

# Event Details

- **Event Name**: Scientific Machine Learning for Pharmacometrics with DeepPumas | Croatia
- **Event Start and End Date**: Mon, 01 Jun, 2026 at 09:00 am – Tue, 02 Jun, 2026 at 05:00 pm (+02:00)
- **Event Description**: This hands-on workshop will take us through the core concepts behind DeepPumas.About this EventOverviewThis hands-on workshop covers the integration of domain knowledge with data-driven methods in pharmacometric modeling using DeepPumas. We’ll bridge mechanistic NLME modeling with modern scientific machine learning (SciML), including Neural ODEs, Universal Differential Equations, and DeepNLME, to discover unknown dynamics, leverage rich auxiliary data through embedding models, and build individualized models while maintaining interpretability.You’ll learn how techniques from generative AI connect to random effects modeling, how SciML methods enable data-driven discovery of biological mechanisms, and how pre-trained embedding models extract prognostic information from complex data modalities. The workshop shows how these seemingly disparate techniques (Neural ODEs, DeepNLME, embeddings, and generative models) relate to each other and integrate into a coherent framework for modern pharmacometric modeling.Beyond teaching specific tools, the workshop offers perspective on the evolving landscape of pharmacometric modeling as machine learning transforms the field. It helps individual modelers upskill and strategists understand what will be important going forward.Instructors: Niklas Korsbo and Lucas PereiraWhat you will Learn:The workshop covers material from classical NLME to DeepNLME, with a focus on practical implementation and real-world applications.Day 1: From NLME to Scientific Machine Learning - Pumas Essentials: Hands-on introduction to population pharmacometric modeling with Pumas - Machine Learning Foundations: Neural networks, overfitting, regularization, and how they apply to pharmacometric problems - Scientific Machine Learning (SciML): Neural ODEs and Universal Differential Equations (UDEs) for discovering unknown dynamics in disease progression and treatment response - Random Effects Fundamentals: Understanding random effects, individual parameters, and population distributions in hierarchical models, building the theoretical foundation for DeepNLMEDay 2: DeepNLME and Intelligent Covariate Integration - Random Effects as Latent Spaces: The deep connection between NLME random effects and generative AI (GenAI), and why this matters for longitudinal modeling - DeepNLME - Conditional Generative Modeling: How DeepNLME extends SciML to hierarchical data, enabling individualization while learning from the population - Post-Hoc Covariate Integration via Augmentation: Using DeepPumas.augment to incorporate rich covariate information into existing NLME models without refitting the base model, learning how covariates predict individual parameters - Embeddings and Pre-Trained Models: Leveraging state-of-the-art pre-trained embedding models (from computer vision, NLP, and other domains) to extract prognostic information from complex data modalities (clinical text, imaging, omics) and seamlessly integrate them into NLME frameworks - Connecting the Pieces: How Neural ODEs, DeepNLME, embeddings, and augmented models work together in practiceWho Should AttendThis workshop is intended for pharmacometricians and quantitative scientists navigating the integration of machine learning into pharmacometric practice. Participants will benefit most if they:Have experience with population PK/PD or other hierarchical modelsWant to understand how modern machine learning can enhance mechanistic modelingAre interested in leveraging rich covariate data (imaging, omics, text) in their modelsSeek mathematically rigorous yet practically applicable methodsAre helping their organizations understand and adopt these emerging methodsKey TakeawaysBy the end of this workshop, you will:Understand the mathematical connections between NLME, generative AI, and scientific machine learningImplement neural-embedded dynamical systems for discovering unknown biological mechanismsApply DeepNLME to create highly individualized models for longitudinal dataIntegrate complex covariates post-hoc into existing models using conditioning approachesLeverage pre-trained machine learning models (embeddings) to extract prognostic information from diverse data modalitiesDiscover prognostic factors from high-dimensional data using machine learning within the NLME frameworkRecognize when and how to leverage these methods in your own work, understanding both their power and limitationsWhy DeepPumas?Machine learning is transforming pharmacometrics, but the path forward requires more than adopting black-box algorithms. The choice isn’t between mechanistic models specified a priori or purely data-driven approaches. Instead, we need methods that genuinely integrate both.DeepPumas enables this integration through:Modularity: Separate development of mechanistic structure and data-driven components, then seamless combinationPost-hoc flexibility: Addition of new covariates or data sources to existing models without refittingPrincipled hierarchical modeling: Leveraging population structure while respecting individual heterogeneityMaintained interpretability: Preserving mechanistic understanding where available while still leveraging machine learning’s predictive powerThese aren’t just technical conveniences. They represent a different approach to scientific modeling in an era of increasing data richness and complexity.Practical InformationFormat: Intensive hands-on workshop with mixture of lectures, live coding demonstrations, and guided exercisesPrerequisites: Familiarity with population modeling concepts; basic programming experience helpful but not requiredSoftware: All materials use Pumas/DeepPumas (Julia-based); no prior Julia experience neededMaterials: All code, data, and documentation providedWhat You’ll Take AwayThis workshop goes beyond teaching specific tools. It provides a framework for thinking about the evolving role of machine learning in pharmacometrics. You’ll gain practical skills for implementing these methods, theoretical understanding of why they work, and perspective on where the field is heading.Whether you’re looking to enhance your own modeling capabilities or help guide your organization through the ML transformation in pharma, this workshop will equip you with both the knowledge and the practical experience to move forward confidently.Pricing: $500 for Industry, $100 for AcademiaBring Your Team, Save More! Groups of 3+ qualify for a group discount. Email sales@pumas.ai to inquire.
- **Event URL**: https://allevents.in/dubrovnik/scientific-machine-learning-for-pharmacometrics-with-deeppumas-|-croatia/100001980380641810
- **Event Categories**: workshops, artificial-intelligence, it, art
- **Interested Audience**: 
  - total_interested_count: 0

