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Contains 1 Component(s) Includes a Live Web Event on 12/09/2026 at 12:00 PM (EST)
Etentamig is a BCMA x CD3 bispecific antibody in development for RRMM and AL amyloidosis. The webinar will showcase the MIDD strategies that guided key decisions and advancements: (1) optimal dosing regimen selection for RRMM, including step-up dosing via exposure-response and PK/IL6/CRS analyses; (2) demonstration of no DDIs via an IL-6 PBPK model; (3) repriming/restart therapy guidance after dosing delays using PK simulations; and (4) interplay between sBCMA, free, and total PK using a semi-mechanistic PK/PD model to recommend free PK assay only in future studies. Overall, MIDD successfully guided optimal dosing regimen selection and key regulatory decisions for etentamig. The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
Etentamig is a BCMA x CD3 bispecific antibody in development for RRMM and AL amyloidosis. The webinar will showcase the MIDD strategies that guided key decisions and advancements: (1) optimal dosing regimen selection for RRMM, including step-up dosing via exposure-response and PK/IL6/CRS analyses; (2) demonstration of no DDIs via an IL-6 PBPK model; (3) repriming/restart therapy guidance after dosing delays using PK simulations; and (4) interplay between sBCMA, free, and total PK using a semi-mechanistic PK/PD model to recommend free PK assay only in future studies. Overall, MIDD successfully guided optimal dosing regimen selection and key regulatory decisions for etentamig.
The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
$i++ ?>Akshanth Polepally
Research Fellow, Director
Abbvie
Dr. Akshanth Polepally is a Research Fellow and Director at AbbVie with over 15 years of experience in drug discovery, clinical pharmacology, and model-informed drug development (MIDD). At AbbVie, he leads efforts in optimal dose selection and the design and execution of clinical pharmacokinetic and pharmacology studies. He has contributed to multiple successful drug approvals and plays a key role in advancing dose optimization strategies across clinical development programs.
$i++ ?>Benjamin Englehardt
Associate Director, Pharmacometrics
Abbvie
Dr. Benjamin Engelhardt is an Associate Director in Pharmacometrics at AbbVie. Over his nine years at AbbVie, he has led the oncology pharmacometrics team and contributed to multiple successful regulatory submissions, applying methods ranging from exposure-response analyses to advanced model-informed drug development. Beyond industry, he is a lecturer at multiple universities, a reviewer for journals including CPT and Nature, and a regular contributor to major scientific conferences and consortia.
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Contains 1 Component(s) Includes a Live Web Event on 12/03/2026 at 11:00 AM (EST)
Transcription factors are important molecules which control the levels of mRNA and proteins within cells by modulating the process of transcription and hence translation. Transcription factors are part of a wider family of molecular interaction networks known as gene regulatory networks (GRNs) which play an important role in key cellular processes such as cell division and apoptosis (e.g. the p53-Mdm2, NFκB pathways). Transcription factors exert control over molecular levels through feedback mechanisms, with proteins binding to gene sites in the nucleus and either up-regulating or down-regulating production of mRNA. In many GRNs, there is a negative feedback in the network and the transcription rate is reduced. Typically, this leads to the mRNA and protein levels oscillating over time and also spatially between the nucleus and cytoplasm. When experimental data for such systems is analyzed, it is observed to be noisy and in many cases the actual numbers of molecules involved are quite low. In order to model such systems accurately and connect with the data in a quantitative way, it is therefore necessary to adopt a stochastic approach as well as take into account the spatial aspect of the problem. In this talk, we present both deterministic and stochastic spatio-temporal models of both observed GRNs and synthetic GRNs e.g. repressilators and activator-repressor systems.
Transcription factors are important molecules which control the levels of mRNA and proteins within cells by modulating the process of transcription and hence translation. Transcription factors are part of a wider family of molecular interaction networks known as gene regulatory networks (GRNs) which play an important role in key cellular processes such as cell division and apoptosis (e.g. the p53-Mdm2, NFκB pathways). Transcription factors exert control over molecular levels through feedback mechanisms, with proteins binding to gene sites in the nucleus and either up-regulating or down-regulating production of mRNA. In many GRNs, there is a negative feedback in the network and the transcription rate is reduced. Typically, this leads to the mRNA and protein levels oscillating over time and also spatially between the nucleus and cytoplasm. When experimental data for such systems is analyzed, it is observed to be noisy and in many cases the actual numbers of molecules involved are quite low. In order to model such systems accurately and connect with the data in a quantitative way, it is therefore necessary to adopt a stochastic approach as well as take into account the spatial aspect of the problem. In this talk, we present both deterministic and stochastic spatio-temporal models of both observed GRNs and synthetic GRNs e.g. repressilators and activator-repressor systems.
