200+ followers. WOWWWWWW…

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Hello Everyone,

Today we have the pleasure of celebrating the fact that we have reached the milestone of 200+ followers on WordPress. Since we started this blog, we have had such a great time connecting with everyone.  we never expected to actually to connect with other people in the blogging community.

we are so incredibly thankful for each and every one of you who follows and comments on my blog posts. Please know that!

we would continue our blogging in these areas FDA Regulation, Medical Devices, Drugs and Biologics, Healthcare Compliance, Biotechnology, Clinical Research, Laboratory Compliance, Quality Management ,HIPAA Compliance ,OSHA Compliance, Risk Management, Trade and Logistics Compliance ,Banking and Financial Services, Auditing/Accounting & Tax, Packaging and Labeling, SOX Compliance, Environmental Compliance, Microsoft Excel Spreadsheet, Geology and Mining, Human Resources Compliance, Food Safety Compliance and etc.

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It is important for non-statisticians to become familiar with biostatistics

biostatistics

Statistics is extremely useful as a decision-making tool in the clinical research arena. In areas such as working in a field where a p-value can determine the next steps on development of a drug or procedure, it is very handy, because of which it is imperative for decision makers to understand the theory and application of statistics.

Many statistical software applications have now been developed and made available to professionals. It needs to be borne in mind that these software applications were developed for statisticians, because of which its use can baffle non-statisticians. Their confusions could be as basic as pressing the right key, let alone performing the best test.

A full learning session on biostatistics for the non-statistician

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A seminar from GlobalCompliancePanel, a leading provider of professional trainings for all the areas of regulatory compliance, will throw light on the importance of biostatistics for the non-statistician.

Elaine Eisenbeisz, a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California, who has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations to start-up companies and individual researchers; will be the Director of this seminar.

Want to understand the importance of biostatistics for the non-statistician? Then, please enrol for this seminar by visiting It is important for non-statisticians to become familiar with biostatistics. This seminar has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

Statistical concepts in clinical research

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Designed essentially for non-statisticians; this seminar provides a non-mathematical introduction to biostatistics. It will be of high value to professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

Elaine will equip participants of this seminar with the information and skills necessary to understand statistical concepts and findings as they relate to clinical research. With this information, they will be able to confidently communicate with people with whom they need to.

Elaine will place emphasis on the actual statistical concepts, application, and interpretation. She will not go into the areas of mathematical formulas or actual data analysis. A basic understanding of statistics is desired from the participants, but is not necessary.

This course on biostatistics for the non-statistician will help professionals involved in this area, such as Physicians, Clinical Research Associates, and Clinical Project Managers/Leaders, Sponsors, Regulatory Professionals who use statistical concepts/terminology in reporting, and Medical Writers who need to interpret statistical reports.

Elaine’s agenda for this two-day seminar will consist of the following:

Why Statistics?

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  • Do we really need statistical tests?
  • Sample vs. Population
  • I’m a statistician not a magician! What statistics can and can’t do
  • Descriptive statistics and measures of variability

The many ways of interpretation

  • Confidence intervals
  • p-values
  • effect sizes
  • Clinical vs. meaningful significance

Common Statistical Tests

  • Comparative tests
  • Regression analysis
  • Non-parametric techniques

Bayesian Logic

  • A different way of thinking
  • Bayesian methods and statistical significance
  • Bayesian applications to diagnostics testing
  • Bayesian applications to genetics

Interpreting Statistics – Team Exercise

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  • Team Exercise: Review a scientific paper and learn how to
    • Interpret statistical jargon
    • Look for reproducibility, transparency, bias, and limitations
    • Convey information coherently to non-statisticians

Study power and sample size

  • Review of p-value, significance level, effect size
  • Formulas, software, and other resources for computing a sample size

Developing a Statistical Analysis Plan

Specialized topics/Closing Comments/Q&A

  • Comparing Survival Curves
  • Pharmacokinetics/Pharmacodynamics (PK/PD)
  • Taking a holistic view to study design and interpretation
  • Question and Answer session.

