Description

This objective of this seminar is to provide participants with an understanding of:

• Basic principles of bio-statistical thinking and methodology
• Design and analysis of clinical trials
• Techniques for increasing trial efficiency with an eye to reducing costs and increasing chance for success

This seminar is intended for non-statisticians and will furnish participants with tools to understand statistical terminology and methodology in clinical trials. The presentation will focus on actual case studies as they relate to regulatory requirements (FDA, EMA and EU). There is no statistical prerequisite for this seminar.

Who will Benefit:

Following titles and departments who are involved with the statistical aspect of clinical trials, in order of bio-statistic’s will be benefited by attending this seminar:

• Departments: Clinical, Regulatory, R&D, Marketing
• Clinical Titles: Medical Director, Director of Clinical Affairs, VP Clinical, Clinical Manager, Clinical Department Manager, Clinical Project Manager, Clinical Staff, CRA (Clinical Research Associate), Study Coordinator
• Regulatory Titles: VP Regulatory Affairs, Manager of Regulatory Affairs, Regulatory Scientist
• R&D Titles: Director of R&D, VP R&D, R&D Project Manager, Engineers, Quality Engineer, Algorithm Developer

Attend this seminar to mitigate below risks:

Stat for device submissions for non-statisticians: Not being exposed to the information in this course is likely to lead to inefficient, and perhaps even erroneous, interactions with FDA. This can result in various difficulties such as:

• Being asked by FDA to meet harsher criteria than might have been needed, thus reducing Company’s chance for success
• Needing a much larger sample size than if the correct approach was used
• Specifying inefficient statistical analyses that reduce a trial’s chance for success (for example, running a clinical trial that does not deal efficiently with missing values)

Bio-statistics for non-statisticians: Not being conversant in statistics means that the staff member cannot understand basic concepts in clinical trials such as endpoint selection, trial sample size and trial length. Not knowing how to deal with these issues can cause a company a great deal of damage in terms of inefficient product development (costly in terms of both time and money), inefficient trial design, and erroneous interactions with statisticians. All these can lead to inefficient product development and regulatory submission and even failure:

• Almost everyone in the clinical, regulatory and R&D departments should be familiar to one degree or another with bio-statistics. It is the language of regulatory submissions, study design and accounts for much that is presented to FDA (and all regulators) in the clinical study report (CSR). The CSR is the final clinical trial document presented to FDA when submitting a product for approval. Company staff must be at least conversant in bio-statistics so that they can:
  • Interact intelligently and efficiently with company statisticians, most of whom are subcontracted (i.e. not part of the organization)
  • Be able to audit the statistician’s decisions
  • Understand what competitors have done to demonstrate their product works to both regulator and the market
  • Assist physicians, who are typically clinically oriented, to think in terms of the research needed for bringing a product to market

Efficient Design for non-statisticians:Designing inefficient trials will, at best, cause unnecessary costs in terms of both time and money and, at worst, produce study failure. Additionally, inefficient trial design can cause studies to be rejected by regulators and/or scientific journals. When the former is the case, product failure is almost ensured; when the latter, company’s marketing efforts will be greatly damaged.

Yossi Tal received his Ph.D. from Northwestern University in the U.S., after which he was a statistician at the National Institutes of Health (NIH) in Bethesda, Maryland. Upon returning to his native Israel, he worked at the Statistical Laboratory of the Technion, Israel Institute of Technology. He is currently President of TechnoSTAT (www.technostat.co.il), a bio-statistical consultancy and CRO with clients internationally including Israel, Switzerland, Italy, Sweden, U.S., Finland, Germany, France and elsewhere. Yossi has been involved in many dozens of regulatory submissions to FDA and EU, and has attended numerous meetings at FDA. Yossi is author of Reading between the Numbers: Statistical Thinking in Everyday Life (McGraw-Hill, 1980) and Strategy and Statistics in Clinical Trials (Academic Press, an imprint of Elsevier, 2011). Both of these books are meant for non-statisticians.

Yossi has been presenting seminars on bio-statistics for non-statisticians for almost 20 years. He is a dynamic speaker who consistently receives the highest participant ratings.

