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Presentations

Study Set-up: The Roadmap For Effective Data Collection

Indrani Kakade

Study Set-up: The Roadmap For Effective Data Collection

Selection and Training of Clinical Research Partners

Celestine Juliet Rebello

Selection and Training of Clinical Research Partners

Study Design: The Blueprint for success

Prathap Tharyan

Study Design: The Blueprint for success

Clinical Research : End User’s Perspective

Dr. R A Badwe

Clinical Research : End User’s Perspective

Pathway to Quality Management of Study Data

Deven Babre

Pathway to Quality Management of Study Data

Analysis Planning and Safety Monitoring: The Statistician as a Trialist

Ritwik Sinha

Analysis Planning and Safety Monitoring: The Statistician as a Trialist

Medical Communications: Messaging to Internal and External customers

Bindu Narang

Medical Communications: Messaging to Internal and External customers

Standards in analysis & reporting

Murali Ganesan

Standards in analysis & reporting

Demystifying the Jargon

Shailaja Chilappagari

Demystifying the Jargon

Regulatory interactions: Engaging effectively for success

Manish Paliwal

Regulatory interactions: Engaging effectively for success

REGULATORY FILINGS IGNORANCE IS BLISS?

Ranjani Nellore

REGULATORY FILINGS IGNORANCE IS BLISS?

eCTD: A farewell to paper submissions

Vijay Srinivasan

eCTD: A farewell to paper submissions

Comparative Effectiveness Research From safety and effectiveness to risk‐benefit

Viraj Suvarna

Comparative Effectiveness Research From safety and effectiveness to risk‐benefit

Statistical concepts for clinical research

Vishwanath Iyer & Ashwini Mathur

Statistical concepts for clinical research

ConSPIC 2011 - Day 1 Track 1

Compiled file

ConSPIC 2011 - Day 1 Track 1

Day 2 Track 2

Day 2 Track 2

Workshop in Pharmacovigilance

Compiled file

Workshop in Pharmacovigilance

Adaptive Bayesian dose findings

Chethana Kalmady

Adaptive Bayesian dose findings

Oxazolidinone for the treatment of Tuberculosis (TB)

DR BALASUBRAMANIAN

Oxazolidinone for the treatment of Tuberculosis (TB)

Clinical Trials Design Workshop

Dr Vishwanath Iyer & Dr Ashwini Mathur

Clinical Trials Design Workshop

Statistical Analysis for Biomarker Identification

Raghunathan Srivastsan

Statistical Analysis for Biomarker Identification

Pharmacometrics – PK/PD Modeling

Jyothi Subramanian

Pharmacometrics – PK/PD Modeling

Role of Toxicology Data in Drug Development

K.S. Rao

Role of Toxicology Data in Drug Development

Meta-analysis in Risk-Benefit Evaluation

Demissie Alemayehu, Ph.D.

Meta-analysis in Risk-Benefit Evaluation

CLINICAL ENDPOINT STUDIES IN GENERIC DRUG DEVELOPMENT

Dr Ravisekhar Kasibhatta

CLINICAL ENDPOINT STUDIES IN GENERIC DRUG DEVELOPMENT

Bridging studies: whether to bridge, how to bridge and what to bridge

Young Jack Lee, Ph.D.

Bridging studies: whether to bridge, how to bridge and what to bridge

Biosimilar Development: Design and Statistical Challenges

Moumita Sinha, PhD

Biosimilar Development: Design and Statistical Challenges

Regulatory Considerations in Designing of Respiratory Studies for Generic Drugs

Dr Sheetal Ingole

Regulatory Considerations in Designing of Respiratory Studies for Generic Drugs

Simulations in Clinical Trial Design

Abhishek Mishra

Simulations in Clinical Trial Design

Sample Size Re-estimation in Late Stage Trials

Dr Vidyadhar Phadke

Sample Size Re-estimation in Late Stage Trials

Using PERL Regular Expression in SAS-Useful and Powerful Tool

K.E.Sudarsan

Using PERL Regular Expression in SAS-Useful and Powerful Tool

Extracting tracking information for data management team from oracle clinical

Dhaval Mehta

Extracting tracking information for data management team from oracle clinical

Integrating Perl scripting with SAS

Ninan M. Luke

Integrating Perl scripting with SAS

Overview of user Defined SAS Functions and Subroutine

Senthilnathan Ramanathan

Overview of user Defined SAS Functions and Subroutine

Utility Macros

Suman Kapoor

Utility Macros

Box Plot and Clinical Trial Analysis

Devayani and Rosemary

Box Plot and Clinical Trial Analysis

A Pragmatic Tool for Clinical Trials in Analyzing Repeated Measures Categorical Data

Sakthivel S, Reshma K R

A Pragmatic Tool for Clinical Trials in Analyzing Repeated Measures Categorical Data

Addition of R Programming in Clinical Domain

Sasikumar S

Addition of R Programming in Clinical Domain

Registering and Reporting Results with Clinicaltrials.gov.in

Swapna Kopalla

Registering and Reporting Results with Clinicaltrials.gov.in

RECIST and Programming Challenges

Mahesh Babu Mayakuntla & Prasanna Kumar Nidamathy

RECIST and Programming Challenges

Exposure to Exposure

Gauri Khatu

Exposure to Exposure

QT analysis: A Guide for Statistical Programmers

Prabhakar Munkampalli

QT analysis: A Guide for Statistical Programmers

Cross Validation Made Easy

Sarfaraz Sayyed

Cross Validation Made Easy

Challenges in Analyzing Laboratory Values and Measurements

Sugunesh Sivalingam

Challenges in Analyzing Laboratory Values and Measurements

10 Possible mistakes in Statistical programming

Rijesh Paramal

10 Possible mistakes in Statistical programming

Validation of Statistical Analyses in Cosmetic Trials using R

Tejaswni Abhyankar

Validation of Statistical Analyses in Cosmetic Trials using R

Utility of SAS Graph Annotation

Urmi Bhatia, Aditi Kakade and Yogesh Yewale

Utility of SAS Graph Annotation

Graphs Made Simple using SG Procedures and GTL

Hari Vardhan J

Graphs Made Simple using SG Procedures and GTL

Visualizing data using SAS GTL (Graphics Template Language)

NISHANTH NALAN

Visualizing data using SAS GTL (Graphics Template Language)

Unleashing Potential of Graphs for Analysis of Adverse Events

Abhinav Jain

Unleashing Potential of Graphs for Analysis of Adverse Events

Competent SAS Programmer: Need of BPO Industry

Imran Khan

Competent SAS Programmer: Need of BPO Industry

Phasing: Concept and Real Life Challenges

Benazir Ibrahim

Phasing: Concept and Real Life Challenges

Do We Know Enough about Drug Exposure?

Vinay Mahajan and Pawan Sharma

Do We Know Enough about Drug Exposure?