 

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Statins ‘should be given to children with heart risks before the age of 10’

Statins 'should be given

Statins should be given to thousands of children by the age of 10 under radical new NHS guidance.

GPs are being urged to identify those who have an inherited risk of high cholesterol, amid warnings that the vast majority of cases are going undetected.

Estimates suggest up to 260,000 people – including 50,000 children – are suffering from genetic deficts which affect the body’s ability to break down cholesterol.

New guidance from the National Institute for Health and Care Excellence (Nice) today says statins should be offered to such cases, to reduce their risk of heart or stroke in midlife.

Just 15 per cent of those with the condition are being treated for it, Nice said, including just 600 of 56,000 children with the genetic problem.

Family doctors are being asked to trawl records to idenitfy those with very high cholesterol levels.

Where levels of more than 9 mmol/l are found in those over 30, and those of 7.5 mmol/l are found in those under 30, high-dose statins should be offered, the NHS guidance states.

And it says gene tests should be used to find other family members – including those below the age of 10 – who are at such heightened risk that they should be put on medication.

Around 56,000 children are estimated to suffer from familial hypercholesterolaemia (FH), yet just 600 have been diagnosed, charities say.

The condition gives men a 50 per cent chance of suffering a heart attack or stroke before the age of 50, while women have a one in three chance by the age of 60.

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Orkambi Reduces Main Biomarker of CF, Vertex Says in Updated Results on Four Therapies

Orkambi Reduces

Orkambi (lumacaftor/ivacaftor) reduced levels of the main biomarker of the lung disease cystic fibrosis and improved the nutritional status of children with the condition, according to a Phase 3 clinical trial.

The results were part of a recent update that Vertex Pharmaceuticals provided on Orkambi and three of its other CF therapies, Kalydeco (ivacaftor), tezacaftor (VX-661) and VX-371.

Vertex conducted the Phase 3 trial (NCT02797132) of Orkambi to evaluate its effectiveness and safety in preschoolers with two copies of the CFTR gene’s F508del mutation. The 60 children were aged 2 to 5. Mutations of the gene cause CF by producing faulty versions of the CFTR protein.

An indication of Orkambi’s effectiveness in the trial was that it reduced the production of the children’s sweat chloride and improved their nutritional status.

A sweat test is the gold standard for diagnosing CF because people with the disease have more chloride in their sweat than those who don’t. As for nutrition, the thick mucus that CF produces in the digestive system can prevent patients from absorbing nutrients and fat properly, leading to difficulty gaining weight and slower growth. CF also produces the mucus in lungs and other organs.

The Phase 3 trial also showed that Orkambi was safe and that the children tolerated it well. Researchers reported no adverse events besides those seen in studies of patients aged 6 to 11.

Based on the promising results of the trial, Vertex plans to submit a New Drug Application on Orkambi to the U.S. Food and Drug Administration during the first quarter of 2018. It will also ask the European Medicines Agency to extend the therapy’s availability to very young children.

Another Phase 3 trial (NCT02412111) that Vertex conducted evaluated a combination of tezacaftor and Kalydeco’s ability to reduce respiratory problems in patients more than 12 years old.

The study included 151 participants at 68 sites in the United States, Canada, Australia, and the European Union. The patients had one copy of the F508del mutation and one copy of another CFTR mutation.

Eight weeks of treatment with the combo led to a negligible improvement in a measure of patients’ lung function known as forced expiratory volume in one second, or FEV1. This is the amount of air that people can forcefully blow out of their lungs in one second.

The combo did lead to a reduction in sweat chloride that was larger than Kalydeco generated alone, however.

Given the results, Vertex has decided not to continue pursuing regulatory approval for the combo. One reason is that most patients older than 12 are eligible to receive Kalydeco by itself.

The FDA is expected to make a decision by February 2018 on a related New Drug Application that Vertex has filed. That application involves using the tezacaftor-Kalydeco combo to treat patients aged 12 or older who carry two copies of an F508del mutation or one copy of an F508del mutation plus another mutation. The FDA is giving the request priority review.

European regulators are expected to decide whether to approve the combo therapy in the second half of 2018.

