BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 15.4//EN BEGIN:VTIMEZONE TZID:GMT Standard Time BEGIN:STANDARD DTSTART:20251002T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=2;BYMINUTE=0;BYMONTH=10 TZNAME:GMT Standard Time TZOFFSETFROM:+0100 TZOFFSETTO:+0000 END:STANDARD BEGIN:DAYLIGHT DTSTART:20250301T010000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=1;BYMINUTE=0;BYMONTH=3 TZNAME:GMT Daylight Time TZOFFSETFROM:+0000 TZOFFSETTO:+0100 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Date: \;Wednesday 2nd December 2020\nTime: 14:00 - 15:30\nS peakers: Tim Rolfe\, \;Marcin Macowski\, \;Marta Kozinska and  \;Chris Wells.\nWho is this event intended for? \;Anyone who would lik e to learn more about risk based monitoring and how QTLs are being defined in practice.\nWhat is the benefit of attending? \;Receive an introduc tion\, overview and some examples of how some company's are implementing Q TL's and a chance to ask the panel some questions.\n\nRegistration\nYou ca n now register for this event. Registration will close at 12:00 on 1st Dec ember 2020. \;\nPSI Members: \;Free to attend\nNon Members: \; £\;20+VAT\nTo register your place\, please \;click here.\nOvervie w\nSince the introductio of ICH-E6 R2 Addendum sponsors must introduce for mal Quality Risk Management and define Quality Tolerance Limits to their c lnical development programs. \; This webinar will cover an introductio n to those concepts\, recent developments and examples of how companies ar e defining QTL's in practice.\nSpeaker Details\n\n\n\n \n \n \n Speaker\n \n \n Bio graphy\n \n \n Abstract\n \n \n \n \n \n Tim Rolfe\n \n \n Tim Rolfe is Director of Central Monito ring &\; Data Analytics at GlaxoSmithKline &\; has over 20 years of experience working as a statistician at in the pharmaceutical industry. \n He has been part of GSKs RBM team since its inception in 2012\ , providing statistical leadership in the development and implementation o f GSK&rsquo\;s RBM strategy within clinical trials.\n Before jo ining GSK\, Tim studied Applied Statistics at Sheffield Hallam University and holds a MSc in Medical Statistics from the University of Leicester in the UK.\n  \;\n  \;\n \n \n Since the introduction of ICH-E6 R2 Addendum sponsors mus t introduce formal Quality Risk Management processes and decide which risk s to reduce and/or which to accept. Many tools are available to aid with c entralised monitoring of Key Risk Indicators. But there has been much less done to address quality tolerance limits (QTLs) i.e. taking into consider ation the medical/statistical characteristics of the variables and the sta tistical design of the trial\, to identify systematic issues that can impa ct subject safety or integrity of trial. The presentation will cover histo ry behind QTLs\, difference between QTLs and KRIs and mechanisms to establ ish\, track and report deviations of QTLs in the CSR.\n \n \n \n \n \n Marcin Macowski\n \n \n Marcin Makowski is the Head of Centr alized Monitoring and Data Analytics at GSK. Previously Marcin held simila r positions at AstraZeneca and UCB. Last 10 years of Marcin&rsquo\;s caree r was revolving around establishing and improving Risk Based Monitoring mo dels including centralized monitoring and quality tolerance limits. Marcin co-led the group that produced the first TransCelerate recommendations on QTLs in 2017 and is member of the TransCelerate topic team that recently published the expanded QTL framework. Marcin holds MD and PhD degrees from the Warsaw Medical University.\n \n \n \ n \n \n This year TransCelerate QTL topic team published new set of deliverables on Quality Tolerance Limits. The d ocuments build on the proposals published in 2017 by proposing a broader l ist of parameters and process for defining\, monitoring\, and reporting of QTLs. The presentation will explain the content of the new deliverables. The plans for future publication pertaining historical benchmarking data f or QTLs will also be shared.\n \n \n \n \n \n Marta Kozińska\n \n \n Marta Kozińska is an Associate Director Centralized Monitoring with over 10 years of experience in clinical trials which includes\, Data Management\, Site Management (CRA)\, Study Management (Project Manager &n dash\; Global Study Leader) as well as RBQM implementation and Risk Manage ment. Marta has an MSc Eng in Biotechnology from the Warsaw University of Life Sciences and is a certified PMI Project Manager. For the last 8 years Marta has worked for AstraZeneca\, where for 3 years she has been part of Centralized Monitoring Team. During these last 3 years she has been leadi ng multiple projects aiming at e.g. proper implementation of Quality Toler ance Limits\, Centralized Statistical Monitoring and improvements in ways of working. Apart from that she represents AstraZeneca in TransCelerate QT L working group.\n \n \n It has been almo st 4 years since Quality Tolerance Limits\, as a measure of risks&rsquo\; control in Clinical Trials\, have been introduced into ICH-E6 R2 Addendum. During this time TransCelerate QTL topic team has also published tools su pporting QTLs implementation by Sponsors. This presentation will summarize definitions of QTL from ICH GCP R2 and TransCelerate\, will cover CtQ &nd ash\; Risk &ndash\; QTL relationship as well as provide real-life example of an approach to QTL set-up\, both in terms of selection of a parameter a nd identification of a tolerance limit and challenges to QTL implementatio n at scale and speed.\n  \;\n \n \n \n \n \n Chris Wells\n \n \n Chris Wells is a Senior Statistical Scientist who h as a total of 23 years experience in the industry. Chris has an MSc in Med ical Statistics from the London School of Hygiene. For the last 11 years C hris has worked for Roche Products Ltd where for 4 years she led the Stati stical Monitoring Team which during the past year has also included the ap plication of Quality Tolerance Limits. More recently her work is involving the implementation of Data Surveillance and Advanced Analytics.\n  \;\n \n \n Utilizing a Bayesian Hierarchical Model to design quality into a clinical trial and allow compl iance with ICH E6 R2 Quality Tolerance Limits and what approach can be use d for Early Phase Studies.\n ICHE6 R2 has mandated the use of Q uality Tolerance Limits. Roche have utilized a Bayesian Hierarchical Model methodology\, inspired by the Bayesian Meta analysis example in Berry et al (2011). Fixed parameters specify the prior for all unknown parameters\, a conservative prior can be used or it can be informed by historical data and profound medical knowledge. The Prior is combined with the observed d ata (events and exposure) to define a posterior the parameters\, computed using Markov Chain Monte Carlo algorithm. We then use percentiles of the p osterior distribution for rate to establish limits which can in turn help to establish QTLs and Secondary Limits along with profound medical knowled ge. QTLs and Secondary Limits are used to manage parameter risk at the stu dy level and drive quality at the site level by identifying sites with par ameters lying beyond the predefined limits (Trent Alert). This presentatio n will detail the methodology and demonstrate the outputs. We will also ta ke a look at which approach could be useful for early phase studies.\n \n \n \n\n DTEND:20201202T153000Z DTSTAMP:20260721T160444Z DTSTART:20201202T140000Z LOCATION: SEQUENCE:0 SUMMARY:PSI Webinar: Risk Based Monitoring & QTL's UID:RFCALITEM639202466847675990 X-ALT-DESC;FMTTYPE=text/html:

