Wednesday, September 16, 2009

GUIDELINES FOR STANDARD OPERATING PROCEDURES

for Good Statistical Practice in Clinical Research

Written by: PSI Professional Standards Working Party


INTRODUCTION

Professional codes of conduct for statisticians, such as those published by the Royal Statistical Society, stress general principles including the need for professional integrity, a primary concern for the public interest and the preservation of professional standards. However, there is a need for more detailed guidance in specific disciplines. Therefore, the PSI “Professional Standards Working Party” set out to provide guidance for the preparation of Standard Operating Procedures (SOPs) for Good Statistical Practice in clinical research.

The development of Guidelines for Standard Operating Procedures (GSOPs) appeared to be a natural step in the process of encouraging and publicising Good Statistical Practice in the analysis and reporting of clinical trial data. In preparing these GSOPs, the objectives of PSI are:

  • to ensure that statisticians in the pharmaceutical industry are aware of the principles contained in published codes of conduct
  • to provide guidance to encourage adherence to these principles in the application of statistics to clinical trials
  • to publicise the principles of Good Statistical Practice for clinical research to other professionals, internal and external to the pharmaceutical industry
  • to provide guidance in the preparation of SOPs to ensure compliance with the requirements of international Good Clinical Practice so as to satisfy regulatory requirements with respect to the collection, processing, analysis and reporting of clinical trial data.

The many varied roles statisticians fulfil within the pharmaceutical industry and related organisations (e.g. academic institutions and Contract Research Organisations (CROs)) preclude writing a definitive set of SOPs for all PSI members. Hence the decision was taken to develop GSOPs which would give detailed statements of the principles of Good Statistical Practice within the context of clinical research (thus building on the existing codes of conduct), but which would require that statisticians develop the guidelines into SOPs specific to their own organisations. Conversion of these GSOPs into SOPs appropriate for a specific organisation requires expertise. Care should be taken that the level of responsibility given to statisticians is appropriate to the level and depth of statistical expertise within the organisation. The adaptation of the GSOPs into working SOPs should be carried out to reflect the structure and expertise of the organisation.

The GSOPs address the most common requirements of statisticians practising in the field of clinical research. The areas covered are not exhaustive. In some organisations it will be appropriate to combine some of the guidelines into one SOP or to divide other guidelines into several SOPs.

The manner in which procedures are implemented is as important as the procedures themselves if the procedures are to be effective within the structure of a particular organisation. SOPs which are properly implemented as part of an overall quality system not only improve the quality of the service or product but also improve the productivity and efficiency of the process. For example, good trial design and good case report form design can greatly improve the quality of the data collected in a clinical trial.

The PSI “Professional Standards Working Party” was set up in May 1990 and was responsible for developing 11 of the following GSOPs over a period of approximately 18 months. The development process included input from many members of PSI through written comments and workshop discussion sessions. The development process has continued since then with reviews and revisions of existing GSOPs, as well as the preparation of new GSOPs. This review process takes place over a two-yearly cycle, and is the responsibility of the PSI Public Affairs Sub-Committee.

The GSOPs and the Royal Statistical Society Code of Conduct are now augmented by other relevant documents such as the International Conference on Harmonisation (ICH) documents on Clinical Study Reports and Statistical Principles for Clinical Trials and the Association for Clinical Data Management (ACDM) Guidelines for Writing Standard Operating Procedures.

For detailed of this guideline please see the below source for more details

Source:

http://www.psiweb.org/docs/gsop.pdf and

http://www.uk-legislation.hmso.gov.uk/si/si2004/20041031.htm

Wednesday, July 8, 2009

SAS® Product Drug Development Used in Healthcare

Drug Discovery and Development with SAS®
SAS provides a centralized, integrated solution for managing, analyzing, reporting and reviewing clinical research information. This solution enables life sciences organizations to make informed business decisions with confidence, to assess the safety and efficacy of research compounds more effectively, to collaborate across trials, phases and therapeutic areas successfully, and ultimately get better products to market faster.
Available Drug Discovery and Development Solutions from SAS:
SAS Drug Development provides an analysis and reporting solution that enables global collaboration with complete compliance and control. SAS OnDemand: Drug Development offers small and midsize businesses a centralized, controlled, Web-based solution for efficiently developing, executing and managing the transformation, analysis and submission of clinical research data.
SAS® Drug Development:
SAS Drug Development enables the collation and sharing of clinical research data throughout the entire organization via a well-managed, controlled, centralized repository. This single version of the truth enables rapid, efficient sharing of resources, data and knowledge across trials, phases and therapeutic areas at all stages of the clinical R&D process.
Benefits:
A single version of the truth. SAS Drug Development delivers full data integration and standardization via a centralized information repository that gives researchers throughout the organization direct access to both the research content and embedded intelligence tools at all stages of the clinical R&D process.
Full compliance with industry standards. SAS Drug Development provides the ability to meet industry expectations for managing research information content in accordance with government regulations, including 21 CFR Part 11, good industry practices (GxP) and sound business practices.
Automated integrity, traceability and transparency. The degree of transparency and traceability of all data analysis activities provided by the solution ensures ongoing quality control and quality assurance, and makes it easy to confidently address inquiries from regulatory agencies. More confidence in research decisions. Researchers can easily review multiple data sources to analyze research across trials, phases and therapeutic areas. This comprehensive view makes it easier to make go/no-go research program decisions earlier in the process.
Shorter development cycles. With the ability to make more confident decisions and analyze data from a single repository, researchers can reduce the time spent searching for, gathering and aggregating data for analysis. The solution also helps streamline and automate research and analysis tasks.
Download the complete SAS Drug Development Fact Sheet
How SAS Is Different
  • A standardized, centralized repository. SAS Drug Development integrates data from all relevant sources, stores all information related to a clinical research program, and brings this information together in a standardized, centralized repository.
  • Streamlined processes. By providing immediate access and ongoing insight into project progress, SAS Drug Development gives organizations better control over the deployment of resources, as well as the streamlining of clinical R&D processes and tasks.
  • Integrated SAS® program development and execution. An embedded program development environment provides the ability to easily develop SAS programs and macro libraries, review log files and test program functionality.
  • A truly collaborative environment. Research scientists and less technical users have direct access to research data, statistical results and all other relevant clinical research content via a secure, user-friendly interface.
  • Full compliance. SAS Drug Development was carefully designed to meet existing and emerging government regulations, including 21 CFR Part 11, as well as good industry practices and sound business methodologies.