Vertex has completed enrolling children 12 to 24 months for another Phase 3 trial (NCT03277196) of Kalydeco. It will evaluate the therapy’s safety in children less than 2 years old with a CFTR gating mutation and an R117H mutation.

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The use of Applied Statistics for FDA Process Validation

Why you Should be Worried about HIPAAThe use of Applied Statistics for FDA Process Validation is considered a matter of very high importance in the pharmaceutical industry. The FDA’s guidance for the industry, which it called “Process Validation: General Principles and Practices”, was set up in 2011. This guideline sets the framework for Process Validation in the pharmaceutical industry. The FDA prescribes a three-stage process that any organization in the pharmaceutical industry has to set up:

  1. Process Design
  2. Process Qualification
  • Continued Process Verification.

The Process Design stage, which is called Stage 1, is when the organization defines the commercial manufacturing process. The knowledge that the organization has gained through development and scale-up activities serves as the basis for the development of this definition.

The Process Qualification, or Stage 2, involves evaluating the process design for the purpose of determining if the process defined in Stage I has the capability for reproducible commercial manufacturing.

The next stage of the FDA process validation stage is to determine if the Process Design stage and the Process Qualification stage give the ongoing assurance that the process remains in a state of control during routine production. This is what Stage 3, the Continued Process Verification, does.

Thorough understanding of how to implement Applied Statistics for FDA Process Validation

GMPs for Combination Products and 505(b)(2) Products

The ways of using Applied Statistics for FDA Process Validation will be the topic of a two-day seminar that GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will be organizing. At this seminar, Richard Burdick, Emeritus Professor of Statistics, Arizona State University (ASU) and former Quality Engineering Director for Amgen, Inc., will be the Director.

Please visit http://www.globalcompliancepanel.com/control/globalseminars/~product_id=901132SEMINAR?wordpress-SEO to register for this meaningful and highly valuable seminar on applied statistics for process validation. This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

A methodical approach to implementing statistical methodologies

Top 20 Costly Mistakes

The focus of this two-day course on Applied Statistics for FDA Process Validation is the various ways by which a systematic approach to implementing statistical methodologies into a process validation program consistent with the FDA guidance can be established.

Dr. Burdick will begin with a primer on statistics, where he will explain how the methods of Applied Statistics for FDA Process Validation seminar can be applied in each remaining chapter.

The two fundamental requirements for Process Validation, namely the application of statistics for setting specifications and assessing measurement systems (assays), will be taken up next.

The next aspect of applied statistics Dr. Burdick will move on to is how to apply statistics through the three stages of process validation as defined by requirements in the process validation regulatory guidance documents.

Since the methods taught through all these three stages are recommended by regulatory guidance documents; this seminar on Applied Statistics for FDA Process Validation will provide references to the specific citations in the guidance documents.

The aim of this learning on Applied Statistics for FDA Process Validation is to lead participants into ways of establishing a systematic approach to implementing statistical methodologies into a process development and validation program that is consistent with the FDA guidance.

Complete learning on Applied Statistics for FDA Process Validation

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Over the two days of this seminar, the participants will learn how to:

  • Apply statistics for setting specifications
  • Assess measurement systems (assays)
  • Use Design of Experiments (DOE)
  • Develop a control plan as part of a risk management strategy, and
  • Ensure process control/capability.

All concepts at this Applied Statistics for FDA Process Validation seminar are taught within the three-stage product cycle framework defined by requirements in the process validation regulatory guidance documents.

Although aimed at the pharmaceutical industry, this seminar on Applied Statistics for FDA Process Validation provides a useful framework for other related industries, as well.

In this important learning on Applied Statistics for FDA Process Validation; Dr. Burdick will cover the following areas:

  • Apply statistics to set specifications and validate measurement systems (assays)
  • Develop appropriate sample plans based on confidence and power
  • Implement suitable statistical methods into a process validation program for each of the three stages
  • Stage 1, Process Design: utilize risk management tools to identify and prioritize potential critical process parameters; and define critical process parameters and operating spaces for the commercial manufacturing process using design of experiments (DOE)
  • Stage 2, Process Qualification: assess scale effects while incorporating large (pilot and/or commercial) scale data; develop process performance qualification (PPQ) acceptance criteria by characterizing intra and inter-batch variability using process design data and batch homogeneity studies; and develop an appropriate sampling plan for PPQ
  • Stage 3, Continued Process Verification: develop a control plan as part of a risk management strategy; collect and analyze product and process data; and ensure your process is in (statistical) control and capable.

keep enhancing FDA Process Validation

Medicaid platinum, silver for the rest

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Insurance Commissioner Roger Sevigny … Findings of report are “not conclusive.”

