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Creating TFL shells document - Programmer's perspective ... Is it Easy... ??

Conspic 2023 - Day 3

Creating TFL shells document - Programmer's perspective ... Is it Easy... ??

Lab Toxicity Grading – No more Worries on Complex Derivations!!! An Automated Solution which makes IT SIMPLE!

Conspic 2023 - Day 3

Lab Toxicity Grading – No more Worries on Complex Derivations!!! An Automated Solution which makes IT SIMPLE!

Breaking Down Barriers: Strategies for Handling Bidirectional Lab Parameters Data

Conspic 2023 - Day 3

Breaking Down Barriers: Strategies for Handling Bidirectional Lab Parameters Data

Implementation of DHT in Clinical Trials

Conspic 2023 - Day 3

Implementation of DHT in Clinical Trials

From Chaos to Clarity: Standardizing Pediatric Data

Conspic 2023 - Day 3

From Chaos to Clarity: Standardizing Pediatric Data

Synergy of SAS to Python

Conspic 2023 - Day 3

Synergy of SAS to Python

Automating Custom Report Creation in SAS Viya

Conspic 2023 - Day 3

Automating Custom Report Creation in SAS Viya

A practical Approach to handle rescreening

Conspic 2023 - Day 3

A practical Approach to handle rescreening

Different types of tests to check Independence of Categorical Variables: A PROC FREQ method use cases

Conspic 2023 - Day 3

Different types of tests to check Independence of Categorical Variables: A PROC FREQ method use cases

Complications in collection of PGx data and problems in mapping to SDTM

Conspic 2023 - Day 3

Complications in collection of PGx data and problems in mapping to SDTM

Win-Ratio & FS-Pair Algorithm: An intuitive approach to compare the Composite Endpoints in Clinical Research

Conspic 2023 - Day 3

Win-Ratio & FS-Pair Algorithm: An intuitive approach to compare the Composite Endpoints in Clinical Research

Handling Re-screened Subjects in SDTM & ADaM

Conspic 2023 - Day 3

Handling Re-screened Subjects in SDTM & ADaM

SAS welcomes R aboard

Conspic 2023 - Day 3

SAS welcomes R aboard

Juliet to your Romeo ?! May be … Associated Person…

Conspic 2023 - Day 3

Juliet to your Romeo ?! May be … Associated Person…

An Overview on synergies of coupling Real-time monitoring and Predictive analytics.

Conspic 2023 - Day 3

An Overview on synergies of coupling Real-time monitoring and Predictive analytics.

NLP - Custom Document based Q&A Modelling

Conspic 2023 - Day 3

NLP - Custom Document based Q&A Modelling

Text Similarity Models for Clinical Data – from BERT to ChatGPT

Conspic 2023 - Day 3

Text Similarity Models for Clinical Data – from BERT to ChatGPT

ISS / ISE - Significance, Implementation and Challenges

Conspic 2023 - Day 2

ISS / ISE - Significance, Implementation and Challenges

Data Manipulation in R comparing different packages (dplyr, data.table and sqldf)

Conspic 2023 - Day 2

Data Manipulation in R comparing different packages (dplyr, data.table and sqldf)

Evaluation of Seasonal data using the area chart

Conspic 2023 - Day 2

Evaluation of Seasonal data using the area chart

Exploring Perl Regular Expressions in SAS

Conspic 2023 - Day 2

Exploring Perl Regular Expressions in SAS

A Case Study of Implementation SDTM for Medical Device

Conspic 2023 - Day 2

A Case Study of Implementation SDTM for Medical Device

Significant Digit

Conspic 2023 - Day 2

Significant Digit

Developing functions in admiral - A Core Developer’s perspective

Conspic 2023 - Day 2

Developing functions in admiral - A Core Developer’s perspective

How to Create SDTM VS Dataset using SAS and Python step by steps

Conspic 2023 - Day 2

How to Create SDTM VS Dataset using SAS and Python step by steps

MCMC-MI: An Overview

Conspic 2023 - Day 2

MCMC-MI: An Overview

Macros in R ?

Conspic 2023 - Day 2

Macros in R ?

Visualization of evaluation in Drug-Induced Serious Hepatotoxicity

Conspic 2023 - Day 2

Visualization of evaluation in Drug-Induced Serious Hepatotoxicity

Accelerated Submissions including Rolling review and RWE studies – A Paradigm Shift

Conspic 2023 - Day 2

Accelerated Submissions including Rolling review and RWE studies – A Paradigm Shift

An Bring up to date on CDISC-SEND Data Submissions to FDA

Conspic 2023 - Day 2

An Bring up to date on CDISC-SEND Data Submissions to FDA

Breaking down a great debate of New Tools & Technologies vs SAS - Clarifications out of confusions

Conspic 2023 - Day 2

Breaking down a great debate of New Tools & Technologies vs SAS - Clarifications out of confusions

Clinical Data Visualization with Plotly (Python)

Conspic 2023 - Day 2

Clinical Data Visualization with Plotly (Python)

Real-World Evidence (RWE) in Clinical Research: Benefits, Challenges, and Strategies for Success

Conspic 2023 - Day 2

Real-World Evidence (RWE) in Clinical Research: Benefits, Challenges, and Strategies for Success

SDTM SME: The Key to Effective Submission Package Review

Conspic 2023 - Day 2

SDTM SME: The Key to Effective Submission Package Review

Linpk R-package: A time savior for Pharmacokinetic (PK) Data Programmers

Conspic 2023 - Day 2

Linpk R-package: A time savior for Pharmacokinetic (PK) Data Programmers

Unleashing the Power of R For Enhancing Team Cohesion

Conspic 2023 - Day 2

Unleashing the Power of R For Enhancing Team Cohesion

Proc Transpose data =professional out=Leader

Conspic 2023 - Day 2

Proc Transpose data =professional out=Leader

The next Quality Culture: Look at Quality- Compliance will follow, for sure!!

Conspic 2023 - Day 2

The next Quality Culture: Look at Quality- Compliance will follow, for sure!!

An agile transformation as a rescue method for successful completion of a clinical trial!!!

Conspic 2023 - Day 2

An agile transformation as a rescue method for successful completion of a clinical trial!!!

Industry 4.0: Indispensable new age skills that makes you ready for future.

Conspic 2023 - Day 2

Industry 4.0: Indispensable new age skills that makes you ready for future.

