BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 15.4//EN BEGIN:VTIMEZONE TZID:UTC BEGIN:STANDARD DTSTART;VALUE=DATE:20250101 TZNAME:UTC TZOFFSETFROM:+0000 TZOFFSETTO:+0000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Date: Tuesday 21st October 2025\nTime: \;14:00-15:30 BST | 15:00-16:30 CEST\nLocation: \;Online via Zoom\nSpeakers: \;Warren Roche (Sanofi)\, Bernard Francq (GSK) and \;Thomas Zahel (Kö\;rber -Pharma) \;\n\nWho is this event intended for?: \;Statisticians an d interested parties working in the CMC and Manufacturing area of Pharmace utical Industry.\n\nWhat is the benefit of attending?: Presentation and ac tive discussion of technical statistical topics in this field.\nCost\nThis webinar is free to both Members of PSI and Non-Members.\nRegistration\nTo register for this event\, please click here\nOverview\nWebinar dedicated to the topic of stability modelling\; opportunity to hear from statisticia ns working in the CMC field\, with open question and answers. Brought to y ou by the CMC Statistical Network Europe (CSNE) SIG.\nSpeaker details\n\n\ n\n \n \n \n Speaker\n \n \n Biography\n \n \n Abs tract\n \n \n \n \n Warren Roche\, Sanofi\n \n \n Warren Roche is fr om Waterford\, Ireland. Warren has worked as a mathematics and statistics lecturer previously at the South East Technological University in Ireland\ , and also has extensive statistical experience in clinical trial research and pharmaceutical manufacturing. He originally earned his BSc in Mathema tics from Trinity College Dublin in 2012.\n \n \n \n A universal tool for stability predictions of bioth erapeutics\, vaccines and in vitro diagnostic products\n It is of particular interest for biopharmaceutical companies developing and dist ributing fragile biomolecules to warrant the stability and activity of the ir products during long-term storage and shipment. In accordance with qual ity by design principles\, advanced kinetic modeling (AKM) has been succes sfully used to predict long-term product shelf-life and relies on data fro m short-term accelerated stability studies that are used to generate Arrhe nius-based kinetic models that can\, in turn\, be exploited for stability forecasts. The AKM methodology was evaluated through a cross-company persp ective on stability modeling for key stability indicating attributes of di fferent types of biotherapeutics\, vaccines and biomolecules combined in i n vitro diagnostic kits. It is demonstrated that stability predictions up to 3 \;years for products maintained under recommended storage conditi ons (2&ndash\;8 \;°\;C) or for products that have experienced tempe rature excursions outside the cold-chain show excellent agreement with exp erimental real-time data\, thus confirming AKM as a universal and reliable tool for stability predictions for a wide range of product types.\n \n \n \n \n  \;\n  \;\n  \;\n \n \n  \;Bern ard Francq\, GSK\n \n \n \n \n \n \n \n Bernard driv es statistical innovation at GSK for CMC projects worldwide and fosters co llaborations with industry and health authorities. He holds MSc degrees in Molecular Biology Engineering\, and Industrial Statistics\, along with a PhD in Statistics.\n He has earned several international prizes for his research and excellence in technical communication. He is the pri ncipal author of the award-winning paper on tolerance intervals in bridgin g studies (Stat in Med\, 2020)\, and (co)-authored two of Wiley&rsquo\;s m ost downloaded papers (Stat in Med\, 2019\; Analytical Science Advances\, 2022). He also created the R packages BivRegBLS (for method comparison stu dies) and AccelStab.\n Bernard participates in IQ Pharma workin g groups\, serves on scientific committees (e.g.\, the non-clinical statis tics conference in Europe)\, and sits on the board of directors of ENBIS ( European Network for Business and Industrial Statistics).\n His research focuses on design of experiments\, (non)-linear mixed models\, t olerance intervals\, and (accelerated) stability analysis. He is passionat e about sharing his expertise\, mentoring (PhD) students\, and delivering innovative statistical training.\n \n \n Accelerated stability studies: a hybrid frequentist-Bayesian approach\n Accelerated stability studies model the degradation of biological drug products using arbitrary order kinetics\, which are superior to the traditional Arrhenius plot. We compare the delta method\, resampling techn iques\, and a hybrid frequentist-Bayesian approach\, with the latter offer ing the best coverage probabilities and ease of implementation. Case studi es will be demonstrated using the R package AccelStab.\n \n \n \n  \;\n  \;\n &nbs p\;\n \n \n  \;Thomas Zahel\, \;Kö\;r ber-Pharma\n Thomas Zahel is Head of CMC Innovation Consulting at Kö\;rber. He holds a master&rsquo\;s degree in Biochemical Engineer ing from the Technical University of Graz and a PhD in applied statistics from Vienna Technical University. He has expert knowledge in theory and im plementation of a multitude of statistical disciplines and long experience in developing statistical workflows for process characterization.\n \n Advanced Hybrid Kinetic Modelling Using Physics-Inform ed AI for Stability Data\n Stability data in drug development i s inherently non-linear and often influenced by complex\, poorly understoo d factors beyond temperature. We present a novel hybrid modelling approach using neural ODEs that integrates physics-informed AI to capture hidden k inetic effects&mdash\;such as pH or material variability&mdash\;offering g reater flexibility and predictive power across the product lifecycle.\n \n \n \n\n DTEND:20251021T153000Z DTSTAMP:20260608T173538Z DTSTART:20251021T140000Z LOCATION: SEQUENCE:0 SUMMARY:Stability Modelling: New Tools and Approaches UID:RFCALITEM639165369381449070 X-ALT-DESC;FMTTYPE=text/html:Date: Tuesday 21st October 20 25
\nTime: \;14:00-15:30 BST | 15:00-16:30 CEST< br />\nLocation: \;Online via Zoom
\nSpe akers: \;Warren Roche (Sanofi)\, Bernard Francq (GSK) and  \;Thomas Zahel (Kö\;rber-Pharma) \;
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\nWho is this event intended for?: \;Statisticians and inter ested parties working in the CMC and Manufacturing area of Pharmaceutical Industry.
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\nWhat is the benefit of attending?: Presentation and active discussion of technical statistical topics in t his field.
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Cost

