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PHUSE US 2021 Papers - Index

163 papers. Source: PHUSE (Pharmaceutical Users Software Exchange) US Connect conference proceedings.

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1 A Bayesian Approach to Detection of Treatment-related Effects in Toxicology Studies by Borrowing Information from Historical Control Animals Kevin Snyder,
Md Yousuf Ali		 Presentation confidence interval, sample, sample size, binomial distribution, logistic regression, likelihood function, logistic distribution source
video		 15
2 A Macro to Automate Detection of Date Variables and Derivation of RFPENDTC Kiran Kumar Babu P RFPENDTC is a Demographic variable, As per the Implementation Guide, RFPENDTC is the Date/time when a subject ended participation or follow -up in a trial, as defined in the protocol. It should correspond to the last known date of contact. Examples include completion date, withdrawal date, last follow-up, date recorded for lost to follow-up, or death date. So, it requires a check of various sdtm domains, depending up on the study for last contact date of a subject. Manually searching each domain and date variables for latest dates requires lot of time limiting working efficiency and also results in very long code. A simple and easy to understand macro for RFPENDTC derivation using transpose and last.variable is proposed consequently in this paper date variable, proc step, proc contents, cdisc source
video
presentation source		 8
3 A Quantitative and Metrics-driven Framework for Maximizing Data Utility While Balancing Re-identification Risk Stephen Doogan Presentation threshold, by group processing, standard deviation source
video		 18
4 A Sequel Better than the Original: Intuitive Ideas Beyond the Basics of Proc SQL Hector Leitch Presentation proc sql, group by, proc step source
video		 20
5 A Well Design QC Toolkit for Clinical Programming Compliance Checking Huei-Ling Chen,
Sandeep Meesala		 Presentation quality control, adam dataset, data cleaning, clinical programming, output delivery system, clinical trial, ods tagsets.excelxp source
video		 30
6 ADaM Generator Tool Gustav Bernard Presentation adam dataset, sdtm domain, bds, dataset, label statement, excel, format statement, cdisc source
video		 45
7 AI as a Service (AIaaS) in the RWD/RWE Space Aaron Clark,
Himanshu Pandya		 Presentation data science source
video		 21
8 AI Powered Decision Support Systems with Wearable Sensors for Remote Patient Monitoring in Clinical Trials Surabhi Dutta Poster clinical database source 1
9 An R-based Tool to Build Questionnaires, Ratings and Scales (QRS) in EDC for Clinical Trials Catherine Abogado,
Rammprasad Ganapathy		 Presentation data standard, clinical trial, controlled terminology, rest api, clinical data, clinical research, edc, cdisc source
video		 19
10 An SAS Macro for Dynamic Page Breaks Bhavana Bommisetty,
Manohar Modem		 Presentation demographics table, change from baseline, efficacy summary, macro parameter, proc report, proc calis, analysis set source
video		 13
11 Application of Machine Learning (ML) in Tumor Detection in Oncology Study Animesh Patel Machine Learning (ML) has been a buzz word nowadays due to its power to bring huge change. However, the application of ML has been minimal in oncology clinical research and healthcare industry. Deep learning is the current trend of the machine learning field. It is widely used in numerous applications for solving complex problems that required more accurate result and sensitivity like in medical field. In oncology studies, the detection of brain tumor (lesion) is performed by investigator and independent reviewer . This method is impractical in large amount of data so tumor detection using Machine learning would save radiologist time. Our work involves develop and implementation of convolution neural network (CNN) for Magnetic resonance imaging(MRI). The dataset we used in this paper have around 3000 images belong four classes where three o f different type of tumors and no tumor class. The proposed CNN model gives 97.5% training accuracy and 91.6% testing accuracy machine learning, deep learning source
video
presentation source		 5
12 Artificial Intelligence (AI) Innovations in Clinical Research Sanjeeva Thalla Poster: Most drugs take about 10 years or more to come to market, cost billions, and have a potential to financially damage an organization where the late-stage trials fail. Also, patients hardly can wait 15 years for a lifesaving drug. Thus, now is the time to focus on medication revelation and other productive processes which can be easily achieved through Artificial Intelligence (AI). AI can significantly reduce the time spent in the drug development process and can cut the expenses by more than half. In this poster, I aim to explain the different areas of a clinical task to which expert systems can be applied. This poster also states the various ways we may adopt AI in the field of Medicine artificial intelligence, clinical research source 1
13 Automate Scientific Document such as CSR Generation using ML/NLP Farha Feroze Presentation csr, clinical trial, neural network, deep learning, gcp, serious adverse event, adverse events source
video		 13
14 Automated Validation of Clinical Trial Analysis and Reporting Deliverables Using 'testthat' Amin Shirazi,
Jane X. Liao		 Presentation clinical trial, data cleaning, adverse events, regression analysis, survival function, serious adverse event, clinical data source
video		 35
15 Automation of a Web-based Metadata Repository for SAS Datasets with Selenium Technology Eugene Tsykalov Presentation excel, clinical trial, adam dataset, sdtm domain, proc contents, reference data, phase ii, cdisc source
video		 14
16 Automation of CDISC ADaM Using Statistical Data and Metadata eXchange (SDMX) Stuart Malcolm Presentation cdisc source