CONCORD — The path New Hampshire has taken toward expanding Medicaid is pushing prices up for everyone else who buys health insurance on the Obamacare exchange at healthcare.gov, according to an analysis recently completed for the Insurance Department.

The average medical costs for the newly insured Medicaid patients are 26 percent higher than the non-Medicaid population on the exchange, even though the Medicaid patients are on average younger.

That is in large part because Medicaid patients are getting platinum plans that they use more aggressively because they have no co-pays or deductibles, while those paying some or all of their policy premiums are mostly in silver plans that they use more judiciously, according to the actuarial firm conducting the analysis.

“Generally, when populations are enrolled in plan offerings with low member cost-sharing, utilization of services is greater,” according to the actuaries from Gorman Actuarial who wrote the report. “This is referred to as induced demand.”

Gorman found that the presence of the expanded Medicaid population in the individual market raised average claim costs for the entire market by 14 percent.

The findings, based on 2016 claims data, were presented Monday to a legislative commission studying the future of expanded Medicaid in New Hampshire, which, in its current form, expires at the end of 2018.

One goal of Obamacare was to get more people covered, and part of the strategy was to make it easier to qualify for Medicaid, so-called “expanded Medicaid,” with the federal government paying 100 percent of the additional cost through 2016. Starting in 2017, the match declines slightly each year until it reaches 90 percent in 2020 and remains there, assuming the law is not changed or repealed.

Using the private market

Nineteen states, mostly in the South and Midwest, decided not to expand Medicaid, while New Hampshire was among 31 states and the District of Columbia that added to their Medicaid rolls. New Hampshire and Arkansas decided to use the private insurance market to cover the newly insured.

To qualify for traditional Medicaid in New Hampshire, you had to have low income as measured by federal poverty levels, and have an additional qualifying condition, such as being a parent or caretaker, disabled or pregnant.

The analysis can be viewed below:

With expanded Medicaid, unmarried, childless, able-bodied adults earning up to 138 percent of the federal poverty level could qualify, and in New Hampshire 40,000 took advantage of the opportunity.

But New Hampshire did not put those 40,000 new enrollees into the same traditional Medicaid program that was already serving 100,000 residents through managed care organizations that control costs. Instead, they obtained coverage from one of the companies offering plans on healthcare.gov, mostly the Ambetter plans offered by New Hampshire Healthy Families.

When the program was being designed that way, ostensibly to leverage the private sector instead of growing a government program, conservative groups like Americans for Prosperity warned against blending the new Medicaid customers whose costs are fully covered with customers who face co-pays and deductibles.

“Expanding Medicaid at all was a bad idea,” says Greg Moore, state director with Americans for Prosperity. “Expanding Medicaid in the individual marketplace was a disastrous one, and now we are asking people who are forced to buy health insurance under the Affordable Care Act to subsidize this bad decision.”

Proponents of expanded Medicaid, including the state’s hospitals, health care providers and many in the addiction treatment and recovery community, say the expansion has been an overall plus to the state, particularly in getting insurance for people in need of addiction-related services.

Facing a decision

So the state has to decide what to do about the program, as it sunsets in its current form in a little more than a year. Insurance Commissioner Roger Sevigny said the findings in the Gorman analysis are “not conclusive” on whether expanded Medicaid should continue in its current form in New Hampshire.

“How to best cover this population is a complex question that the New Hampshire Legislature will wrestle with in 2018,” he said. “These are times of unprecedented uncertainty for individual markets in New Hampshire and across the country ­— a factor that compounds the difficulty of the reauthorization question.”

