Web-Based Lectures


Friday, September 28, 2018




Title: Why Are Forecasts So Wrong? What Management Must Know About Forecasting
Presenter: Michael Gilliland, SAS Institute
Date and Time: Wednesday, September 19, 12:00 p.m. – 1:30 p.m. Eastern time
Sponsor: Section on Statistical Consulting

Registration Deadline: Monday, Monday, September 17, at 12:00 p.m. Eastern time

Description:
In a series of articles in the journal Foresight, Steve Morlidge reported that 30-50% of real life business forecasts – the forecasts managers are using to run their organizations – are less accurate than a naïve forecast. This is astounding! And it raises the question: Why are real-life business forecasts so frequently so very wrong, and is there anything we can do about it? This presentation reviews the main reasons why forecasts go wrong, and some of the worst practices that contribute to what Morlidge has called “avoidable error.” It shows how the method of Forecast Value Added analysis – now being employed at dozens of companies worldwide – can identify the waste and inefficiency in a forecasting process and result in more accurate forecasts. Rather than focus on ever more elaborate data and modeling efforts, a more direct route to forecasting improvement is to instead focus on the organizational practices that just make a forecast worse. This presentation provides material you will find useful when dealing with organizational forecasting processes, and with organizational management.

Bio:
Michael Gilliland is Marketing Manager for SAS forecasting software. Prior to SAS, he spent 15 years in forecasting positions in the food, consumer electronics, and apparel industries, and in consulting. Mike is author of The Business Forecasting Deal (2010), principal editor of Business Forecasting: Practical Problems and Solutions (2015), and writes The Business Forecasting Deal blog. He is an editor for Foresight: The International Journal of Applied Forecasting, and co-chaired the 2016 Foresight Practitioner Conference. Mike serves on the Board of Directors of the International Institute of Forecasters, and received the 2017 Lifetime Achievement Award from the Institute of Business Forecasting. Mike holds a BA in Philosophy from Michigan State University, and Master’s degrees in Philosophy and Mathematical Sciences from Johns Hopkins University. He is interested in issues relating to forecasting process, such as worst practices and Forecast Value Added analysis, and in applying research findings for real-life improvement in business forecasting.

Registration Fees:
Member of the Section on Statistical Consulting: $20
ASA Member: $65
Nonmember: $85

Each registration is allowed one web connection and one audio connection. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Registration is closed.

Access Information
Registered persons will be sent an email the afternoon of Monday, September 17, with the access information to join the webinar and the link to download and print a copy of the presentation slides.




Title: An Innovative Design to Combine Proof-of-Concept and Dose Ranging
Presenter: Naitee Ting and Qiqi Deng
Date and Time: Thursday, September 27, 2018, 12:00 p.m. – 2:00 p.m. Eastern time
Sponsor: Biopharmaceutical Section

Registration Deadline: Tuesday, September 25, at 12:00 p.m. Eastern time

Description:
In Phase II clinical development of a new drug, the two most important deliverables are proof of concept (PoC), and dose ranging. Traditionally a PoC study is designed as the first Phase II clinical trial. In this PoC, there are two treatment groups – a high dose of the study medication, against the placebo control. After the concept is proven, the next Phase II study is a dose ranging design with many test doses. This presentation proposes a two-stage design with the first stage attempting to generate an early signal of efficacy. If successful, the second stage will adopt a “Go Fast” plan to expand the current study and add lower study doses of the test drug to explore the efficacy dose range. Otherwise, a “Go Slow” strategy is triggered, and the study will stop at a reduced sample size with high dose and placebo only.

Speaker Bios:
Naitee Ting is a Fellow of American Statistical Association (ASA). He is currently a Director in the Department of Biostatistics and Data Sciences at Boehringer-Ingelheim Pharmaceuticals Inc. (BI). He joined BI in September of 2009, and before joining BI, he was at Pfizer Inc. for 22 years (1987-2009). Naitee received his Ph.D. in 1987 from Colorado State University (major in Statistics). He has an M.S. degree from Mississippi State University (1979, Statistics) and a B.S. degree from College of Chinese Culture (1976, Forestry) at Taipei, Taiwan.