video		 29
17 Automation of Patient Narratives Using Natural Language Generation Sam Tomioka,
Shiva Katepalli		 Presentation adverse event leading to discontinuation, adverse events, data science, audit trail, verbatim term, concomitant medications, dose source
video		 16
18 Becoming Agile in a Regulated Environment Anton Sarov Presentation data cleaning source
video		 17
19 Building an SCE that Users Want to Use Alastair Scarlett,
Chris Decker		 Presentation data science, clinical programming, audit trail, clinical data, clinical trial, statistical programmer source
video		 9
20 Central Statistical False Positives - Predicting True Signals with Machine Learning Dorothea Ugi Presentation type i error, sample, test set, sensitivity analysis, auc, phase iii, response variable source
video		 24
21 Challenges and Solutions in SDTM Implementation and Programming of the Ophthalmic Examinations (OE) Domain Shivam Kumar,
Vinita Dora		 Presentation output delivery system, repeated measures, longitudinal data, do loop, array, controlled terminology, if-then-else, cdisc source
video		 16
22 Changing How We Collect, Store, Manage, Transform and Analyze Clinical Data, One Microservice at a Time Mark Bynens,
Paul Fioole		 Presentation clinical data source
video		 17
23 China Center for Drug Evaluation, NMPA Electronic Study Data Submission Requirements Majdoub Haloui,
Yanhong Li		 Presentation clinical trial, adam dataset, clinical data, reviewer guide, label statement, clinical programming, annotated crf, cdisc source
video		 16
24 CO Hands-on Workshop: COVID Data Access to Analysis with Power BI Aditya Gadiko,
Christopher C. Hurley		 Presentation excel, proc sql, sql server, machine learning, output delivery system, standard deviation, data visualization source
video		 94
25 CO Panel Discussion: COVID-19 Managing Programming Deliverables Under an EUA Caroline Shi,
Liping Zhang		 Presentation output delivery system source
video		 7
26 Coming Out Ahead by Driving Change in Teams and Departments Paul K. Slagle Presentation proof of concept source
video		 20
27 Commercially Confidential Information in clinical data publishing Parvee Kumar Presentation clinical trial, clinical data, key, service provider, data science source
video		 17
28 Common JumpStart Data Quality Findings Alan Shapiro,
Michael Xue		 Presentation cdisc source
video		 16
29 Comparative Characteristics of Logistic Regression Implementation in SAS and R in the Example of Cardiovascular Diseases Serhii Kashyn Presentation logistic regression, logistic distribution, regression analysis, maximum likelihood estimation, likelihood function, model validation, odds ratio source
video		 22
30 Concept of Generating Polished SAS Code for Regulatory Submissions Norihiko Oharu,
Ravi Mokkarala		 Poster data cleaning, mprint source 1
31 Confused with PROC MIXED? Find Out What is the Best Model Savithri Jajam,
Vamshi Matta		 proc mixed, covariance structure, covariance, proc step, correlation, ods output, output delivery system, data science source
video
presentation source		 7
32 Containers You Can Count On: A Framework for Qualifying Community Container Images Eli Miller Presentation data cleaning source
video		 11
33 Controlled Terminology Best Practices Sarah Angelo Presentation cdisc controlled terminology, data cleaning, controlled terminology, sdtm programming, raw data, data validation rules, adverse events, cdisc source
video		 29
34 COVID-19 Outbreak Visualization Using a Clinical Data Science Platform Iryna Kotenko,
Sergey Glushakov		 Presentation statistical programmer, output delivery system, clinical endpoint, clinical programming, clinical sas, data standard, sas programmer source
video		 15
35 COVID-19 Presentation: CO01: Harnessing the Power of Shiny to Visualize Missing Data due to the COVID-19 Pandemic Mark Rothe,
Sangeeta Bhattacharya		 Presentation study day, missing value, adam dataset, data visualization, clinical trial, protocol deviations, likelihood function, cdisc source 13
36 COVID-19 Presentation: CO02: Takeda's COVID-19 Response to Aid Collection to Submission Veena Nataraj Presentation source 25
37 Creation of Adverse Event (AE) Table Using R Programming Dilip Patel,
Kamleshkumar Patel		 Poster source 1
38 CSR Narratives Automation Ritesh Dhimmar Presentation adverse events, concomitant medications, vital signs, serious adverse event, medical history, clinical trial, adverse event of special interest source
video		 23
39 Data Science Presentations: DSc01: How Automation Using Machine Learning Technology Can Overcome the Limitations of Double Programming Hugh Donovan,
Ilan Carmeli		 Presentation independent qc, data cleaning, clinical research, tables, life sciences, clinical programming source 18
40 Data Science Presentations: DSc02: The Digital Era Outpaces Traditional QA Karl Brand,
Miriam Ferrer-Gonzale		 Presentation quality assurance, data cleaning source 45
41 Data Visualizations for Publication, Decision-making and Submission Maria Dalton Presentation data cleaning, validation documentation, access control, audit trail, data visualization, inferential statistics, clinical trial source
video		 18
42 Demographic and Socio-economic Disparities in Preference to Getting Vaccinated by the Flu Shot versus the Flu Spray in the United States Swapna Ambati Influenza (Flu) is one of the most common causes of respiratory illness and absenteeism at work and school. Flu is a common virus whose ability to change its genetic makeup could result in a pandemic proportion of the disease. In 2009, a novel Influenza virus caused the first Influenza related pandemic in the 21st century. The major step in preventing Flu is taking a Flu vaccine every year. A Flu vaccine can be administered as a shot or a spray. In this paper, we examined children using the national survey database the National Immunization Survey (NIS) in 2019. We discussed the disparities in the demographic and the socio-economic characteristics in preferring to get vaccinated for Flu. We also discuss ed the availability and preference to take Flu vaccine based on the type of administration mainly Flu shot and Flu spray. Also, we examined the reasons for the low usage in administration types and their trends in the past and prospects in the future proc step, proc surveymeans, proc surveyfreq, nominal variable, data science source
