Professor Daniel Markl
Strathclyde Institute of Pharmacy and Biomedical Sciences
Personal statement
Daniel Markl’s research focuses on developing predictive systems, in-silico design methods and self-driving labs for drug product development and manufacturing that accelerate the pace at which new medicines are developed and delivered. He obtained a BSc (2010) and MSc (2012) in telematics with a focus on neural networks and a PhD (2015) in chemical engineering from Graz University of Technology. Daniel secured an Erasmus Mundus in 2010, which allowed him to study modelling and control system design for one year during his MSc at Lund University. During his PhD he was employed by the Research Center Pharmaceutical Engineering (RCPE) GmbH, where he was in the group Process and Manufacturing Science and involved in several projects at the interface of pharmaceutical engineering, materials science and process modelling. He continued as Senior Scientist and Scientific Project Leader at RCPE after completing his PhD. In 2016 he joined Professor Zeitler’s group (Terahertz Applications Group) as a postdoctoral research associate at the University of Cambridge. Daniel worked for two years in the Terahertz Applications Group before becoming a Chancellor’s Fellow and Lecturer/Assistant Professor at the University of Strathclyde in the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS).
Daniel is Associate Director at CMAC (www.cmac.ac.uk), Training Director of the EPSRC Centre of Doctoral Training in Cyberphysical Systems for Medicines Development and Manufacturing and leads the MHRA-funded Centre of Excellence in Regulatory Science and Innovation (CERSI) for the digital transformation of medicines development and manufacturing.
Area of Expertise
Key expertise and capabilites:
-
Materials–Process–Product–Performance Relationships
Fundamental and applied understanding of how material properties and processing conditions govern drug product structure, quality, and performance. -
Self-Driving and Autonomous Laboratories
Design and deployment of closed-loop experimental platforms that integrate automation, real-time analytics, and machine learning for accelerated pharmaceutical development. -
Advanced Measurement and Characterization
Development and application of high-resolution, high-throughput measurement techniques to capture critical material, process, and product attributes. -
Predictive Modeling and In-Silico Design
Data-driven and physics-informed models for virtual formulation and process design, optimization, and scale-up. -
Digital Process and Product Design
Integration of computational tools, experimental data, and automation to enable rational, efficient drug product development and manufacturing. -
Pharmaceutical Manufacturing Innovation
Intelligent, adaptive manufacturing strategies aimed at improving robustness, efficiency, and product quality while reducing development time and risk.
Prize And Awards
- President of Pharmaceutical Solid State Research Cluster
- Recipient
- 2020
- Fellowship of Higher Education
- Recipient
- 2020
- AAPS Pharmaceutical Research Meritorious Manuscript Award
- Recipient
- 2019
- Best Poster Award
- Recipient
- 2016
- Erasmus Mundus
- Recipient
- 2010
Publications
- Empowering the pharmaceutical workforce for the digital future
- Maclean Natalie, Abrahmsén-Alami Susanna, Clark Catriona, Dörr Frederik, Florence Alastair, Ketolainen Jarkko, Lindow Morten, Mantanus Jérôme, Rantanen Jukka, Reynolds Gavin, Robertson Amy, Markl Daniel
- European Journal of Pharmaceutical Sciences (2026)
- https://doi.org/10.1016/j.ejps.2026.107449
- Quantification of terahertz scattering in water-oil emulsion
- Jahangir Reehab, Markl Daniel, Li Jun, Naftaly Mira
- 2025 50th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) 2025 50th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) 2025 50th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), pp. 1-2 (2026)
- https://doi.org/10.1109/irmmw-thz61557.2025.11319712
- Modelling THz TDS spectra of powder compacts for analysis of pharmaceutical oral solid dosages
- Gorecki Jon, Murphy Keir N, Markl Daniel, Burnett Andrew D, Naftaly Mira
- 2025 50th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) (2026)
- https://doi.org/10.1109/irmmw-thz61557.2025.11320042
- Linking powder to tablet stability : length- and time-scale prediction of moisture sorption
- Ibrahim Isra, Mann James, Abbott Alexander, Winge Fredrik, Davis Adrian, Hens Bart, Khadra Ibrahim, Markl Daniel
- International Journal of Pharmaceutics Vol 684 (2025)
- https://doi.org/10.1016/j.ijpharm.2025.126154
- Spatially-resolved quantification of erosion and swelling of tablets in a paddle dissolution apparatus with integrated optical coherence tomography
- Jesney Hannah, Maclean Natalie, Salehian Mohammad, Mann James, Barker Richard, Khadra Ibrahim, Markl Daniel
- International Journal of Pharmaceutics Vol 683 (2025)
- https://doi.org/10.1016/j.ijpharm.2025.126082
- In-silico analysis of API particle size and drug loading on direct compression tablet properties
- Salehian Mohammad, Florence Alastair, Markl Daniel
- International Particle Technology Forum (2025)
Research Interests
Our laboratory conducts multidisciplinary research at the intersection of materials, processes, products, and performance, with the goal of transforming how medicines are designed, developed, and manufactured. We seek to establish a fundamental, predictive understanding of how material properties and processing conditions jointly determine product structure, quality, and performance.