Naitee published articles in Technometrics, Statistics in Medicine, Drug Information Journal, Journal of Statistical Planning and Inference, Journal of Biopharmaceutical Statistics, Biometrical Journal, Statistics and Probability Letters, and Journal of Statistical Computation and Simulation. His book “Dose Finding in Drug Development” was published in 2006 by Springer, and is considered as the leading reference in the field of dose response clinical trials. The book “Fundamental Concepts for New Clinical Trialists”, co-authored with Scott Evans, was published by CRC in 2015. Another book “Phase II Clinical Development of New Drugs”, co-authored with Chen, Ho, and Cappelleri was published in 2017 (Springer). Naitee is an adjunct professor of Columbia University and University of Connecticut. Naitee has been an active member of both the ASA and the International Chinese Statistical Association (ICSA).

Dr. Qiqi Deng is a Senior principle Biostatistician at Boehringer Ingelheim Pharmaceutical. She is currently a member of the Methodology Expert team within global statistics, which focuses on statistical methodology innovation. Her research area includes hypothesis and modeling in dose finding, pragmatic considerations in designing dose finding trials, including adaptive design aspects. Before she joined the methodology group, she has served as leading statistician for multiple projects, across different clinical development phases and therapeutic areas. Dr. Deng received her B.S. degree in Mathematics from Peking University in China, and obtained her Ph. D. in Statistics from University of Minnesota.

Registration Fees:
Biopharmaceutical Section Members: $0
ASA Members: $59
Nonmembers: $74

Each registration is allowed one web connection. Sound is received via audio streaming from your computer’s speakers. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register

Access Information
Registered persons will be sent an email the afternoon of Tuesday, September 25, with the access information to join the webinar and the link to download and print a copy of the presentation slides.




Title: How to Avoid Some Common Graphical Mistakes
Presenter: Joyce Robbins, Columbia University & Naomi Robbins, NBR
Date and Time: Friday, September 28, 2018, 12:00 p.m. – 1:00 p.m. Eastern time
Sponsor: Section on Medical Devices and Diagnostics

Registration Deadline: Wednesday, September 26, at 12:00 p.m. Eastern time

Description:
Good graphs are extremely powerful tools for communicating quantitative information clearly and accurately. Unfortunately, many of the graphs we see today are poor graphs that confuse, mislead or deceive the reader. These poor graphs often occur because the graph designer is not familiar with principles of effective graphs or because the software used has a poor choice of default settings. We point out some of these graphical mistakes, and show how, in most cases, very simple changes make the resulting graphs easier for the reader to understand. We illustrate many of these principles with examples from the medical device literature.

Registration Fees:
Member of the Section for Medical Devices and Diagnostics (MDD): $40
ASA Member: $65
Nonmember: $85

Each registration is allowed one web connection. Sound is received via audio streaming from your computer’s speakers. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register

Access Information
Registered persons will be sent an email the afternoon Wednesday, September 26, with the access information to join the webinar and the link to download and print a copy of the presentation slides.




Title: Statistical Programmer Career Planning and Development Webinar – Biopharmaceutical Sector
Presenters: Wenyun Ji, Director, Biostatistical Programming; Robert Goodloe, Consultant Statistician, Global Patient Safety
Date and Time: Thursday, October 11, 2018, 12:00 p.m. – 1:00 p.m. Eastern time
Sponsor: Section for Statistical Programmers and Analysts

Registration Deadline: Tuesday, October 9, at 12:00 p.m. Eastern time

Description:
This is the first series of Webinar sponsored by SSPA discussing the career development and planning for the statistical programmers and analysts. Speakers from the biopharmaceutical industry will present with the following components:

Part I: Framework for Critical Thinking – Introducing Lean Philosophy to Statistical Programmers— Wenyun Ji, Amgen Inc

This Webinar will introduce and discuss the lean principles in the context of statistical programming in the pharmaceutical industry. ‘Lean’, coined by Jim Womack’s team at MIT in the late 1980s, describes the Toyota Production System that aims to deliver goods and services of the highest quality at the lowest cost in the shortest lead time. Businesses in all industries including healthcare are adapting the ‘lean’ principles to guide their best practices.