video
presentation source		 12
43 Developing R Package Capability in a Historically SAS-based Organization - The GSK Clinical Programming Experience Benjamin Straub,
Michael Rimler		 Poster: Our roadmap to R includes a commitment to continued development of internal R package functionality and more contributions to open-sourced R packages which support the delivery of the clinical data pipeline clinical programming, data pipeline, r package source 1
44 Digitalization, Agile Mindset and Virtual Collaboration - Yet Delivering a "Pile of Paper"? Jesper Zeth,
Parag Wani		 Presentation pharmaceutical industry, statistical programmer, missing value, adam dataset, adam programmer, adverse event summary, artificial intelligence source
video		 17
45 Do EudraCT the Easy Way: Semi-automation of Inputting Study & Treatment Event Information in EudraCT Kevin Miller,
Larry Sleeper		 Presentation adverse events, serious adverse event, clinical trial, excel, system organ class, clinical research, error message source
video		 21
46 DSc Hands-on Workshop: Data Storytelling Sascha Ahrweiler Presentation statistical programmer source
video		 73
47 DSc Panel Discussion: How Data Scientists are Transforming the Biometrics Organization Asha Mahesh,
Christopher J. Colangelo		 Presentation data science, pharmaceutical industry, clinical programming source
video		 9
48 Dynamic Macro Using the Convergence Dataset to Generate the Odds Ratio (OR), Risk Ratio (RR) and Risk Difference (RD) per SOC and PT Using the Genmod Procedure Jagadish Katam Presentation proc genmod, keyword parameter, %macro parameters, macro call, system organ class, call execute, macro parameter, cdisc source
video		 26
49 Effective Leadership to Thrive in the "New Normal" Bhavesh Patkar Presentation source
video		 12
50 Exploring Categorical Data Using Unsupervised Graph-based Machine Learning Irina Kotenko,
Kostiantyn Drach		 Presentation logistic regression, regression analysis, logistic distribution, machine learning, odds ratio, unsupervised learning, clinical trial source
video		 34
51 FDA & PMDA Validator Rules - What, Why and How ... But Should You Care? Charanjit Kahlon,
Kishore Pothuri		 Presentation adverse events, data validation rules, trial summary, system organ class, cdisc controlled terminology, data cleaning, clinical trial, cdisc source
video		 21
52 FDA Conformance Analysis and Upcoming Implementation of Technical Rejection Criteria for Study Data Ethan Chen,
Heather Crandall		 Presentation data cleaning, clinical trial, data validation rules, trial summary, csr, sample source 36
53 File Split: Handling LB, QS and VS Listing Files Deepak Kumar,
Swetha Mandava		 Poster proc step, proc print source 1
54 From Digital Data to Decision Intelligence: Infrastructure and Algorithms Powering Automation in RBM and Data Review Raj Indupuri Presentation artificial intelligence, clinical research source
video		 12
55 Generating .xpt files with SAS, R and Python Todd Case Presentation dataset, trial summary, label statement, adaptive design, in=, regulatory submission, sas library source
video		 22
56 Get Ready in One Click: Clean SDTM Datasets by Using Library Backend Rules Annelies Van Zeveren,
Sofie Stynen		 Presentation sdtm domain, cdisc source
video		 49
57 Good Cooperation Between SAS and R for Regulatory Submission Jingyuan Chen Presentation clinical trial, quality control, crf, csr, adlb, proc compare, adam dataset source
video		 19
58 Graphs Made Easy Using SAS Graph Template Language Manohar Modem In clinical domain, we used to create graphs using traditional SAS/GRAPH procedures like PROC GPLOT. To create better graphs, SAS developed Graph Template Language (GTL). GTL has many significant advantages over traditional SAS/GRAPH procedures like more c ontrol over visual attributes of the graph, less annotation and minimal coding. Statistical Graphics (SG) procedures like PROC SGPLOT, SGPANEL etc., which require minimal coding use GTL to create commonly used graphs. But, writing graphs in GTL has more ad vantages compared to SG procedures and traditional SAS/GRAPH procedures. GTL code might look a little lengthy and intimidating, but once you understand how to read GTL code, it will be very useful to cr eate not only simple graphs but also complex graphs. T he purpose of this paper is to help the programmer understand and utilize various elements of GTL to create wonderful graphs proc step, proc template, line chart, scatter plot, bar chart, box plot, class variable, adverse events, forest plot, histogram, confidence interval, output delivery system, if-then-else, kaplan-meier plot, proc freq source
video
presentation source		 27
59 Harness Analytical Strengths: SAS, R, Python Web Services Ben E. Bocchicchio,
Sandeep Juneja		 Presentation source
video		 18
60 How Enterprise Architecture Can Benefit the Clinical Trial Process Guy R. Garrett Poster source 1