Role of a Statistical Programmer in an Intra-patient Dose Escalation Trial

Sudarshan Sareddy and Vikram Venugopal

Role of a Statistical Programmer in an Intra-patient Dose Escalation Trial

Copy, Paste and Misanalysis

Ramkumar M.Rajendiran

Copy, Paste and Misanalysis

Bag it, Tag it & Put it::Project tracking one click away!

Abhishek Bakshi

Bag it, Tag it & Put it::Project tracking one click away!

Tools, Technologies and Techniques in Clinical Data Standardization

Pankaj Bharadwaj

Tools, Technologies and Techniques in Clinical Data Standardization

SAS Programming Tool to Create Statistical Outputs for Bioavailability and Bioequivalence studies

Gaurav Chauhan, Arun Kumar, Pankaj Mishra

SAS Programming Tool to Create Statistical Outputs for Bioavailability and Bioequivalence studies

Adaptive Designs in Clinical Trials

Pratibha Jalui

Adaptive Designs in Clinical Trials

Randomization

Rajalakshmi

Randomization

Array Presentation

Vibhavari Inamdar

Array Presentation

Data Manipulation using SAS Arrays

Ravisekhar Jayanti

Data Manipulation using SAS Arrays

SAS@XML Mapper Tool – An Underdog in Clinical Domain!

Rahul Paul Chaudhary

SAS@XML Mapper Tool – An Underdog in Clinical Domain!

Bringing repeatability and automation to the data integration process for organizing, standardizing and managing clinical research data and metadata

Saumil Tripathi

Bringing repeatability and automation to the data integration process for organizing, standardizing and managing clinical research data and metadata

Overview of SAS Education

Raj Jhaveri

Overview of SAS Education

Healthy Numbers – Historical perspective of quantitative analysis of health

Prof. A. P. Gore

Healthy Numbers – Historical perspective of quantitative analysis of health

Clinical Trials – History and Ethics

Dr. Ashwini Mathur

Clinical Trials – History and Ethics

Advances in safety data analysis - the Journey

Dr. Vivek Ahuja

Advances in safety data analysis - the Journey

Role of PK/PD in Evidence based Medicine

Dr. Tausif Ahmed

Role of PK/PD in Evidence based Medicine

Adoption of SaaS and cloud technology by pharma & CROs

Dr. Saurav Roy

Adoption of SaaS and cloud technology by pharma & CROs

Creating Evidence Base: An Example of NSDs

Dr. Vasudeo Paralikar

Creating Evidence Base: An Example of NSDs

Cohort studies in HIV: The Journey of Evidence for HIV in India & Registry Match Studies: HIV Database and Cancer Registry Match

Dr. Sheela Godbole

Cohort studies in HIV: The Journey of Evidence for HIV in India & Registry Match Studies: HIV Database and Cancer Registry Match

Systematic Reviews & Meta Analyses

Dr.B.Unnikrishnan

Systematic Reviews & Meta Analyses

Communicating Results in Publications: A Perspective

Dr. Sunita R. Nair

Communicating Results in Publications: A Perspective

Use & presentation of evidence while launching & marketing products

Dr. Piyush Agarwal

Use & presentation of evidence while launching & marketing products

How is the evidence used by a prescriber?

Dr. Gouri Pantvaidya

How is the evidence used by a prescriber?

Current state of clinical research in India

Dr Arun Bhatt

Current state of clinical research in India

Statistics in Clinical Trials – Some emerging issues

Dr. Arun Nanivadekar [Keynote Speaker]

Statistics in Clinical Trials – Some emerging issues

Introduction to Survival Analysis - Workshop slides

Sanjib Basu

Introduction to Survival Analysis - Workshop slides

PLAN YOUR WORK USING PROC CALENDAR

SURESH KUMAR KOTHAKONDA

PLAN YOUR WORK USING PROC CALENDAR

Managing the Unspoken Customer Expectations

Pratibha Jalui & Pooja Shinde

Managing the Unspoken Customer Expectations

The Graph Template Language (GTL)

Manoj Panday

The Graph Template Language (GTL)

Conducting clinical trials in India - efficient planning and ensuring success

Dr. Chirag Trivedi

Conducting clinical trials in India - efficient planning and ensuring success

Execute efficiently by using call execute

Santhosh Chetpelly and Paramkusham Kishore Kumar

Execute efficiently by using call execute

Insights into Data Visual Analytics - A new Paradigm

Sridhar Kantamani

Insights into Data Visual Analytics - A new Paradigm

A Study to Identify Assessments Impacting Patient Burden

Ramya Kode Dhaval Naik

A Study to Identify Assessments Impacting Patient Burden

Lab CTC Grades Unveiled

Giriprasad Bommisetty & Manjushree

Lab CTC Grades Unveiled

Enhancing outputs with PROC TEMPLATE

Madhubhushan Eada and Satyendra Kuril

Enhancing outputs with PROC TEMPLATE

INTERVAL CENSOR DATA WITH SAS

Raju Tadala

INTERVAL CENSOR DATA WITH SAS

What, How and WHY’s Law

Priyesh Sura

What, How and WHY’s Law

Sneak peek of Trial Design Model

Jasmin Jobanputra

Sneak peek of Trial Design Model

Molecular modeling – to ease drug discovery in clinical industry

Madhusudhan Bandi

Molecular modeling – to ease drug discovery in clinical industry

Idiosyncratic Plots to Visualize the Clinical data

Aditi Kakade & Garima Joshi & Vidya Raja & Tamilselvi Senthilkumar

Idiosyncratic Plots to Visualize the Clinical data

Out of Box Thinking

Senthilkumar and Srihari

Out of Box Thinking

Analysis Data Reviewer’s Guide (ADRG) – A Road Map

Renjana Prasannan and Apoorva Singh

Analysis Data Reviewer’s Guide (ADRG) – A Road Map

PERL REGULAR EXPRESSION IN SAS

Ravi Gupta and Jagadish Katam

PERL REGULAR EXPRESSION IN SAS

Methods of Creating Define.xml and Challenges Faced

Mustaq

Methods of Creating Define.xml and Challenges Faced

Imputation of Missing Data through Bayesian Approach

Pratibha Jalui and Reetabrata Bhattacharyya

Imputation of Missing Data through Bayesian Approach

Patient Reported Outcomes - PROgressive approach to clinical trials

Shilpakala Vasudevan and Padmashree Jahagirdar

Patient Reported Outcomes - PROgressive approach to clinical trials

Analysis of Failure Times in the Presence of Competing Risks and its SAS procedures

Aditi Marate and Naseema Shaik

Analysis of Failure Times in the Presence of Competing Risks and its SAS procedures

Construction of Williams Square Design and Randomization in Cross Over Trails Using SAS

Nandana Prabhu

Construction of Williams Square Design and Randomization in Cross Over Trails Using SAS

Unleashing the black box of debugging in Validation

Chaitanya pradeep repaka

Unleashing the black box of debugging in Validation

“D” Wise approach for “Device” trial

Praveen Aleti

“D” Wise approach for “Device” trial

SAS functions – easy way to remember

Sadanand Deshmukh

SAS functions – easy way to remember

Importance of RAV analysis in Hepatitis-c studies

Shrikrishna shroff

Importance of RAV analysis in Hepatitis-c studies

Guidance For Evaluating Responses in Multiple Myeloma

Janki Chokshi

Guidance For Evaluating Responses in Multiple Myeloma

Deciding Clinical Trial Endpoints in Oncology Studies

Srinivas Devasani and Anupkumar Baheti

Deciding Clinical Trial Endpoints in Oncology Studies

SDLC in Statistical Programming - A Possibility?

