2 SAS Programming in the Pharmaceutical Industry This chapter provides the context and universal guidelines for the material in this book. It is best to begin by . Very good resources to learn SAS. Contribute to beckwang80/SAS development by creating an account on GitHub. 20 SAS Programming in the Pharmaceutical Industry, Second Edition. Preparing Clinical Trial Data. Clinical trial data come to the statistical programmer in two.
|Language:||English, Spanish, Indonesian|
|Genre:||Health & Fitness|
|Distribution:||Free* [*Registration needed]|
années, tant d'un point de vue scientifique que d'un point de vue humain. Merci à . apoptosis Intracellular mechanism SAS Programming in the. Editorial Reviews. About the Author. Jack Shostak, Associate Director of Statistics , manages a group of statistical programmers at the Duke Clinical Research. SAS Programming in the Pharmaceutical Industry, Second Edition - Jack Shostak Like many industries, the pharmaceutical industry has a vocabulary and.
The FDA helps to do this with a drug approval process that can easily cost hundreds of millions of dollars and can take a decade or more to move a drug from discovery to a pharmacy near you. There are several progressive levels of studies that are conducted as part of the drug approval process.
Pre-clinical studies are the experiments that are conducted in the laboratory and with animals long before a new drug is ever introduced for use by humans. The IND application allows the drug maker to conduct clinical trials of the new compound on human subjects. These studies are usually carried out on small samples of subjects.
The idea here is to determine the safety of the drug in a small and usually healthy volunteer study population. Phase 2 trials go beyond phase 1 studies in that they begin to explore the efficacy of a drug. Phase 2 studies have larger — patients study populations than phase 1 studies and are aimed at narrowing the dose range for the new medication. Safety is monitored at this stage as well, and phase 2 trials are generally conducted in the target study population.
Phase 3 trials are large-scale clinical trials on populations numbering in the hundreds to thousands of patients.
These are the critical trials that the drug maker runs to show that its new drug is both safe and efficacious in the target study population.
Phase 4 trials, or post-marketing trials, are usually conducted to monitor the long-term safety of a new drug after the drug is already available to consumers. The device approval process at the FDA varies based on the degree of risk inherent in the device.
Class 1 devices carry little risk for the patient; they include devices such as elastic bandages and surgical instruments. Class 2 devices carry slightly higher risk for the patient; they include such devices as infusion pumps and motorized wheelchairs.
Class 3 devices are high-risk devices and thus require the most regulatory scrutiny. Class 3 devices include replacement heart valves and implantable defibrillators.
Obviously, the approval requirements for a class 3 device are much higher than for a class 1 device. Clinical Trial Study Designs There are many types of clinical trials, and there are some general trial design concepts that you need to understand.
One key concept is the randomization of study therapy. When you randomly assign patients to study therapy, you reduce potential treatment bias. Another key concept is treatment blinding. Blinding a patient to treatment means the patient does not know what treatment is being administered. In a single-blind trial, only the patient does not know what treatment is being administered. There are other trial design concepts for you to be aware of. A clinical trial can be carried out at a single site or it can be a multi-center trial.
In a single-site trial all of the patients are seen at the same clinical site, and in a multi-center trial several clinical sites are used. Multi-center trials are needed sometimes to eliminate site-specific bias or because there are more patients required than a single site can enroll.
Trials may be designed to determine equivalence or superiority between therapies. An equivalence trial is designed to show that there is no clinically significant difference between therapies, and a superiority trial is intended to show that one therapy is significantly better than another.
Finally, trials can follow parallel or crossover study designs. In a parallel trial, patients are assigned to a therapy that they remain on, and they are compared with patients in alternate therapy groups. In a crossover trial, patients switch or change therapy assignments during the course of the trial. Industry Regulations and Standards Regulatory authorities govern and direct much of the work of the statistical programmer in the pharmaceutical industry.
It is important for you to know about the following regulations, guidance, and standards organizations.
The goal of the ICH is to define a common set of regulations so that a pharmaceutical regulatory application in one country can also be used in another.
CDISC has developed numerous data models that you should familiarize yourself with. The SDTM was originally designed to simplify the production of case report tabulations CRTs , and therefore the SDTM is listing friendly, but not necessarily friendly for creating statistical summaries and analysis. These data sets are designed for creating statistical summaries and analysis.
Because define. This allows the FDA to work more easily with the data submitted to it. You will be exporting, importing, and creating data for these models, so it is important that you learn about them. The FDA has begun to formally endorse the use of these data models in their guidance.
Any work that you perform that contributes to a submission to the FDA is covered by these federal regulations. There are a number of specific regulations and guidance you must know. This guidance is of major importance, as you are often required to generate tables, figures, case report tabulations, and perhaps clinical narrative support for the clinical study report. It details trial design, trial conduct, and data analysis and reporting.
Although most useful Chapter 1: Environment and Guiding Principles 7 to the statistician, this guidance gives an excellent overview of how a clinical trial should be conducted. Anyone who works on a clinical trial needs to understand this document. Of particular interest to the statistical programmer are the following parts of E6.
The italics have been added for emphasis. Part This reporting requires you to create adverse event, death, and subject dropout summaries annually for any drug under an IND application. The PDF page should be a standard 8. Please select Ok if you would like to proceed with this request anyway. WorldCat is the world's largest library catalog, helping you find library materials online.
Your request to send this item has been completed. APA 6th ed. Citations are based on reference standards. However, formatting rules can vary widely between applications and fields of interest or study.
The specific requirements or preferences of your reviewing publisher, classroom teacher, institution or organization should be applied.
The E-mail Address es field is required. Please enter recipient e-mail address es. The E-mail Address es you entered is are not in a valid format. Please re-enter recipient e-mail address es. You may send this item to up to five recipients.