61 How the R Programming Language Handles the CDISC Library API Joseph W. Hinson CDISC is currently ushering in a new era of automated standards-based clinical programming where software can directly access the CDISC standards. This is through a massive cloud-based metadata repository called "CDISC Library", which also contains a REST-based Application Programming Interface (API) and which already has been shown to be accessible by SAS and JAVA programs. Meanwhile, the R programming language is gaining a substantial foothold in big pharma and CROs, due to the open-source language's extensive suite of advanced statistical, modeling, and graphical tools, plus over 12,000 ancillary software packages. This paper aims to demonstrate that R is also well-suited for doing CDISC Library-based programming rest api, api, cdisc source
video
presentation source		 11
62 How to Submit Study Data to Comply with Technical Rejection Criteria Lina Cong Poster data cleaning, data standard source 1
63 How Will Knowledge Graphs Improve Clinical Reporting Workflows? Alexey Kuznetsov,
Jorine Putter		 Presentation adverse events, privacy, data standard, laboratory data, vital signs, data cleaning source 9
64 Hydrating a Data Lake to Power Innovation - Enabling Pharmaceutical Companies to Automate Data De-identification for Secondary Use Cathal Gallagher,
Kristin McDougall		 Presentation data lake, machine learning, audit trail, clinical trial, data masking, flat file source
video		 16
65 Indenting Lengthy Text Strings in PROC REPORT Outputs Jeppe Juul,
Kavita Math		 Presentation do loop, proc report, macro call, proc step, system organ class, adverse events source
video		 19
66 Industry Metrics for Extensions of CDISC Terminology Sergiy Sirichenko Presentation data cleaning, cdisc controlled terminology, missing value, label statement, crossover study, follow-up period, unstructured data, cdisc source
video		 36
67 Integration of Translational and Longitudinal Clinical Trial Data Using Machine Learning to Gain Predictive Insights from Legacy Studies Arpitha Hanumanthiah,
Rajalaxmi Sharanappa		 Poster: Data transformation for normalization and harmonization Data generated over a period in the immunological studies/ cell/ gene therapy are very large and are often stored in many places. To make it available for insight generation at the right time and right place will require tools to standardize and integrate these data for their respective clinical data. Automation and recommendation engine using Machine Learning algorithms working on the principle of supervised learning will both speed up and standardize and harmonize the data to a chosen libraries/ontologies. Validation of the data for transformation and consistency Indexed and stored in a customizable Universal Data Model. Metadata capturing at various levels of the data and making it available for search and selection of cohort machine learning, clinical data source 1
68 Interactive Visualization and Summarization of Toxicology Study Results Across Species, Routes and Durations Throughout a Drug Development Program Using R Shiny Kevin Snyder,
Md Yousuf Ali		 Presentation clinical significance, clinical research source
video		 14
69 Is it ART? An Application of TransCelerate's MoA Framework for Assessing Accuracy, Reproducibility and Traceability in Novel Software Implementations Michael S Rimler,
Tim Kuhn		 Presentation machine learning, quality assurance, clinical programming, clinical research, regulatory reporting, data cleaning source 20
70 Keeping Calm and Carrying On: Bringing Graduates Onboard in a World Disrupted Diana Stuart,
Stephanie Boyle		 Presentation source
video		 12
71 Keynote Presentation: Our Access to Real-world Data is Not Sustainable Without Transparency and Inclusion Craig Lipset Presentation clinical trial, health insurance source 33
72 LE Panel Discussion: Leadership and Innovation Benedikt Egersdoerfer,
Delyth Jones		 Presentation source
video		 6
73 Leadership Presentations: LE01: The Power of Three Alberto Montironi,
Ryan Krause		 Presentation clinical programming, data science, statistical programmer source 15
74 Leadership Presentations: LE02: How to Build Knowledge Capacity for a High-performance Team Xiaohui Wang Presentation clinical trial, data validation rules, exploratory endpoint, phase i, clinical programming source 14
75 Leadership Presentations: LE06: One Sprint at a Time - Agile Transformation in Clinical Research Aman Bahl,
Steve Benjamin		 Presentation data science, clinical trial, clinical programming, clinical research, adaptive design, customer experience, predictive analytics source 17
76 Leveraging Standard Analytics in Central Monitoring: The Good, The Bad, & The Ugly Angela Geiger,
Arianna Galli		 Presentation data review, data science, adverse events, clinical data, bar chart, concomitant medications, dose modification source
video		 20
77 Managing Multiple Versions of R in a Clinical Environment Philip Bowsher,
Sean Lopp		 Presentation statistical programmer source
video		 19
78 Managing TFL Development in LSAF 5.3 Using SAS and R Code Jean-Marc Ferran,
Stijn Rogiers		 Presentation life sciences, data cleaning, full analysis set, dataset, adam dataset, analysis set, pharmaceutical industry, cdisc source
video		 33
79 Mapping Missing QRS Responses in the SDTM Mahesh Minnakanti,
Vinita Dora		 Presentation source
video		 12
80 Metadata-based Auto-programming by Python and SAS Harry Chen Presentation data step, proc sort, if-then-else, implicit loop, raw data, sample, excel source
video		 10
81 Neurological Examination and Procedure Results in SDTM: Challenges and Solutions Shivam Kumar Presentation clinical significance, sample source
video		 14
82 Next Evolution Step(s) for Statistical Programmers: "Clinical Data Scientist" or "Clinical Data Analytics Engineer"? Amar Mahidadia,
Sascha Ahrweiler		 Presentation clinical research, data science, statistical programmer, machine learning, pharmaceutical industry, outlier, sas engineer source
video		 16
83 Onboarding a junior Clinical Data Manager (CMD) in an Early Phase Team: My Story from University to First Database Lock Glenn Borgmans,
Sofie Stynen		 Presentation database lock source
video		 30
