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PHUSE EU Connect 2025

16/11/2025 - 19/11/2025
Congressplatz 1, 20355 Hamburg
PHUSE EU Connect 2025 brings together leading minds from the fields of life sciences, clinical research and data analysis in Hamburg from November 16 to 19. The international conference is regarded as a catalyst for exchange on regulatory topics, new technologies and data-driven innovations in drug development.

The event stands for open knowledge transfer, practical insights and lively dialog. This is why HMS will be there again this year - with our own contributions and exciting insights into our project work.

Visit us at our booth or experience us live on stage - we look forward to the opportunity to exchange ideas!
To the official PHUSE EU Connect website

Our presentations

Generative AI (GenAI) is in full hype, but it can be difficult to determine whether it is the right solution for your challenges, especially within the complex workflows and regulatory pipelines of the pharmaceutical industry.

In this beginner-friendly session, we will provide practical guidance to help you navigate this decision. We will start by clearly distinguishing between classical (or “discriminative”) AI and generative AI, and explore which types of problems are best suited for each approach. Using real-world pharmaceutical examples, we will explain how GenAI models are leveraged and what must be built around a model to solve a use case. In addition, we will explore strategies to operationalize such use cases, from self-service platforms to a distributed system of GenAI tools via MCP Servers.

This session is ideal for newcomers to GenAI and decision-makers looking to confidently integrate AI into real business processes.
Project "Poseidon" aims to streamline regulatory screening of HA websites at Merck Healthcare, where SMEs currently spend a lot of effort dedicated to this task including manually screening for relevant documents and triage for priorities. By developing an AI/Machine Learning (ML) system to automatically screen updates from international Health Authorities (HAs), Poseidon will reduce manual efforts and allow to reallocate these efforts on more strategic activities. This initiative will enhance efficiency, minimize human error, and create a knowledge repository, ultimately improving regulatory compliance and providing comprehensive assessments of regulatory impacts. Scalability: The system should be scalable to different healthcare and life science departments (e.g. regulations' scope of screening covering clinical, medical devices, manufacturing, safety). Reduction in Time Spent on Regulatory Screening: A measurable decrease in the time spent by business SMEs on regulatory screening activities is expected.
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Programming specifications and in particular ADaM specifications consolidate analysis and trial-specific information, as well as industry-wide standards to allow for effective comparison of results across trials. Delivering analysis packages for clinical trials requires a solid understanding of protocol and statistical analysis plan (SAP) to deliver statistical analysis based on the necessary variables and datasets, described in the programming specifications. Specifications creation is usually a time-consuming task, that requires manual input, which makes it difficult to standardize metadata across trials. We introduce a tool called Smart Assistant for Metadata and Biostatistics Analysis (SAMBA) to assist statistical programmers and accelerate the creation of ADaM specifications, while leveraging existing study documents. SAMBA leverages large language models (LLM) to automate the creation of ADaM specifications. The tool thus reduces effort when creating or updating ADaM specs. We discuss the tool’s architecture, development process, feedback gathered from users and point to future avenues of development.
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While in the past SAS has been the de facto standard for the statistical analysis of clinical trials, in recent years a growing portion of the industry has had their eyes on open-source alternatives. Arguably the most popular is the programming language R. Boehringer Ingelheim established a ClinPharm task force for the transition from SAS to R supported by a team of experts from HMS.

Here, we present our joint effort for the migration of a collection of SAS macros and templates in the context of PK/PD analyses into R using GenAI to streamline the process. We discuss the different approaches we piloted including direct translation as well as utilizing existing packages of the pharmaverse and the pros and cons of each approach.

Finally, we discuss both the advantages and limitations of using GenAI in this context and the need for a guiding framework to successfully leverage its capabilities.
Getting from feature requests or bug reports to the next validated package release in an agile fashion is the vision of many R package product owners, developers, validation managers and users. Add further colleagues from quality departments, deployment pipeline operations and management to the list of stakeholders and we see that the topic heavily relies on alignment of people and processes in addition to tools. We present how the tooling landscape for managing software development can be set up with sophisticated use of the technical possibilities offered by platforms such as GitLab, Jira, Azure DevOps and Github. They include workflows, issue statuses, labels, scoped labels, tags, components and timing related iterations, sprints, and milestones. However, efficient configuration and use of those options is the art to master for effective tracking of development and validation activities that involve many review steps.
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Our speaker

Dr. Robert Bauer

Senior AI Engineer

Robert Bauer works as a Senior AI Engineer at HMS Analytical Software GmbH in the Data Science and Business Intelligence Department. As the Lead Expert for AI-assisted code migration, he has contributed to numerous projects focused on modernizing program code, such as migrations to R, Python, and PySpark. Additionally, Dr. Bauer drives the development of various in-house tools for code migration used at HMS. These include the solutions for automatic migration from SAS to R discussed in the poster session. 

Christoph Bergen

Team Lead GenAI

Christoph Bergen studied mathematics and currently serves as a Senior Data Scientist and Team Lead GenAI at HMS Analytical Software. He collaborates with a diverse range of clients, leveraging machine learning and data science techniques to extract valuable insights from their data. His work includes all aspects of modern data science - from traditional model training to constructing scalable machine learning pipelines.Recently, he has been consulting clients in harnessing the potential of Generative AI models to enhance their data-driven processes.

To the LinkedIn profile of Christoph Bergen

Sophia Stahl-Toyota

Software Engineer for Life Science

Sophia Stahl-Toyota is a Software Engineer at HMS Analytical Software GmbH and co-chair of the life science competence center. She actively continues development of the R package “TLGcat” (Tables, Listings, Graphics catalog) that was presented at PhUSE EU Connect 2024. 

To the LinkedIn profile of Sophia Stahl-Toyota

 

Fabian Wahren

AI Engineer

Fabian Wahren is a Data Scientist at HMS Analytical Software GmbH. With a background in Mechanical Engineering and a master’s degree in Autonomous Systems and Robotics, he brings solid expertise in machine learning and artificial intelligence. His international academic and project experience has given him a strong understanding of data-driven processes and interdisciplinary collaboration.

To the LinkedIn profile of Fabian Wahren.

Nicolai Henrichs
Account Manager

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