Employee Branding - Cherished Connect

Conspic 2023 - Day 2

Employee Branding - Cherished Connect

Simplification of results for Registries (CTg & EudraCT)

Conspic 2023 - Day 1

Simplification of results for Registries (CTg & EudraCT)

Evaluating Clinical Events as Annualized Event Rate to Measure Therapeutic Effect

Conspic 2023 - Day 1

Evaluating Clinical Events as Annualized Event Rate to Measure Therapeutic Effect

Tips on ADaM Standards

Conspic 2023 - Day 1

Tips on ADaM Standards

Are you still monotonous with BIMO submission??? Here are the AGILE ways to explore/accomplish…

Conspic 2023 - Day 1

Are you still monotonous with BIMO submission??? Here are the AGILE ways to explore/accomplish…

Impact of COVID-19 on SDTMs

Conspic 2023 - Day 1

Impact of COVID-19 on SDTMs

Statistical Programmer’s Endurance Guide for FDA

Conspic 2023 - Day 1

Statistical Programmer’s Endurance Guide for FDA

Biomarker analysis in clinical trials

Conspic 2023 - Day 1

Biomarker analysis in clinical trials

ADaM Implementation Guide for Medical Devices

Conspic 2023 - Day 1

ADaM Implementation Guide for Medical Devices

Dynamic Approach of Reviewer’s Guide for Integrated Studies

Conspic 2023 - Day 1

Dynamic Approach of Reviewer’s Guide for Integrated Studies

Amazing way to use NLP to tag source of P21 data Issues.

Conspic 2023 - Day 1

Amazing way to use NLP to tag source of P21 data Issues.

P21 Validation Notes: Explain or Fix ?

Conspic 2023 - Day 1

P21 Validation Notes: Explain or Fix ?

Looking at data to see what it seems to say EDA

Conspic 2023 - Day 1

Looking at data to see what it seems to say EDA

NLP-assisted SAP-to-TLF Automation

Conspic 2023 - Day 1

NLP-assisted SAP-to-TLF Automation

Accessible Healthcare Information through Large Language Models: An Automated Plain Language Summary Generator

Conspic 2023 - Day 1

Accessible Healthcare Information through Large Language Models: An Automated Plain Language Summary Generator

AI in Clinical Reporting

Conspic 2023 - Day 1

AI in Clinical Reporting

Topological Clinical Data Analysis - Exploring the hidden wonders of data geometry!

Conspic 2023 - Day 1

Topological Clinical Data Analysis - Exploring the hidden wonders of data geometry!

PROPENSITY SCORE-INTEGRATED APPROACH FOR LEVERAGING OF EXTERNAL DATA

Conspic 2023 - Day 1

PROPENSITY SCORE-INTEGRATED APPROACH FOR LEVERAGING OF EXTERNAL DATA

Sensitivity Analysis using Tipping Point Approach

Conspic 2023 - Day 1

Sensitivity Analysis using Tipping Point Approach

A Comparative Study of Fallback and Pocock Methods

Conspic 2023 - Day 1

A Comparative Study of Fallback and Pocock Methods

Statistical approach to Implement Individual Bioequivalence (IBE) in a 2x2 crossover design study

Conspic 2023 - Day 1

Statistical approach to Implement Individual Bioequivalence (IBE) in a 2x2 crossover design study

A Case Study of Assurance Calculation in Bayesian Dynamic Borrowing Design

Conspic 2023 - Day 1

A Case Study of Assurance Calculation in Bayesian Dynamic Borrowing Design

Inference under covariate adaptive randomization: A simulation study

Conspic 2023 - Day 1

Inference under covariate adaptive randomization: A simulation study

Advancements in R for evaluating penalized Cox regression models on high-dimensional survival data: A contemporary review

Conspic 2023 - Day 1

Advancements in R for evaluating penalized Cox regression models on high-dimensional survival data: A contemporary review

Inference under covariate-adaptive randomization: accounting for centre effects

Conspic 2023 - Day 1

Inference under covariate-adaptive randomization: accounting for centre effects

Analysis of composite endpoints using generalized Win-ratio based approach

Conspic 2023 - Day 1

Analysis of composite endpoints using generalized Win-ratio based approach

Mastering Regulatory Submission: Best Practices and Compliance

Regulatory Workshop

Mastering Regulatory Submission: Best Practices and Compliance

R for Clinical Trial Data Analysis

DEEPAYAN SARKAR

R for Clinical Trial Data Analysis

PMDA e-submissions - Expectations & Experiences

Takashi Kitahara

PMDA e-submissions - Expectations & Experiences

CLINICAL DATA SECURITY AUGMENTATION – STEGANOGRAPHY

VINOTHKUMAR SUBRAMANI & RADHIKA MOHAN MADAVILAKAM

CLINICAL DATA SECURITY AUGMENTATION – STEGANOGRAPHY

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

VINODHKUMAR KATIKALA

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

Utility of parallel processing in clinical SAS

VINAYAMANI MENNENI

Utility of parallel processing in clinical SAS

Immunogenicity in Oncology Studies – A Programmer’s View

VIJAY RAGHAVENDRA

Immunogenicity in Oncology Studies – A Programmer’s View

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.

Clinical SAS Programming by Automapper

VIGNESH KUMAR B

Clinical SAS Programming by Automapper

The Future of SDTM Mapping

VASANTH & JEY

The Future of SDTM Mapping

Weighting in survey data, introduction to why and how

USHA K THAMATTOOR

Weighting in survey data, introduction to why and how

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

STANDARDIZATION OF BIOMARKER TO CDISC STANDARDS

SURESH

STANDARDIZATION OF BIOMARKER TO CDISC STANDARDS

Plots in Oncology Studies

SUMIT PRATAP PRADHAN & NIMIT AGRAWAL

Plots in Oncology Studies

Basket and Umbrella in Oncology Trials

SUGUNESH SIVALINGAM

Basket and Umbrella in Oncology Trials

Do you contemplate Visual Programming? A Python Library will rescue

SUDHARSAN DHANAVEL

Do you contemplate Visual Programming? A Python Library will rescue

RTOR Fast-Track Approval

SRINIVAS KOLAMURI

RTOR Fast-Track Approval

Significance of Early Development trials in Drug Development

SRIKANTH NEELAKANTHAM

Significance of Early Development trials in Drug Development

Data Anonymization – Need & Challenges

SRIDHAR. P & PRIYA. G

Data Anonymization – Need & Challenges

Diagnosis of Diabetes using Support Vector Machines

SOUMITRA KAR

Diagnosis of Diabetes using Support Vector Machines

Estimation of Sample Size in Immunogenicity Trial

SHIRSENDU SARKAR

Estimation of Sample Size in Immunogenicity Trial

The Changing L&Dscape of Skill Building

SHIKSHA PATHAK

The Changing L&Dscape of Skill Building

ENCODING, TRANSCODING with UTF-8

SHIKHA SRESHTHA

ENCODING, TRANSCODING with UTF-8

Learning Eligibility in Cancer Clinical Trials Using Deep Neural Networks

SHANTANU NAGPAL

Learning Eligibility in Cancer Clinical Trials Using Deep Neural Networks

Big Data = Big Challenge to Data Integrity!

