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\n\nThroughout 21 CFR and guidance documents for t he pharmaceutical\, biopharmaceutical\, and medical device industries\, th e application of statistical methods are specified for: setting validation criteria and specifications\, performing measurement systems analysis (MS A)\, conducting stability analysis\, using design of experiment (DOE) for process development and validation\, developing process control charts\, a nd determining process capability indices.
\n\nDifferent statistical methods are required for each of these particular applications. Data and tolerance intervals are common tools used for setting acceptance criteria and specifications. Simple linear regression and analysis-of-covariance (A NCOVA) are used for setting expiries and conducting stability analysis stu dies. Two-sample hypothesis tests\, analysis-of-variance (ANOVA)\, regress ion\, and ANCOVA are methods used for analyzing designed experiment for pr ocess development and validation studies. Descriptive statistics (distribu tion\, summary statistics)\, run charts\, and probability (distributions) are used for developing process control charts and developing process capa bility indices.
\n\nThis course provides instruction on how to apply the appropriate statistical approaches: descriptive statistics\, data int ervals\, hypothesis testing\, ANOVA\, regression\, ANCOVA\, and model buil ding. Once competence in each of these areas is established\, industry-spe cific applications are presented for the participants.
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\n21 CFR and guid
ance documents for the pharmaceutical\, biopharmaceutical\, and medical de
vice industries specify the application of statistical methods across the
product quality lifecycle.
According to the Quality System Regul ation (QSR) for medical devices\, "\;Where appropriate\, each manufact urer shall establish and maintain procedures for identifying valid statist ical techniques required for establishing\, controlling\, verifying the ac ceptability of process capability and product characteristics."\; Alth ough there are many statistical method that may be applied to satisfy this portion of the QSR\, there are some commonly accepted methods that all co mpanies can and should be using to develop acceptance criteria\, to ensure accurate and precise measurement systems\, to fully characterize manufact uring processes\, to monitor and control process results and to select an appropriate number of samples.
\n\nAccording to both 21 CFR and guid ance documents\, the need for statistical methods is well established from discovery through product discontinuation. 21 CFR specifies the "\;th e application of suitable statistical procedures"\; to establish both in-process and final specifications. The guidance documents necessitate th e application of statistical methods for development and validation of mea surement systems\, process understanding using Quality by Design (QbD) pri nciples\, process validation\, as well as ensuring the manufacturing proce ss is in control and is capable.
\n\nThis course provides instructio n statistical methods for data analysis of applications related to the pha rmaceutical\, biopharmaceutical\, and medical device industries.
\n\n
\nThis
seminar is designed for pharmaceutical\, biopharmaceutical\, and medical d
evice professionals who are involved with product and/or process design:
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\n\nAGENDA
\n\n<
br />\nDay 1 Schedule
\n
\nLecture
1:
Basic Statistics
\nsample versus populatio
n
\ndescriptive statistics
\ndescribing a distribution of values
\n
\nLecture 2:
Intervals\nconfidence intervals
\nprediction intervals
\ntolerance in
tervals
\n
\nLecture 3:
Hypo
thesis Testing
\nintroducing hypothesis testing
\nperforming mea
ns tests
\nperforming normality tests and making non-normal data norm
al
\n
\nLecture 4:
ANOVA
\ndefining analysis of variance and other terminology
\ndiscussing
assumptions and interpretation
\ninterpreting hypothesis statements f
or ANOVA
\nperforming one-way ANOVA
\nperforming two-way ANOVA
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\n\nDay 2 Schedule
\n
\n
Lecture 1:
Regression and ANCOVA
\nproduci
ng scatterplots and performing correlation
\nperforming simple linear
regression
\nperforming multiple linear regression
\nperforming
ANCOVA
\nusing model diagnostics
\n
\nLecture
2:
Applied Statistics
\nsetting specification
s
\nMeasurement Systems Analysis (MSA) for assays
\nstability an
alysis
\nintroduction to design of experiments (DOE)
\nprocess c
ontrol and capability
\npresenting results
\n
SPEAKER
\n\n
Jim Wisnowski \;is the cofounder of Adsurgo LLC and co-author of the book Design and Analysi s of Experiments by Douglas Montgomery: A Supplement for using JMP. He has over 25 years of experience and currently provides training and consultin g services to industry and government in Design of Experiments (DOE)\, Rel iability Engineering\, Data Visualization\, Predictive Analytics\, and Tex t Mining. Dr. Wisnowski has been an invited speaker on applicability of st atistics for national and international conferences. Prior to his current position\, he was a senior program manager for URS\, Chief of the Statisti cs Division in the Mathematics Department at the Air Force Academy\, and a retired military officer. He is currently a member of the editorial board of Quality Engineering and has published numerous international refereed journal articles on statistics. Jim has a PhD in Industrial Engineering fr om Arizona State University.
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