$i++ ?>Mark Chaplain
Gregory Chair, Applied Mathematics
University of St. Andrews
Mark Chaplain is the Gregory Chair of Applied Mathematics at the University of St. Andrews. He received his Ph.D. in mathematics from the University of Dundee in 1990 and has been actively working mathematical biology with an emphasis on oncology since then. During this time he has published over 300 research articles and books.
Additional details can be found at:
https://research-portal.st-and...-
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Contains 1 Component(s) Includes a Live Web Event on 11/04/2026 at 12:00 PM (EST)
The ICH M15 Guideline “General Principles for MIDD” stresses the importance of performing model evaluation targeting the Question of Interest (QoI) that model is intended to help to answer. In this presentation we elaborate on how reference corrected visual predictive check (rcVPC) methodology can be used for this purpose. The rcVPC can provide an efficient and more easily communicable tool to validate models, increasing confidence in model-informed decision-making among broader, non-modeling stakeholders. The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
The ICH M15 Guideline “General Principles for MIDD” stresses the importance of performing model evaluation targeting the Question of Interest (QoI) that model is intended to help to answer. In this presentation we elaborate on how reference corrected visual predictive check (rcVPC) methodology can be used for this purpose. The rcVPC can provide an efficient and more easily communicable tool to validate models, increasing confidence in model-informed decision-making among broader, non-modeling stakeholders.
The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
$i++ ?>Moustafa Ibrahim
Global Clinical Pharmacology Lead
Astrazeneca
Moustafa M. A. Ibrahim obtained his Ph.D. in Pharmacometrics from Uppsala University, Sweden. Following his Ph.D., Moustafa joined Pharmetheus AB as MIDD Consultant, where he provided pharmacometrics expertise across the spectrum of drug development, from non-clinical studies through late-stage clinical development and regulatory submissions. In 2024, Moustafa joined the Clinical Pharmacology and Safety Sciences Department at AstraZeneca, within the Rare Disease Unit, as a Global Clinical Pharmacology Lead. In this role, he provides scientific and strategic leadership for multiple global development programs to inform dose selection, optimize study design, support regulatory interactions, and enable data-driven decision-making throughout clinical development.
$i++ ?>Martin Bergstrand
Principal Consultant and MIDD Platform Science Lead
Pharmetheus
Martin obtained his PhD in Pharmacometrics from Uppsala University. He has 20+ years of drug development experience in areas such as metabolic disorders, autoimmune disease, infectious disease, hematological disorders etc. In 2012 Martin co-founded the consulting company Pharmetheus AB. In the consultant role he has been engaged as strategic advisor on behalf of multiple clients and acted as the main responsible consultant for 50+ pharmacometric data analysis projects on behalf of more than 20 different clients. The projects have ranged from pre-clinical translational projects to submission ready large-scale phase III PKPD analysis. These analyses have among other things contributed to 5+ successful NDA filings.
