My SAS Tutorials

Tuesday 21 December 2021

How Analytics is transforming Life-Sciences Manufacturing Quality?

Government, industry and academia are converging to find solutions to the quandaries caused by COVID-19, which emerged in the city of Wuhan, China, in December 2019. Unsurprisingly, the life sciences and healthcare sectors are at the heart of the work. Health care may make most of the headlines, but the work abaft the scenes in life sciences labs is just as crucial.

Analytics is currently revolutionizing the life- science industry, as the analytics solutions are used to improve quality and production. However, the ordinant dictation for essential medical equipment is incrementing, placing immensely colossal pressure on medical contrivance manufacturing companies. They are being asked to expedite engenderment while maintaining quality and compliance with regulatory requisites. Pharmaceutical companies are working frantically to test subsisting medicines, such as hydroxychloroquine, to optically discern if they may be efficacious against COVID-19.

Patents and Process validation:

The customary approach to pharmaceutical development – patents – is not going to work with the coronavirus. This pandemic is too immensely colossal and consequential for any single company to be sanctioned to prehend the manufacturing process. Instead, it seems likely that once a vaccine is approved, its manufacture will be licensed around the world. This, however, makes it harder to ascertain the quality of the vaccine. Patents define the content. But what about the manufacturing process quality? One way is through process validation.

A standard consolidated process validation system could integrate all the COVID-19 vaccine engenderment systems into a single ecumenical environment. This would sanction more expeditious replication of the pristine process and enable other biotechnology companies to utilize it. It would withal avail regulatory bodies abbreviate delays and errors when checking international quality and safety standards.

Improving Manufacturing Quality:

Beyond process validation, however, there are ways in which analytics can avail to amend manufacturing quality in biotech, pharmaceutical, and medical contrivance companies. Analytics solutions can avail to ameliorate enterprise quality, lower the cost of inferior quality, and increment engenderment yields. They can additionally avail you adhere to regulatory requisites through perpetual process verification monitoring. For example, analytics systems linked to IoT in manufacturing can ameliorate quality pass rates and equipment performance and achieve process optimization.

For example, one ecumenical pharmaceutical company that implemented an analytics system linked to IoT ameliorated its adherence to regulatory guidelines with a simplified and standard ecumenical process. Its truncated stability reporting time by 94% and the batch failure rate from 10% to 1%. Widespread adoption of these systems could have a sizably voluminous impact on ecumenical engenderment capacity. A supplemental 9% per batch on an ecumenical scale is an abundance of the vaccine.

Covid-19 and Beyond

Machine learning and big data analytics are being used efficaciously in the manufacturing sector to achieve superior quality control. Leveraging principles of advanced sizably voluminous data analytics and machine learning concepts such as neural networks, manufacturing companies can identify defects, unearth the root cause of quandaries, soothsay quality- critical deviations with precision, truncate the peril of shipping non-conforming components and additionally enable engineering improvements.

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Sunday 12 December 2021

Why Pharma Students need SAS Knowledge?

For Pharma Students, adding SAS skills will make the most sought after a profile in the healthcare industry. Sankhyana’s (SAS Authorized Training Partner in India) Clinical Programme will not only help them to get a better opportunity but also launch a career in the pharmaceutical industry.

While SAS programs are utilized across a variety of industries, their utilization in healthcare is becoming ubiquitous. Jobs analyzing data in health indemnification, pharmaceuticals, care providers, billing, and regime agencies are proliferating and increasingly, a construal of SAS programming is required.

According to a study from Money magazine and Payscale.com which outlined skills considered most valuable by employers across 350 different industries, SAS skills took the No. 1 spot with an average pay boost of 6.1%. Data mining and modeling were withal listed as highly valuable skills, both of which are a component of SAS operations.

The market for SAS certified employment candidates is growing at an expeditious rate. More than 80,000 companies are utilizing SAS software, according to the SAS Institute, and the number of potential employers utilizing its implements is liable to increment.

SAS Unleashes the power of Analytics

Through SAS programs, healthcare companies can cultivate cleaner data that is more consummate, consistent, and reliable. It additionally provides incipient ways to report and visualize data.

For clinicians, some major benefits of SAS programs include the competency to quantify treatment efficacy and develop clinical profiles that can reveal insights about a doctor’s practice patterns and compare it with that of other medicos and industry standards.