84 Oncology Trial Endpoint Tracking Using RShiny Kavitha Nagarajan,
Michael Briganti		 Presentation proc means, excel source
video		 19
85 Open APIs and Open Source for Open Minds Sven Prasse Presentation data cleaning, audit trail, clinical data, rest api, data science source
video		 19
86 Open-Source Development for Traditional Clinical Reporting Michael Stackhouse,
Nathan Kosiba		 Presentation clinical programming, data standard, demographics table, pharmaceutical industry, regulatory reporting source
video		 12
87 Our Experience with Scrum and Kanban: Noob to Novice Ari Siggaard Knoph,
Kristian Troejelsgaard		 Presentation statistical programmer, clinical programming source
video		 26
88 Parmsurv: An SAS Macro for Flexible Parametric Survival Analysis with Long-term Predictions Han Fu,
Shahrul Mt-Isa		 likelihood function, proc calis, macro call, macro definition, regression analysis, survival analysis, normal distribution, logistic distribution, hazard function, confidence interval, exponential distribution, covariance, proc phreg, follow-up period, interval censoring, maximum likelihood estimation, right censoring, sample size, survival function, sample, accelerated failure time source
video
presentation source		 10
89 Patient Registries - New Gold Standard for Real World Data Lavanya Peddibhotla,
Sivasankar Konda		 Presentation clinical programming, population, clinical trial, life sciences, insurance claims, clinical research, raw data source
video		 14
90 Pinnacle 21: Improving the Data Fitness Score for eSubmission Renu Motwani data cleaning, controlled terminology, sdtm domain, cdisc controlled terminology, reviewer guide, data validation rules, cdisc source
video
presentation source		 9
91 Planning and Execution of Real-world Data Evidence Analysis Nicole Thorne,
Ramesh Sundaram		 The usage of Real World Data Evidence (RWDE) can optimize the cost and time of drug development process, so in recent days the role of RWDE analysis are significantly increased in each stage of drug development and its decision making process, like identifying target patient population, finding right variants, gene mutation, even comparators for an investigational product, etc. Unlike clinical studies, working with RWDE data has its own challenges, this paper demonstrates planning and execution of RWDE, like general workflow, data analysis, data Integration (RWDE & clinical data) related challenges and workarounds, overview of data review & cleaning process and a list of factors needs to consider for overall timeline estimation raw data, data cleaning, clinical trial, sample, adam dataset, data science, cdisc source
video
presentation source		 6
92 Power BI in Clinical Data Exploration: Powerful Visuals that Answer Relevant Questions Lotte Jacobs,
Roxane Debrus		 Nowadays, dynamic data visualization is vital for clinical study conduct and decision making. Power BI is a user-friendly business analytics service by Microsoft which provides interactive visualizations and business intelligence capabilities, offering uni que integration options with Python, R and SQL. Although a leader in Business Intelligence (BI) and Analytics Platforms, its potential in clinical research is currently unexplored. To test it in this capacity and help our clinical and medical teams, we utilized it to design modern-looking, interactive dashboards, with the aim to improve the way we a ccess, review and interact with data. As a result, we developed several tools that facilitate monitoring, analyzing and testing the study data in real time throughout the study, confirming that Power BI is perfectly suited to answer the needs of clinical and medical teams adverse events, business intelligence, clinical trial, excel source
video
presentation source		 10
93 Process Improvements for Quality and Efficiency Ghanshyam Jangid,
Suresh Acharya		 Presentation data cleaning source
video		 13
94 Process Optimization for Submissions Participating in the FDA's Real Time Oncology Review Pilot Program Grace Sun,
Kevin Liu		 Poster: Pfizer has successfully completed several submissions participating FDA Real Time Oncology Review (RTOR) pilot program. To meet RTOR timelines, we have optimized operation process to plan and prepare submission package in advance in order to reduce cycle time. Study Data standardization Plan (SDSP) is created and communicated with FDA in type B/C meeting to clarify final data format. Pinnacle 21 (P21) report is run on regular basis from study start up to proactively address data issues in time and prepare final P21 report with minimum turnaround time. Before final database lock, technical documents in submission package such as Review Guide and Define.xml are completed to maximum, only need minor update once final data is available; PK and biomarker data in blinded format is made available for programming related outputs and completing technical documents. All CSR tables and datasets are submitted together to FDA for RTOR review database lock, clinical programming, cdisc source 1
95 Processes and Techniques for Creating Integrated Summary of Safety (ISS) Ghanshyam Jangid,
Jane E. Marrer		 adam dataset, adverse event summary, data cleaning, clinical trial, laboratory data, concomitant medications, cdisc source
video
presentation source		 9
96 Project Success Forecast - Random Forest Machine Learning Application Using R Shiny Aman Bahl,
Hrideep Antony		 Poster source 1
97 Protocols on FHIR - Exchanging Study Designs with EHR Systems Andy Richardson,
Geoffrey Low		 Presentation study day, sample, data integration, visit, vital signs source
video		 24