ARUNA CHAKRABORTY

SDLC in Statistical Programming - A Possibility?

OVERVIEW OF PATIENT PROFILES

Pavithra and Melvin and Roshan

OVERVIEW OF PATIENT PROFILES

SMAC AND ITS ROLE IN CLINICAL TRIALS

Dhivagaran and Sandeep

SMAC AND ITS ROLE IN CLINICAL TRIALS

EXCEL'ing Quality With Efficiency

Harish Kumar and K Pallayya Guptha Vura

EXCEL'ing Quality With Efficiency

Creating consolidated XML by using VBA to EUDRACT/ICTRP/FDA

Rammohan and Naveen

Creating consolidated XML by using VBA to EUDRACT/ICTRP/FDA

Tips for Handling and Creating Special Characters in SAS

Apoorva Singh

Tips for Handling and Creating Special Characters in SAS

Implementing multiple baselines in ADaM BDS datasets

Vamsidhar Terala

Implementing multiple baselines in ADaM BDS datasets

TD - Trial Disease Assessments Domain in SDTM IG 3.2

Sandhya Yalla

TD - Trial Disease Assessments Domain in SDTM IG 3.2

Cross Over Trial Design:CDISC Data Structure

Anusha Bhimavarapu & Ashok Kodali

Cross Over Trial Design:CDISC Data Structure

Handling correlated data using GLIMMIX procedure

Anitha Cecelia

Handling correlated data using GLIMMIX procedure

Monitoring Safety Signal in Clinical Trial(s)

Satish Bhosale & Amitava Mukhopadhyay

Monitoring Safety Signal in Clinical Trial(s)

Bootstrap - Resampling

Venkateshwarlu Y

Bootstrap - Resampling

Optimal Planning of Clinical Trials

Soumya Rout

Optimal Planning of Clinical Trials

Challenges in Building better 'EDC System in Clinical Trials'

Sarath Krishna

Challenges in Building better 'EDC System in Clinical Trials'

An Activity to Track Ongoing Clinical Study Data Capturing Process Efficiently

Thoufic Ahamed

An Activity to Track Ongoing Clinical Study Data Capturing Process Efficiently

Pooling of 25 years old legacy studies data captured in different languages for DSUR preparation

Sakthivel Sivam

Pooling of 25 years old legacy studies data captured in different languages for DSUR preparation

An observational study – as observed by a programmer

Swati Kapuganti and Naveen Katarki

An observational study – as observed by a programmer

Efficient Data Specification creation for ADAM studies in a multi-resourcing model environment

Gloria D'Souza

Efficient Data Specification creation for ADAM studies in a multi-resourcing model environment

How ‘Significant digits’ are significant in clinical trials

Swarnalatha Madupu

How ‘Significant digits’ are significant in clinical trials

Quality adjusted survival (Q-TWiST)

Puliraju Mandati

Quality adjusted survival (Q-TWiST)

Think Twice before using Regression

Suman Kapoor

Think Twice before using Regression

Methods of Safety Recurrence Analysis and its SAS Procedures

Aditi Marathe

Methods of Safety Recurrence Analysis and its SAS Procedures

PK/PD Modeling in Support of Drug Development

Ranjith Kumar & Madhu Guruvelli

PK/PD Modeling in Support of Drug Development

Significance of Periodical Submissions in Clinical Research

Sambasivarao Tedla, Sandeep Kambhampati

Significance of Periodical Submissions in Clinical Research

R Programming Validation for the Clinical Study Report

Sridhar Punniamurthi, Harish Chellam Narayanan

R Programming Validation for the Clinical Study Report

EASE YOUR WORK WITH NOTEPAD++

Amarnath Vijayarangan

EASE YOUR WORK WITH NOTEPAD++

Strengthening Your Trial Arms

Arwa Topiwalla

Strengthening Your Trial Arms

Bridging Statistical Analysis Plan, ADaM Datasets & Metadata

Nilesh Kumar Muthyala

Bridging Statistical Analysis Plan, ADaM Datasets & Metadata

EXPOSURE TO EXPOSURE 'AS COLLECTED'

Mousumi Biswas

EXPOSURE TO EXPOSURE 'AS COLLECTED'

Magic of Analytics in Clinical Trails

Soujanya Konda, Padmavathi Karumuru and Amruta Pathak

Magic of Analytics in Clinical Trails

MEDICAL MONITORING

CHARAN KUMAR, SRINIVAS RAPELLY

MEDICAL MONITORING

Usage Of Mahalanobis Distance Statistics in Clinical Data

Karuna Gawde

Usage Of Mahalanobis Distance Statistics in Clinical Data

Dashboard for Project Management Using Excel adn R

Kalaivani Raghunathan, Egappan Rama

Dashboard for Project Management Using Excel adn R

Standard Macro System

Pratibha Jalui

Standard Macro System

Risk Mitigation In Clinical Trail Projects

Bibas Timilsina

Risk Mitigation In Clinical Trail Projects

FSP Business Model

Nishanth N

FSP Business Model

Electronic Submissions

Vikas Dhongde

Electronic Submissions

EudraCT-A new way forward for greater transparency

Ramya Deepak, Aditya Shah

EudraCT-A new way forward for greater transparency

Anonymization of Clinical Trial Data

Satheesh Kantam,Sathish Reddy Ganga,Sarita Pasi,Aditya Kamat

Anonymization of Clinical Trial Data

ADAPTIVE DESIGN CLINICAL TRIALS

PRASANTHI BONALA,VIJAYAN GOVINDHARAJAN

ADAPTIVE DESIGN CLINICAL TRIALS

Selection of Test Model

Karunakar Narahari

Selection of Test Model

ROC Curve:Making way for correct diagnosis

Manoj Pandey,Writwik Mandal

ROC Curve:Making way for correct diagnosis

Effortless Validation:It's so simple

Anusuiya Ghanghas

Effortless Validation:It's so simple

Automating the code for Command Line Interface in OpenCDISC Validator

Rajasekhar Mudugu

Automating the code for Command Line Interface in OpenCDISC Validator

SDTM Annotations-Checker and Mapper-Automated Approach

Dhananjay Thakur

SDTM Annotations-Checker and Mapper-Automated Approach

HIV Studies:An Overview for Programmers

Rupali Belose, Aditya Tembe

HIV Studies:An Overview for Programmers

An Overview of Key Efficacy endpoints and how to attain them in Oncology Trails

Narasimha Rao B

An Overview of Key Efficacy endpoints and how to attain them in Oncology Trails

OPHTHALMOLOGY IN CLINICAL TRIALS

ARUNA CHAKRABORTY

OPHTHALMOLOGY IN CLINICAL TRIALS

OpenTLF

Ashwin V

OpenTLF

Next Generation Sequencing magnifying glasses to read your DNA

Neelam Yadav

Next Generation Sequencing magnifying glasses to read your DNA

ODS Graphics Designer - beyond point and click!