Most New Hampshire residents who have health insurance obtain it through their employer in a group plan. But the state has about 90,000 individuals who buy insurance on the individual market, via healthcare.gov.

Of that 90,000, almost half (40,000) consist of the fully covered, expanded Medicaid population. The other half, about 50,000, consist of individuals who purchased policies on the exchange, many with premium subsidies.

The big question

One of the big questions the state has to face, if it keeps expanded Medicaid at all, is whether or not to keep the newly eligible population in the individual market or put it under traditional Medicaid.

Tyler Brannen, health care policy analyst in the Insurance Department, says the choice is not that obvious. Leaving the Medicaid population with the paying customers increases costs, but losing nearly half the risk pool in the online exchange would come with consequences of its own.

“They have increased claims cost,” says Brannen of the new Medicaid patients, “but in the future, they may be the ones who provide some stability because they may not be the people dropping out because of price increases.”

dsolomon@unionleader.com

Data visualization can have a great effect on statistical presentations

Data visualization 2

It is said that a picture is worth a thousand words. This adage may appear figurative and allegorical when applied to the realm of statistics, but there is no denying the fact that a visual approach to statistics enlivens the subject like no other. A dash of pictorial work and some coloring at the right places enhance the presentation of otherwise drab statistical figures and slides dramatically.

Graphic displays illustrate the facts and truths behind statistics very artistically. They augment the appeal of what is conveyed by the statistical figures without altering or diluting the effect or the content. This is why presenting data visually is a great enhancer. It is very useful in any compliance analytics workflow.

Graphic enhancements can be used to uplift and raise the presentational aspects of statistics, but it requires skill and specific tools, because the pictorial aspect has to fit rightly into the statistical presentations. Any mismatch or mix-ups can have the opposite effect, making the statistical pictures gaudy, out of place and jarring.

Get to the ways of doing it

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A two-day seminar from GlobalCompliancePanel, a highly respected provider of professional trainings for the regulatory areas, will offer thorough and complete learning on the proper ways of beautifying statistical presentations with the right mix of graphics, so that the intended purpose of embellishing is met.

James Wisnowski, who is the cofounder of Adsurgo LLC and co-author of the book, Design and Analysis of Experiments by Douglas Montgomery: A Supplement for using JMP and currently provides training and consulting services to industry and government in Design of Experiments (DOE), Reliability Engineering, Data Visualization, Predictive Analytics, and Text Mining; will be the Director at this two-day seminar.

Please visit Data visualization can have a great effect on statistical presentations  to enroll for this highly interesting seminar, which has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

All about graphics in statistics

Data visualization 4

This seminar on data visualization will present methods using which participants can interactively discover relationships graphically. James will offer participants the foundations that will help them create better graphical information with which to accelerate the insight discovery process and improve the comprehension of reported results.

He will lead participants to an exploration of the first principles and the “human as part of the system” aspects of information visualization from multiple leading sources such as Harvard Business Review, Edward Tufte, and Stephen Few. All this will be done using representative example data sets. Best practices for graphical excellence to most effectively, clearly, and efficiently communicate a thought will be explained. He will show how to construct visualizations for univariate, multivariate, time-dependent, and geographical data. Participants are encouraged to bring laptops to follow along demonstrations in JMP (free trial download at www.jmp.com), and open source solutions such as R (https://www.r-project.org) and Tableau Public (https://public.tableau.com/s/).

Meeting the requirements of analytic solutions

Data visualization 3

As all regulated industries have now come to expect data-driven decisions; compliance regulations require analytic solutions. The starting point of these solutions is the development of data visualization for discovering relationships and finish with crisp graphs communicating results. To take the example of 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries; these documents specify the application of statistical methods for the following:

For each of these areas, data visualization serves as the foundation. Data visualization plays a major role in varying degrees in varied areas such as:

  • meeting FDA analytical requirements for third-tier critical to quality attributes for analytical bio similarity evaluations where graphical plots and tables alone may sufficiently address compliance criteria

 

  • HIPAA compliance, risk management and analysis, and many others of the quality functions.