98 Python for Visualization in Solid Tumor Studies Hengwei Liu Visualization is an integral part of the statistical analysis in solid tumor studies. When it comes to the tools for visualization, the programmers do have a choice. There are many tools available: SAS visual analytics, R shiny and Spotfire, to name just a few. So why Python? Python has a large user community. It is easy to get help online. Python programs for figures are succinct and easy to understand. Python figures have dynamic features such as tooltip and can be saved in many formats. Python can handle compressed SAS datasets and can easily convert them to CSV files. In this paper we show how to use Python to create figures for solid tumor studies change from baseline, percent change from baseline, sample, forest plot, waterfall chart, swimmer plot, adam dataset, scatter plot, cdisc source
video
presentation source		 10
99 Python in Healthcare: Coding the Future of Medicine Swetha Mandava Presentation data science source
video		 26
100 R + JavaScript = Amazing Applications Maya Gans Presentation visit, line chart source
video		 27
101 R Clinical Cloud Strategy Developments Philip Bowsher,
Sean Lopp		 Poster source 1
102 R Package Validation Framework Ellis Hughes Presentation data cleaning, excel source
video		 35
103 R Shiny Application for the PHUSE Open Data Repository Hanming Tu Presentation relational database, set statement, data cleaning, excel, data science, error message, raw data source
video		 15
104 Rave Web Services (RWS) Approach for Rollover Trials: Reducing the Burden Liesbeth Renneboog,
Tom De Coster		 Presentation source
video		 24
105 Real-Time Clinical Trial Analytics Using Automation with IBM Clinical, Medidata Rave and Datacise Amritpal Singh Presentation machine learning, data standard, data transformation, big data, excel source
video		 10
106 Real-Time Clinical Trial Analytics Using Automation with IBM Clinical, Medidata Rave and Datacise Aditya Gadiko,
Christopher C. Hurley		 Presentation clinical trial, data science, sas visual analytics, outlier source
video		 7
107 Reflect and Get More Information Out of Data than Ever Before Catharina Dahlbo,
Eva Kelty		 Poster clinical trial, clinical data source 1
108 Regulatory Update & Townhall Ram Iyer Presentation feature extraction source 26
109 Regulatory Update & Townhall Ethan Chen Presentation data cleaning, clinical trial, data standard, regulatory submission, adverse events, clinical data, raw data source 28
110 Rescreened Subjects, Data Collection and Standard Domain Mapping Savithri Jajam,
Vamshi Matta		 per protocol, clinical trial source
video
presentation source		 6
111 SAS2P21CLI Gustav Bernard Presentation macro definition, data cleaning, sas log, macro parameter, sas grid, sas enterprise guide, numeric functions source
video		 31
112 Scientific Listening: Content Analysis for Online Discussion of Bipolar Disorder Bowen Lu Presentation data science, normalization source
video		 13
113 SDTM Mapping and Conversion Using NLP Eric Weising Presentation sdtm programming, response variable, data cleaning, machine learning, neural network, proc freq, imbalanced data, cdisc source
video		 16
114 SDTM, ADaM and Database Normal Forms Implementation Andrii Borzenkov Presentation key, trial design model, length statement, adverse events, concomitant medications, natural key, relational database, cdisc source
video		 21
115 Self-sufficient Exploration of Clinical Trial Events in Different Ways and in Different Contexts Eva Kelty Presentation clinical research, clinical trial, relational database source
video		 15
116 SimSCE: Building an SCE City to Support My Process Andrew B. Ratcliffe,
Chris Decker		 Presentation csr, big data, clinical trial, data cleaning source
video		 36
117 Software Demonstration: SD08: entimICE FastTrack Next Generation Statistical Computing Environment Jörn Bilow Presentation hash table, rest api, 21 cfr part 11, biostatistics, clinical data, macro loop, macro conditional source 17
118 Software Demonstration: SD11: Streamline Your Quantitative Anonymization Process and Deliver Consistent Outputs for Every Disclosure Scenario Stephen Doogan Presentation privacy, data protection, threshold, unstructured data, batch processing, extract, key performance indicator source 8
119 Software Demonstration: SD12: Reporting Application that Provides Instant Oversight to Management and Actively Helps Programmers to Save Time, Implement Standards and Raise Quality Shafi Chowdhury Presentation clinical trial, data cleaning, adam dataset, data review, resource allocation, cdisc source 11
120 Software Demonstration: SD13: RStudio Pharma Updates Sean Lopp Presentation data science, data cleaning source 12
121 Software Demonstration: SD14: Accelerate your Transition to R in 4 months: Learn About the Accel2R Accelerated Learning Program Steve Walker Presentation confidence interval, safety population, proc phreg, hazard ratio, censoring, predictor variable, binary variable source 22
122 Solution When a Global Pandemic Resurrects Paper-based PROs, Creating Collection Headaches for Data Managers Hayley Jeffery,
Terek J. Peterson		 Unforeseen COVID-19, country wide lockdowns and site closures impacted data collection processes, shifting eCOA data collection to paper assessments. This paper explores the challenges of processing urgent paper assessments, estimated at 6 months to complete. Using dynamic worksheets, integrated with each study's SQL database, allowed accurate and efficient data entry. eCOA systems employ parent/child relationship database models, allowing dynamic question entry in logical order. The solution mirrored this approach for paper, maintaining data integrity and providing a logical/simple tool for Data Management. Dropdown selection boxes dynamically updated on selected choices, permitting only the correct options. Translations were implemented, applying the applicable language to reduce inaccuracies. Current processes leveraged existing verification step prior to committing, creating staging tables which were validated by another individual for accuracy data integrity, proc sql source