SAS® in the Life Sciences Industry – Facts & Figures

  • 100% life sciences companies on the Fortune 500 use SAS
  • >2,350 life sciences companies of all sizes use SAS
  • 45 countries with life sciences companies using SAS

Clinical SAS Training Key features with Sankhyana:

  • Learn fundamental programming skills on SAS covering modules on Base SAS, SAS Macros & SAS SQL.
  • Learn fundamental concepts and approaches that govern the design, analysis, and interpretation of clinical research studies.
  • Learn a basic overview of the clinical research industry and new drug development. Students will be introduced to the language that is typically associated with clinical research and the pharmaceutical industry.
  • They will have an opportunity to learn, understand, and apply this terminology in the context of clinical research.
  • Training also includes an overview of the process of new drug development from discovery through regulatory to approval and introduction to the market.
  • Training is designed to provide students with the background needed to pursue several additional courses in the areas of biostatistics, clinical data analysis, and biostatistical programming.
  • The course is a combination of course-work & hands-on learning and focused on the practical aspects of performing clinical trial analyses in the pharmaceutical industry.
  • Important topics such as CDISC, MedDRA, WHODrug, and SOPs, and other industry regulations and standards will be also presented to the students during the course.
  • At the end of the training, students will acquire skills in the area of creating datasets, tables, and listings; preparing graphics; and performing commonly used statistical analysis.

Conclusion:

SAS skills are utilizable in many departments. With a bachelor’s degree, jobs like data management and SAS programming are good commencement. The position sanctions you be habituated with the data and structure, access and process data, and make tables, listings, and graphics. With advanced degrees in master or Ph.D. in statistics or cognate field, there are more chances to be culled for statistician roles.

About SAS: SAS is the leader in analytics. SAS is the No.1 advanced analytics skills to have in this data-driven world.

About Sankhyana: Sankhyana (SAS Authorized Training Partner in India) is a premium and the best Clinical SAS Training Institute in Bangalore/India offers the best Clinical SAS training on SAS and Data Management tools.

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Saturday 4 December 2021

What is CDISC and What it means for SAS Programmers?

Clinical Data Interchange Standards Consortium (CDISC) is a global not-for-profit organization that focused on the interchange of clinical information within the pharmaceutical market. Categorically, CDISC is very aligned with the desiderata of clinical tribulation data exchange as it relates to clinical research workflow.

The goal of CDISC is to catalyze the information permeate pre-clinical and clinical research process, from study protocol and sundry data amassment to analysis and reporting through regulatory submission and electronic data archive. CDISC mainly consists of the following:

  • Study Data Tabulation Model (SDTM)
  • Analysis Data Model (ADaM)
  • Operational Data Model (ODM)
  • Laboratory Data Model (LAB)
  • Case Report Tabulation Data Define Designation (CRTDDS) – Define.xml
  • Protocol Representation (PR)
  • Tribulation Design Model (TDM)
  • Clinical Data Acquisition Standards Harmonization (CDASH)
  • Terminology

Benefits of implementing CDISC standards?

  • Fostered efficiency
  • Complete traceability
  • Enhanced innovation
  • Amended data quality
  • Facilitated data sharing
  • Abbreviated costs
  • Incremented predictability
  • Streamlined processes

Involvement of SAS Programmers in Clinical Trials

The role of Clinical Trials SAS Programmers vary from simple SAS programming to engendering the analysis data and the table, listing, and graphs. The following are examples of various roles for clinical trials SAS programmers:

  • Edit Check Programming
  • eCRF annotation
  • Engendering the derived data sets
  • Engendering the tables, listings, and graphs.
  • Importing the external data and converting to SAS data sets.

The implementation of CDISC standards requires more than programming from SAS programmers. The role of SAS programmers in CDISC depends on the job description in each company, but SAS programmers can be exposed to the following areas in the CDISC environment other than SAS programming adeptness.