James will show how to use data visualization and optimize the effect of these areas. The following agendas will be part of the two-day presentation:

  • Introduction and definitions
  • Examples of data visualizations for compliance and regulated industries
  • Historical context
  • Characteristics of data
  • Interactive data visualization exploration with Excel and websites
  • Human side of data visualization
  • Principles of good graphic design
  • Data visualization methodology
  • Best practices
  • Software introduction: JMP
  • Univariate plots
  • Distributions and histograms
  • Pie graphs, violin plots, pareto plots, box plots
  • Conditional formatting
  • Mulitvariate plots and heatmaps
  • Correlation
  • Multivariate scatterplots and density graphs
  • Contour plots
  • Categorical data plots: treemaps, mosaic plots
  • Software introduction: R
  • Software introduction: Tableau Public
  • Univariate plots with R and Tableau
  • Multivariate plots with R and Tableau
  • Dynamic and interactive graphs
  • Brushing, dynamic linking, and filtering
  • Profilers on response variables and optimization
  • Time series plots
  • Waterfall plots
  • Sparklines and trend lines
  • Statistical Process Control charts
  • Maps
  • Text data visualization
  • Dashboards
  • Course summary.

 

Seminar Calendar of Upcoming Courses – June to July – 2017

seminars are a wonderful opportunity for professionals in the regulatory compliance

Upcoming-Courses-for-French-Circles-Club

GlobalCompliancePanel’s seminars are a wonderful opportunity for professionals in the regulatory compliance areas to understand the latest happenings and updates in the regulatory compliance areas and to implement them, something they need to climb in their professions. GlobalCompliancePanel brings together a few of the best recognized names in the field of regulatory compliance on its panel of experts. The result: Learning that is effective, valuable and helpful.

GlobalCompliancePanel’s experts help you unravel all the knowledge you need in all the areas of regulatory compliance. At these seminars which are held all over the globe, you get to interact with them in person, so that any doubt or clarification you have is sorted out by none other than the honcho. They help professionals like you implement the regulations and stay updated, so that regulatory compliance causes no stress for you.

GlobalCompliancePanel’s experts offer their insightful analysis into the issues that are of consequence to regulatory professionals in their daily work. Their thoughts help you implement the best practices of the industry into your work. They also offer updates on the latest regulatory requirements arising out of a host of the laws and issues related to regulatory compliance, including, but not limited to medical devices, food and beverages, pharmaceuticals, life sciences, biotechnology and pharmaceutical water systems.

Take a look at our upcoming webinars from GlobalCompliancePanel, which will put you on the road to learning about any area that is of importance to your profession. You can plan your learning from GlobalCompliancePanel by looking at our seminars in the next few weeks at locations of convenience to you. You can choose from a whole range of topics. See which among these trainings suit you: Design of Experiments (DOE) for Process Development and Validation, Writing and implementing effective SOP’s, new FSMA rules, risk management and device regulations, data integrity, combination products, and what have you!

Contact us today!
NetZealous LLC DBA GlobalCompliancePanel
john.robinson@globalcompliancepanel.com
Toll free: +1-800-447-9407
FAX : 302 288 6884
Website: http://bit.ly/Courses-June-to-July-2017

Understanding the practical application of statistics?

The application of statistical methods is specified all through 21 CFR and guidance documents

The application of statistical methods is specified all through 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries for these activities:

o  Setting validation criteria and specifications

o  Performing Measurement Systems Analysis (MSA)

o  Conducting stability analysis

o  Using Design of Experiment (DOE) for process development and validation

o  Developing process control charts

o  Determining process capability indices.

The Quality System Regulation (QSR) for medical devices states that manufacturers should take steps, where appropriate, for establishing and maintaining procedures with which to identify valid statistical techniques needed to establish, control, and verify that the process capability and product characteristics are acceptable.

Methods are specified in 21 CFR and guidance documents

Both 21 CFR and guidance documents emphasize the need for statistical methods from discovery through product discontinuation. While 21 CFR specifies the suitable statistical procedures needed to establish both in-process and final specifications; the guidance documents require applying statistical methods for development and validation of measurement systems, process understanding using Quality by Design (QbD) principles, process validation, as well as ensuring that the manufacturing process is in a state of control and is capable.