SANTANU KUMAR MOHANTY

Big Data = Big Challenge to Data Integrity!

Tips to improve TLFs SAS programming

SANGEETHA SATHAIAH

Tips to improve TLFs SAS programming

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

SAISURAJ SRINIVASAN

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

STRATEGIES AND CHALLENGES IN PK/PD PROGRAMMING

SAIRA KONAR

STRATEGIES AND CHALLENGES IN PK/PD PROGRAMMING

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

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

RISHAV MUKHERJEE

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

Visualization for Project management to Trial Management

RAVI GUPTA

Visualization for Project management to Trial Management

Pinnacle21 - Make it more robust and effective!!

RANJAN ROUTRAY & M CHANUKYA SAMRAT & AJAY SINHA

Pinnacle21 - Make it more robust and effective!!

Immunogenicity Cut-point Evaluations

RAMKUMAR M.RAJENDIRAN

Immunogenicity Cut-point Evaluations

ECOG Performance Status

RAM REDDY KANTHALA

ECOG Performance Status

Nuclear Medicine

RAKESH KUMAR

Nuclear Medicine

Shared Frailty Model under the Bayesian Mechanism

RAJNEESH SINGH

Shared Frailty Model under the Bayesian Mechanism

Implementation of Data Cut Off in Interim Analysis of Clinical Trials

RAJITHA P

Implementation of Data Cut Off in Interim Analysis of Clinical Trials

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

RAJARAM VENKATESAN

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

Findings About Custom “Findings About” and FA Representation

RAGHAVA REGULLA

Findings About Custom “Findings About” and FA Representation

SOFA SCORE AS PRIMARY ENDPOINT IN A SEPSIS STUDY

PURNENDU CHAKRABORTY & AMRITA NANDY

SOFA SCORE AS PRIMARY ENDPOINT IN A SEPSIS STUDY

Sailing with LOINC & iRECIST

PRIYESH SURA

Sailing with LOINC & iRECIST

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

Legacy studies & MedDRA version update

PRERANA JAIN

Legacy studies & MedDRA version update

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

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)

OVERVIEW OF CDISC-SEND

E P PIRAISOODAN

OVERVIEW OF CDISC-SEND

Data Standards and Observational Studies

PAYAL SHAH

Data Standards and Observational Studies

Exploratory Analysis & Data Visualization of Clinical Trial Outcomes using R

PADMA A & ARCHANA P

Exploratory Analysis & Data Visualization of Clinical Trial Outcomes using R

DOMAIN ANALYSIS MODEL

OBULPATHI NAIDU

DOMAIN ANALYSIS MODEL

Can a Programmer be a Statistician???

NIRAV MISTRY

Can a Programmer be a Statistician???

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

Tricky sorting's in sas - LINGUISTIC

NEHA SAXENA

Tricky sorting's in sas - LINGUISTIC

Suspect in Anticipated Aspect

NEHA GAHALOT

Suspect in Anticipated Aspect

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

NEELIMA SAMA

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

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

MACROS TRIO IN SAS: DATASET COMPARISON AND REPORTING

NAGARAJU MANCHA

MACROS TRIO IN SAS: DATASET COMPARISON AND REPORTING

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

MOULI & KARTHIK & JAYASHREE

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

Sample Size Estimation with Covariate Adjustment

MEENAKSHI MAHANTA

Sample Size Estimation with Covariate Adjustment

Traceability

MARSHAL CHETTIAR

Traceability

Different Approaches - BIMO Site Level Settings

MANEESHA UNNIKRISHNA & UMAYAL ANNAMALAI

Different Approaches - BIMO Site Level Settings

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

M CHANUKYA SAMRAT, RANJAN ROUTRAY & AJAY SINHA

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

Making workday easier through Technolog

LUCKY SINGH

Making workday easier through Technolog

Pinnacle 21 report Why GUI when you can automate!!

KIRUTHIKA BALASUBRAMANIAN

Pinnacle 21 report Why GUI when you can automate!!

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!!

Population Enrichment Design

KIRAN WADJE

Population Enrichment Design

NONMEM PK Programmers Bird View

KIRAN H & KPS BHARATH KUMAR

NONMEM PK Programmers Bird View

RE-SCREENED SUBJECT? WE ARE READY FOR YOU!

KALPESH VALAKI

RE-SCREENED SUBJECT? WE ARE READY FOR YOU!

Correlate of Protection – Introduction and challenge Prentice Criteria

JYOTI SONI

Correlate of Protection – Introduction and challenge Prentice Criteria

What functions are in your future?

JOHNSON DSOUZA

What functions are in your future?

R-Shiny Dashboards

JOHN THOMAS JOHNSON

R-Shiny Dashboards

Programmer’s perspective: LEANing TFL shells

JITENDRA SINGH

Programmer’s perspective: LEANing TFL shells

Simplifying Clinical Trial Disclosure Through Automation

CHANDRIMA PAL, JENY R & SWATHI S S

Simplifying Clinical Trial Disclosure Through Automation

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

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

BIMO- FDA’s eye on Site Compliance

JASMIN JOBANPUTRA & SHREETAM SHEREGAR

BIMO- FDA’s eye on Site Compliance

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

Multiple Studies BIMO Submission Package - A Programmer's Perspectivee

HARSHA HANDIGODU DYAVAPPA

Multiple Studies BIMO Submission Package - A Programmer's Perspectivee

DON’T BE REL-wRECked!!

HARITHA VARANASI

DON’T BE REL-wRECked!!

Basic Result Disclosure Report in one click

HARISH KUMAR

Basic Result Disclosure Report in one click

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

HARISH GOPALARATHNAM

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

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

DR.SANGRAM PARBHANE

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

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

DHANANJAY SRIVASTAVA & DHEERAJ RANE

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

The Great Bounce Back!!!

DEVI GOPALAKRISHNAN

The Great Bounce Back!!!