Central to our approach is the coupling of self-driving laboratories, advanced measurement techniques, and digital process and product design. By integrating automation, high-throughput experimentation, real-time analytics, and data-driven modeling, we aim to dramatically accelerate development timelines while improving robustness, efficiency, and knowledge generation across the pharmaceutical lifecycle.
Our research includes the development of predictive systems, in-silico design methods, and autonomous experimental platforms for drug product development and manufacturing. These tools enable rapid exploration of complex formulation and process spaces, support rational decision-making, and reduce reliance on trial-and-error experimentation. Ultimately, our work lays the foundation for adaptive, intelligent manufacturing systems that deliver higher-quality medicines more efficiently and reliably.
Professional Activities
- Accelerated Drug Product Development using a Digital Formulator and a Self-Driving Tableting DataFactory
- Speaker
- 2025
- Self-Driving Tableting DataFactory
- Speaker
- 2025
- Digital CMC Center of Excellence in Regulatory Science & Innovation (CERSI)
- Speaker
- 2025
- A Self-optimised Tableting DataFactory: Accelerating Process and Formulation Development
- Speaker
- 2024
- Accelerating tablet formulation and process development: Synergising a self-driving tableting system with predictive modelling
- Speaker
- 2024
- A Self-optimised Tableting DataFactory: Accelerating Process and Formulation Developmen
- Speaker
- 2024
Projects
- AI enabled CMC Datafactory
- Markl, Daniel (Principal Investigator) Florence, Alastair (Co-investigator)
- 01-Jan-2025 - 30-Jan-2026
- CERSI for the Digital Transformation of Medicines Development and Manufacturing
- Markl, Daniel (Principal Investigator) Florence, Alastair (Co-investigator) Johnston, Blair (Co-investigator)
- 01-Jan-2025 - 31-Jan-2026
- INtegrated Spectroscopy and Photonics for Increased productivity and Resource Efficiency in MEDicines manufacture: Sustainable Medicines Manufacturing Expression of Interest
- Nordon, Alison (Principal Investigator) Littlejohn, David (Co-investigator) Markl, Daniel (Co-investigator)
- 01-Jan-2025 - 30-Jan-2025
- DPN-MED: Digital Plug-and-Produce Network for Sustainable Medicines Development and Manufacturing
- Fitzpatrick, Stephen (Principal Investigator) Florence, Alastair (Principal Investigator) Florence, Alastair (Co-investigator) Johnston, Blair (Co-investigator) Markl, Daniel (Co-investigator)
- 01-Jan-2025 - 30-Jan-2025
- NF987
- Markl, Daniel (Principal Investigator) Macdonald, Janine (Co-investigator)
- 25-Jan-2024 - 19-Jan-2024
- Industrial CASE Account - University of Strathclyde 2024 | Jahangir, Reehab
- Markl, Daniel (Principal Investigator) Li, Jun (Co-investigator) Jahangir, Reehab (Research Co-investigator)
- 01-Jan-2024 - 01-Jan-2028
Contact
Professor
Daniel
Markl
Strathclyde Institute of Pharmacy and Biomedical Sciences
Email: daniel.markl@strath.ac.uk
Tel: 444 7115