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Contains 1 Component(s) Includes a Live Web Event on 09/23/2026 at 12:00 PM (EDT)
IVIG co-administration with monoclonal-antibodies/bispecifics is common across autoimmunity, immunodeficiencies, and transplantation. These therapies undergo FcRn-mediated recycling, raising potential for PK-PD interactions. Mechanistic IgG-disposition model utilized to investigate how IVIG dose/timing, and IgG dynamics influence IgG behavior and PK/PD outcomes. Model well-described total/endogenous-IgG kinetics across autoimmune/transplantation. It recapitulated reduced tesidolumab exposure with IVIG in transplantation, explaining associated PD alterations. Model examined IVIG supplementation in multiple-myeloma receiving teclistamab, and rituximab-IVIG co-therapy for transplant desensitization. Simulations revealed IVIG co-therapy alters mAb PK-PD depending on IVIG-regimen, IgG-pool and exposure-response-relationship of the mAb. Model provides mechanistic framework for MIDD and prospective management of IgG interactions. The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
IVIG co-administration with monoclonal-antibodies/bispecifics is common across autoimmunity, immunodeficiencies, and transplantation. These therapies undergo FcRn-mediated recycling, raising potential for PK-PD interactions. Mechanistic IgG-disposition model utilized to investigate how IVIG dose/timing, and IgG dynamics influence IgG behavior and PK/PD outcomes. Model well-described total/endogenous-IgG kinetics across autoimmune/transplantation. It recapitulated reduced tesidolumab exposure with IVIG in transplantation, explaining associated PD alterations. Model examined IVIG supplementation in multiple-myeloma receiving teclistamab, and rituximab-IVIG co-therapy for transplant desensitization. Simulations revealed IVIG co-therapy alters mAb PK-PD depending on IVIG-regimen, IgG-pool and exposure-response-relationship of the mAb. Model provides mechanistic framework for MIDD and prospective management of IgG interactions.
The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
$i++ ?>Paridhi Gupta
Research Investigator, Clinical Pharmacology-Early Oncology Group
Bristol Myers Squibb
Dr. Paridhi Gupta is a Research Investigator in the Clinical Pharmacology–Early Oncology group at Bristol Myers Squibb. She earned her Ph.D. in Pharmaceutical Sciences with a specialization in Pharmacometrics from the University of Tennessee Health Science Center under the mentorship of Prof. Bernd Meibohm. Paridhi has completed internships at Merck, Bristol Myers Squibb, and Johnson & Johnson, gaining broad experience in leveraging modeling and simulation to support preclinical and clinical drug development.
$i++ ?>Vivaswath Ayyar
R&D Innovation Director, Translational Medicine; Adjunct Asst Professor, Pharmaceutical Sciences
GSK, University of Buffalo
Dr. Vivaswath Ayyar is the R&D Innovation Director for Translational Medicine at GSK and Adjunct Assistant Professor of Pharmaceutical Sciences at the University at Buffalo. His work focuses on advancing innovative therapeutics through translational science and model-informed approaches, leveraging causal data analytics and mechanistic platform modeling to inform decision-making across the R&D stages for emerging modalities, including advanced biologics and nucleic acid medicines. Prior to GSK, he spent six years at Johnson & Johnson, where him and his team built and leveraged mechanistic and/or systems pharmacology models to inform the biologics and oligonucleotide portfolios across disease areas.
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Contains 1 Component(s) Includes a Live Web Event on 09/08/2026 at 10:00 AM (EDT)
The ISoP QSP SIG is hosting its annual fully-student-focused Virtual Student QSP Symposium on Sep 8th, 2026. This event allowed current students and trainees to learn about training and career paths and share their work with each other and professionals in the field. The Symposium featured a stellar line-up of speakers and panelists from industry and academia.
The ISoP QSP SIG is hosting its annual fully-student-focused Virtual Student QSP Symposium on Sep 8th, 2026. This event allowed current students and trainees to learn about training and career paths and share their work with each other and professionals in the field. The Symposium featured a stellar line-up of speakers and panelists from industry and academia.
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Contains 1 Component(s) Includes a Live Web Event on 08/26/2026 at 12:00 PM (EDT)
Pediatric dose optimization is constrained by small cohorts and sampling limits. We applied Bayesian Forecasting to select the RP2D for pediatric patients with ALK-fusion tumors. An established PopPK model using adult data as prior in combination with real-time PK monitoring during Cycle 1 guided dose confirmation and/or adjustments. Doses were selected to match the adult steady-state therapeutic exposures. Model‑predicted doses achieved target exposure without adjustment in all 14 patients ≥20kg; 4/5 patients
Pediatric dose optimization is constrained by small cohorts and sampling limits. We applied Bayesian Forecasting to select the RP2D for pediatric patients with ALK-fusion tumors. An established PopPK model using adult data as prior in combination with real-time PK monitoring during Cycle 1 guided dose confirmation and/or adjustments. Doses were selected to match the adult steady-state therapeutic exposures. Model‑predicted doses achieved target exposure without adjustment in all 14 patients ≥20kg; 4/5 patients <20kg required up-titration. Bayesian borrowing of adult knowledge enabled efficient pediatric dose optimization and rapid confirmation by improving the accuracy of exposure predictions across weight bands.