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presentation source		 6
123 Splitting Character Variables into Meaningful Text Savithri Jajam,
Vamshi Matta		 macro parameter, sample source
video
presentation source		 6
124 Standards and Governed Data in the Clinical Data Pipeline Robert Musterer Presentation web service source
video		 8
125 Standing Room Only Presentation: AS11: Cross-study Analysis of SEND Datasets Using an R Package: sendigR Kevin Snyder,
William Houser		 Presentation r package source 14
126 Standing Room Only Presentation: CM03: Quality Tolerance Limits: Leveraging Predictive Modeling Christina Dinger,
Slade McKee		 Presentation csr, data audit, clinical trial, quality assurance source 18
127 Standing Room Only Presentation: CT05: Programmatic Approach to Ensure Data Package Contents Simon Xue,
Tanmay Khole		 Presentation macro parameter, clinical programming, clinical trial, excel, macro definition source 9
128 Standing Room Only Presentation: DH02: On the Other Side of the Fence: When Two Skill Areas Join Forces and Boundaries Dissolve Mette Krogh Beyer,
Stine Ross		 Presentation clinical trial, sdtm programmer, data cleaning, clinical database, statistical programmer, cdisc source 15
129 Standing Room Only Presentation: DS06: CDISC Analysis Results Standard Bess LeRoy Presentation change from baseline, confidence interval, adam dataset, bds, adsl, primary endpoint, sdtm programming, cdisc source 25
130 Standing Room Only Presentation: DV10: Topline Results Dashboards with Rmarkdown & Flexdashboard Harsha Kalikivayi,
Robert Adams		 Presentation dataset, data wrangling, clinical trial, secondary endpoint, data cleaning source 26
131 Standing Room Only Presentation: ML08: You Are the Company You Keep: Converting Words to Numbers Using Text Embeddings Michael Stackhouse Presentation machine learning, test set, training set, proc freq source 23
132 Standing Room Only Presentation: SI09: Accelerating Beyond Excel: Mapping Specifications in an Intelligent Web-based GUI Nathan Johnson Presentation excel source 43
133 Standing Room Only Presentation: SP11: Agile Development Methodology for Delivery of the Clinical Data Pipeline Benjamin Arancibia,
Michael S Rimler		 Presentation proof of concept, clinical programming source 21
134 Statistical Computing Environment White Paper Jorine Putter,
Mark Bynens		 data cleaning, validation documentation, cloud storage, quality control, clinical trial source
pdf
video		 45
135 Statistical Programming Team Contributions to Registrational Clinical Research Collaborations (rCRCs) Norihiko Oharu,
Yan Shen		 Poster: Pfizer has a number of collaborative studies with academic collaborators and their study data are intended to be used for Pfizer regulatory submissions. Statistical programming team has been involved in more than statistical programming activities but engaged with collaborators of the trials to gain alignment of Pfizer submission activities using their data by explaining regulatory requirements and Pfizer processes for the successful regulatory submissions. Number of collaborative discussions and meetings and SMEs input are needed between organizations as interest of data usage and processes are different between pharmaceutical and academic collaborators. Proactively preparing for the technical challenges are critical for the successful submission. The poster is to illustrate the involvement and contribution of the statistical programming team to successful regulatory submissions using CRC collaborator data for Pfizer regulatory submissions regulatory submission, clinical programming, clinical research source 1
136 Strengthening Relationships with External Business Partners in Statistical Programming - The Why and the How Devang Bhatt,
Yongcun Zhang		 Presentation customer satisfaction, statistical programmer, clinical programming source
video		 12
137 Table-based Data Visualizations Using R Matthew Kumar Presentation data visualization, swimmer plot, hazard ratio, feature selection, cards, odds ratio, relative risk source
video		 26
138 Taking better control of ODS outputs using ODS TAGSETS Kamleshkumar Patel Most of the outputs in pharmaceutical industry are produced by using SAS/ODS. SAS/ODS is powerful to produce various custom reports as per stakeholders' requirements. One of unique feature of SAS/ODS is ODS TAGSETS. It gives immense power to programmer to control ODS outputs. However, the usage of ODS TAGSETS among programmer is comparatively less. Hence, this paper would try to cover simple ways to take control of various types of ODS outputs using ODS TAGSETS put statement, pharmaceutical industry source
video
presentation source		 9
139 Template of Analysis Reviewer's Guide in Oncology Hong Qi,
Mary N. Varughese		 Presentation adam dataset, adverse events, sample, adae, clinical programming, in=, crosswalk, cdisc source
video		 19
140 The Case for Pandemic-disrupted Studies and Challenges Implementing CDISC and FDA COVID-19 Guidelines for NDA Submissions Vidya Muthukumar Presentation clinical trial, protocol deviations, weighted mean, output delivery system, edc, adverse events, clinical endpoint source 44
141 The Encoding Dilemma Angelo Tinazzi It is not uncommon to see in SAS log files messages such as "Some character data was lost during transcoding in the dataset." What are we risking if we do not take care of such a message? What is the message telling us? How can we prevent the message to occur or what actions do we need to take to eventually correctly reading the data we have received? Moreover, regulatory agencies such as the Japanese (PMDA) or more recently the Chinese (NMPA) [8], are now asking to submit datasets, and not surprisingly (or surprisingly for someone), they are requesting not only datasets in CDISC format but they are also requesting or suggesting the use of SAS XPT format as a file data format; furthermore, the NMPA has specific requirements with regards to the use of Chinese language for things like label of datasets and variables and contact of character variables e.g. adverse events terms sas library, dataset, sas log, sdtm domain, proc step, adverse events, cdisc source