Only SAS provides a secure, collaborative framework that puts controlled power into the hands of researchers who need it. The result is greater productivity and efficiency in these areas:

  • Integration. Efficiently integrate and manage data from a wide range of sources – such as electronic data capture (EDC) systems, in-house clinical data management systems (CDMS), labs and contract research organizations (CROs) – while leveraging investments in existing systems and resources.
  • Analysis and reporting. Accurately assess and report on study data in a timely manner. Efficiently generate presentation-ready statistical summaries of clinical trials data and easily share results with researchers or reviewers on demand.
  • Discovery. Use your growing research information repository to rapidly investigate critical drug safety issues, pursue new marketing claims and explore potential product-line extensions.
  • Regulatory compliance. Document research content via integrated processes that provide versioning, audit trails and electronic signatures, as well as fully describing the relationships between all process inputs, transformations, analyses and results.

Note: The matter has been taken from the SAS® Site

Wednesday, July 1, 2009

WinNonlin® 6.0

Phoenix™ WinNonlin® 6.0 — Next Generation of the Industry Standard for PK/PD Modeling and NCA

Phoenix WinNonlin improves scientific productivity during critical drug development tasks by providing a comprehensive analysis environment that implements efficient reusable workflows and high quality outputs while reducing barriers to learning and collaboration, enabling more impactful quantitative decision making.
Phoenix WinNonlin 6.0 offers the following benefits:
  • Comprehensive Analysis Environment: Perform virtually all of the analyses for standard PK and PK/PD studies. MORE
  • Efficient Workflow Management: Create, reuse, and share analyses as stored workflows. Easily process, visualize, and tabulate data while allowing the flexibility to edit in Excel. MORE
  • High Quality Outputs: Generate high-quality graphs, tables, and figures allowing for integrated communication of analysis results. MORE
  • Easy to Learn and Share: Minimize the amount of time spent learning the software and promote collaboration through easily transferable project files, workflows, and templates. MORE
  • Enables Compliance: Provide technical controls for 21 CFR Part 11 compliance when used in conjunction with Pharsight Knowledgebase Server™. MORE

Phoenix™ WinNonlin® Features

Key features of Phoenix WinNonlin include the following:

  • Comprehensive Analysis Environment

Perform noncompartmental analysis of both blood and urine data using methods for rich or sparse datasets in a single run.

Three methods of AUC calculation: linear trapezoidal, linear/log trapezoidal, and linear up/log down.

Descriptive statistics, including weighted descriptive statistics.

Units definition and conversions, including the ability to specify preferred output units, units for a dosing regimen, and unit conversions.

Powerful data management tools allow users to append worksheets, change properties and/or transform columns, add BQL Rules or map cross product worksheets, as well as filter, join, merge, pivot, rank, split, and stack data.

Toolbox functions for deconvolution, semicompartmental modeling, nonparametric superposition and crossover design.

Automatic determination of initial estimates.

Analysis using general linear modeling approaches, including bioequivalence tests as appropriate.

Built-in scripting language (Pharsight Modeling Language or PML).

  • Efficient Workflow Management

Workflow management tools that enable users to create, reuse, and share models and projects.

More powerful data management tools. Excel compatible workbooks, including formulas, functions, data import/export, missing value codes, sort, transformations and worksheet merge.

Insert favorite workflow components and/or sub-workflows into larger workflow diagrams.
Easily map data inputs to multiple models.

  • High Quality Outputs

Significantly improved, report-ready graphs, plots, tables and listings greatly reduce the reliance on external graphics software.

Easily insert bar, column, and box plots; histograms; XY, QQ plots, and/or scatter plot matrices into your workflows.

Easily change the formatting of any plot to suit reporting requirements.

One-click export of results, plots, and tables to Microsoft Excel® or Word®, SAS, graphic files, or text.

  • Easy to Learn and Share

An intuitive user interface provides multiple click-paths to accomplish the same tasks, allowing users to use the software in ways that make suit their personal preferences.

All data, models, scripts, tables, BQL rules, documents, models, workflows, plots, graphs, and outputs are contained in one project file that can easily be shared.

Classroom and online training courses will be offered regularly to support new users.

  • Enables Compliance

Every workflow object has a 'Verification' tab that explains whether the object executed properly and any errors that may have occurred.

Full integration with the Pharsight Knowledgebase Server™ (PKS™) data repository enabling all changes to projects to be logged in the PKS database

Validation can be speeded up significantly with the Phoenix Validation Suite™

Note: If anything needed please see the below link-

http://www.pharsight.com/products/prod_phoenix_winnonlin_feature.php