Priyanka & Satish

ODS Graphics Designer - beyond point and click!

Presenting statistics in KM Plot in the way Clinicians & Statisticians would love to see it !!

Anantha Jothi Sankaran

Presenting statistics in KM Plot in the way Clinicians & Statisticians would love to see it !!

Statistics for non-statisticians - concepts useful for clinical research..

Vishwanath Iyer, Ashwini Mathur

Statistics for non-statisticians - concepts useful for clinical research..

Advances in safety data analysis – the journey

Vivek Ahuja

Advances in safety data analysis – the journey

Adoption of SaaS and cloud technology by pharma and CROs

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Adoption of SaaS and cloud technology by pharma and CROs

Clinical Study Design: Statistical Considerations

Jagannatha P.S.

Clinical Study Design: Statistical Considerations

ConSPIC 2011 - Day 2 Track 2

Compiled file

ConSPIC 2011 - Day 2 Track 2

Adaptive-Monitoring

Chirag Trivedi

Adaptive-Monitoring

Database Design and Optimization for Signal Detection

Krishna Asvalayan

Database Design and Optimization for Signal Detection

Life Science Market Sell

Smit Shanker

Life Science Market Sell

Next Generation Sequencing - Challenges and solutions

Saurabh Gupta

Next Generation Sequencing - Challenges and solutions

Predictive Modelling for Commercial Usage

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Predictive Modelling for Commercial Usage

Safety Signal

----

Safety Signal

Text-Analytics-IASCT

Harsha Urlam

Text-Analytics-IASCT

Safety in clinical research

Vishwanath Iyer(Mahesh)

Safety in clinical research

The value of data 2014

Stephen Pyke

The value of data 2014

CLM Social Media

Manish Pathak, Konark Garg

CLM Social Media

Detecting safety signals

Ramanan Ezhil Arasan

Detecting safety signals

Insights from Data

S Anand

Insights from Data

PYNE Statistical Frameworks for Big Data Analysis

Saumyadipta Pyne

PYNE Statistical Frameworks for Big Data Analysis

Signal Detection Regulations Data Sciences Paradigm

Chitra Lele

Signal Detection Regulations Data Sciences Paradigm

Challenges in creating SDTM trial design datasets for complex study designs

Charumathy Sreeraman

Challenges in creating SDTM trial design datasets for complex study designs

Adaptive designs in biopharmaceutical development

Arunava Chakravartty

Adaptive designs in biopharmaceutical development

Statistical Applications in Clinical Trials

Shashidhar J Savanur, Vishwanath Iyer (Mahesh)

Statistical Applications in Clinical Trials

Deep Dive into ADaM - Workshop material

Anish Shah, Ashish Aggarwal, Roshan Stephen, Harun Rasheed

Deep Dive into ADaM - Workshop material

Graphs made by easy using SAS & R -material

Prerit Pancholiya, Sameer Bamnote

Graphs made by easy using SAS & R -material

PHARMACOKINETICS ANALYSIS WORKSHOP MATERIAL

Jagannath Kota, Vinay Kumar Venishetty, Prasanna Kumar Nidamarthy, Chandrasekhar Bhupathi

PHARMACOKINETICS ANALYSIS WORKSHOP MATERIAL

Signal Detection in Pharmacovigilance

Nithiya Ananthakrishnan, Sridhar Punniamurthi

Signal Detection in Pharmacovigilance

Safety Signal How far are we from detecting it

Pratibha Jalui, Amitava Mukhopadhyay

Safety Signal How far are we from detecting it

Using Analytics to Monitor Patient Safety

Arnab Sengupta, Rajat Nanda

Using Analytics to Monitor Patient Safety

Risk Based Monitoring

Venkatesh Krishnamurthy, Sravan NagiReddy, SatyaVyshnavi Thondapu, Milan Bhagat

Risk Based Monitoring

Predicting Future Course of Clinical Trials

Rohan Sathe

Predicting Future Course of Clinical Trials

Big data analysis in Clinical Trials

Rajan Josephraj Paul, Swarna

Big data analysis in Clinical Trials

Forecasting Trial Cost at Pre-clinical Development Stage

Manigandan Ramkumar, Kapil J Anand

Forecasting Trial Cost at Pre-clinical Development Stage

Data Driven Approach to identify Scientific Misconduct in Clinical Operation

Vikas Sharma, Deepali Pilankar, Swati Rizhwani

Data Driven Approach to identify Scientific Misconduct in Clinical Operation

Associated Person Domain

Padmasree Sirigireddy

Associated Person Domain

Multiple Baseline Implementation

SUNIL GANESHNA

Multiple Baseline Implementation

Vertical ADaM a long look

V Vishnu BapuNaidu

Vertical ADaM a long look

Biomarkers as Clinical Endpoints

Vamsidhar Terala

Biomarkers as Clinical Endpoints

Adverse Events-Intensity behind the scenes

Neha Srivastava

Adverse Events-Intensity behind the scenes

Implementation & Applicability of PROC FCMP-Creating Dynamic Custom Functions

Prathamesh Athavale, Vikramaditya Yandapalli, Ajay Yalwar

Implementation & Applicability of PROC FCMP-Creating Dynamic Custom Functions

Overview of Reporting Adverse Eevents of Special Interest

Shelendra Singh Pawar, Meghana Kulkarni, Shveta Natu

Overview of Reporting Adverse Eevents of Special Interest

The BRIDG MODEL- DAM for regulated clinical research

Naveenpal Arumugam

The BRIDG MODEL- DAM for regulated clinical research

SDTM TRAIL DESIGN MODELS

Peddiboyena Lalitha,Rathan Kumar Rangu

SDTM TRAIL DESIGN MODELS

Challenges In Assignment Of EPOCH In Partial Blinded Crossover Trials

Sagar Das

Challenges In Assignment Of EPOCH In Partial Blinded Crossover Trials

Can we automate human life value

Rohith, Neelam

Can we automate human life value

Pharmacokinetics -Compartmental Model and Data handling Challenges in CIDSC world

Prabhatha Mateti, Marshal Chettiar, Ajay Daparthi

Pharmacokinetics -Compartmental Model and Data handling Challenges in CIDSC world