Operational Excellence using R Shiny

DEEPTHI BM

Operational Excellence using R Shiny

Cancer prediction: Random forest VS logistic classifie

DEBADRITA BANERJEE

Cancer prediction: Random forest VS logistic classifie

Multiple Imputation

DAYASAGAR CHAUDHARY

Multiple Imputation

Email Dashboard Using SAS and HTML

SANDEEP DANDOTHKAR

Email Dashboard Using SAS and HTML

Risky RASCI of a SME in the programming world

CHARUMATHY SREERAMAN & DIVYA CETLUR

Risky RASCI of a SME in the programming world

PAINS AND GAINS IN SOFTWARE DEVELOPMENT - FROM POC TO MARKET

CHARAN KUMAR & RESHMA RAJPUT

PAINS AND GAINS IN SOFTWARE DEVELOPMENT - FROM POC TO MARKET

Master protocols

CHANDRAKANTH KAMLEKAR

Master protocols

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

Framing estimands and handling missing data for multiple intercurrent events

BHARATH KUMAR

Framing estimands and handling missing data for multiple intercurrent events

Archiving our deliverables when there is no version-controlled system

BASKARAN DHARMALINGAM

Archiving our deliverables when there is no version-controlled system

Discrepancy Analysis of clinical data sets using Python

ASLAM BASHA SHAIK

Discrepancy Analysis of clinical data sets using Python

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

Competing risks in survival analysis: An Oncology case study

ASHWIN ADRIAN KALLOR

Competing risks in survival analysis: An Oncology case study

Personalized medicine at the age of RealWorld Evidence and AI

ARNAB GOSWAMI

Personalized medicine at the age of RealWorld Evidence and AI

RMST: an alternative way for the estimation of treatment effect

ANUBRATA KUNDU

RMST: an alternative way for the estimation of treatment effect

Vital Role of Exposure Response Analysis in Drug Development

PRAVEEN REDDY ALETI

Vital Role of Exposure Response Analysis in Drug Development

Adverse Events summary by Exposure Adjusted Incidence Rate (EAIR)

ADITYA MOVVA

Adverse Events summary by Exposure Adjusted Incidence Rate (EAIR)

SAS solution to analyze competing risk in time to event data

ABHRAMOY MANDAL

SAS solution to analyze competing risk in time to event data

Python Workshop

Dr. Vikram Pudi and Ashwin Venkat

Python Workshop

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

Workshop on Estimands

Angshuman Sarkar & Bharath Kumar

Workshop on Estimands

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

Modelling and Analysis of Recurrent Event Data

Rajan Sareen, Sonam Singh, Keerthana Palwai

Modelling and Analysis of Recurrent Event Data

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

Ashok Kumar Singh

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

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

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

Different approaches for handling treatment switching for reporting in clinical studies

Ravinder Arakati

Different approaches for handling treatment switching for reporting in clinical studies

Gate Keeping Strategies in Clinical Trials

Suresh Kumar Kothakonda

Gate Keeping Strategies in Clinical Trials

Different imputation methods use in Clinical Trials

Bristi Bose, Pankaj Tiwari

Different imputation methods use in Clinical Trials

Exploring the underlying distribution of PK parameters

Abhinandan Chakraborty

Exploring the underlying distribution of PK parameters

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

Securing Privacy by Minimizing Disclosure Risk in De-identified Data

Debasis Dey

Securing Privacy by Minimizing Disclosure Risk in De-identified Data

Statistical Method for Identification of Biomarker Driven Subgroups

Chaitali Pisal

Statistical Method for Identification of Biomarker Driven Subgroups

Tipping point as a sensitivity analysis

Neha Pandey

Tipping point as a sensitivity analysis

Covariate Selection in Model Building

Aditi Marathe, Garima Joshi

Covariate Selection in Model Building

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

Importance of Randomly selected blocks in Block Randomization

Meera Mohan

Importance of Randomly selected blocks in Block Randomization

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

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

Phase II Clinical Trial Design Incorporating Toxicity Monitoring

Dr.Shesh Rai

Phase II Clinical Trial Design Incorporating Toxicity Monitoring

Seamless two stage adaptive design in clinical trials

Gordhan Bagri

Seamless two stage adaptive design in clinical trials

Two Stage Multi-Arm Design

Soorma Das

Two Stage Multi-Arm Design

XML And Webservices-A match made in SAS

Snehal Patange

XML And Webservices-A match made in SAS

Two stage group sequential analysis

suman sarkar

Two stage group sequential analysis

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

Bayesian predictive approach to interim monitoring in clinical trials

Ashwini Shenoy

Bayesian predictive approach to interim monitoring in clinical trials

Statistical Analysis of Neuroscience Data

Amruta

Statistical Analysis of Neuroscience Data

Modelling efficacy and toxicity in Oncology dose-finding studies

Yajnaseni Chakraborti

Modelling efficacy and toxicity in Oncology dose-finding studies

Star charts in SAS

Swapna Biradar

Star charts in SAS

Dose Escalation Designs

Ramakrishna Battula, Paridhi Jain, Shital Pokharkar

Dose Escalation Designs

Some Statistics on Palliative care in India

Sahana Prasad

Some Statistics on Palliative care in India

SAS Grid - Simplified

Kumar Rajinder

SAS Grid - Simplified

Do we really need high sample and power for BE studies

Chandrasekhar Bhupathi

Do we really need high sample and power for BE studies

Randomization schedule using Proc Plan

Shirisha Sugavasi

Randomization schedule using Proc Plan

Sample size determination in clinical trials

Suryakant Somvanshi, Mahendra Bijarnia, Ayan Das Gupta

Sample size determination in clinical trials

Proc GLIMMIX

Priya Govindswamy

Proc GLIMMIX

Beta regression models for analyzing QOL data in Acromegaly

Pritam Gupta

Beta regression models for analyzing QOL data in Acromegaly

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

Overview of Class III Device trials

Ganesh L

Overview of Class III Device trials

MEDICAL DEVICE - DO YOU KNOW

Shailesh Gupte

MEDICAL DEVICE - DO YOU KNOW

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

Managing Textual information dynamically in a Graph using Proc Template

Devender Sandhi

Managing Textual information dynamically in a Graph using Proc Template

Latent class analysis using proc LCA

Anitha Cecelia

Latent class analysis using proc LCA

Let graphs speak using r

vura k pallayya guptha

Let graphs speak using r

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

Sreekumaran Nair

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

Lasagna Plot

Avinash gupta, Pritam gupta

Lasagna Plot

KMplot Macro-to generate enhanced Kaplan-Meier plots

Poorna devi Ch

KMplot Macro-to generate enhanced Kaplan-Meier plots

Incidence Rate

Vaishali Marathe, Yogesh Jagtap

Incidence Rate

Identifying and Reviewing Outliers using Statistical methods

Manjinder Dalam

Identifying and Reviewing Outliers using Statistical methods

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

GTL - Customizing graphs made easy

Mahesh, Ranjan, Shoba, YellaReddy

GTL - Customizing graphs made easy

Enhanced Pinnacle 21 Reports using SAS

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

Enhanced Pinnacle 21 Reports using SAS

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

Working with define.xml V2.0 in SDTM environment

Vijay Reddy

Working with define.xml V2.0 in SDTM environment

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

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

Generalized Poisson Regression Model with an Application to Malnutrition Data

Devika Shanmugasundaram, Lakshmanan Jeyaseelan

Generalized Poisson Regression Model with an Application to Malnutrition Data

Data De-identification and Anonymization - Guidelines and Implementation Challenges_