Date: \;Wednesday 2nd December 2020
\nTime: 14:00 - 15:30
\nS peakers: Tim Rolfe\, \;Marcin Macowski\, \;Marta Kozinska and \;Chris Wells.

\nWho is this event intended for? \;Anyone who would like to learn more about risk based monitoring and how QTLs are being defined in practice.
\nWhat is the ben efit of attending? \;Receive an introduction\, overview and s ome examples of how some company's are implementing QTL's and a chance to ask the panel some questions.
\n
\n

Registration

\n

You can now register for this event. Registration will close at 12:00 on 1st December 2020. \;
\nPSI Members:&nb sp\;Free to attend
\nNon Members: \;£\;20+V AT
\nTo register your place\, please \;click here.

\n

Overview

\n

Since the introductio of ICH-E6 R2 Addendum sponsors must introduce formal Quality Risk Manageme nt and define Quality Tolerance Limits to their clnical development progra ms. \; This webinar will cover an introduction to those concepts\, rec ent developments and examples of how companies are defining QTL's in pract ice.

\n

Speaker Details

\n\n
\n\n \n \n \n \n \n \n \n \ n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n
END:VEVENT END:VCALENDAR
\n

Speaker

\n 		\n

Biography

\n 		\n

Abstract

\n
\n

Timedit
\n Tim Rolfe

\n 		\n

Tim Rolfe is Director of Central Monitoring &\; Data Analytics at GlaxoSmit hKline &\; has over 20 years of experience working as a statistician at in the pharmaceutical industry.

\n

He has been part of GSKs RBM team since its inception in 2012\, providing statistical leadersh ip in the development and implementation of GSK&rsquo\;s RBM strategy with in clinical trials.

\n

Before joining GSK\, Tim studied A pplied Statistics at Sheffield Hallam University and holds a MSc in Medica l Statistics from the University of Leicester in the UK.