The name field is required. Please enter your name. The E-mail message field is required. It is important for you to know about the following regulations, guidance, and standards organizations. The International Conference on Harmonization ICH is a non-profit group that works with the pharmaceutical regulatory authorities in the United States, Europe, and Japan to develop common regulatory guidance for all three. The goal of the ICH is to define a common set of regulations so that a pharmaceutical regulatory application in one country can also be used in another.
CDISC has developed numerous data models that you should familiarize yourself with. Three of these models are of particular importance to you:. Therefore, the SDTM is designed to be listing friendly, but not necessarily friendly for creating statistical summaries and analysis.
These data sets are designed for creating statistical summaries and analysis. As a statistical programmer, you may find these data sets to be the primary source for your reporting work.
You may be very involved in the creation of these data sets. Because define. This enables the FDA to work more easily with the data submitted to it.
It may also enable you to do your work more efficiently and effectively if you are able to leverage your metadata. You will be exporting, importing, and even creating data for these models, so it is important that you learn about them. The FDA endorses the use of these data models in their guidance and data submission documents. The FDA is the department within the United States Department of Health and Human Services that is charged with ensuring the safety and effectiveness of drugs, biologics , and devices marketed in the United States as well as food, cosmetics, and tobacco.
Any work that you perform that contributes to a submission to the FDA is covered by these federal regulations. There are a number of specific regulations and guidance that you should know. Of particular interest to the statistical programmer are the following requirements of Part Validation of systems to ensure accuracy, reliability, consistent intended performance, and the ability to discern invalid or altered records.
Adequate controls over the distribution of, access to, and use of documentation for systems operation and maintenance. Revision and change control procedures to maintain an audit trail that documents time-sequenced development and modification of systems documentation. The " E3 " describes in detail what reporting goes into a clinical study report for an FDA submission.
This guidance is of major importance, as you are often required to generate tables, figures, case report tabulations, and perhaps clinical narrative support for the clinical study report. The " E9 " discusses the statistical issues in the design and conduct of a clinical trial.
It details trial design, trial conduct, and data analysis and reporting. Although most useful to the statistician, this guidance gives an excellent overview of how a clinical trial should be conducted. The " E6 " or GCP s discusses the overall standards for implementing a clinical trial. Anyone who works on a clinical trial needs to understand this document.
Of particular interest to the statistical programmer are the following parts of E6. The italics have been added for emphasis.
Part This reporting requires you to create adverse event, death, and subject dropout summaries annually for any drug under an IND application. The ICH has more recently published the E2F document, which is an international standard for annual safety reports.
This specification was developed by the International Conference on Harmonization ICH as an open-standards solution for electronic submissions to worldwide regulatory authorities. This is a document that you will want to understand, and the FDA does a good job in keeping it up to date with what their expectations are for electronic submission of data.
You should keep up to date on the current information in this document as well as the parent Study Data Standards document. On February 6, , the FDA posted three draft guidance documents that will require the submission of electronic data in standard format.
You will want to keep a close watch on this group in the future, because it is from here that further data standards mandates and processes will emanate.
Within any pharmaceutical company or contract research organization, you work with groups and individuals outside the biostatistics department. The people that you work with most tend to be within the biostatistics or statistics group itself. Traditionally, this department is primarily composed of statisticians and statistical programmers who are responsible for the analysis and reporting of clinical trials work.
The analysis and reporting work typically consists of obtaining data, building analytic data structures, and reporting out the trial results through a collection of tables, figures, and listings.
The division of labor between statisticians and statistical programmers can often be blurred, because the skill sets can overlap a great deal. On occasion, you may also find other job roles within a biostatistics group where they may have their own data managers or informaticists. The site management group is responsible for clinical site relations. They recruit doctors at clinics to participate in clinical trials, train their staff in trial conduct, monitor the sites for protocol compliance, and serve as an all-around advocate for the clinical site.
The monitoring of sites is done by a job title called a clinical research associate, or CRA. Site management can be your ally in getting the data entered in a clean and readily usable form. Clean data at the start of the data collection process precludes the need for extra data queries from data management and helps prevent subsequent data analysis problems.
The importance of site management has grown with the establishment of electronic data capture EDC technology, because data entry has moved from the data management group to the clinical site itself where initial data quality is established. Sometimes site management can be included in a larger group called clinical operations, which may include project leadership and data management functions as well. Next to the clinical trial statistician, the statistical programmer works most closely with the data management group.
The data management group is usually responsible for case report form CRF design, database design and setup, data cleaning, data coding, data quality control, and providing the clinical trial data for analysis by the statistics group.
Cleaning the data involves scouring the data for problems by using programmatic and manual checks of the data. Coding the data entails applying generic codes to categorize freely entered text fields such as adverse events, medications, and medical histories.
Quality control of the data involves auditing the data to make sure that it was entered properly. Finally, the data management group typically provides the data to the statistical programmer via some kind of relational database management system RDBMS , which can then be imported into SAS.
You save time when data management provides a well cleaned and well coded clinical database, because this means you do not have to program around dirty data.
The information technology IT group has varying responsibilities, depending on the size of your organization. IT is usually responsible for computer systems infrastructure, maintenance, and general computer help desk support.
The IT group may also perform some level of software development. In small to midsize organizations, IT may simply make application program interfaces APIs between off-the-shelf systems, while at large organizations, IT may be responsible for full software applications architecture and development.
You need to work with the IT department within your organization as well as with external sponsors and vendors. Internally, you may work with IT for SAS configuration management and installation qualification, encryption technologies, and desktop publishing or report distribution concerns. The most common reason for you to work with external IT staff is usually in regard to information exchange technologies such as FTP and encryption tools.