Farooq Ali, Kedar Maheshwari

Data De-identification and Anonymization - Guidelines and Implementation Challenges_

Features of Nanotechnology in Clinical industry

Pavan Sagi

Features of Nanotechnology in Clinical industry

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

Exploring Oncology Domains

Senthil Yuvaraja, Suresh reddy

Exploring Oncology Domains

DOSUBL AN IMPROVED VERSION_OFCALL_EXECUTE

Pradeep Acharya, Thejas M S

DOSUBL AN IMPROVED VERSION_OFCALL_EXECUTE

Mindfullness

Nishanth N

Mindfullness

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

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

The seven year itch

Korak Datta

The seven year itch

Can there be an alternative to cancer clinical trials

Husayn Ahmed

Can there be an alternative to cancer clinical trials

Strategies to overcome the future resourcing demands of SAS Programmers

Dineshkumar.N

Strategies to overcome the future resourcing demands of SAS Programmers

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

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

ADTTE - A Dynamic Tool To Effectively interpret clinical outcomes

Mangala, Shilpakala

ADTTE - A Dynamic Tool To Effectively interpret clinical outcomes

Baseline calculation and visit mapping in Concomitant medication

Pradeep Kiran

Baseline calculation and visit mapping in Concomitant medication

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

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

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

Jumpstart- A Quick Data Review Tool

Rashmi Seta

Jumpstart- A Quick Data Review Tool

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

Metadata Repository (MDR) When it Fails

Tushar Sakpal

Metadata Repository (MDR) When it Fails

SDTMiG 3.3-New Domains and Variables

Prashant Suthar

SDTMiG 3.3-New Domains and Variables

Evolution of SDTM, General Pit falls and Best practices

Ranjan Routray, Lekshmanan, Shrishaila Patil

Evolution of SDTM, General Pit falls and Best practices

Traceability Checks For CDISC ADaM

Obulpathi Naidu K

Traceability Checks For CDISC ADaM

Basic to Advance, ODS is all you need to know

Shabbir Bookseller, Abdulkadir Lokhandvala

Basic to Advance, ODS is all you need to know

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

Can we automate human life value

Rohith, Neelam

Can we automate human life value

Challenges In Assignment Of EPOCH In Partial Blinded Crossover Trials

Sagar Das

Challenges In Assignment Of EPOCH In Partial Blinded Crossover Trials

SDTM TRAIL DESIGN MODELS

Peddiboyena Lalitha,Rathan Kumar Rangu

SDTM TRAIL DESIGN MODELS

The BRIDG MODEL- DAM for regulated clinical research

Naveenpal Arumugam

The BRIDG MODEL- DAM for regulated clinical research

Overview of Reporting Adverse Eevents of Special Interest

Shelendra Singh Pawar, Meghana Kulkarni, Shveta Natu

Overview of Reporting Adverse Eevents of Special Interest

Implementation & Applicability of PROC FCMP-Creating Dynamic Custom Functions

Prathamesh Athavale, Vikramaditya Yandapalli, Ajay Yalwar

Implementation & Applicability of PROC FCMP-Creating Dynamic Custom Functions

Adverse Events-Intensity behind the scenes

Neha Srivastava

Adverse Events-Intensity behind the scenes

Biomarkers as Clinical Endpoints

Vamsidhar Terala

Biomarkers as Clinical Endpoints

Vertical ADaM a long look

V Vishnu BapuNaidu

Vertical ADaM a long look

Multiple Baseline Implementation

SUNIL GANESHNA

Multiple Baseline Implementation

Associated Person Domain

Padmasree Sirigireddy

Associated Person Domain

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

Forecasting Trial Cost at Pre-clinical Development Stage

Manigandan Ramkumar, Kapil J Anand

Forecasting Trial Cost at Pre-clinical Development Stage

Big data analysis in Clinical Trials

Rajan Josephraj Paul, Swarna

Big data analysis in Clinical Trials

Predicting Future Course of Clinical Trials

Rohan Sathe

Predicting Future Course of Clinical Trials

Risk Based Monitoring

Venkatesh Krishnamurthy, Sravan NagiReddy, SatyaVyshnavi Thondapu, Milan Bhagat

Risk Based Monitoring

Using Analytics to Monitor Patient Safety

Arnab Sengupta, Rajat Nanda

Using Analytics to Monitor Patient Safety

Safety Signal How far are we from detecting it

Pratibha Jalui, Amitava Mukhopadhyay

Safety Signal How far are we from detecting it

Signal Detection in Pharmacovigilance

Nithiya Ananthakrishnan, Sridhar Punniamurthi

Signal Detection in Pharmacovigilance

PHARMACOKINETICS ANALYSIS WORKSHOP MATERIAL

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

PHARMACOKINETICS ANALYSIS WORKSHOP MATERIAL

Graphs made by easy using SAS & R -material

Prerit Pancholiya, Sameer Bamnote

Graphs made by easy using SAS & R -material

Deep Dive into ADaM - Workshop material

Anish Shah, Ashish Aggarwal, Roshan Stephen, Harun Rasheed

Deep Dive into ADaM - Workshop material

Statistical Applications in Clinical Trials

Shashidhar J Savanur, Vishwanath Iyer (Mahesh)

Statistical Applications in Clinical Trials

Adaptive designs in biopharmaceutical development

Arunava Chakravartty

Adaptive designs in biopharmaceutical development

Challenges in creating SDTM trial design datasets for complex study designs

Charumathy Sreeraman

Challenges in creating SDTM trial design datasets for complex study designs

Signal Detection Regulations Data Sciences Paradigm

Chitra Lele

Signal Detection Regulations Data Sciences Paradigm

PYNE Statistical Frameworks for Big Data Analysis

Saumyadipta Pyne

PYNE Statistical Frameworks for Big Data Analysis

Insights from Data

S Anand

Insights from Data

Detecting safety signals

Ramanan Ezhil Arasan

Detecting safety signals

CLM Social Media

Manish Pathak, Konark Garg

CLM Social Media

The value of data 2014

Stephen Pyke

The value of data 2014

Safety in clinical research

Vishwanath Iyer(Mahesh)