Lean is based on creating a culture on how to respond to a problem rather than what tool to use. The lean approach creates a problem-solving mindset. It has four main principles: customer first, trusting and respecting each other, continuous process improvement (CPI), and elimination of waste. Customer first is to understand what is of the highest value to the customers. Trusting and respecting people is to build the best team and create a learning-centered environment. It promotes the concept of treating every mistake as a learning opportunity. CPI is to apply rapid improvement methods of PDCA (Plan, Do, Check and Act) at all organizational levels. Waste elimination is to identify and minimize the activities that do not add value. Lean philosophy also calls for the management to create an environment that empowers the people.

In conclusion, lean is a culture and a mindset. It works when everyone in the organization is on board and follows the lean principles in their daily work.

Part II: Non-Clinical Big data: Exploration of Statistical Programming and Applications – Robert Goodloe, Eli Lilly and Company

One of the most common associations made of statisticians, in the pharmaceutical industry, is that the work only revolves around regulated clinical trials. While clinical statisticians are a part of the pharmaceutical industry, the abilities of a statistician are not limited to just that one area. There are a multiple of functional areas, such as market research, finance, business analytics, patient safety & risk assessments, data sciences, etc.

This presentation will discuss the skillsets and available toolkits, such as R, SAS, SQL, Python, VBA, Shell scripting, etc. that can be leveraged to influence various functional areas. Individuals will gain a broader sense of various non-clinical roles that statisticians and programmers play in the pharmaceutical industry, as well as understand the type of problems that are addressed. The presentation will also provide participants with insightful information of technical skills that are in-demand, which can serve as an advantage when starting a career in the pharmaceutical industry.

We will conclude with a Q&A session. Please note that there are no open phone lines so the audience submits their questions using a chat feature built into the webinar dashboard.

Registration Fees:
Member of the Section for Statistical Programmers and Analysts: $0
ASA Member: $59
Nonmember: $74

Each registration is allowed one connection to the webinar. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register

Access Information
Registered persons will be sent an email the afternoon of Tuesday, October 9, with the access information to join the webinar and the link to download and print a copy of the presentation slides.




Title: Pragmatic Benefit:Risk Evaluation: Using Outcomes to Analyze Patients Rather than Patients to Analyze Outcomes
Presenter: Scott Evans, PhD, MS, FIDSA
Date and Time: Thursday, October 18, 2018, 12:00 p.m. – 2:00 p.m. Eastern time
Sponsor: Biopharmaceutical Section

Registration Deadline: Tuesday, October 16, at 12:00 p.m. Eastern time

Description:
Randomized clinical trials are the gold standard for evaluating the benefits and risks of interventions. However these studies often fail to provide the necessary evidence to inform practical medical decision-making. The important implications of these deficiencies are largely absent from discourse in medical research communities.

Typical analyses of clinical trials involve intervention comparisons for each efficacy and safety outcome. Outcome-specific effects are tabulated and potentially systematically or unsystematically combined in benefit:risk analyses with the belief that such analyses inform the totality of effects on patients. However such approaches do not incorporate associations between outcomes of interest, suffer from competing risk challenges, and since efficacy and safety analyses are conducted on different analysis populations, the population to which these benefit:risk analyses apply, is unclear.

This deficit can be remedied with more thoughtful benefit:risk evaluation with a pragmatic focus in future clinical trials. Critical components of this vision include: (i) using outcomes to analyze patients rather than patients to analyze outcomes, (ii) incorporating patient values, and (iii) evaluating personalized effects. Crucial to this approach entails improved understanding of how to analyze one patient before analyzing many. Newly developed approaches to the design and analyses of trials such as partial credit and the desirability of outcome ranking (DOOR), are being implemented to more optimally inform patient treatment.

Registration Fees:
Biopharmaceutical Section Members: $0
ASA Members: $59
Nonmembers: $74

Each registration is allowed one web connection. Sound is received via audio streaming from your computer’s speakers. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).

Register

Access Information
Registered persons will be sent an email the afternoon of Tuesday, October 16, with the access information to join the webinar and the link to download and print a copy of the presentation slides.