  • SDTM – Electronic Data Capture (EDC) and Electronic Case Report Form(eCRF) annotation
  • ADaM – Statistics
  • ODM – XML programming cognizance
  • LAB – Conversion of aeonian data to SAS data set format
  • Define.xml – Metadata of SDTM and ADaM and XML programming cognizance
  • PR – Protocol
  • TDM – Statistical Analysis Plan (SAP) and SDTM
  • CDASH – EDC system
  • Terminology

As indicated above, each standard requires different skills and backgrounds from SAS programmers. Conventionally SAS programmers get involved in developing SDTM and ADaM. SDTM can be developed from raw data from EDC by SAS. So, SAS programmers need to understand the following:

  • Electronic Data Capture (EDC) system (ex. Oracle Clinical, Apprise, ClinTrial, etc.)
  • Database Structure
  • Domains or tables
  • Data Type – numeric, character, timing, etc.
  • Conversion of data to SAS format
  • SDTM Concepts

ADaM is customarily derived from SDTM. The rudimentary principles of ADaM are analysis readiness, traceability, and the link to metadata. In order to provide traceability and metadata, SAS programmers need to understand SDTM. To engender analysis-ready ADaM, SAS programmers need to understand the statistical method for some of the efficacy analysis.

SAS programmers withal need to understand the exact SAS statistical procedures for analysis such as proc

denotes, proc freq, proc ttest, proc glm, proc npar1way, proc reg, proc commixed, proc life test, proc phreg, proc logistics, and so on.

Advantages for SAS Programmers

There will be more data in the health care industry to analyze because all the data including the clinical trial data become standardized. It will be much easier to obtain and analyze the data and SAS will provide the best solution. SAS won’t be the only software, but simply one of the best out there especially in the data manipulation and analysis. Due to the current involvement in the clinical trial, the role of SAS programmers will expand. Because SAS programmers are the last group in the CDISC path, we will be in the ideal position to review the final output as well as all the CDISC clinical trial processes. The SAS programmers’ involvement in the CDISC clinical trial is likely to expand. There will be more opportunities for SAS programmers who have CDISC experiences. Rather than starting from scratch, some sponsors will outsource CDISC implementation and manage that process. Therefore, SAS programmers who have extensive CDISC experiences will have more opportunities as consultants as well as project managers.

Disadvantages for SAS Programmers

There will be more software package to analyze CDISC data adjacent to SAS. Because CDISC is a standardized form, it is much more facile to import the data into the software for the automatic analysis. For example, JMP® Clinical apperceives. CDISC data and automates the analytics and reporting of the safety data albeit the users do not have CDISC cognizance. Consequently, some of SAS programming could be superseded because of the emergence of other CDISC concrete software.

Because of the emergence of ODM, there will be a great demand in XML data format. XML format data will be used in data transfer more. CDISC is a component of electronic clinical tribulation rather than paper, so the pace of CDISC clinical tribulation will go more expeditious, so SAS programmers do not have as much time as afore. CDISC is the standardized process, so SAS programmers need to work in a more structured and standardized setting than before.

Things to consider

The pharmaceutical industry heavily depends on SAS programming for data manipulation and statistical analysis. But, the FDA relishes being neutral in terms of vendor cull. XML is an open data model and vendor-neutral so even FDA discusses the possibility to accept SDTM and ADaM by XML format not by SAS XPORT format in the future. It is not sure if the transition from XPORT to XML will ever transpire because of the nature of clinical data, but it is sure that XML format data will be utilized more. It will be a great advantage if SAS programmers ken about XML data format.

Since all the clinical data is standardized, it will be more facile to integrate the clinical data. So, there will be more opportunities in data mining. The company and agencies will endeavor to analyze the clinical data across different clinical tribulations and therapeutic areas. CDISC is a component of drive that all the data should be in the standardized form, so CDISC will follow the direction that its data can be merged into other standardized data such as HL7. So, SAS programmers who have the faculty to understand the different data structures and formats will be able to take full advantage of the standardization movement in health care data.

For example, unlike the mundane tabular structure in the clinical tribulation such as SDTM and ADaM, the ODM XML data structure is hierarchical. In additament, SAS programmers will spend more time developing structured codes such as CDISC concrete macros rather than custom SAS programming. SAS programmers should have a clear understanding of CDISC for FDA submission to evade the delay or repudiation by the FDA because the submission does not meet FDA prospects.