Safety in clinical research

Text-Analytics-IASCT

Harsha Urlam

Text-Analytics-IASCT

Safety Signal

----

Safety Signal

Predictive Modelling for Commercial Usage

-------

Predictive Modelling for Commercial Usage

Next Generation Sequencing - Challenges and solutions

Saurabh Gupta

Next Generation Sequencing - Challenges and solutions

Life Science Market Sell

Smit Shanker

Life Science Market Sell

Database Design and Optimization for Signal Detection

Krishna Asvalayan

Database Design and Optimization for Signal Detection

Adaptive-Monitoring

Chirag Trivedi

Adaptive-Monitoring

ConSPIC 2011 - Day 2 Track 2

Compiled file

ConSPIC 2011 - Day 2 Track 2

Clinical Study Design: Statistical Considerations

Jagannatha P.S.

Clinical Study Design: Statistical Considerations

Adoption of SaaS and cloud technology by pharma and CROs

------

Adoption of SaaS and cloud technology by pharma and CROs

Advances in safety data analysis – the journey

Vivek Ahuja

Advances in safety data analysis – the journey

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

Vishwanath Iyer, Ashwini Mathur

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

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 !!

ODS Graphics Designer - beyond point and click!

Priyanka & Satish

ODS Graphics Designer - beyond point and click!

Next Generation Sequencing magnifying glasses to read your DNA

Neelam Yadav

Next Generation Sequencing magnifying glasses to read your DNA

OpenTLF

Ashwin V

OpenTLF

OPHTHALMOLOGY IN CLINICAL TRIALS

ARUNA CHAKRABORTY

OPHTHALMOLOGY IN CLINICAL TRIALS

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

HIV Studies:An Overview for Programmers

Rupali Belose, Aditya Tembe

HIV Studies:An Overview for Programmers

SDTM Annotations-Checker and Mapper-Automated Approach

Dhananjay Thakur

SDTM Annotations-Checker and Mapper-Automated Approach

Automating the code for Command Line Interface in OpenCDISC Validator

Rajasekhar Mudugu

Automating the code for Command Line Interface in OpenCDISC Validator

Effortless Validation:It's so simple

Anusuiya Ghanghas

Effortless Validation:It's so simple

ROC Curve:Making way for correct diagnosis

Manoj Pandey,Writwik Mandal

ROC Curve:Making way for correct diagnosis

Selection of Test Model

Karunakar Narahari

Selection of Test Model

ADAPTIVE DESIGN CLINICAL TRIALS

PRASANTHI BONALA,VIJAYAN GOVINDHARAJAN

ADAPTIVE DESIGN CLINICAL TRIALS

Anonymization of Clinical Trial Data

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

Anonymization of Clinical Trial Data

EudraCT-A new way forward for greater transparency

Ramya Deepak, Aditya Shah

EudraCT-A new way forward for greater transparency

Electronic Submissions

Vikas Dhongde

Electronic Submissions

FSP Business Model

Nishanth N

FSP Business Model

Risk Mitigation In Clinical Trail Projects

Bibas Timilsina

Risk Mitigation In Clinical Trail Projects

Standard Macro System

Pratibha Jalui

Standard Macro System

Dashboard for Project Management Using Excel adn R

Kalaivani Raghunathan, Egappan Rama

Dashboard for Project Management Using Excel adn R

Usage Of Mahalanobis Distance Statistics in Clinical Data

Karuna Gawde

Usage Of Mahalanobis Distance Statistics in Clinical Data

MEDICAL MONITORING

CHARAN KUMAR, SRINIVAS RAPELLY

MEDICAL MONITORING

Magic of Analytics in Clinical Trails

Soujanya Konda, Padmavathi Karumuru and Amruta Pathak

Magic of Analytics in Clinical Trails

EXPOSURE TO EXPOSURE 'AS COLLECTED'

Mousumi Biswas

EXPOSURE TO EXPOSURE 'AS COLLECTED'

Bridging Statistical Analysis Plan, ADaM Datasets & Metadata

Nilesh Kumar Muthyala

Bridging Statistical Analysis Plan, ADaM Datasets & Metadata

Strengthening Your Trial Arms

Arwa Topiwalla

Strengthening Your Trial Arms

EASE YOUR WORK WITH NOTEPAD++

Amarnath Vijayarangan

EASE YOUR WORK WITH NOTEPAD++

R Programming Validation for the Clinical Study Report

Sridhar Punniamurthi, Harish Chellam Narayanan

R Programming Validation for the Clinical Study Report

Significance of Periodical Submissions in Clinical Research

Sambasivarao Tedla, Sandeep Kambhampati

Significance of Periodical Submissions in Clinical Research

PK/PD Modeling in Support of Drug Development

Ranjith Kumar & Madhu Guruvelli

PK/PD Modeling in Support of Drug Development

Methods of Safety Recurrence Analysis and its SAS Procedures

Aditi Marathe

Methods of Safety Recurrence Analysis and its SAS Procedures

Think Twice before using Regression

Suman Kapoor

Think Twice before using Regression

Quality adjusted survival (Q-TWiST)

Puliraju Mandati

Quality adjusted survival (Q-TWiST)

How ‘Significant digits’ are significant in clinical trials

Swarnalatha Madupu

How ‘Significant digits’ are significant in clinical trials

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

An observational study – as observed by a programmer

Swati Kapuganti and Naveen Katarki

An observational study – as observed by a programmer

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 Activity to Track Ongoing Clinical Study Data Capturing Process Efficiently

Thoufic Ahamed

An Activity to Track Ongoing Clinical Study Data Capturing Process Efficiently

Challenges in Building better 'EDC System in Clinical Trials'

Sarath Krishna

Challenges in Building better 'EDC System in Clinical Trials'

Optimal Planning of Clinical Trials

Soumya Rout

Optimal Planning of Clinical Trials

Bootstrap - Resampling

Venkateshwarlu Y

Bootstrap - Resampling

Monitoring Safety Signal in Clinical Trial(s)

Satish Bhosale & Amitava Mukhopadhyay

Monitoring Safety Signal in Clinical Trial(s)