The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
$i++ ?>Tu Mai
Senior Principal Scientist, Clinical Pharmacology, Modeling & Simulation
Genentech
Tu Mai is a Senior Principal Scientist in Clinical Pharmacology, Modeling & Simulation at Genentech, where she leads clinical pharmacology and modeling and simulation strategies across multiple early and late-stage development programs. She has extensive experience in model-informed drug development (MIDD), including population PK/PD modeling, Bayesian forecasting, exposure-response analysis, and MIDD strategies to support regulatory submissions and dose optimization. Her work spans ophthalmology, oncology, immunology in small molecules and biologics. Tu received her Ph.D. in Pharmacology from Vanderbilt University.
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Contains 1 Component(s) Includes a Live Web Event on 07/21/2026 at 12:00 PM (EDT)
A model-based dose selection and pharmacokinetic (PK) bridging approach was applied to support development of pembrolizumab SC (pembrolizumab with berahyaluronidase alfa for subcutaneous administration) from intravenous (IV) administration. Methodology, results and conclusions will be discussed in this presentation. The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
A model-based dose selection and pharmacokinetic (PK) bridging approach was applied to support development of pembrolizumab SC (pembrolizumab with berahyaluronidase alfa for subcutaneous administration) from intravenous (IV) administration. Methodology, results and conclusions will be discussed in this presentation.
The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
$i++ ?>Gina Song
Gina Song is a Director in the Oncology Global Clinical Development organization, Quantitative Pharmacology and Pharmacometrics (QP2) function at Merck. She has over 10 years of experiences in the Pharmaceutical industry across therapeutic areas including preclinical and clinical oncology, infectious disease and pediatric development for different modalities with time spent at Hamner Institute, Labcorp and currently Merck. She is currently leading SC pembrolizumab program for clinical pharmacology and modeling &simulation efforts across indications as well as supporting regulatory submissions in global markets.
$i++ ?>Mallika Lala
Mallika Lala is Senior Director, Group Leader at Merck in the Oncology Global Clinical Development organization, Quantitative Pharmacology and Pharmacometrics function. She has 15 years of drug development experience across therapeutic modalities, including early and late clinical oncology, infectious diseases and CV-met. She has been involved with the clinical development of pembrolizumab across indications and regulatory submissions in several global markets, most recently MIDD for dosing regimen and SC formulation additions, as well as multiple oncology assets including ADCs and targeted therapies. Before joining Merck, in industry in India to advancing pharmacometrics and was an ORISE fellow at FDA with focus on application of innovative quantitative approaches to enhance pediatric drug development.
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Contains 1 Component(s) Recorded On: 05/28/2026
This talk will cover how to evaluate and optimize clinical trial designs using the Fisher Information Matrix (FIM), as implemented in tools like NONMEM's $DESIGN and PopED. While clinical trial simulation is a powerful approach for assessing design characteristics, such as model identifiability, parameter precision, and even type I error and power, FIM-based evaluation offers a faster alternative that enables exploration of many more designs and makes true design optimization feasible. A number of examples will be presented to show how design evaluation and optimization can be useful in a model-informed drug development context. Robust design techniques that account for uncertainty in models and model parameters will also be discussed.
This talk will cover how to evaluate and optimize clinical trial designs using the Fisher Information Matrix (FIM), as implemented in tools like NONMEM's $DESIGN and PopED. While clinical trial simulation is a powerful approach for assessing design characteristics, such as model identifiability, parameter precision, and even type I error and power, FIM-based evaluation offers a faster alternative that enables exploration of many more designs and makes true design optimization feasible. A number of examples will be presented to show how design evaluation and optimization can be useful in a model-informed drug development context. Robust design techniques that account for uncertainty in models and model parameters will also be discussed.
The MIDD Webinar Series, coordinated by Yash Kapoor and Fulya Akpinar Singh, is a series of webinars focused on shaping the future of drug development and regulatory decision-making sponsored by the ISoP Education Committee. Topics range from MIDD approaches in regulatory submission to pharmacometrics topics that are at the core of model development.
