logs and reports the activities.

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Statistical Programing / CDISC references

ViforFerinject® in Patient With Thrombocytosis Secondary to Inflammatory Bowel Disease (IBD)

Dignity ScienceA Randomised, Double-blind, Placebo-Controlled, Single-

Ascending Dose and Multiple Dose Phase I Study to Assess the Safety, Pharmacokinetics and Effect of Food

on Orally Administered DS107G in Healthy Subjects

Boehringer IngelheimADESPI: Adherence to Spiriva® in Patients With COPD (Chronic Obstructive Pulmonary Disease), Measured by Morisky-8 (MMAS-8) Scale, in Routine Medical Practice

ApellisA Phase I Study to Assess the Safety APL-2 as an Add-On to Standard of Care in Subjects With PNH

ABBOTT / AbbvieObservational Study to Evaluate the Time to Achieving

the Maintenance Dose of Zemplar® (Paricalcitol Injection) in the Treatment of Patients Suffering From End-stage Renal Disease and Severe Over-reactivity of

the Parathyroid Glands

AstraZenecaCorRELation Between PatIent PErception and Findings on

Clinical Examination (RELIEF)

Characterisation of the staff

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Role # Availability for 2015-2016

Q3 Q4 Q1 Q2Head László Szakács On-demand 60% 70% 80%

Senior Programmer (8+ years of exp.)Hourly rate (€)

1 empl’s+2 contr’s

65

0+2 1+1 1+1 1+2

Advanced Programmer (5+ years of exp.) Hourly rate (€)

2 empl’s+3 contr’s

48

1+2 1+1 1+2 2+3

Novice Programmer (2+ years of exp.) Hourly rate (€)

2 empl’s +3 contr’s

36

1+0 0+1 2+0 2+2

Total 3+4 2+3 4+3 5+7

Vaci út 95BudapestHungary, H-1139

+36 30 933 89 20+36 30 429 88 05

Contact Details

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www.planimeter.hu

janosi@planimeter.netbibor@planimeter.net