Handling correlated data using GLIMMIX procedure

Anitha Cecelia

Handling correlated data using GLIMMIX procedure

Cross Over Trial Design:CDISC Data Structure

Anusha Bhimavarapu & Ashok Kodali

Cross Over Trial Design:CDISC Data Structure

TD - Trial Disease Assessments Domain in SDTM IG 3.2

Sandhya Yalla

TD - Trial Disease Assessments Domain in SDTM IG 3.2

Implementing multiple baselines in ADaM BDS datasets

Vamsidhar Terala

Implementing multiple baselines in ADaM BDS datasets

Tips for Handling and Creating Special Characters in SAS

Apoorva Singh

Tips for Handling and Creating Special Characters in SAS

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

Rammohan and Naveen

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

EXCEL'ing Quality With Efficiency

Harish Kumar and K Pallayya Guptha Vura

EXCEL'ing Quality With Efficiency

SMAC AND ITS ROLE IN CLINICAL TRIALS

Dhivagaran and Sandeep

SMAC AND ITS ROLE IN CLINICAL TRIALS

OVERVIEW OF PATIENT PROFILES

Pavithra and Melvin and Roshan

OVERVIEW OF PATIENT PROFILES

SDLC in Statistical Programming - A Possibility?

ARUNA CHAKRABORTY

SDLC in Statistical Programming - A Possibility?

Deciding Clinical Trial Endpoints in Oncology Studies

Srinivas Devasani and Anupkumar Baheti

Deciding Clinical Trial Endpoints in Oncology Studies

Guidance For Evaluating Responses in Multiple Myeloma

Janki Chokshi

Guidance For Evaluating Responses in Multiple Myeloma

Importance of RAV analysis in Hepatitis-c studies

Shrikrishna shroff

Importance of RAV analysis in Hepatitis-c studies

SAS functions – easy way to remember

Sadanand Deshmukh

SAS functions – easy way to remember

“D” Wise approach for “Device” trial

Praveen Aleti

“D” Wise approach for “Device” trial

Unleashing the black box of debugging in Validation

Chaitanya pradeep repaka

Unleashing the black box of debugging in Validation

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

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

Patient Reported Outcomes - PROgressive approach to clinical trials

Shilpakala Vasudevan and Padmashree Jahagirdar

Patient Reported Outcomes - PROgressive approach to clinical trials

Imputation of Missing Data through Bayesian Approach

Pratibha Jalui and Reetabrata Bhattacharyya

Imputation of Missing Data through Bayesian Approach

Methods of Creating Define.xml and Challenges Faced

Mustaq

Methods of Creating Define.xml and Challenges Faced

PERL REGULAR EXPRESSION IN SAS

Ravi Gupta and Jagadish Katam

PERL REGULAR EXPRESSION IN SAS

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

Renjana Prasannan and Apoorva Singh

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

Out of Box Thinking

Senthilkumar and Srihari

Out of Box Thinking

Idiosyncratic Plots to Visualize the Clinical data

Aditi Kakade & Garima Joshi & Vidya Raja & Tamilselvi Senthilkumar

Idiosyncratic Plots to Visualize the Clinical data

Molecular modeling – to ease drug discovery in clinical industry

Madhusudhan Bandi

Molecular modeling – to ease drug discovery in clinical industry

Sneak peek of Trial Design Model

Jasmin Jobanputra

Sneak peek of Trial Design Model

What, How and WHY’s Law

Priyesh Sura

What, How and WHY’s Law

INTERVAL CENSOR DATA WITH SAS

Raju Tadala

INTERVAL CENSOR DATA WITH SAS

Enhancing outputs with PROC TEMPLATE

Madhubhushan Eada and Satyendra Kuril

Enhancing outputs with PROC TEMPLATE

Lab CTC Grades Unveiled

Giriprasad Bommisetty & Manjushree

Lab CTC Grades Unveiled

A Study to Identify Assessments Impacting Patient Burden

Ramya Kode Dhaval Naik

A Study to Identify Assessments Impacting Patient Burden

Insights into Data Visual Analytics - A new Paradigm

Sridhar Kantamani

Insights into Data Visual Analytics - A new Paradigm

Execute efficiently by using call execute

Santhosh Chetpelly and Paramkusham Kishore Kumar

Execute efficiently by using call execute

Conducting clinical trials in India - efficient planning and ensuring success

Dr. Chirag Trivedi

Conducting clinical trials in India - efficient planning and ensuring success

The Graph Template Language (GTL)

Manoj Panday

The Graph Template Language (GTL)

Managing the Unspoken Customer Expectations

Pratibha Jalui & Pooja Shinde

Managing the Unspoken Customer Expectations

PLAN YOUR WORK USING PROC CALENDAR

SURESH KUMAR KOTHAKONDA

PLAN YOUR WORK USING PROC CALENDAR

Introduction to Survival Analysis - Workshop slides

Sanjib Basu

Introduction to Survival Analysis - Workshop slides

Statistics in Clinical Trials – Some emerging issues

Dr. Arun Nanivadekar [Keynote Speaker]

Statistics in Clinical Trials – Some emerging issues

Current state of clinical research in India

Dr Arun Bhatt

Current state of clinical research in India

How is the evidence used by a prescriber?

Dr. Gouri Pantvaidya

How is the evidence used by a prescriber?

Use & presentation of evidence while launching & marketing products

Dr. Piyush Agarwal

Use & presentation of evidence while launching & marketing products

Communicating Results in Publications: A Perspective

Dr. Sunita R. Nair

Communicating Results in Publications: A Perspective

Systematic Reviews & Meta Analyses

Dr.B.Unnikrishnan

Systematic Reviews & Meta Analyses

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

Creating Evidence Base: An Example of NSDs

Dr. Vasudeo Paralikar

Creating Evidence Base: An Example of NSDs

Adoption of SaaS and cloud technology by pharma & CROs

Dr. Saurav Roy

Adoption of SaaS and cloud technology by pharma & CROs

Role of PK/PD in Evidence based Medicine

Dr. Tausif Ahmed

Role of PK/PD in Evidence based Medicine

Advances in safety data analysis - the Journey

Dr. Vivek Ahuja

Advances in safety data analysis - the Journey

Clinical Trials – History and Ethics

Dr. Ashwini Mathur

Clinical Trials – History and Ethics

Healthy Numbers – Historical perspective of quantitative analysis of health

Prof. A. P. Gore

Healthy Numbers – Historical perspective of quantitative analysis of health

Overview of SAS Education

Raj Jhaveri

Overview of SAS Education

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

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

Rahul Paul Chaudhary

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

Data Manipulation using SAS Arrays

Ravisekhar Jayanti

Data Manipulation using SAS Arrays

Array Presentation

Vibhavari Inamdar

Array Presentation

Randomization

Rajalakshmi

Randomization

Adaptive Designs in Clinical Trials

Pratibha Jalui

Adaptive Designs in Clinical Trials

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

Tools, Technologies and Techniques in Clinical Data Standardization

Pankaj Bharadwaj

Tools, Technologies and Techniques in Clinical Data Standardization

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

Abhishek Bakshi

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

Copy, Paste and Misanalysis

Ramkumar M.Rajendiran

Copy, Paste and Misanalysis

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

Do We Know Enough about Drug Exposure?