Basic to Advance, ODS is all you need to know

Shabbir Bookseller, Abdulkadir Lokhandvala

Basic to Advance, ODS is all you need to know

Traceability Checks For CDISC ADaM

Obulpathi Naidu K

Traceability Checks For CDISC ADaM

Evolution of SDTM, General Pit falls and Best practices

Ranjan Routray, Lekshmanan, Shrishaila Patil

Evolution of SDTM, General Pit falls and Best practices

SDTMiG 3.3-New Domains and Variables

Prashant Suthar

SDTMiG 3.3-New Domains and Variables

Metadata Repository (MDR) When it Fails

Tushar Sakpal

Metadata Repository (MDR) When it Fails

A Practical Approach to create Define.xml and Define

Soma Sekhar.K, Thamarai Selvan.P, HUSSAIN SABIR, SAMUNDEESWARI

A Practical Approach to create Define.xml and Define

Jumpstart- A Quick Data Review Tool

Rashmi Seta

Jumpstart- A Quick Data Review Tool

A SAS® Macro for Computation of Exp-Adjusted Incidence & Event Rate with CI in AE Analysis

Sugunesh Sivalingam

A SAS® Macro for Computation of Exp-Adjusted Incidence & Event Rate with CI in AE Analysis

Utility to automate creation of datasets with metadata and simplify process of updating datasets

Kiruthiga

Utility to automate creation of datasets with metadata and simplify process of updating datasets

Robust macro for issue tracking and to check the Data and Metadata updates between data transfers

Shivaram Sharma

Robust macro for issue tracking and to check the Data and Metadata updates between data transfers

Baseline calculation and visit mapping in Concomitant medication

Pradeep Kiran

Baseline calculation and visit mapping in Concomitant medication

ADTTE - A Dynamic Tool To Effectively interpret clinical outcomes

Mangala, Shilpakala

ADTTE - A Dynamic Tool To Effectively interpret clinical outcomes

Building ADaMDataset for Oncology (Non time to event and Exposure) data the BDS way

Janki Chokshi

Building ADaMDataset for Oncology (Non time to event and Exposure) data the BDS way

can medical devices change the way we treat the patient

m l n v sai krishna, m ratna sarika

can medical devices change the way we treat the patient

Strategies to overcome the future resourcing demands of SAS Programmers

Dineshkumar.N

Strategies to overcome the future resourcing demands of SAS Programmers

Can there be an alternative to cancer clinical trials

Husayn Ahmed

Can there be an alternative to cancer clinical trials

The seven year itch

Korak Datta

The seven year itch

Comparison of Weibull and Cox proportional hazard model for time to event data

Pavan Kumar Anna

Comparison of Weibull and Cox proportional hazard model for time to event data

Detecting miRNA expression level diff for Gingivo buccal squamous cell carcinoma patients

Noirrit Kiran Chandra, Prof Sourabh Bhattacharya

Detecting miRNA expression level diff for Gingivo buccal squamous cell carcinoma patients

Mindfullness

Nishanth N

Mindfullness

DOSUBL AN IMPROVED VERSION_OFCALL_EXECUTE

Pradeep Acharya, Thejas M S

DOSUBL AN IMPROVED VERSION_OFCALL_EXECUTE

Exploring Oncology Domains

Senthil Yuvaraja, Suresh reddy

Exploring Oncology Domains

Evaluation & regression diagnostics of covariate adjusted Cox PH model with patient-scored prognostic factors

Rajendra Desai, Ayan Das Gupta

Evaluation & regression diagnostics of covariate adjusted Cox PH model with patient-scored prognostic factors

Features of Nanotechnology in Clinical industry

Pavan Sagi

Features of Nanotechnology in Clinical industry

Data De-identification and Anonymization - Guidelines and Implementation Challenges_

Farooq Ali, Kedar Maheshwari

Data De-identification and Anonymization - Guidelines and Implementation Challenges_

Generalized Poisson Regression Model with an Application to Malnutrition Data

Devika Shanmugasundaram, Lakshmanan Jeyaseelan

Generalized Poisson Regression Model with an Application to Malnutrition Data

The Tangled Tale - Painful process in laboratory data integration, reconciliation and review

Manohar Naidu V., Praveenraj Mathivannan

The Tangled Tale - Painful process in laboratory data integration, reconciliation and review

GLM with advanced SAS procedure PROC HPGENSELECT and its comparison with PROC GENMOD

Sreenath Kodoth

GLM with advanced SAS procedure PROC HPGENSELECT and its comparison with PROC GENMOD

Working with define.xml V2.0 in SDTM environment

Vijay Reddy

Working with define.xml V2.0 in SDTM environment

Graphical tool for visualizing Liver-Tox with other patient treatment parameters –a macrowised approach

Venugopal Purini, Pradeep Acharya

Graphical tool for visualizing Liver-Tox with other patient treatment parameters –a macrowised approach

Enhanced Pinnacle 21 Reports using SAS

Amitkumar Kawle,Kishore kumar Paramkusham, Abhinav Kumar, Nitin Suryawanshi

Enhanced Pinnacle 21 Reports using SAS

GTL - Customizing graphs made easy

Mahesh, Ranjan, Shoba, YellaReddy

GTL - Customizing graphs made easy

Identification of Stochastic Pattern in the Return Time Distribution of K-Mers in Mumps Virus Genomic Data

Trupti Vaidya

Identification of Stochastic Pattern in the Return Time Distribution of K-Mers in Mumps Virus Genomic Data

Identifying and Reviewing Outliers using Statistical methods

Manjinder Dalam

Identifying and Reviewing Outliers using Statistical methods

Incidence Rate

Vaishali Marathe, Yogesh Jagtap

Incidence Rate

KMplot Macro-to generate enhanced Kaplan-Meier plots

Poorna devi Ch

KMplot Macro-to generate enhanced Kaplan-Meier plots

Lasagna Plot

Avinash gupta, Pritam gupta

Lasagna Plot

Systemic Review - Has it been a game changer in clinical research

Sreekumaran Nair

Systemic Review - Has it been a game changer in clinical research

Let graphs speak using r

vura k pallayya guptha

Let graphs speak using r

Latent class analysis using proc LCA

Anitha Cecelia

Latent class analysis using proc LCA

Managing Textual information dynamically in a Graph using Proc Template

Devender Sandhi

Managing Textual information dynamically in a Graph using Proc Template

Forecasting the efficacy in Longitudinal studies using change points in mixed models

Priya D'silva

Forecasting the efficacy in Longitudinal studies using change points in mixed models

MEDICAL DEVICE - DO YOU KNOW

Shailesh Gupte

MEDICAL DEVICE - DO YOU KNOW

Overview of Class III Device trials

Ganesh L

Overview of Class III Device trials

Insights on QT/QTc studies in clinical trials-Evolution Elaboration and Evaluation

Jairaj, Bhargav, Ramiya

Insights on QT/QTc studies in clinical trials-Evolution Elaboration and Evaluation