Please contact the event manager Marilyn (marilyn.b.turner(at)nyeventslist.com ) below for: 
- Discounts for multiple participants.
- Require a price quotation.
- Require to pay by wire transfer or PayPal
- Invitation letter for visa applications

NO REFUNDS ALLOWED ON REGISTRATIONS 
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Who will Benefit:

Following titles and departments who are involved with the statistical aspect of clinical trials, in order of bio-statistic’s will be benefited by attending this seminar:

• Departments: Clinical, Regulatory, R&D, Marketing
• Clinical Titles: Medical Director, Director of Clinical Affairs, VP Clinical, Clinical Manager, Clinical Department Manager, Clinical Project Manager, Clinical Staff, CRA (Clinical Research Associate), Study Coordinator
• Regulatory Titles: VP Regulatory Affairs, Manager of Regulatory Affairs, Regulatory Scientist
• R&D Titles: Director of R&D, VP R&D, R&D Project Manager, Engineers, Quality Engineer, Algorithm Developer

Attend this seminar to mitigate below risks:

Stat for device submissions for non-statisticians: Not being exposed to the information in this course is likely to lead to inefficient, and perhaps even erroneous, interactions with FDA. This can result in various difficulties such as:

• Being asked by FDA to meet harsher criteria than might have been needed, thus reducing Company’s chance for success
• Needing a much larger sample size than if the correct approach was used
• Specifying inefficient statistical analyses that reduce a trial’s chance for success (for example, running a clinical trial that does not deal efficiently with missing values)

Bio-statistics for non-statisticians: Not being conversant in statistics means that the staff member cannot understand basic concepts in clinical trials such as endpoint selection, trial sample size and trial length. Not knowing how to deal with these issues can cause a company a great deal of damage in terms of inefficient product development (costly in terms of both time and money), inefficient trial design, and erroneous interactions with statisticians. All these can lead to inefficient product development and regulatory submission and even failure:

• Almost everyone in the clinical, regulatory and R&D departments should be familiar to one degree or another with bio-statistics. It is the language of regulatory submissions, study design and accounts for much that is presented to FDA (and all regulators) in the clinical study report (CSR). The CSR is the final clinical trial document presented to FDA when submitting a product for approval. Company staff must be at least conversant in bio-statistics so that they can:
  • Interact intelligently and efficiently with company statisticians, most of whom are subcontracted (i.e. not part of the organization)
  • Be able to audit the statistician’s decisions
  • Understand what competitors have done to demonstrate their product works to both regulator and the market
  • Assist physicians, who are typically clinically oriented, to think in terms of the research needed for bringing a product to market

Efficient Design for non-statisticians:Designing inefficient trials will, at best, cause unnecessary costs in terms of both time and money and, at worst, produce study failure. Additionally, inefficient trial design can cause studies to be rejected by regulators and/or scientific journals. When the former is the case, product failure is almost ensured; when the latter, company’s marketing efforts will be greatly damaged.

• 08.30 AM - 09.00 AM: Registration
• 09.00 AM: Session Start
• Lecture 1: Background
  • Statistical thinking in the everyday and in clinical trials
  • The statistician's role in clinical trials
• Lecture 2: Samples and Populations
  • What they are
  • Inclusion/exclusion criteria in clinical trials
• Lecture 3: Describing Data: Overview, Methods and Goals
  • Descriptive methods: central tendency, variation, confidence intervals, etc.
  • Dealing with error in statistics
• Lecture 3: Statistical Inference: Hypothesis Tests and Distributions
  • Logic of hypothesis testing in clinical trials
  • Meaning of P-value and Alpha
  • The normal and other frequently used distributions
• Lecture 4: Overview of Commonly used Tests in Bio-statistics
  • The general linear model (t-test, regression, ANOVA, ANCOVA, etc.)
  • Logistic regression
  • Mixed model repeated measures (MMRM)
  • Selected Nonparametric procedures (Fisher’s Exact, Wilcoxon, survival analysis/Cox Regression)

• Lecture 5: Clinical Trial Design: The Basics
  • Blinding and Randomization
  • Eliminating bias
  • Confirmatory and exploratory trials
  • Sample size determination
  • The statistical analysis plan (SAP)
• Lecture 6: Endpoints
  • Selecting endpoints for your trial: Clinical and statistical considerations
  • Primary and secondary endpoints
• Lecture 7: Common Adaptive Designs: Classic and Bayesian
  • Stopping rules (efficacy, futility, harm)
  • Allocation rules (adjusting subject allocation during the trial)
  • Sampling rules (adjusting sample size)
• Lecture 8: Statistics for Reducing Study Cost
  • Endpoint selection
  • Effect size (or, in the case of diagnostics, accuracy)
  • Reducing noise in the data
  • Statistical analysis