\n

 \;

\n

 \;

\n 		\n

Since the introd uction of ICH-E6 R2 Addendum sponsors must introduce formal Quality Risk M anagement processes and decide which risks to reduce and/or which to accep t. Many tools are available to aid with centralised monitoring of Key Risk Indicators. But there has been much less done to address quality toleranc e limits (QTLs) i.e. taking into consideration the medical/statistical cha racteristics of the variables and the statistical design of the trial\, to identify systematic issues that can impact subject safety or integrity of trial. The presentation will cover history behind QTLs\, difference betwe en QTLs and KRIs and mechanisms to establish\, track and report deviations of QTLs in the CSR.

\n
\n

Marcinedit
\n Marcin Macow ski

\n 		\n

Marcin Makowski is the Head of Centralized Mon itoring and Data Analytics at GSK. Previously Marcin held similar position s at AstraZeneca and UCB. Last 10 years of Marcin&rsquo\;s career was revo lving around establishing and improving Risk Based Monitoring models inclu ding centralized monitoring and quality tolerance limits. Marcin co-led th e group that produced the first TransCelerate recommendations on QTLs in 2 017 and is member of the TransCelerate topic team that recently published the expanded QTL framework. Marcin holds MD and PhD degrees from the Warsa w Medical University.
\n
\n
\n

\n 		\n

This year TransCelerate QTL topic team publishe d new set of deliverables on Quality Tolerance Limits. The documents build on the proposals published in 2017 by proposing a broader list of paramet ers and process for defining\, monitoring\, and reporting of QTLs. The pre sentation will explain the content of the new deliverables. The plans for future publication pertaining historical benchmarking data for QTLs will a lso be shared.

\n
\n

Martaedit
\n Marta Kozińska\n

\n

Marta Kozińska is an Associate Director Centralized Moni toring with over 10 years of experience in clinical trials which includes\ , Data Management\, Site Management (CRA)\, Study Management (Project Mana ger &ndash\; Global Study Leader) as well as RBQM implementation and Risk Management. Marta has an MSc Eng in Biotechnology from the Warsaw Universi ty of Life Sciences and is a certified PMI Project Manager. For the last 8 years Marta has worked for AstraZeneca\, where for 3 years she has been p art of Centralized Monitoring Team. During these last 3 years she has been leading multiple projects aiming at e.g. proper implementation of Quality Tolerance Limits\, Centralized Statistical Monitoring and improvements in ways of working. Apart from that she represents AstraZeneca in TransCeler ate QTL working group.

\n 		\n

It has been almost 4 years since Quality Tolerance Limits\, as a measure of risks&rsquo\; control in Clini cal Trials\, have been introduced into ICH-E6 R2 Addendum. During this tim e TransCelerate QTL topic team has also published tools supporting QTLs im plementation by Sponsors. This presentation will summarize definitions of QTL from ICH GCP R2 and TransCelerate\, will cover CtQ &ndash\; Risk &ndas h\; QTL relationship as well as provide real-life example of an approach t o QTL set-up\, both in terms of selection of a parameter and identificatio n of a tolerance limit and challenges to QTL implementation at scale and s peed.

\n

 \;

\n
\n

Chris edit
\n Ch ris Wells

\n 		\n

Chris Wells is a Senior Statistical Scie ntist who has a total of 23 years experience in the industry. Chris has an MSc in Medical Statistics from the London School of Hygiene. For the last 11 years Chris has worked for Roche Products Ltd where for 4 years she le d the Statistical Monitoring Team which during the past year has also incl uded the application of Quality Tolerance Limits. More recently her work i s involving the implementation of Data Surveillance and Advanced Analytics .

\n

 \;

\n 		\n

Utilizing a Bayes ian Hierarchical Model to design quality into a clinical trial and allow c ompliance with ICH E6 R2 Quality Tolerance Limits and what approach can be used for Early Phase Studies.

\n

ICHE6 R2 has m andated the use of Quality Tolerance Limits. Roche have utilized a Bayesia n Hierarchical Model methodology\, inspired by the Bayesian Meta analysis example in Berry et al (2011). Fixed parameters specify the prior for all unknown parameters\, a conservative prior can be used or it can be informe d by historical data and profound medical knowledge. The Prior is combined with the observed data (events and exposure) to define a posterior the pa rameters\, computed using Markov Chain Monte Carlo algorithm. We then use percentiles of the posterior distribution for rate to establish limits whi ch can in turn help to establish QTLs and Secondary Limits along with prof ound medical knowledge. QTLs and Secondary Limits are used to manage param eter risk at the study level and drive quality at the site level by identi fying sites with parameters lying beyond the predefined limits (Trent Aler t). This presentation will detail the methodology and demonstrate the outp uts. We will also take a look at which approach could be useful for early phase studies.

\n