Beta regression models for analyzing QOL data in Acromegaly

Pritam Gupta

Beta regression models for analyzing QOL data in Acromegaly

Proc GLIMMIX

Priya Govindswamy

Proc GLIMMIX

Sample size determination in clinical trials

Suryakant Somvanshi, Mahendra Bijarnia, Ayan Das Gupta

Sample size determination in clinical trials

Randomization schedule using Proc Plan

Shirisha Sugavasi

Randomization schedule using Proc Plan

Do we really need high sample and power for BE studies

Chandrasekhar Bhupathi

Do we really need high sample and power for BE studies

SAS Grid - Simplified

Kumar Rajinder

SAS Grid - Simplified

Some Statistics on Palliative care in India

Sahana Prasad

Some Statistics on Palliative care in India

Dose Escalation Designs

Ramakrishna Battula, Paridhi Jain, Shital Pokharkar

Dose Escalation Designs

Star charts in SAS

Swapna Biradar

Star charts in SAS

Modelling efficacy and toxicity in Oncology dose-finding studies

Yajnaseni Chakraborti

Modelling efficacy and toxicity in Oncology dose-finding studies

Statistical Analysis of Neuroscience Data

Amruta

Statistical Analysis of Neuroscience Data

Bayesian predictive approach to interim monitoring in clinical trials

Ashwini Shenoy

Bayesian predictive approach to interim monitoring in clinical trials

The Uncommon Macro Debugging Techniques – A must to know for the Statistical Programmers

Vishal Kundan

The Uncommon Macro Debugging Techniques – A must to know for the Statistical Programmers

Two stage group sequential analysis

suman sarkar

Two stage group sequential analysis

XML And Webservices-A match made in SAS

Snehal Patange

XML And Webservices-A match made in SAS

Two Stage Multi-Arm Design

Soorma Das

Two Stage Multi-Arm Design

Seamless two stage adaptive design in clinical trials

Gordhan Bagri

Seamless two stage adaptive design in clinical trials

Phase II Clinical Trial Design Incorporating Toxicity Monitoring

Dr.Shesh Rai

Phase II Clinical Trial Design Incorporating Toxicity Monitoring

Two Sample Comparisons Involving Zero-Inflated Continuous Data - Parametric Approach and Recommendations

Dr. H. V. Kulkarni

Two Sample Comparisons Involving Zero-Inflated Continuous Data - Parametric Approach and Recommendations

Comorbidity as prognostic factor in clinical trials in patients with hematologic indication

Tuli De

Comorbidity as prognostic factor in clinical trials in patients with hematologic indication

Importance of Randomly selected blocks in Block Randomization

Meera Mohan

Importance of Randomly selected blocks in Block Randomization

A Spline Enhanced Population Pharmacokinetic Ordinal longitudinal Model subject to Informative Dropout

Dr.Arindom Chakraborty

A Spline Enhanced Population Pharmacokinetic Ordinal longitudinal Model subject to Informative Dropout

Covariate Selection in Model Building

Aditi Marathe, Garima Joshi

Covariate Selection in Model Building

Tipping point as a sensitivity analysis

Neha Pandey

Tipping point as a sensitivity analysis

Statistical Method for Identification of Biomarker Driven Subgroups

Chaitali Pisal

Statistical Method for Identification of Biomarker Driven Subgroups

Securing Privacy by Minimizing Disclosure Risk in De-identified Data

Debasis Dey

Securing Privacy by Minimizing Disclosure Risk in De-identified Data

Modeling Unstructured Covariance Matrix-When it works and when it doesn't

Hitendra Pandey

Modeling Unstructured Covariance Matrix-When it works and when it doesn't

Exploring the underlying distribution of PK parameters

Abhinandan Chakraborty

Exploring the underlying distribution of PK parameters

Different imputation methods use in Clinical Trials

Bristi Bose, Pankaj Tiwari

Different imputation methods use in Clinical Trials

Gate Keeping Strategies in Clinical Trials

Suresh Kumar Kothakonda

Gate Keeping Strategies in Clinical Trials

Different approaches for handling treatment switching for reporting in clinical studies

Ravinder Arakati

Different approaches for handling treatment switching for reporting in clinical studies

Use of Propensity Score Matching (PSM) in Non-interventional Study

Surbhi Vijay, Ashutosh Mishra, Prashant Kulkarni, Shyam B Tiwari

Use of Propensity Score Matching (PSM) in Non-interventional Study

A class of Covariate-Adjusted Response-Adaptive Allocation Designs for Multi-treatment Binary Response Trials

Dr.Atanu Biswas

A class of Covariate-Adjusted Response-Adaptive Allocation Designs for Multi-treatment Binary Response Trials

Analysis of Competing Risk Data with Masked Cause-of-Event

Ashok Kumar Singh

Analysis of Competing Risk Data with Masked Cause-of-Event

Modelling and Analysis of Recurrent Event Data

Rajan Sareen, Sonam Singh, Keerthana Palwai

Modelling and Analysis of Recurrent Event Data

Quality control and quality assurance in clinical trial workshop - Slides

Sakthivel Sivam and Renjana Prasannan

Quality control and quality assurance in clinical trial workshop - Slides

Workshop on Estimands

Angshuman Sarkar & Bharath Kumar

Workshop on Estimands

Study designs in Oncology and programming perspectives

Jagannatha P.S, P Gajendran, Veena Vincent, Jomy Jose, Sugunesh S

Study designs in Oncology and programming perspectives

Python Workshop

Dr. Vikram Pudi and Ashwin Venkat

Python Workshop

SAS solution to analyze competing risk in time to event data

ABHRAMOY MANDAL

SAS solution to analyze competing risk in time to event data

Adverse Events summary by Exposure Adjusted Incidence Rate (EAIR)

ADITYA MOVVA

Adverse Events summary by Exposure Adjusted Incidence Rate (EAIR)

Vital Role of Exposure Response Analysis in Drug Development

PRAVEEN REDDY ALETI

Vital Role of Exposure Response Analysis in Drug Development

RMST: an alternative way for the estimation of treatment effect

ANUBRATA KUNDU

RMST: an alternative way for the estimation of treatment effect

Personalized medicine at the age of RealWorld Evidence and AI

ARNAB GOSWAMI

Personalized medicine at the age of RealWorld Evidence and AI

Competing risks in survival analysis: An Oncology case study

ASHWIN ADRIAN KALLOR

Competing risks in survival analysis: An Oncology case study

Impact and Risk assessment of modification in ULN of ALT on Liver Safety Monitoring to inform National Health Authorities

ASHWINI SHENOY

Impact and Risk assessment of modification in ULN of ALT on Liver Safety Monitoring to inform National Health Authorities

