R Programming
Solutions
At ESQlabs, we provide comprehensive R programming solutions tailored for the Open Systems Pharmacology (OSP) Suite. As core developers of the base OSPSuite-R package and creators of the specialized esqlabsR package, we enable robust, reproducible, and regulatory-compliant workflows for Model-Informed Drug Development (MIDD) and Next Generation Risk Assessment (NGRA).
Physiologically based biopharmaceutics modeling (PBBM) is a specific field of PBPK model applications that aims to establish the link between the formulation’s properties and in vivo performance.
This field of application of PBPK modeling is evolving at a fast-pace and offers the link between in vivo and in vitro to support pharmaceutical development in the selection of the best drug substance and product, as well as later in development in the establishment of manufacturing quality and controls.
Dissolution testing is often a key input in PBBM. Results from in vitro experiments characterizing drug substances and the formulation behavior (e.g., solubility, particle size, dissolution) can be linked to key ADME parameters and integrated into full PBPK models to predict PK exposure in plasma and/or specific tissues or organs.
These models can also be linked to Pharmacodynamic (PD) relationships to derive the impact of physicochemical, drug and formulation properties on safety and efficacy. The role of Physiologically Based Biopharmaceutics Modeling (PBBM) in drug development spans multiple stages, including supporting patient-centric design, guiding life cycle management, informing regulatory submissions, streamlining development processes, optimizing dosing strategies, enhancing study design, and aiding in formulation development and developability assessment.
What we can offer
R package development for the Open Systems Pharmacology
ESQlabs is one of the leading developers of the OSPSuite R packages. We drive the innovations in the R packages landscape of the OSP, allowing more complex workflows and enabling new ways of PBK and QSP/T modelling from R. ESQlabs drives the development of such core packages as the {ospsuite}, {ospsuite.parameteridentification}, {rSharp}, and contributes to the development and maintenance of many more packages from the OSP.
{esqlabsR} – the open source solution for standardized M&S workflows
With the {esqlabsR} package, we develop and maintain a solution for standardized and self-contained M&S projects utilizing the OSP software and the R packages ecosystem. The key elements of the {esqlabsR} projects are:
End-to-end R workflows for MIDD and NGRA
We design, implement, and maintain R workflows that leverage the OSP R ecosystem to support PBK and QSP/T model development, application, and qualification. We offer:
Interactive Shiny Applications
We build custom Shiny applications that make complex models accessible to non-programmers. Examples include parameter exploration tools, decision-support dashboards, and user interfaces to in-house databases and workflows.
System / Code Qualification for GxP and GAMP5
We support the transition from research code to regulatory-grade tools. Our services include the design of qualification frameworks, automated testing, and documentation to ensure your R workflows and systems are compliant with GxP and GAMP5 standards.
Related Platforms
High-Throughput Screening and ADMET-PBPK
Large Molecules, Biologics and Novel Modalities
Small Molecules and Chemicals
QSP Disease and QST Models
Women’s Health
Digital Twins for Micro-physiological Systems: MPSlabs
Meet the Team
Anastasiia Kostiv (Ext)
Anastasiia discovered her passion for programming as a teenager, participating in Google-organized youth programming contests such as Google Code-in. She later developed an interest in data analysis and earned a Master’s degree in Data Analytics. Anastasiia has worked on projects for the World Health Organization (WHO) and the International Finance Corporation (IFC), a sister organization of the World Bank, and contributed to the Bohemia project, a groundbreaking clinical trial focused on malaria prevention in Sub-Saharan Africa. Beyond her professional work, she is committed to continuous learning and knowledge-sharing, developing her own R packages. In her spare time, she explores 3D modeling to advance data analysis and storytelling through immersive visualization, believing that VR will play an important role in the future of the data analytics industry.
Benjamín M. Pérez (Ext)
Benjamín is an accomplished software engineer with a passion for crafting code that is both intuitive and maintainable.
Hailing from Argentina, Benjamín has amassed diverse experience across various industries, including retail, postmail, manufacturing, and banking. His work spans multiple platforms, bringing innovative solutions to complex problems in each domain.
Benjamín takes pride in developing robust and scalable software solutions, whether for desktop, web, or server environments. His dedication to continuous improvement and adaptability has made him a valuable contributor in every project he’s undertaken.
Diane Lefaudeux
Diane Lefaudeux is an interdisciplinary scientist with a strong drive to understand complex mechanisms and in particular those arising from biological systems.
Before joining ESQlabs, she worked at Novadiscovery where she developed PBPK-QSP models on various therapeutic areas to predict outcomes using virtual populations.
Diane obtained her Master’s degree in General Engineering from École Centrale Paris, France, as well as in Control Systems Engineering and Systems Biology from University of Stuttgart, Germany.
Félix Mil
Felix Mil is an experienced data scientist and creative problem solver with a strong foundation in software development and biotechnology. He excels at building user‑centric tools that automate workflows, simplify complex tasks, and turn raw data into actionable insights.
Passionate about delivering high‑quality, maintainable code, Felix adheres to best practices while designing intuitive applications, dashboards, and streamlined data pipelines. He loves crafting solutions that make life easier for both colleagues and end‑users, combining solid back‑end architecture with thoughtful, user‑friendly experiences.
Previously, Felix worked in research and development, data analysis, and software engineering roles, where he honed his skills in creating custom analytical tools and improving data workflows across teams. This experience gave him a broad perspective on the entire data lifecycle, from raw data handling to delivering clear, impactful results.