$i++ ?>Andrew Hooker, PhD, ISOP member
Professor of Pharmacometrics
Uppsala University
Andrew C. Hooker, PhD, is a Professor of Pharmacometrics at Uppsala University, Sweden. Andrew received a BS in Physics with a Mathematics Minor at the University of Colorado and received a Masters and then a PhD in Bioengineering from the University of Washington, Seattle. Andrew joined the faculty at Uppsala University in 2006. His research ranges between methodological and applied pharmacometrics, including: optimal (adaptive) experimental design, methodological problems associated with building, evaluating and using pharmacometric models (including using models for bioequivalence evaluation) and the development and use of PKPD models in a range of therapeutic areas and drug classes. Andrew is a co-developer of a number of software programs including Xpose, PsN, Pharmpy and the optimal design program PopED. Andrew has published over 90 papers in peer reviewed journals, supervised 12 students to their PhD degree and mentored 11 post-docs. In 2012, he co-founded the model-informed drug development consultancy company Pharmetheus.
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Contains 1 Component(s) Recorded On: 04/27/2026
This session provides Working Group updates, two presentations and a panel discussion.
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Chair(s): Blerta Shtylla
Federico Reali: Working Group Updates
Alexander Kulesza: The Landscape of QSP Modelling and Virtual Populations in the AI Era: From Current to Best Practice
Conner I. Sandefur: AI-Ready QSP: How Emerging Standards can Support Transparency, Credibility, and Future Regulatory Use
Alexander Kulesza, Conner I. Sandefur, Federico Reali: Panel Discussion: AI, Reporting, and Trust in QSP Modelling$i++ ?>Blerta Shtylla, PhD
Research Fellow Pharmacometrics & Systems Pharmacology
Pfizer Research and Development
$i++ ?>
Federico Reali
Fondazione The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI)
Federico Reali, PhD, is Group Leader of the Quantitative Systems Pharmacology (QSP) group at Fondazione The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI). His expertise is in systems biology and QSP modeling applied to drug development across multiple therapeutic areas, including neurodegenerative disorders and lysosomal storage diseases. He leads and coordinates multidisciplinary research teams and collaborates with pharmaceutical companies and non-profit organizations on translational QSP projects. He is also a Teaching Fellow at the University of Trento, where he teaches probability and statistics and supervises undergraduate and graduate students. Federico Reali serves as Vice President of the Scientific Committee of the Italian National Life Sciences Cluster ALISEI. His current interests focus on using quantitative models, digital twins, and data-driven approaches to support clinical decision-making, therapeutic stratification, and the translation of complex biological data into clinically meaningful insights.
$i++ ?>Alexander Kulesza, PhD
Principal Scientist
ESQLabs
Alexander is a Chemist with a PhD focusing on theoretical and computational methods for structural and optical property predictions. He then spent several years in academia (U. of Lyon) working on molecular dynamics simulation and free energy methods dedicated to protein structure and aggregation. Alex moved to systems pharmacology applying large-scale disease and quantitative systems pharmacology models integrated into clinical trial simulations, across a number of disease areas. Alex is now leading the QSP team within ESQlabs with the aim to promote widespread application of integrated PBPK and QSP modeling. He is also currently affiliated at the pharmacy Department of University of Namur, working towards better qualifying PBPK/QSP for regulatory decision making.
$i++ ?>Conner Sandefer
Simulations Plus
Conner Sandefur, PhD, is a Senior Scientist in QSP Solutions at Simulations Plus, where he develops mechanistic, systems-based models to support client decision-making and model‑informed drug development. His work focuses on injury and repair dynamics and nonlinear disease processes, with an emphasis on transparent, mechanism‑first model design that strengthens credibility across QSP applications.
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Contains 1 Component(s) Recorded On: 04/27/2026
This session provides a Working Group update and two presentations.
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Chair(s): Prakash Packrisamy, Vincent Hurez
Prakash Packrisamy, Vincent Hurez: Working Group Update: Addressing Modeling Challenges in QSP: Survey-Based Perspectives on Preclinical Data Handling
Anuraag Saini: Addressing the QSP Knowledge Bottleneck with AI
Xiao Qiu, Lu Huang: From Biology to Scores in Ulcerative Colitis: A QSP Platform Powered by Temporal Machine Learning$i++ ?>Prakash Packrisamy
$i++ ?>Vincent Hurez
$i++ ?>Anuraag Saini
$i++ ?>Xiao Qiu
$i++ ?>Lu Huang
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