Vinay Mahajan and Pawan Sharma

Do We Know Enough about Drug Exposure?

Phasing: Concept and Real Life Challenges

Benazir Ibrahim

Phasing: Concept and Real Life Challenges

Competent SAS Programmer: Need of BPO Industry

Imran Khan

Competent SAS Programmer: Need of BPO Industry

Unleashing Potential of Graphs for Analysis of Adverse Events

Abhinav Jain

Unleashing Potential of Graphs for Analysis of Adverse Events

Visualizing data using SAS GTL (Graphics Template Language)

NISHANTH NALAN

Visualizing data using SAS GTL (Graphics Template Language)

Graphs Made Simple using SG Procedures and GTL

Hari Vardhan J

Graphs Made Simple using SG Procedures and GTL

Utility of SAS Graph Annotation

Urmi Bhatia, Aditi Kakade and Yogesh Yewale

Utility of SAS Graph Annotation

Validation of Statistical Analyses in Cosmetic Trials using R

Tejaswni Abhyankar

Validation of Statistical Analyses in Cosmetic Trials using R

10 Possible mistakes in Statistical programming

Rijesh Paramal

10 Possible mistakes in Statistical programming

Challenges in Analyzing Laboratory Values and Measurements

Sugunesh Sivalingam

Challenges in Analyzing Laboratory Values and Measurements

Cross Validation Made Easy

Sarfaraz Sayyed

Cross Validation Made Easy

QT analysis: A Guide for Statistical Programmers

Prabhakar Munkampalli

QT analysis: A Guide for Statistical Programmers

Exposure to Exposure

Gauri Khatu

Exposure to Exposure

RECIST and Programming Challenges

Mahesh Babu Mayakuntla & Prasanna Kumar Nidamathy

RECIST and Programming Challenges

Registering and Reporting Results with Clinicaltrials.gov.in

Swapna Kopalla

Registering and Reporting Results with Clinicaltrials.gov.in

Addition of R Programming in Clinical Domain

Sasikumar S

Addition of R Programming in Clinical Domain

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

Box Plot and Clinical Trial Analysis

Devayani and Rosemary

Box Plot and Clinical Trial Analysis

Utility Macros

Suman Kapoor

Utility Macros

Overview of user Defined SAS Functions and Subroutine

Senthilnathan Ramanathan

Overview of user Defined SAS Functions and Subroutine

Integrating Perl scripting with SAS

Ninan M. Luke

Integrating Perl scripting with SAS

Extracting tracking information for data management team from oracle clinical

Dhaval Mehta

Extracting tracking information for data management team from oracle clinical

Using PERL Regular Expression in SAS-Useful and Powerful Tool

K.E.Sudarsan

Using PERL Regular Expression in SAS-Useful and Powerful Tool

Sample Size Re-estimation in Late Stage Trials

Dr Vidyadhar Phadke

Sample Size Re-estimation in Late Stage Trials

Simulations in Clinical Trial Design

Abhishek Mishra

Simulations in Clinical Trial Design

Regulatory Considerations in Designing of Respiratory Studies for Generic Drugs

Dr Sheetal Ingole

Regulatory Considerations in Designing of Respiratory Studies for Generic Drugs

Biosimilar Development: Design and Statistical Challenges

Moumita Sinha, PhD

Biosimilar Development: Design and Statistical Challenges

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

CLINICAL ENDPOINT STUDIES IN GENERIC DRUG DEVELOPMENT

Dr Ravisekhar Kasibhatta

CLINICAL ENDPOINT STUDIES IN GENERIC DRUG DEVELOPMENT

Meta-analysis in Risk-Benefit Evaluation

Demissie Alemayehu, Ph.D.

Meta-analysis in Risk-Benefit Evaluation

Role of Toxicology Data in Drug Development

K.S. Rao

Role of Toxicology Data in Drug Development

Pharmacometrics – PK/PD Modeling

Jyothi Subramanian

Pharmacometrics – PK/PD Modeling

Statistical Analysis for Biomarker Identification

Raghunathan Srivastsan

Statistical Analysis for Biomarker Identification

Clinical Trials Design Workshop

Dr Vishwanath Iyer & Dr Ashwini Mathur

Clinical Trials Design Workshop

Oxazolidinone for the treatment of Tuberculosis (TB)

DR BALASUBRAMANIAN

Oxazolidinone for the treatment of Tuberculosis (TB)

Adaptive Bayesian dose findings

Chethana Kalmady

Adaptive Bayesian dose findings

Workshop in Pharmacovigilance

Compiled file

Workshop in Pharmacovigilance

Day 2 Track 2

Day 2 Track 2

ConSPIC 2011 - Day 1 Track 1

Compiled file

ConSPIC 2011 - Day 1 Track 1

Statistical concepts for clinical research

Vishwanath Iyer & Ashwini Mathur

Statistical concepts for clinical research

Comparative Effectiveness Research From safety and effectiveness to risk‐benefit

Viraj Suvarna

Comparative Effectiveness Research From safety and effectiveness to risk‐benefit

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Ranjani Nellore

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Regulatory interactions: Engaging effectively for success

Manish Paliwal

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Standards in analysis & reporting

Murali Ganesan

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Medical Communications: Messaging to Internal and External customers

Bindu Narang

Medical Communications: Messaging to Internal and External customers

Analysis Planning and Safety Monitoring: The Statistician as a Trialist

Ritwik Sinha

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Pathway to Quality Management of Study Data

Deven Babre

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Clinical Research : End User’s Perspective

Dr. R A Badwe

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Study Design: The Blueprint for success

Prathap Tharyan

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Selection and Training of Clinical Research Partners

Celestine Juliet Rebello

Selection and Training of Clinical Research Partners

Study Set-up: The Roadmap For Effective Data Collection

Indrani Kakade

Study Set-up: The Roadmap For Effective Data Collection