Discrepancy Analysis of clinical data sets using Python

ASLAM BASHA SHAIK

Discrepancy Analysis of clinical data sets using Python

Archiving our deliverables when there is no version-controlled system

BASKARAN DHARMALINGAM

Archiving our deliverables when there is no version-controlled system

Framing estimands and handling missing data for multiple intercurrent events

BHARATH KUMAR

Framing estimands and handling missing data for multiple intercurrent events

Sensitivity analyses of time-to-event data using Pattern Mixture Model Approaches

CHAITHRA SHETTY

Sensitivity analyses of time-to-event data using Pattern Mixture Model Approaches

Master protocols

CHANDRAKANTH KAMLEKAR

Master protocols

PAINS AND GAINS IN SOFTWARE DEVELOPMENT - FROM POC TO MARKET

CHARAN KUMAR & RESHMA RAJPUT

PAINS AND GAINS IN SOFTWARE DEVELOPMENT - FROM POC TO MARKET

Risky RASCI of a SME in the programming world

CHARUMATHY SREERAMAN & DIVYA CETLUR

Risky RASCI of a SME in the programming world

Email Dashboard Using SAS and HTML

SANDEEP DANDOTHKAR

Email Dashboard Using SAS and HTML

Multiple Imputation

DAYASAGAR CHAUDHARY

Multiple Imputation

Cancer prediction: Random forest VS logistic classifie

DEBADRITA BANERJEE

Cancer prediction: Random forest VS logistic classifie

Operational Excellence using R Shiny

DEEPTHI BM

Operational Excellence using R Shiny

The Great Bounce Back!!!

DEVI GOPALAKRISHNAN

The Great Bounce Back!!!

Graphical Presentation of Data/ Results using R, for Oncology Trials

DHANANJAY SRIVASTAVA & DHEERAJ RANE

Graphical Presentation of Data/ Results using R, for Oncology Trials

‘Sync to Link’ ..Towards Adoption of Automation in Statistical Programming

DR.SANGRAM PARBHANE

‘Sync to Link’ ..Towards Adoption of Automation in Statistical Programming

Electronic Diary (E-Diary) – A SAS®sy advent to optimize Questionnaires

HARISH GOPALARATHNAM

Electronic Diary (E-Diary) – A SAS®sy advent to optimize Questionnaires

Basic Result Disclosure Report in one click

HARISH KUMAR

Basic Result Disclosure Report in one click

DON’T BE REL-wRECked!!

HARITHA VARANASI

DON’T BE REL-wRECked!!

Multiple Studies BIMO Submission Package - A Programmer's Perspectivee

HARSHA HANDIGODU DYAVAPPA

Multiple Studies BIMO Submission Package - A Programmer's Perspectivee

Information Value – A way to select good predictors in Big Data Modeling

HIMANSHU SEKHAR PRADHAN & ABHEENAVA KUMAR

Information Value – A way to select good predictors in Big Data Modeling

BIMO- FDA’s eye on Site Compliance

JASMIN JOBANPUTRA & SHREETAM SHEREGAR

BIMO- FDA’s eye on Site Compliance

Association Patterns within Adverse Events and other Domains in Clinical Trials using Data Mining Techniques

JASMINE KHURANA & NAEEM SHAIKH

Association Patterns within Adverse Events and other Domains in Clinical Trials using Data Mining Techniques

4 things I wish I knew when I was starting out as a Statistical Programmer

JEFFY SARTO

4 things I wish I knew when I was starting out as a Statistical Programmer

Simplifying Clinical Trial Disclosure Through Automation

CHANDRIMA PAL, JENY R & SWATHI S S

Simplifying Clinical Trial Disclosure Through Automation

Programmer’s perspective: LEANing TFL shells

JITENDRA SINGH

Programmer’s perspective: LEANing TFL shells

R-Shiny Dashboards

JOHN THOMAS JOHNSON

R-Shiny Dashboards

What functions are in your future?

JOHNSON DSOUZA

What functions are in your future?

Correlate of Protection – Introduction and challenge Prentice Criteria

JYOTI SONI

Correlate of Protection – Introduction and challenge Prentice Criteria

RE-SCREENED SUBJECT? WE ARE READY FOR YOU!

KALPESH VALAKI

RE-SCREENED SUBJECT? WE ARE READY FOR YOU!

NONMEM PK Programmers Bird View

KIRAN H & KPS BHARATH KUMAR

NONMEM PK Programmers Bird View

Population Enrichment Design

KIRAN WADJE

Population Enrichment Design

How sysinfo can save your time, it’s all about automation, quality!!

KIRANMAI BYRICHETTI

How sysinfo can save your time, it’s all about automation, quality!!

Pinnacle 21 report Why GUI when you can automate!!

KIRUTHIKA BALASUBRAMANIAN

Pinnacle 21 report Why GUI when you can automate!!

Making workday easier through Technolog

LUCKY SINGH

Making workday easier through Technolog

Study Level Codelist Now#here (or) No#where ?

M CHANUKYA SAMRAT, RANJAN ROUTRAY & AJAY SINHA

Study Level Codelist Now#here (or) No#where ?

Different Approaches - BIMO Site Level Settings

MANEESHA UNNIKRISHNA & UMAYAL ANNAMALAI

Different Approaches - BIMO Site Level Settings

Traceability

MARSHAL CHETTIAR

Traceability

Sample Size Estimation with Covariate Adjustment

MEENAKSHI MAHANTA

Sample Size Estimation with Covariate Adjustment

Subject level data using Python ~ Building the ADSL.Py~

MOULI & KARTHIK & JAYASHREE

Subject level data using Python ~ Building the ADSL.Py~

MACROS TRIO IN SAS: DATASET COMPARISON AND REPORTING

NAGARAJU MANCHA

MACROS TRIO IN SAS: DATASET COMPARISON AND REPORTING

Overview of standardization and analysis of medical devices data into CDISC standards

NAVEEN PAL ARUMUGAM

Overview of standardization and analysis of medical devices data into CDISC standards

Clinical Trials for Medical Devices – How do they play in SDTM ?

NEELIMA SAMA

Clinical Trials for Medical Devices – How do they play in SDTM ?

Suspect in Anticipated Aspect

NEHA GAHALOT

Suspect in Anticipated Aspect

Tricky sorting's in sas - LINGUISTIC

NEHA SAXENA

Tricky sorting's in sas - LINGUISTIC

LEVERAGE PROCESS MAPS Raising the bar of automation to its highest possible extent

NIKHIL UPADHYAY

LEVERAGE PROCESS MAPS Raising the bar of automation to its highest possible extent

Can a Programmer be a Statistician???

NIRAV MISTRY

Can a Programmer be a Statistician???