Even though many statistical methods may be applied to fulfil this part of the QSR; there exist a few commonly accepted methods that all companies can and preferably should use for:

o  Developing acceptance criteria

o  Ensuring accurate and precise measurement systems

o  Fully characterizing manufacturing processes

o  Monitoring and controlling process results, and

o  Selecting an appropriate number of samples.

Learn the dynamics of statistical methods

The nitty gritty of application of statistical methods will be the teaching a two-day seminar from GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will be offering. At this seminar, Heath Rushing, who is the cofounder of Adsurgo and author of the book Design and Analysis of Experiments by Douglas Montgomery: A Supplement for using JMP; will be the Director.

This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion. To understand the areas of implementation of statistical methods that comply with the requirements set out in CFR 21 and guidance documents, please enroll for this session by visiting “Understanding the practical application of statistics”

A full description of statistical processes

This course provides instruction on the statistical methods for data analysis of applications related to the pharmaceutical, biopharmaceutical, and medical device industries. The Director will explain the appropriate statistical approaches: descriptive statistics, data intervals, hypothesis testing, ANOVA, regression, ANCOVA, and model building need to be applied. Upon establishment of competence in each of these areas; he will present the way these need to be applied in an industry-specific manner.

During the course of these two days, Heath will cover the following areas:

·        Describe and analyze the distribution of data

·        Develop summary statistics

·        Generate and analyze statistical intervals and hypothesis tests to make data-driven decisions

·        Describe the relationship between and among two or more factors or responses

·        Understand issues related to sampling and calculate appropriate sample sizes

·        Use statistical intervals to setting specifications/develop acceptance criteria

·        Use Measurement Systems Analysis (MSA) to estimate variance associated with: repeatability, intermediate precision, and reproducibility

·        Ensure your process is in (statistical) control and capable.

Article on “Statistical Sampling Plans for Medical Devices”

One of the important aspects of design control of medical devices is statistical sampling plans for medical devices. To gain an understanding of the idea of statistical sampling plans for medical devices, one needs to understand the process of medical device design controls.

Statistical sampling plans for medical devices needs to be seen in this background: Under Sec. 820.30 of Title 21 of Code of Federal Regulations (CRF) the FDA sets out requirements from medical device manufacturers -which want to market certain categories of medical devices in the US -for establishing and maintaining procedures to implements design controls into the device.

An understanding of design controls is necessary first

First of all, what are design controls? Design controls are linearly and logically described and recommended steps that manufacturers have to take for ensuring that they have developed what they meant to develop. In addition, design controls have to also be implemented to ensure that the final product is in line with the expectations and needs from the customer’s perspective.

Statistical sampling plans for medical devices come at a slightly later stage. Design controls pave way for the validation processes of design verification and design, which are done to ensure that the device design has met critical specifications or outputs and fulfill the requirements for the safety requirements, intended use, or specified application.

Verification and validation

This stage makes way for the next, which is fulfillment of design verification and validation (V&V), as required under Sec. 820.50 of 21 CFR. A core part of this code is the requirement from manufacturers for establishing and maintaining procedures to locate valid and proper statistical techniques for the process capability and product characteristics to be considered applicable. These are what constitute statistical sampling plans for medical devices

More of rule of thumb

Statistical sampling plans for medical devices need to be written and based on a well-established statistical foundation. However, the FDA does not prescribe a formal plan for writing down statistical sampling plans for medical devices. These are to be based more on rule of thumb. In other words, there are no acceptable limits violations under statistical sampling plans for medical devices. The statistical sampling plans for medical devices need to be implemented on a case-to-case basis, based on the device’s characteristics and features.

In arriving at statistical sampling plans for medical devices, the FDA sets out the following rule:

Table 1

Binomial Staged Sampling Plans

Binomial Confidence Levels

able 2

Binomial Staged Sampling Plans

Binomial Confidence Levels

ucl = Upper Confidence Level

These constitute the core guidance for statistical sampling plans for medical devices.

Learn more on this topic by visiting: Article on “Statistical Sampling Plans for Medical Devices”