Booths #8 and #9

Date: Jun 4-6, 2025

Location: Thessaloniki Concert Hall, Thessaloniki, Greece

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Join us at our booth and discover how our innovative solutions can transform your business operations and drive success. Our team of brilliant scientific minds will be on hand to showcase our latest offerings, including cutting-edge technologies and services designed to enhance efficiency and productivity.

Explore our interactive demos, participate in engaging discussions, and learn how we can help you achieve your goals. Whether you're looking to streamline your processes, improve customer engagement, or gain valuable insights through data analytics, we have something for you.

Don't miss out on this opportunity to connect and see firsthand how we can support your business's growth and success. We look forward to meeting you!

Register for our exclusive pre-conference workshops:

• Scientific Modeling Augmented by Machine Learning with DeepPumas

June 2-3, 2025 • Click here to register!

This workshop will give participants practical skills in hybrid mechanistic and machine learning modeling, a comprehension of how complex covariates can help forecast longitudinal outcomes, and an insight into the possible implications of this technology.

• Nonlinear Mixed Effects Modeling Workflows using Pumas

June 3, 2025 • Click here to register!

This workshop provides a deep dive into Pumas, a powerful pharmacometric platform designed for modeling and simulation in drug development. Participants will gain hands-on experience and knowledge of the standard workflows in population pharmacokinetics (PK) and sequential PKPD modeling. Experts will guide attendees through various stages of model building, diagnostics, and data wrangling, with opportunities to explore specialized areas like absorption models, using non-Gaussian random effects.

Podium Presentations:

• Free-form text as an NLME covariate: how Embedding models enable effective use of predictive factors from complex data

Speaker: Niklas Korsbo, PhD

“In order for generative AI to respond meaningfully to the information you prompt it with, it needs to first extract a machine-intelligible and informative representation of the prompt you provided. In this talk, we'll show how such an informative representation of your data, sometimes called an "embedding", can be used directly in Nonlinear Mixed Effect models. With this, we can leverage predictive factors from complex covariates to update our individualized outcome and drug-response predictions. As an example, we'll showcase how free-form textual patient self-assessments can be effectively used as NLME covariates. By leveraging pre-trained machine learning models, we can make this effective even for small data sets (N<100), and since embedding models provide similar outputs for different modalities of input, our results are easily extensible from text to images and other data modalities. This paves an effective way for leveraging complex patient covariates (and the massive amount of effort that the ML community have already put into being able to process such data) to improve predictive analytics and to learn more from the data we have.”

• A DeepNLME framework for modeling ordinal data to describe disease progression in patients with Alzheimer’s disease

Speaker: Christos Kaikousidis

“This talk focuses on developing a streamlined workflow for modeling ordinal data using Deep Nonlinear Mixed Effects (DNLME) models, with the aim of identifying baseline covariates and biomarkers that enhance predictive performance. While our primary application is on Clinical Dementia Rating (CDR) scores to model disease progression in Alzheimer's patients, the approach is generalizable to any domain involving multidimensional ordinal scores.”

Poster Presentations:

1. Population Pharmacokinetic Analysis Supporting Fixed and Extended-Interval Dosing of Balstilimab Alone and Combined with Botensilimab in Advanced Solid Tumors | Presenting Author: Mélanie Wilbaux, PhD
2. Neural ODE-Based Framework for Modeling Delayed and Multi-Phase Drug Absorption | Presenting Author: Sreenath Krishnan, PhD
3. Population Pharmacokinetic and Exposure-Response Modeling of Mavacamten in Hypertrophic Cardiomyopathy: Impact of Japanese Ethnicity | Presenting Author: Asma Baliouze, PharmD
4. Generalized FOCE for Discrete Response Models with Pumas | Presenting Author: Hailemichael Hishe, PhD
5. Understanding the numerical issues in and instability of fits based on the laplace approximation | Presenting Author: Patrick Kofod Mogensen, PhD
6. Utilizing Typst and Quarto for Efficient Reporting in Pharmacometrics | Presenting Author: Aida Kawuma, PhD