DOMAIN ANALYSIS MODEL

OBULPATHI NAIDU

DOMAIN ANALYSIS MODEL

Exploratory Analysis & Data Visualization of Clinical Trial Outcomes using R

PADMA A & ARCHANA P

Exploratory Analysis & Data Visualization of Clinical Trial Outcomes using R

Data Standards and Observational Studies

PAYAL SHAH

Data Standards and Observational Studies

OVERVIEW OF CDISC-SEND

E P PIRAISOODAN

OVERVIEW OF CDISC-SEND

Futility Analysis using the concept of Predictive Probability of Success(PPoS)

PRATEEK GARG & MRIGANK JAIN

Futility Analysis using the concept of Predictive Probability of Success(PPoS)

Usefulness of Predictive Probability assessment in a Phase 2 clinical trial set u

PREENAN SARKAR

Usefulness of Predictive Probability assessment in a Phase 2 clinical trial set u

Legacy studies & MedDRA version update

PRERANA JAIN

Legacy studies & MedDRA version update

An application of joint frailtylogistic model to investigate the association between rate and severity of exacerbations in COPD

DR. PRITAM GUPTA

An application of joint frailtylogistic model to investigate the association between rate and severity of exacerbations in COPD

Sailing with LOINC & iRECIST

PRIYESH SURA

Sailing with LOINC & iRECIST

SOFA SCORE AS PRIMARY ENDPOINT IN A SEPSIS STUDY

PURNENDU CHAKRABORTY & AMRITA NANDY

SOFA SCORE AS PRIMARY ENDPOINT IN A SEPSIS STUDY

Findings About Custom “Findings About” and FA Representation

RAGHAVA REGULLA

Findings About Custom “Findings About” and FA Representation

One Macro to Produce Descriptive Statistic Summary Tables with P-Values

RAJARAM VENKATESAN

One Macro to Produce Descriptive Statistic Summary Tables with P-Values

Implementation of Data Cut Off in Interim Analysis of Clinical Trials

RAJITHA P

Implementation of Data Cut Off in Interim Analysis of Clinical Trials

Shared Frailty Model under the Bayesian Mechanism

RAJNEESH SINGH

Shared Frailty Model under the Bayesian Mechanism

Nuclear Medicine

RAKESH KUMAR

Nuclear Medicine

ECOG Performance Status

RAM REDDY KANTHALA

ECOG Performance Status

Immunogenicity Cut-point Evaluations

RAMKUMAR M.RAJENDIRAN

Immunogenicity Cut-point Evaluations

Pinnacle21 - Make it more robust and effective!!

RANJAN ROUTRAY & M CHANUKYA SAMRAT & AJAY SINHA

Pinnacle21 - Make it more robust and effective!!

Visualization for Project management to Trial Management

RAVI GUPTA

Visualization for Project management to Trial Management

A story about how a trial starts (for a statistician)

RISHAV MUKHERJEE

A story about how a trial starts (for a statistician)

Analysis of HMIS data with standard software tools to generate insightful empirical evidence of Ayurveda practice in a University hospital

SADANAND DESHMUKH

Analysis of HMIS data with standard software tools to generate insightful empirical evidence of Ayurveda practice in a University hospital

STRATEGIES AND CHALLENGES IN PK/PD PROGRAMMING

SAIRA KONAR

STRATEGIES AND CHALLENGES IN PK/PD PROGRAMMING

No Mess!!! No Fuss!!! Hassle free Deliverable with “SWIGGY” !!

SAISURAJ SRINIVASAN

No Mess!!! No Fuss!!! Hassle free Deliverable with “SWIGGY” !!

Tips to improve TLFs SAS programming

SANGEETHA SATHAIAH

Tips to improve TLFs SAS programming

Big Data = Big Challenge to Data Integrity!

SANTANU KUMAR MOHANTY

Big Data = Big Challenge to Data Integrity!

Learning Eligibility in Cancer Clinical Trials Using Deep Neural Networks

SHANTANU NAGPAL

Learning Eligibility in Cancer Clinical Trials Using Deep Neural Networks

ENCODING, TRANSCODING with UTF-8

SHIKHA SRESHTHA

ENCODING, TRANSCODING with UTF-8

The Changing L&Dscape of Skill Building

SHIKSHA PATHAK

The Changing L&Dscape of Skill Building

Estimation of Sample Size in Immunogenicity Trial

SHIRSENDU SARKAR

Estimation of Sample Size in Immunogenicity Trial

Diagnosis of Diabetes using Support Vector Machines

SOUMITRA KAR

Diagnosis of Diabetes using Support Vector Machines

Data Anonymization – Need & Challenges

SRIDHAR. P & PRIYA. G

Data Anonymization – Need & Challenges

Significance of Early Development trials in Drug Development

SRIKANTH NEELAKANTHAM

Significance of Early Development trials in Drug Development

RTOR Fast-Track Approval

SRINIVAS KOLAMURI

RTOR Fast-Track Approval

Do you contemplate Visual Programming? A Python Library will rescue

SUDHARSAN DHANAVEL

Do you contemplate Visual Programming? A Python Library will rescue

Basket and Umbrella in Oncology Trials

SUGUNESH SIVALINGAM

Basket and Umbrella in Oncology Trials

Plots in Oncology Studies

SUMIT PRATAP PRADHAN & NIMIT AGRAWAL

Plots in Oncology Studies

STANDARDIZATION OF BIOMARKER TO CDISC STANDARDS

SURESH

STANDARDIZATION OF BIOMARKER TO CDISC STANDARDS

Sample Size Determination with Multiple Co-Primary Endpoints in Clinical Trials

TUSHAR NIKUMBH & RAJENDRA DESAI

Sample Size Determination with Multiple Co-Primary Endpoints in Clinical Trials

Weighting in survey data, introduction to why and how

USHA K THAMATTOOR

Weighting in survey data, introduction to why and how

The Future of SDTM Mapping

VASANTH & JEY

The Future of SDTM Mapping

Clinical SAS Programming by Automapper

VIGNESH KUMAR B

Clinical SAS Programming by Automapper

ERROR: A lock is not available for YYYXX.DATA - No Worries!! You can still update and continue your Job.

VIJAY DHARMARAJ. A

ERROR: A lock is not available for YYYXX.DATA - No Worries!! You can still update and continue your Job.

Immunogenicity in Oncology Studies – A Programmer’s View

VIJAY RAGHAVENDRA

Immunogenicity in Oncology Studies – A Programmer’s View

Utility of parallel processing in clinical SAS

VINAYAMANI MENNENI

Utility of parallel processing in clinical SAS

Automation of Analysis Data Reviewer’s Guide(ADRG) through R language

VINODHKUMAR KATIKALA

Automation of Analysis Data Reviewer’s Guide(ADRG) through R language

CLINICAL DATA SECURITY AUGMENTATION – STEGANOGRAPHY

VINOTHKUMAR SUBRAMANI & RADHIKA MOHAN MADAVILAKAM

CLINICAL DATA SECURITY AUGMENTATION – STEGANOGRAPHY

PMDA e-submissions - Expectations & Experiences

Takashi Kitahara

PMDA e-submissions - Expectations & Experiences

R for Clinical Trial Data Analysis

DEEPAYAN SARKAR

R for Clinical Trial Data Analysis