A collaborative and knowledge‑driven team player, Felix enjoys helping others grow, sharing expertise, and fostering a culture of continuous improvement. His versatility across data engineering, analytics, and user experience makes him a valuable asset to any data‑driven initiative.
Laura Villain
Laura Villain is a biomodeler with interests in various mechanistic modeling approaches and statistical methods. She has experience with popPK, QSP, and PBPK models, complemented by her biostatistics skills.
Before joining ESQlabs, she worked at Novadiscovery, where she developed and improved several PBPK and PBPK-QSP models to reproduce in silico trials. She gained in-depth knowledge of all the steps required to develop a model that can reproduce clinical outputs in compliance with regulatory guidelines. She is also interested in R programming and has provided internal training on R within the company. Before that, she worked as a postdoctoral researcher in biostatistics in the oncology field at INRIA (Bordeaux University). There, she explored high-dimensional methods to link omics data with time-to-event outcomes.
Laura received her Master’s degree in biomodeling sciences from INSA Lyon (France). For her Ph.D. thesis, she studied the impact of interleukin 7 injections on HIV-infected patients. She used a mechanistic model and proposed an adaptive protocol of injections. Her PhD research was supervised by Dr. Daniel Commenges and Prof. Rodolphe Thiébaut at the Department of Public Health at Bordeaux University.
Patrick Kaiser
Patrick brings a rich and diverse background that blends 𝐜𝐫𝐞𝐚𝐭𝐢𝐯𝐞 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐦𝐞𝐝𝐢𝐚, 𝐭𝐡𝐞𝐨𝐫𝐞𝐭𝐢𝐜𝐚𝐥 𝐜𝐡𝐞𝐦𝐢𝐬𝐭𝐫𝐲, 𝐀𝐈, 𝐚𝐧𝐝 𝐛𝐥𝐨𝐜𝐤𝐜𝐡𝐚𝐢𝐧 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭.
He began his professional journey in creative digital media, working as a web and graphic designer. He later pursued academic studies in physical and theoretical chemistry, earning a B.Sc. in Physical Chemistry with a thesis on finite element simulations of polymer film drying, followed by an M.Sc. focused on simulating the nitrogenase mechanism using DFT.
Alongside his studies, he contributed to open-source scientific software, developing a Python interface between CP-PAW and the Atomic Simulation Environment (ASE). After his master’s, he specialized in AI and blockchain development. His work includes implementing local generative AI models and contributing to smart contract ecosystems. We can tell that his journey is anything but linear, and that’s exactly why he fits right in!
Since joining ESQlabs, Patrick has focused on integrating large language models (LLMs) into day-to-day workflows, driving innovation in scientific data processing and decision support.
Pavel Balazki
Pavel Balazki is a bioinformatitian by training with over 10 years of experience in PB(P)K and QSP/T modeling and software development.
Pavel’s modeling expertices is focused on developing complex PB-QSP/T disease models, such as the Diabetes Platform or the Thyroid Hormones Toxicology Platform.
Pavel leads the Software ToolChain team at ESQlabs, developing new technologies to enable an integrated ecosystem of software, models, and solutions.
- Development of an end-to-end Quantitative Model-Informed Drug Development (MIDD) ECOSYSTEM
- Evaluation of the drug-drug interaction potential of treosulfan using a physiologically-based pharmacokinetic modelling approach
- Application of High-Throughput PBPK Modeling to Develop an IVIVE Approach for Oral Permeability
- Harnessing Open-Source Solutions: Insights From the FirstOpen Systems Pharmacology (OSP) Community Conference
- Harnessing Open-Source Solutions: Insights From the First Open Systems Pharmacology (OSP) Community Conference
- Advancing Maternal-Fetal and Lactation PBK Models for Cross-Species Risk Assessment in Toxicology
- High-Throughput PBPK Framework in R using Open Systems Pharmacology Software for Anti-Tuberculosis Drug Development
Robert McIntosh (Ext)
Robert McIntosh is an experienced software professional with a particular interest in creating code that is easy to understand and easy to maintain.
Before joining ESQlabs, he worked on a wide range of platforms and projects. He has written software that runs golf carts, electric bikes, electric riding lawn mowers, mobile apps for Android and iOS, and software for web, desktops, and servers.
As a contractor to Bayer Technology Services GmbH, Robert McIntosh has already contributed to the Open Systems Pharmacology Suite before joining ESQlabs.
Rudolf Engelke
Siavash Mirzaee
Siavash is an academic MS biostatistician and R developer since the days of S-PLUS 2000, he brings a mix of AIoT expertise in industrial settings, marketing intelligence insight, and hands-on experience running workshops on privacy-aware AI/LLM implementation. He values the explainability of ML/AI over raw precision, ensuring solutions are transparent, trustworthy, and impactful. At ESQlabs, he works developing predictive models and Shiny Apps, supporting our software team.
Stefano Pizzamiglio
Stefano is an experienced IT System Administrator with a strong background in managing secure and high-availability infrastructure.
He specializes in system architecture, virtualization, and automation across both Linux and Windows environments.
His work focuses on ensuring reliability, optimizing performance, and resolving issues proactively.
He has successfully led deployments in both on-premises and cloud-based systems.
He is passionate about building robust, scalable solutions that support teams and safeguard critical data.