Conclusion:

CDISC will present the disadvantages and advantages to SAS programmers. If SAS programmers want to prosper in the CDICS environment, they require to understand the purport of CDISC implementation and each critical path and furthermore, learn the compulsory skills. In additament, the current CDISC is not a final product. It will keep evolving. It is not sure how CDISC will evolve, but if SAS programmers are open to changes and are able to acclimate to the incipient changes and skills, SAS programmers will be able to take full advantage of it as CDISC progresses.

About SAS: SAS is the leader in analytics. SAS is the No.1 advanced analytics skills to have in this data-driven world.

About Sankhyana Education: Sankhyana (SAS Authorized Training Partner in India) is a premium and the best Online Clinical SAS Training Institute in Bangalore/India offers the best Clinical SAS training on SAS and Data Management tools.

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Wednesday 13 October 2021

 



SAS Tutorials for Beginners: All You Need to Know


In this blog, you will learn SAS from the basics. This SAS tutorial includes various aspects of SAS programming like data sets, data table, functions, write and submit SAS code, arrays, and use interactive features to quickly generate graphs and statistical analyses.

What is SAS?

SAS is one of the most popular tools for data analysis and statistical Modeling. It is one of the powerful software tools for data management, data collection, data extraction, data mining, data exploration, report writing, statistical analysis, business modeling, application development, and data warehousing, data integration, data visualization, building predictive models, etc. SAS is an asset in many job markets as it holds the largest market share in terms of jobs in the advanced analytics field.

Why SAS is popular in this data-driven world?

  • SAS is the leader in the field of Analytics and the largest independent vendor in the BI (Business Intelligence) market.
  • SAS provides software to 96 of the top 100 companies on the Global Fortune 500.
  • In SAS software we can work on millions of different data to gain business insights.
  • SAS is versatile with different types of input and output formats. 
  • SAS can read files created by statistical packages. SAS sanctions Minitab, Stata, SPS, Excel and other data files to include directly in the SAS program or through file conversion software.
  • SAS is a fourth-generation programming language. A fourth-generation programming language is a programming language designed with a specific purpose in mind such as the development of commercial business software.
  • SAS documentation is very detailed as compared to open-source software like R and Python.

SAS Tutorial for beginners:

  • Using SAS: This video describes SAS software and various user interfaces.

https://www.youtube.com/watch?v=4dg86Vw5E2I&list=PLVBcK_IpFVi8NP3eH1DqxSPFBw5TcPdAK&index=1

  • Working in SAS Studio: In this video, we explore how the features of the navigation pane can avail you as you work in SAS Studio.

https://www.youtube.com/watch?v=usnucvpnGLM&list=PLVBcK_IpFVi8NP3eH1DqxSPFBw5TcPdAK&index=2

  • Getting started with SAS studio: In this video, you get commenced with programming in SAS Studio. You view a data table, indite and submit SAS code, view the log and results, and use interactive features to expeditiously engender graphs and statistical analyses.

https://www.youtube.com/watch?v=pE5awNW53z8&list=PLVBcK_IpFVi8NP3eH1DqxSPFBw5TcPdAK&index=3

  • Accessing your existing data for SAS university edition: This video shows you how to access your subsisting local files utilizing the SAS Studio interface and in the SAS program code.

https://www.youtube.com/watch?v=cFuaaavKvSE&list=PLVBcK_IpFVi8NP3eH1DqxSPFBw5TcPdAK&index=4

  • Importing a Microsoft excel file in SAS university edition: In this video, you learn how to utilize the Import XLSX File snippet in SAS University Edition. You withal learn how to engender a custom snippet to import an XLS file.

https://www.youtube.com/watch?v=oWBOEy9wSjo&list=PLVBcK_IpFVi8NP3eH1DqxSPFBw5TcPdAK&index=5

  • Reading and generating CSV files using SAS studio: In this video, you learn to read and engender comma-disunited-value files utilizing SAS Studio.

https://www.youtube.com/watch?v=OSX5ZPtB5A&list=PLVBcK_IpFVi8NP3eH1Dq



xSPFBw5TcPdAK&index=6

I Hope, this info is productive for beginners. If you are looking for SAS classroom, online/live- web, corporate or academia training, kindly enquire here: https://forms.gle/U7mHt5kebtT57hKG8

Sankhyana Consultancy Services (SAS Authorized Training Partner) is a premium and best sas training institute in bangalore that provides innovative, flexible, accessible blended learning solutions and career-oriented training following a competitive tendering process.

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