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This webinar is free to both Members o f PSI and Non-Members.

\n

Registration

\n

To register for this event\, please < strong>click here

\n

Overview

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Webinar dedicated to the topic of stability modelling\; opportunity to hear from statisticians wor king in the CMC field\, with open question and answers. Brought to you by the CMC Statistical Network Europe (CSNE) SIG.

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Speaker details\n\n
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END:VEVENT END:VCALENDAR
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Speaker

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Biogra phy

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Abstract

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warren-rocheWarren Roche\, Sanofi

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Warren Roche is from Waterford\, Ireland. Warren has worked a s a mathematics and statistics lecturer previously at the South East Techn ological University in Ireland\, and also has extensive statistical experi ence in clinical trial research and pharmaceutical manufacturing. He origi nally earned his BSc in Mathematics from Trinity College Dublin in 2012.

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A universal tool for stability predictions of biotherapeutics\, va ccines and in vitro diagnostic products

\n < p>It is of particular interest for biopharmaceutical companies developing and distributing frag ile biomolecules to warrant the stability and activity of their products d uring long-term storage and shipment. In accordance with quality by design principles\, advanced kinetic modeling (AKM) has been successfully used t o predict long-term product shelf-life and relies on data from short-term accelerated stability studies that are used to generate Arrhenius-based ki netic models that can\, in turn\, be exploited for stability forecasts. Th e AKM methodology was evaluated through a cross-company perspective on sta bility modeling for key stability indicating attributes of different types of biotherapeutics\, vaccines and biomolecules combined in in vitro diagn ostic kits. It is demonstrated that stability predictions up to 3 \;ye ars for products maintained under recommended storage conditions (2&ndash\ ;8 \;°\;C) or for products that have experienced temperature excurs ions outside the cold-chain show excellent agreement with experimental rea l-time data\, thus confirming AKM as a universal and reliable tool for sta bility predictions for a wide range of product types.

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 \;MySelf2Bernard Francq\, GSK< /em>\n \n \n \n \n
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Bernard drives statistical innovation at GSK for C MC projects worldwide and fosters collaborations with industry and health authorities. He holds MSc degrees in Molecular Biology Engineering\, and I ndustrial Statistics\, along with a PhD in Statistics.

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He has earned several international prizes for his research and excellenc e in technical communication. He is the principal author of the award-winn ing paper on tolerance intervals in bridging studies (Stat in Med\, 2020)\ , and (co)-authored two of Wiley&rsquo\;s most downloaded papers (Stat in Med\, 2019\; Analytical Science Advances\, 2022). He also created the R pa ckages BivRegBLS (for method comparison studies) and AccelStab.

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Bernard participates in IQ Pharma working groups\, serves on sci entific committees (e.g.\, the non-clinical statistics conference in Europ e)\, and sits on the board of directors of ENBIS (European Network for Bus iness and Industrial Statistics).

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His research focuses on design of experiments\, (non)-linear mixed models\, tolerance interval s\, and (accelerated) stability analysis. He is passionate about sharing h is expertise\, mentoring (PhD) students\, and delivering innovative statis tical training.

\n 		\n

A ccelerated stability studies: a hybrid frequentist-Bayesian approach

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Accelerated stability studies model the degradation of biologica l drug products using arbitrary order kinetics\, which are superior to the traditional Arrhenius plot. We compare the delta method\, resampling tech niques\, and a hybrid frequentist-Bayesian approach\, with the latter offe ring the best coverage probabilities and ease of implementation. Case stud ies will be demonstrated using the R package AccelStab.

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&nb sp\; \; \;
 \;Thomas Zahel\, \;Kö\;rber-Pharma Thomas Zahel is Head of CMC Innovation Consulting at Kö \;rber. He holds a master&rsquo\;s degree in Biochemical Engineering from the Technical University of Graz and a PhD in applied statistics from Vien na Technical University. He has expert knowledge in theory and implementat ion of a multitude of statistical disciplines and long experience in devel oping statistical workflows for process characterization.\n

Advanced Hybrid Kinetic Modelling Using Phys ics-Informed AI for Stability Data

\n

Stability data in drug d evelopment is inherently non-linear and often influenced by complex\, poor ly understood factors beyond temperature. We present a novel hybrid modell ing approach using neural ODEs that integrates physics-informed AI to capt ure hidden kinetic effects&mdash\;such as pH or material variability&mdash \;offering greater flexibility and predictive power across the product lif ecycle.

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