video
presentation source		 10
142 The Journey to Responsible and Ethical AI Shobhit Shrotriya Presentation artificial intelligence, privacy source
video		 22
143 The JumpStart Traceability Assessment Jesse Anderson,
Sarah Rodgers		 Presentation source
video		 20
144 Tipping the Scale: Moving from Scaling Experts to Balancing them with Novel Technologies Christopher J. Colangelo Presentation cpu time, raw data source
video		 12
145 Transforming Clinical Data Chaos with elluminate Dawn Kaminski Presentation data cleaning, web service source
video		 12
146 Transitioning to R for Clinical Submissions Philip Bowsher,
Sean Lopp		 Presentation data cleaning, data governance source 16
147 Unnoticed Individual and Mean Line Plot Issue While Using the SGPLOT Procedure, and the Solution to Avoid Jagadish Katam Poster source 1
148 Using Central Monitoring to Mitigate Data Quality Risk during the COVID-19 Pandemic Adrienne Strickler,
Anna Wojcik		 Presentation sas risk engine, protocol deviations, adverse events, data cleaning, missing value, insurance risk score, raw data source
video		 21
149 Using Computer Vision to Identify and Extract Tables from Various File Formats Kanishk Mair,
Shashank Pagidimarri		 Presentation csr, neural network, batch processing, clinical trial, deep learning, model training, protocol deviations source
video		 22
150 Using Natural Language Processing to Create Subject Safety Narratives Frank Meloni,
Tim Willittes		 Presentation neural network, adverse events, clinical data, clinical research, clinical trial, medical history, regulatory submission source
video		 8
151 Using Real-world Data in Supporting Health Authority Submission Ruoying Fang,
Shuang Zhang		 Presentation clinical trial, propensity score, analysis set, data science, imputation, multiple imputation, pd source
video		 26
152 Using the Computational Power of Julia to Drive Clinical Trial Simulations (CTS) Patrick Hannon Presentation imputation, multiple imputation, parallel processing source 13
153 VALSPEC Utility to Validate CDISC Specifications Aman Bahl,
Hrideep Antony		 Presentation clinical programming, data cleaning, controlled terminology, database lock, sdtm domain, sdtm programming, statistical programmer, cdisc source
video		 12
154 Veeva CDB Workbench Accelerates Data Cleaning, Mapping and Reporting with Complete and Concurrent Clinical Data in the Cloud Drew Garty,
Pavel Burmenko		 Presentation source
video		 28
155 Visual Programming for ADaM Derivation Clara Beck,
Robert Adams		 Presentation data cleaning, independent qc, clinical data, dataset, data science, sas log, deep learning source
video		 33
156 Visualization of Sparse PK Concentration Sampling Data, Step by Step (Improvement by Improvement) Ilya Krivelevich Pharmacokinetic (PK) data is collected for a variety of purposes in clinical trials. PK data is critical in understanding a drug's safety and determining its dosing frequency. Pharmacokinetic analysis is a major part of clinical trials to obtain informatio n on drug disposition in humans. Graphics are always a powerful tool in reporting, and Concentration vs. Timeline graphs are standard for reporting PK data. Data visualization tools are widely used in PK analysis, so meaningful graphics play a very import ant role. There are many presentations and examples that deal with displaying results of rich sample collections; however, there is a significant shortage of similar presentations that cover the visualization of results of the widely used sparse PK data co llection. This article may be interesting from a methodology standpoint; it presents examples and suggestions of step -by-step development of figures for sparse PK concentration using powerful ODS SAS tools proc sgplot, proc step, box plot, sample, clinical trial source
video
presentation source		 12
157 Visualizations to Support DSMB Monitoring Derek Coombs Presentation vital signs, data visualization, proc means, outlier, adverse events, bar chart, proc print source
video		 14
158 Visualizing Efficacy Data from Phase II or III Randomized, Double Blind Placebo Controlled Trials Munish Mehra Presentation change from baseline, clinical trial, proc sgplot, proc step, bubble plot, heatmap, contour plot source
video		 18
159 Visually-enhanced Patient Narrative Abhinav Srivastva Poster csr, serious adverse event source 1
160 Waffle Chart in SAS Abhinav Srivastva A Waffle Chart can be used to represent parts -to-whole relationship, such as percentage of a metric completed to its target. Multiple waffle charts can be juxtaposed to compare similar or contrasting features among several categories. Although SAS has no direct charting option or Procedure (PROC) to create a waffle chart, it can be easily accomplished using the Graph Annotation utility. The paper utilized RECTANGLE annotation function to create filled squares, along with TEXT function to place custom text on the chart complete response, sample source
video
presentation source		 4
161 What About Having a "Google" for Your Study Data? R-Shiny-based Customized Data Viewer and Search Engine Aman Bahl,
Hrideep Antony		 Poster source 1
162 Why Business Users Should Care About Systems Architecture Hans-Peter Schreiter Presentation out=, where statement, data cleaning source
video		 16
163 Wiki - Your Team's Collective Memory Michael Thomsen Presentation source
video		 32

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