## Ticket Details

- **Ticket URL**: https://consumer.pxf.io/c/1339408/3151484/39691?partnerpropertyid=1191892&MediaPartnerPropertyId=1191892&svlink=14105511&level=1&u=https%3A%2F%2Fwww.eventbrite.com%2Fe%2Fscientific-machine-learning-for-pharmacometrics-with-deeppumas-croatia-tickets-1980380641810
- **Ticket Price Range**: min: 108.55, max: 535.38, currency: USD

## Event venue details

- **city**: Dubrovnik
- **state**: DN
- **country**: Croatia
- **location**: Valamar Lacroma Hotel
- **lat**: 42.6601384
- **long**: 18.0624203
- **full address**: Valamar Lacroma Hotel, 34 Ulica Iva Dulčića, Dubrovnik, Croatia

## Event Organizer details

- **affiliate_id**: 10
- **organizer**: Pumas-AI, Inc. (https://allevents.in/org/pumas-ai-inc/17623589)

## Event gallery

- **Alt text**: banner
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- **Alt text**: thumbnail
  - **Image URL**: https://cdn-az.allevents.in/events8/banners/81a89425deb771da16bb399bfb9da5dfb1dfb66113768101f0c2395fd8939cc2-rimg-w400-h400-dcfefef8-gmir.jpg?v=1769353560

## FAQs

- **Q**: When is the event happening?
  - **A:** Mon, 01 Jun, 2026 at 09:00 am (+02:00)
- **Q**: Where is the event happening?
  - **A:** Valamar Lacroma Hotel, 34 Ulica Iva Dulčića, Dubrovnik, Croatia
- **Q**: What is the ticket price?
  - **A:** starting from 108.55 up to 535.38 USD
- **Q**: Who is organizing the event?
  - **A:** Pumas-AI, Inc.
- **Q**: What type of event is this?
  - **A:** workshops, artificial-intelligence, it, art
- **Q**: Where can I find ticket details about Scientific Machine Learning for Pharmacometrics with DeepPumas | Croatia ?
  - **A:** You can find ticket details about this event on AllEvents.

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